vvEPA
United States Office of Chemical Safety and
Environmental Protection Agency Pollution Prevention
Final Risk Evaluation for
n-Methylpyrrolidone
Supplemental Information on Occupational Exposure Assessment
CASRN: 872-50-4
December 2020
o
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TABLE OF CONTENTS
ABBREVIATIONS 13
1 INTRODUCTION 15
1.1 Overview 15
1.2 Scope 15
1.3 Components of the Occupational Exposure Assessment 16
1.4 Approach and Methodology for Occupational Exposures 16
1.4.1 Process Description 16
1.4.2 Number of Sites, Workers, and ONUs 16
1.4.3 PBPK Input Parameter Determination 17
1.4.3.1 General Approach 18
1.4.3.2 Approach for thi s Ri sk Evaluati on 19
1.4.3.2.1 Weight Fraction of NMP 20
1.4.3.2.2 Skin Surface Area 20
1.4.3.2.3 Glove Usage 21
1.4.3.2.4 Duration of Dermal Contact with Liquids 22
1.4.3.2.5 Air Concentration for Inhalation and Vapor-through-Skin Exposure 22
1.4.3.2.6 Body Weight 23
2 ENGINEERING ASSESSMENT 24
2.1 Manufacturing 24
2.1.1 Process Description 24
2.1.2 Exposure Assessment 25
2.1.2.1 Worker Activities 25
2.1.2.2 Number of Potentially Exposed Workers 25
2.1.2.3 Occupational Exposure Assessment Methodology 27
2.1.2.3.1 Inhalation and Vapor-Through-Skin 27
2.1.2.3.2 Dermal Exposure to Liquid 28
2.1.3 PBPK Inputs 29
2.1.4 Summary 30
2.2 Repackaging 30
2.2.1 Process Description 30
2.2.2 Exposure Assessment 31
2.2.2.1 Worker Activities 31
2.2.2.2 Number of Potentially Exposed Workers 31
2.2.2.3 Occupational Exposure Assessment Methodology 33
2.2.2.3.1 Inhalation and Vapor-Through-Skin 33
2.2.2.3.2 Dermal Exposure to Liquid 34
2.2.3 PBPK Inputs 36
2.2.4 Summary 37
2.3 Chemical Processing, Excluding Formulation 37
2.3.1 Process Description 37
2.3.1.1 Agricultural Chemical Manufacturing 37
2.3.1.2 Petrochemical Manufacturing 38
2.3.1.3 Polymer Manufacturing 38
2.3.1.4 Miscellaneous 39
2.3.2 Exposure Assessment 39
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2.3.2.1 Worker Activities 39
2.3.2.2 Number of Potentially Exposed Workers 40
2.3.2.3 Occupational Exposure Assessment Methodology 43
2.3.2.3.1 Inhalation and Vapor-Through-Skin 43
2.3.2.3.2 Dermal Exposure to Liquid 44
2.3.3 PBPK Inputs 45
2.3.4 Summary 46
2.4 Incorporation into Formulation, Mixture, or Reaction Product 46
2.4.1 Process Description 46
2.4.2 Exposure Assessment 47
2.4.2.1 Worker Activities 47
2.4.2.2 Number of Potentially Exposed Workers 48
2.4.2.3 Occupational Exposure Assessment Methodology 51
2.4.2.3.1 Inhalation and Vapor-Through-Skin 51
2.4.2.3.2 Dermal Exposure to Liquid 53
2.4.3 PBPK Inputs 54
2.4.4 Summary 55
2.5 Metal Finishing 56
2.5.1 Process Description 56
2.5.2 Exposure Assessment 56
2.5.2.1 Worker Activities 56
2.5.2.2 Number of Potentially Exposed Workers 57
2.5.2.3 Occupational Exposure Assessment Methodology 59
2.5.2.3.1 Inhalation and Vapor-Through-Skin 59
2.5.2.3.2 Dermal Exposure to Liquid 60
2.5.3 PBPK Inputs 61
2.5.4 Summary 62
2.6 Application of Paints, Coatings, Adhesives, and Sealants 62
2.6.1 Process Description 62
2.6.2 Exposure Assessment 63
2.6.2.1 Worker Activities 63
2.6.2.2 Number of Potentially Exposed Workers 64
2.6.2.3 Occupational Exposure Assessment Methodology 67
2.6.2.3.1 Inhalation and Vapor-Through-Skin 67
2.6.2.3.2 Dermal Exposure to Liquid 69
2.6.3 PBPK Inputs 70
2.6.4 Summary 71
2.7 Recycling and Disposal 71
2.7.1 Process Description 71
2.7.2 Exposure Assessment 75
2.7.2.1 Worker Activities 75
2.7.2.2 Number of Potentially Exposed Workers 76
2.7.2.3 Occupational Exposure Assessment Methodology 76
2.7.2.3.1 Inhalation and Vapor-Through-Skin 76
2.7.2.3.2 Dermal Exposure to Liquid 78
2.7.3 PBPK Inputs 79
2.7.4 Summary 80
2.8 Removal of Paints, Coatings, Adhesives, and Sealants 80
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2.8.1 Process Description 80
2.8.2 Exposure Assessment 81
2.8.2.1 Worker Activities 81
2.8.2.2 Number of Potentially Exposed Workers 81
2.8.2.3 Occupational Exposure Assessment Methodology 82
2.8.2.3.1 Inhalation and Vapor-Through-Skin 82
2.8.2.3.2 Dermal Exposure to Liquid 83
2.8.3 PBPK Inputs 85
2.8.4 Summary 86
2.9 Other Electronics Manufacturing 86
2.9.1 Process Description 86
2.9.2 Exposure Assessment 87
2.9.2.1 Worker Activities 87
2.9.2.2 Number of Potentially Exposed Workers 88
2.9.2.3 Occupational Exposure Assessment Methodology 89
2.9.2.3.1 Inhalation and Vapor-Through-Skin 89
2.9.2.3.2 Dermal Exposure to Liquid 90
2.9.3 PBPK Inputs 90
2.9.4 Summary 91
2.10 Semiconductor Manufacturing 91
2.10.1 Process Description 91
2.10.2 Exposure Assessment 92
2.10.2.1 Worker Activities 92
2.10.2.2 Number of Potentially Exposed Workers 92
2.10.2.3 Occupational Exposure Assessment Methodology 93
2.10.2.3.1 Inhalation and Vapor-Through-Skin 93
2.10.2.3.2 Dermal Exposure to Liquid 95
2.10.3 PBPK Inputs 97
2.10.4 Summary 100
2.11 Printing and Writing 100
2.11.1 Process Description 100
2.11.2 Exposure Assessment 101
2.11.2.1 Worker Activities 101
2.11.2.2 Number of Potentially Exposed Workers 101
2.11.2.3 Occupational Exposure Assessment Methodology 102
2.11.2.3.1 Inhalation and Vapor-Through-Skin 102
2.11.2.3.2 Dermal Exposure to Liquid 103
2.11.3 PBPK Inputs 104
2.11.4 Summary 105
2.12 Soldering 105
2.12.1 Process Description 105
2.12.2 Exposure Assessment 106
2.12.2.1 Worker Activities 106
2.12.2.2 Number of Potentially Exposed Workers 106
2.12.2.3 Occupational Exposure Assessment Methodology 107
2.12.2.3.1 Inhalation and Vapor-Through-Skin 107
2.12.2.3.2 Dermal Exposure to Liquid 108
2.12.3 PBPK Inputs 108
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2.12.4 Summary 109
2.13 Commercial Automotive Servicing 109
2.13.1 Process Description 109
2.13.2 Exposure Assessment 110
2.13.2.1 Worker Activities 110
2.13.2.2 Number of Potentially Exposed Workers Ill
2.13.2.3 Occupational Exposure Assessment Methodology 112
2.13.2.3.1 Inhalation and Vapor-Through-Skin 112
2.13.2.3.2 Dermal Exposure to Liquid 113
2.13.3 PBPK Inputs 114
2.13.4 Summary 115
2.14 Laboratory Use 115
2.14.1 Process Description 115
2.14.2 Exposure Assessment 116
2.14.2.1 Worker Activities 116
2.14.2.2 Number of Potentially Exposed Workers 116
2.14.2.3 Occupational Exposure Assessment Methodology 117
2.14.2.3.1 Inhalation and Vapor-Through-Skin 117
2.14.2.3.2 Dermal Exposure to Liquid 118
2.14.3 PBPK Inputs 119
2.14.4 Summary 120
2.15 Lithium Ion Cell Manufacturing 120
2.15.1 Process Description 120
2.15.2 Exposure Assessment 120
2.15.2.1 Worker Activities 120
2.15.2.2 Number of Potentially Exposed Workers 121
2.15.2.3 Occupational Exposure Assessment Methodology 122
2.15.2.3.1 Inhalation and Vapor-Through-Skin 122
2.15.2.3.2 Dermal Exposure to Liquid 123
2.15.3 PBPK Inputs 125
2.15.4 Summary 127
2.16 Cleaning 127
2.16.1 Process Description 127
2.16.1.1 Aerosol Degreasing 128
2.16.1.2 Dip Degreasing and Cleaning 128
2.16.1.3 Wipe Cleaning, Including Use of Spray-Applied Cleaning Products 128
2.16.2 Exposure Assessment 129
2.16.2.1 Worker Activities 129
2.16.2.2 Number of Potentially Exposed Workers 129
2.16.2.3 Occupational Exposure Assessment Methodology 130
2.16.2.3.1 Inhalation and Vapor-Through-Skin 130
2.16.2.3.2 Dermal Exposure to Liquid 131
2.16.3 PBPK Inputs 132
2.16.4 Summary 133
2.17 Fertilizer Application 133
2.17.1 Process Description 133
2.17.2 Exposure Assessment 134
2.17.2.1 Worker Activities 134
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2.17.2.2 Number of Potentially Exposed Workers 135
2.17.2.3 Occupational Exposure Assessment Methodology 136
2.17.2.3.1 Inhalation and Vapor-Through-Skin 136
2.17.2.3.2 Dermal Exposure to Liquid 136
2.17.3 PBPK Inputs 137
2.17.4 Summary 138
3 DISCUSSION OF RESULTS 139
3.1 Variability 139
3.2 Uncertainties and Limitations 139
3.2.1 Number of Workers 139
3.2.2 PBPK Input Parameters 139
3.2.2.1 Tank Tmck and Railcar Loading and Unloading Release and Inhalation Exposure
Model ." 141
3.2.2.2 Drum Loading and Unloading Release and Inhalation Exposure Model 141
3.2.2.3 Model for Occupational Exposures during Aerosol Degreasing of Automotive Brakes
141
3.2.2.4 Near-Field/Far-Field Model Framework 142
REFERENCES 143
APPENDICES 153
Appendix A Inhalation Data for Each Occupational Scenario 153
A. 1 M anufactur i ng 153
A.2 Repackaging 158
A.3 Chemical Processing, Excluding Formulation 158
A.4 Incorporation into Formulation, Mixture, or Reaction Product 163
A.5 Metal Finishing 170
A.6 Application of Paints, Coatings, Adhesives, and Sealants 172
A.7 Recycling and Disposal 177
A.8 Removal of Paints, Coatings, Adhesives, and Sealants 179
A.9 Other Electronics Manufacturing 183
A. 10 Semiconductor Manufacturing 185
A. 11 Printing and Writing 190
A. 12 Soldering 192
A. 13 Commercial Automotive Servicing 193
A. 14 Laboratory use 194
A. 15 Lithium Ion Cell Manufacturing 196
A. 16 Cleaning 198
A. 17 Fertilizer Application 202
A. 18 Additional Monitoring Data 204
Appendix B Description of Models used to Estimate Worker and ONU Exposures 213
B. 1 Approaches for Estimating Number of Workers 213
B.2 Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model
Approach and Parameters 218
B.2.1 Displacement of Saturated Air Inside Tank Trucks and Railcars 218
B.2.2 Emissions of Saturated Air that Remain in Transfer Hoses/Loading Arm 219
B.2.3 Emission from Leaks 220
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B.2.3.1 Exposure Estimates 223
B.2.4 Sensitivity of Model Parameters 224
B.3 Drum Loading and Unloading Release and Inhalation Exposure Model Approach and
Parameters 226
B.3.1 Model Air Release and Inhalation Exposure Equations 226
B.3.2 Number of Containers and Short-Term Exposure Duration Equations 228
B.3.3 Model Input Parameters 229
B.3.4 Monte Carlo Simulation Results 233
B.3.1 Sensitivity of Model Parameters 234
B.4 Brake Servicing Near-Field/Far-Field Inhalation Exposure Model Approach and Parameters235
B.4.1 Model Design Equations 235
B.4.2 Model Parameters 240
B.4.2.1 Far-Field Volume 244
B.4.2.2 Air Exchange Rate 244
B. 4.2.3 N ear-F i el d Indoor AirSpeed 244
B.4.2.4 Near-Field Volume 245
B.4.2.5 Application Time 245
B.4.2.6 Averaging Time 245
B.4.2.7 NMP Weight Fraction 245
B.4.2.8 Volume of Degreaser Used per Brake Job 246
B.4.2.9 Number of Applications per Brake Job 246
B.4.2.10 Amount of NMP Used per Application 246
B.4.2.11 Operating Hours per Week 246
B.4.2.12 Number of Brake Jobs per Work Shift 246
B.4.3 Sensitivity of Model Parameters 247
Appendix C Data Integration Strategy for Occupational Exposure and Release
Data/Information 248
Appendix D NMP Weight Fraction Data 253
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LIST OF TABLES
Table 1-1. Glove Protection Factors for Different Dermal Protection Strategies from ECETOC TRA v3
22
Table 2-1. US Number of Establishments and Employees for Manufacturing 26
Table 2-2. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Manufacturing 28
Table 2-3. Summary of Parameters for Worker Dermal Exposure to Liquids During Manufacturing.... 29
Table 2-4. Characterization of PBPK Model Input Parameters for Manufacturing of NMP 30
Table 2-5. PBPK Model Input Parameters for Manufacturing of NMP 30
Table 2-6. US Number of Establishments and Employees for Repackaging 33
Table 2-7. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure Repackaging 34
Table 2-8. Summary of Parameters for Worker Dermal Exposure to Liquids During Repackaging 35
Table 2-9. Characterization of PBPK Model Input Parameters for Repackaging 36
Table 2-10. PBPK Model Input Parameters for Repackaging 37
Table 2-11. US Number of Establishments and Employees for Chemical Processing, Excluding
Formulation 41
Table 2-12. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Chemical Processing, Excluding Formulation 43
Table 2-13. Summary of Parameters for Worker Dermal Exposure to Liquids During Chemical
Processing, Excluding Formulation 45
Table 2-14. Characterization of PBPK Model Input Parameters for Chemical Processing, Excluding
Formulation 45
Table 2-15. PBPK Model Input Parameters for Chemical Processing, Excluding Formulation 45
Table 2-16. US Number of Establishments and Employees for Incorporation into Formulation, Mixture,
or Reaction Product 49
Table 2-17. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Incorporation into Formulation, Mixture, or Reaction Product 52
Table 2-18. Summary of Area Monitoring During Incorporation into Formulation, Mixture, or Reaction
Product 52
Table 2-19. Summary of Parameters for Worker Dermal Exposure to Liquids During Incorporation into
Formulation, Mixture, or Reaction Product 54
Table 2-20. Characterization of PBPK Model Input Parameters for Incorporation into Formulation,
Mixture, or Reaction Product 54
Table 2-21. PBPK Model Input Parameters for Incorporation into Formulation, Mixture, or Reaction
Product 55
Table 2-22. US Number of Establishments and Employees for Metal Finishing 58
Table 2-23. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Metal Finishing 59
Table 2-24. Summary of Area Monitoring During Metal Finishing 60
Table 2-25. Summary of Parameters for Worker Dermal Exposure to Liquids During Metal Finishing 61
Table 2-26. Characterization of PBPK Model Input Parameters for Metal Finishing 61
Table 2-27. PBPK Model Input Parameters for Metal Finishing 61
Table 2-28. US Number of Establishments and Employees for Application of Paints, Coatings,
Adhesives, and Sealants 65
Table 2-29. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Application of Paints, Coatings, Adhesives, and Sealants 67
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Table 2-30. Summary of Occupational Non-User Inhalation and Vapor-Through-Skin Exposure During
Application of Paints, Coatings, Adhesives, and Sealants 68
Table 2-31. Summary of Parameters for Worker Dermal Exposure to Liquids During Application of
Paints, Coatings, Adhesives, and Sealants 70
Table 2-32. Characterization of PBPK Model Input Parameters for Application of Paints, Coatings,
Adhesives, and Sealants 70
Table 2-33. PBPK Model Input Parameters for Application of Paints, Coatings, Adhesives, and Sealants
71
Table 2-34. US Number of Establishments and Employees for Recycling and Disposal 76
Table 2-35. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Recycling and Disposal 77
Table 2-36. Summary of Parameters for Worker Dermal Exposure to Liquids During Recycling and
Disposal 78
Table 2-37. Characterization of PBPK Model Input Parameters for Recycle and Disposal 79
Table 2-38. PBPK Model Input Parameters for Recycle and Disposal 80
Table 2-39. US Number of Establishments and Employees for Removal of Paints, Coatings, Adhesives,
and Sealants 82
Table 2-40. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Removal of Paints, Coatings, Adhesives, and Sealants 83
Table 2-41. Summary of Parameters for PBPK Modeling of Worker Dermal Exposure to Liquids During
Removal of Paints, Coatings, Adhesives, and Sealants 84
Table 2-42. Characterization of PBPK Model Input Parameters for Removal of Paints, Coatings,
Adhesives, and Sealants 85
Table 2-43. PBPK Model Input Parameters for Removal of Paints, Coatings, Adhesives, and Sealants 85
Table 2-44. US Number of Establishments and Employees for Other Electronics Manufacturing 88
Table 2-45. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Other Electronics Manufacturing 89
Table 2-46. Summary of Parameters for Worker Dermal Exposure to Liquids During Other Electronics
Manufacturing 90
Table 2-47. Characterization of PBPK Model Input Parameters for Other Electronics Manufacturing .. 91
Table 2-48. PBPK Model Input Parameters for Other Electronics Manufacturing 91
Table 2-49. US Number of Establishments and Employees for Semiconductor Manufacturing 93
Table 2-50. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Semiconductor Manufacturing 94
Table 2-51. Summary of Area Monitoring During Semiconductor Manufacturing 95
Table 2-52. Summary of Parameters for Worker Dermal Exposure to Liquids During Semiconductor
Manufacturing 95
Table 2-53. Characterization of PBPK Model Input Parameters for Semiconductor Manufacturing 97
Table 2-54. PBPK Model Input Parameters for Semiconductor Manufacturing 97
Table 2-55. Industry Proposed PBPK Model Input Parameters for Semiconductor Manufacturing (SIA,
2020) 99
Table 2-56. US Number of Establishments and Employees for Printing and Writing 102
Table 2-57. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Printing and Writing 102
Table 2-58. Summary of Parameters for Worker Dermal Exposure to Liquids During Printing and
Writing 104
Table 2-59. Characterization of PBPK Model Input Parameters for Printing and Writing 104
Table 2-60. PBPK Model Input Parameters for Printing and Writing 105
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Table 2-61. US Number of Establishments and Employees for Soldering 107
Table 2-62. Summary of Parameters for Soldering 107
Table 2-63. Summary of Parameters for Worker Dermal Exposure to Liquids During Soldering 108
Table 2-64. Characterization of PBPK Model Input Parameters for Soldering 109
Table 2-65. PBPK Model Input Parameters for Soldering 109
Table 2-66. US Number of Establishments and Employees for Commercial Automotive Servicing.... Ill
Table 2-67. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Commercial Automotive Servicing 113
Table 2-68. Summary of Occupational Non-User Inhalation and Vapor-Through-Skin Exposure During
Commercial Automotive Servicing 113
Table 2-69. Summary of Parameters for Worker Dermal Exposure to Liquids During Commercial
Automotive Servicing 114
Table 2-70. Characterization of PBPK Model Input Parameters for Commercial Automotive Servicing
115
Table 2-71. PBPK Model Input Parameters for Commercial Automotive Servicing 115
Table 2-72. US Number of Establishments and Employees for Laboratory Use 117
Table 2-73. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Laboratory Use 118
Table 2-74. Summary of Parameters for Worker Dermal Exposure to Liquids During Laboratory Usel 19
Table 2-75. Characterization of PBPK Model Input Parameters by Laboratory Use 119
Table 2-76. PBPK Model Input Parameters for Laboratory Use 120
Table 2-77. US Number of Establishments and Employees for Lithium Ion Cell Manufacturing 121
Table 2-78. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Lithium Ion Cell Manufacturing 122
Table 2-79. Summary of Parameters for Worker Dermal Exposure to Liquids During Lithium Ion Cell
Manufacturing 124
Table 2-80. Characterization of PBPK Model Input Parameters for Lithium Ion Cell Manufacturing . 126
Table 2-81. PBPK Model Input Parameters for Lithium Ion Cell Manufacturing 126
Table 2-82. US Number of Establishments and Employees for Cleaning 130
Table 2-83. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Cleaning 131
Table 2-84. Summary of Parameters for Worker Dermal Exposure to Liquids During Cleaning 132
Table 2-85. Characterization of PBPK Model Input Parameters for Cleaning 132
Table 2-86. PBPK Model Input Parameters for Cleaning 133
Table 2-87. U.S. Number of Establishments and Employees for Fertilizer Application 135
Table 2-88. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-Through-Skin
Exposure During Fertilizer Application 136
Table 2-89. Summary of Parameters for Worker Dermal Exposure to Liquids During Fertilizer
Application 137
Table 2-90. Characterization of PBPK Model Input Parameters for Fertilizer Application 137
Table 2-91. PBPK Model Input Parameters for Fertilizer Application 138
TableApx A-l. Summary of Inhalation Monitoring Data for Manufacturing 155
TableApx A-2. Summary of Inhalation Monitoring Data for Chemical Processing, Excluding
Formulation 160
Table Apx A-3. Summary of Inhalation Monitoring Data for Incorporation into Formulation, Mixture,
or Reaction Product 165
Table Apx A-4. Summary of Inhalation Monitoring Data for Metal Finishing 171
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TableApx A-5. Summary of Inhalation Monitoring Data for Application of Paints, Coatings,
Adhesives, and Sealants 174
Table Apx A-6. 2016 TRI Off-Site Transfers lor NMP 177
Table Apx A-7. Summary of Inhalation Monitoring Data for Removal of Paints, Coatings, Adhesives,
and Sealants 180
Table Apx A-8. Summary of Inhalation Monitoring Data for Other Electronics Manufacturing 184
Table_Apx A-9. Summary of SIA Data SIA (SIA, 2019b) 187
Table Apx A-10. Summary of Inhalation Monitoring Data for Semiconductor Manufacturing 188
TableApx A-l 1. Summary of Parameters for Inhalation Monitoring Data for Printing and Writing .. 191
Table_Apx A-12. Aerosol Degreasing Model Results 193
TableApx A-13. Summary of Inhalation Monitoring Data for Laboratory Use 195
Table Apx A-14. Summary of Inhalation Monitoring Data for Lithium Ion Cell Manufacturing 197
Table Apx A-l 5. Summary of Inhalation Monitoring Data for Cleaning 199
Table Apx A-16. Summary of Inhalation Monitoring Data for Fertilizer Application 203
Table Apx A-17. Summary of Inhalation Monitoring Data for Unknown Occupational Exposure
Scenarios 205
Table Apx B-l. SOCs with Worker and ONU Designations for All Conditions of Use Except Dry
Cleaning 213
Table Apx B-2. SOCs with Worker and ONU Designations for Dry Cleaning Facilities 214
Table_Apx B-3. Estimated Number of Potentially Exposed Workers and ONUs under NAICS 812320
215
Table Apx B-4. Example Dimension and Volume of Loading Arm/Transfer System 219
Table Apx B-5. Default Values for Calculating Emission Rate of n-Methylpyrrolidone from
Transfer/Loading Arm 220
Table Apx B-6. Parameters for Calculating Emission Rate of n-Methylpyrrolidone from Equipment
Leaks 221
Table_Apx B-7. Default Values for Fa and N 221
Table Apx B-8. Parameters for Calculating Exposure Concentration Using the EPA/OPPT Mass
Balance Model 223
Table Apx B-9. Calculated Emission Rates and Resulting Exposures of n-Methylpyrrolidone from the
Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model
224
Table Apx B-10. Summary of Parameter Values and Distributions Used in the Inhalation Exposure
Model 230
Table Apx B-l 1. Drum Loading and Unloading Inhalation Exposure Simulation Results 233
Table Apx B-12. Summary of Parameter Values and Distributions Used in the Brake Servicing Near-
Field/Far-Field Inhalation Exposure Model 241
Table Apx C-l. Hierarchy Guiding Integration of Occupational Exposure Data/Information 251
Table Apx C-2. Hierarchy Guiding Integration of Environmental Release Data/Information 252
Table Apx D-l. Summary NMP Weight Fraction Data for All Occupational Exposure Scenarios 254
LIST OF FIGURES
Figure 2-1. NMP Manufacturing Under Adiabatic Conditions 24
Figure 2-2. NMP Manufacturing Using Gamma-Butyrolactone (GBL) and Monomethylamine (MMA)24
Figure 2-3. General Process Flow Diagram for Repackaging 31
Figure 2-4. Typical Waste Disposal Process (U.S. EPA, 2017a) 72
Figure 2-5. Typical Industrial Incineration Process 74
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FigureApx B-l. Illustration of Transfer Lines Used During Tank Truck Unloading and Associated
Equipment Assumed by EPA 222
Figure Apx B-2. Graphical Probability Density Function of Monte Carlo Simulation Results 233
Figure Apx B-3. The Near-Field/Far-Field Model as Applied to the Brake Servicing Near-Field/Far-
Field Inhalation Exposure Model 236
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ABBREVIATIONS
ACGIH
AIA
AIHA
AP-42
APF
BLS
CARB
CASRN
CBI
CDR
CFR
cm2
CSPA
DOD
DOEHRS-M
ECETOC
ECHA
EPA
ESD
EU
EVOH
FDA
FFEM
FIFRA
FR
g
GBL
GS
HERO
HHE
hr
HVLP
IBC
IFA
kg
kPa
L
lb
LEV
LPG
3
m
MEMA
mg
MMA
mmHg
s
American Conference of Government Industrial Hygienists
Aerospace Industries Association
American Industrial Hygiene Association
Compilation of Air Pollutant Emissions Factors
Assigned Protection Factor
Bureau of Labor Statistics
California Air Resources Board
Chemical Abstracts Service Registry Number
Confidential Business Information
Chemical Data Reporting
Code of Federal Regulations
Centimeters squared
Consumer Specialty Products Association
Department of Defense
Defense Occupational and Environmental Health Readiness System -
Industrial Hygiene
European Center for Ecotoxicology and Toxicology of Chemicals
European Chemicals Agency
Environmental Protection Agency
Emission Scenario Documents
European Union
Ethylene vinyl alcohol (gloves)
Food and Drug Administration
FUJIFILM Electronic Materials
Federal Insecticide, Fungicide and Rodenticide Act
Federal Register
grams
Gamma-butyrolactone
Generic Scenario
Health & Environmental Research Online
Health Hazard Evaluation
Hour
High-Volume Low-Pressure
Intermediate bulk container
German Institute for Occupational Safety and Health
Kilogram(s)
kilopascal
Liter(s)
Pound
Local Exhaust Ventilation
Liquefied Petroleum Gas
Cubic Meter(s)
Motor & Equipment Manufacturers Association
Milligram(s)
Monomethylamine
Millimeter(s) of Mercury
Seconds
Page 13 of 292
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SDS
Safety Data Sheet
NABTU
North America's Building Trades Unions
NAICS
North American Industry Classification System
NEMA
National Electrical Manufacturers Association
NICNAS
National Industrial Chemicals Notification and Assessment Scheme
NIOSH
National Institute of Occupational Safety and Health
NKRA
Not Known or Reasonably Ascertainable
NMP
n-Methylpyrrolidone
NPDES
National Pollutant Discharge Elimination System
OAQPS
Office of Air Quality Planning and Standards
OARS
Occupational Alliance for Risk Science
OECD
Organisation for Economic Co-operation and Development
OEL
Occupational Exposure Limit
OES
Occupational Exposure Scenario
ONU
Occupational Non-User
OPPT
Office of Pollution Prevention and Toxics
OSHA
Occupational Safety and Health Administration
PBPK
Physiologically Based Pharmacokinetic (Modeling)
PBZ
Personal Breathing Zone
PEL
Permissible Exposure Limit
PF
Protection Factor
POTW
Publicly Owned Treatment Works
PNOR
Particulates Not Otherwise Regulated
PPE
Personal Protective Equipment
ppm
Part(s) per Million
PPS
Polyphenylene Sulfide
QC
Quality Control
RCRA
Resource Conservation and Recovery Act
RDF
Refuse-Derived Fuel
REL
Recommended Exposure Limit
RIVM
The Netherlands' National Institute for Public Health and the Environment
SDS
Safety Data Sheet
SIA
Semiconductor Industry Association
SOC
Standard Occupational Classification
SOCMI
Synthetic Organic Chemical Manufacturing Industry
SUSB
Statistics of U.S. Businesses
TLV
Threshold Limit Value
TRA
Targeted Risk Assessment (tool)
TRI
Toxics Release Inventory
TSCA
Toxic Substances Control Act
TWA
Time-Weighted Average
U.S.
United States
UV
Ultraviolet
USD A
U.S. Department of Agriculture
VOC
Volatile Organic Compound
WEEL
Workplace Environment Exposure Limit
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1 INTRODUCTION
This document supports the occupational exposure assessment in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
1.1 Overview
For the purpose of this assessment, EPA considered occupational exposure of the total workforce of
exposed users and non-users, which include but are not limited to male and female workers of
reproductive age who are >16 years of age. Female workers of reproductive age are >16 to less than 50
years old. Adolescents (>16 to <21 years old) are a small part of this total workforce. The occupational
exposure assessment is applicable to and covers the entire workforce who are exposed to NMP.
EPA evaluated acute and chronic exposures to workers and occupational non-users (ONUs) by dermal
and inhalation routes in association with NMP use in industrial and commercial applications, which are
discussed in Section 1.2. Oral exposure via incidental ingestion of inhaled vapor/mist/dust will be
considered as discussed in the "Risk Evaluation for n-Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-)
(NMP)"
EPA assessed these exposures by inputting exposure parameters into a physiologically based
pharmacokinetic (PBPK) model, which is described in Appendix I of the Risk Evaluation document.
Parameter development for each occupational exposure scenario assessed are described in Section 2.
For each scenario, EPA distinguishes exposures for workers and ONUs when possible. Normally, a
primary difference between workers and ONUs is that workers may handle chemical substances and
have direct dermal contact with liquid chemicals that they handle, while ONUs are working in the
general vicinity of workers but do not handle the assessed chemical substances and do not have direct
dermal contact with liquid chemicals being handled by the workers. EPA expects that ONUs may often
have lower inhalation and vapor-through-skin exposure than workers since they may be further from the
exposure source than workers. For inhalation, if EPA cannot distinguish ONU exposures from workers,
EPA assumes that ONU inhalation may be less than the inhalation estimates for workers.
1.2 Scope
Workplace exposures have been assessed for the following industrial and commercial uses of NMP, also
referred to as occupational exposure scenarios (OES):
1. Manufacturing
2. Repackaging
3. Chemical Processing, Excluding Formulation
4. Incorporation into a Formulation, Mixture or Reaction Product
5. Metal Finishing
6. Application of Paints, Coatings, Adhesives and Sealants
7. Recycling and Disposal
8. Removal of Paints, Coatings, Adhesives, and Sealants
9. Other Electronics Manufacturing
10. Semiconductor Manufacturing
11. Printing and Writing
12. Soldering
13. Commercial Automotive Servicing
14. Laboratory Use
15. Lithium Ion Cell Manufacturing
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16. Cleaning
17. Fertilizer Application
These are mapped to the conditions of use in the "Risk Evaluation for n-Methylpyrrolidone (2-
Pyrrolidinone, 1 Methyl-) (NMP)."
1.3 Components of the Occupational Exposure Assessment
The occupational exposure assessment of each use comprises the following components:
Process Description: A description of the use, including the role of the chemical in the use;
process vessels, equipment, and tools used during the use; and descriptions of the worker
activities, including an assessment for potential points of worker exposure.
Number of Sites: An estimate of the number of sites that use the chemical for the given use.
Number of Workers and Occupational Non-Users: An estimate of the number of workers and
occupational non-users potentially exposed to the chemical for the given use.
PBPK Input Parameter Determination: A development of a set of central tendency and a set
of high-end PBPK input parameters for each occupational exposure scenario within a use,
accounting for both inhalation and dermal exposure to liquid.
1.4 Approach and Methodology for Occupational Exposures
EPA reviewed data such as general facility data (e.g., process descriptions, NMP concentration data),
inhalation monitoring data (i.e., personal exposure monitoring data and area monitoring data), and
environmental release data, found in published literature. Literature sources were evaluated using the
evaluation strategies laid out in Appendix D of the Application of Systematic Review in TSCA Risk
Evaluations (U.S. EPA 2018a). Results of the evaluations are in the supplemental files titled "Risk
Evaluation for n-Methylpyrrolidone (NMP), Systematic Review Supplemental File: Data Quality
Evaluation for Occupational Exposure and Release Data. Docket EPA-HQ-OPPT-2019-0236" and "Risk
Evaluation for n-Methylpyrrolidone (2-Pyrrolidinone, 1-Methyl-) Systematic Review Supplemental File:
Data Quality Evaluation of Environmental Releases and Occupational Exposure Common Sources.
Docket EPA-HQ-OPPT-2019-0236."
Each data source received an overall confidence of high, medium, low, or unacceptable. For the risk
evaluation, EPA used the data of the highest quality. Data of lower rated quality may be used to
supplement analyses. Data that were found to be unacceptable were not used for risk assessment
purposes. Overall confidence ratings for the data used in this document (i.e., high, medium, low, or
unacceptable) are included in Section 2 and the tables in Appendix A. The Data Integration Strategy is
described in Appendix C.
1.4.1 Process Description
EPA performed a literature search to find descriptions of processes involved in each use to identify
worker activities that could potentially result in occupational exposures. Where process descriptions
were unclear or not available, EPA referenced relevant Emission Scenario Documents (ESDs) or
Generic Scenarios (GSs). Process descriptions for each use can be found in Section 2.
1.4.2 Number of Sites, Workers, and ONUs
Where available, EPA used CDR data to provide a basis to estimate the numbers of sites, workers, and
occupational non-users (ONUs). EPA supplemented the available CDR data with U.S. economic data
using the following method:
1. Identify the North American Industry Classification System (NAICS) codes for the industry
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sectors associated with these uses.
2. Estimate total employment by industry/occupation combination using the Bureau of Labor
Statistics' (BLS) Occupational Employment Statistics (OES) data (U.S. BLS. 2016).
3. Refine the OES estimates where they are not sufficiently granular by using the U.S. Census'
Statistics of US Businesses (SUSB) (citation) data on total employment by 6-digit NAICS.
4. Use market penetration data to estimate the percentage of employees likely to be using NMP
instead of other chemicals.
5. Combine the data generated in Steps 1 through 4 to produce an estimate of the number of
employees using NMP in each industry/occupation combination, and sum these to arrive at a
total estimate of the number of employees with exposure.
Market penetration data for NMP are not readily available at this time; therefore, site, worker, and ONU
estimates do not take this into account and likely overestimate the number of sites, workers, and ONUs
potentially exposed to NMP. Where end-use sector is not clear, relevant GSs and ESDs are used to
estimate the number of sites and workers, such as for metal finishing.
1.4.3 PBPK Input Parameter Determination
For each occupational exposure scenario, PBPK modeling requires a set of input parameters related to
dermal, inhalation, and vapor-through-skin exposure. The occupational exposure parameters and
information needed for the PBPK modeling are the following:
NMP weight fraction in the liquid product,
Total skin surface area in contact with the liquid product,
Glove protection factor (if applicable),
Duration of dermal contact with the liquid product,
Air concentration for inhalation and vapor-through-skin exposure, and
Body weight of the exposed worker.
EPA assumed that the skin of the hands was exposed dermally to NMP at the specified liquid weight
fraction and skin surface area and that there was simultaneous exposure by inhalation and vapor-
through-skin absorption for unobstructed skin areas. As described below, air concentrations were
adjusted to duration of contact of liquid on the skin, which is assumed to be removed by cleaning at the
end of the work period. Acute scenarios assumed 1 day of exposure and chronic scenarios assumed 5
days of exposure per week.
EPA used literature sources for estimating many of these occupational exposure parameters. EPA used
modeling or generic assumptions when data were not available. For most PBPK input parameters, EPA
did not find enough data to determine statistical distributions of the actual exposure parameters and
concentrations. Within the distributions, central tendencies describe 50th percentile or the substitute that
most closely represents the 50th percentile. A central tendency is assumed to be representative of
occupational exposures in the center of the distribution for a given use. For risk evaluation, EPA may
use the 50th percentile (median), mean (arithmetic or geometric), mode, or midpoint values of a
distribution as representative of the central tendency scenario. EPA's preference is to provide the 50th
percentile of the distribution. However, if the full distribution is not known, EPA may assume that the
mean, mode, or midpoint of the distribution represents the central tendency depending on the statistics
available for the distribution. However, these substitutes are highly uncertain and not ideal substitutes
for the percentiles. EPA could not determine whether these substitutes were suitable to represent
statistical distributions of real-world scenarios.
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The high-end of a distribution describes the range of the distribution above 90th percentile (U.S. EPA.
1992). A high-end is assumed to be representative of occupational exposures that occur at probabilities
above the 90th percentile but below the exposure of the individual with the highest exposure (U.S. EPA.
1992). For risk evaluation, EPA provided high-end results at the 95th percentile, where available. If the
95th percentile is not available, EPA may use a different percentile greater than or equal to the 90th
percentile but less than or equal to the 99.9th percentile, depending on the statistics available for the
distribution. If the full distribution is not known and the preferred statistics are not available, EPA may
estimate a maximum or bounding estimate in lieu of the high-end. Ideally, EPA would use the 50th and
95th percentiles for each parameter. Where these statistics were unknown, the mean or mid-range (mean
is preferable to mid-range) served as substitutes for 50th percentile and the high-end of ranges served as
a substitute for 95th percentile. However, these substitutes were highly uncertain and not ideal
substitutes for the percentiles. EPA could not determine whether these substitutes were suitable to
represent statistical distributions of real-world scenarios.
For each occupational exposure scenario, EPA developed two sets of PBPK input parameters, one
representative of central tendency conditions and one representative of high-end conditions. To generate
each central tendency scenario result, EPA used a group of all central tendency input parameter values
relevant to the scenario. To generate each high-end scenario result, EPA used a group of mostly high-
end input parameter values relevant to the scenario except body weight, which is a median value. Using
mostly high-end input values is a plausible approach to estimate a high-end PBPK result for the periods
of acute and chronic exposures of 1 to 5 days.
1.4.3.1 General Approach
This section discusses EPA's general approach for data selection. EPA follows the following hierarchy
in selecting data and approaches for estimating air concentrations:
1. Monitoring data:
a. Personal and directly applicable
b. Area and directly applicable
c. Personal and potentially applicable or similar
d. Area and potentially applicable or similar
2. Modeling approaches:
a. Surrogate monitoring data
b. Fundamental modeling approaches
c. Statistical regression modeling approaches
3. Occupational exposure limits:
a. Company-specific occupational exposure limits (OELs) (for site-specific exposure
assessments, e.g., there is only one manufacturer who provides to EPA their internal OEL but
does not provide monitoring data)
b. Occupational Safety and Health Administration (OSHA) Permissible Exposure Limit (PEL)
c. Voluntary limits (American Conference of Governmental Industrial Hygienists [ACGIH]
Threshold Limit Value [TLV], National Institute for Occupational Safety and Health
[NIOSH] Recommended Exposure Limits [RELs], Occupational Alliance for Risk Science
(OARS) workplace environmental exposure level [WEEL] [formerly by AIHA])
Within each level of the hierarchy, EPA used the data with the highest overall confidence rating from
EPA's systematic review process. Note that EPA did not rate EPA models used to estimate air
concentrations; where these models are used, the overall confidence rating is listed as "not applicable".
EPA models are standard sources used by RAD for engineering assessments. EPA did not systematically
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review models that were developed by EPA.
Exposures are calculated from the datasets provided in the sources depending on the size of the dataset.
For datasets with six or more data points, central tendency and high-end exposures were estimated using
the 50th percentile and 95th percentile. For datasets with three to five data points, central tendency
exposure was calculated using the 50th percentile and the maximum was presented as the high-end
exposure estimate. For datasets with two data points, the midpoint was presented as a midpoint value
and the higher of the two values was presented as a higher value. Finally, data sets with only one data
point presented the value as a what-if exposure. For datasets including exposure data that were reported
as below the limit of detection (LOD), EPA estimated the exposure concentrations for these data,
following EPA's Guidelines for Statistical Analysis of Occupational Exposure Data (U.S. EPA. 1994b).
which recommends using the ^'=¦ if the geometric standard deviation of the data is less than 3.0 and
if the geometric standard deviation is 3.0 or greater. Specific details related to each occupational
exposure scenario can be found in Section 2.
Air concentrations may be a point estimate (i.e., a single descriptor or statistic, such as central tendency
or high-end) or a full distribution. EPA will consider three general approaches for estimating air
concentrations:
Deterministic calculations: EPA will use combinations of point estimates of each model
parameter to estimate a central tendency and high-end for air concentration. EPA will document
the method and rationale for selecting parametric combinations to be representative of central
tendency and high-end.
Probabilistic (stochastic) calculations: EPA will pursue Monte Carlo simulations using the full
distribution of each parameter to calculate a full distribution of the air concentration results and
selecting the 50th and 95th percentiles of this resulting distribution as the central tendency and
high-end, respectively.
Combination of deterministic and probabilistic calculations: EPA may have full distributions for
some parameters but point estimates of the remaining parameters. For example, EPA may pursue
Monte Carlo modeling to estimate exposure concentrations, but only have point estimates of
working years of exposure, exposure duration and frequency, and lifetime years. In this case,
EPA will document the approach and rationale for combining point estimates with distribution
results for estimating central tendency and high-end results.
EPA follows the following hierarchy in selecting data and approaches for estimating other dermal input
parameters:
1. Monitoring data (in general, for weight fractions of NMP, glove usage information, and exposure
durations).
2. Industry data:
a. Data provided directly by industry (i.e., public comments, reports written by the company
where the data originates from, safety datasheets [SDSs])
b. Industry data from an indirect source (i.e., government documents, other risk assessment
reports, online vendors [for weight fractions of NMP])
3. Values from the 2011 edition of EPA's Exposure Factors Handbook (U.S. EPA 2011).
4. Assumptions.
1.4.3.2 Approach for this Risk Evaluation
For most exposure parameters, EPA did not find enough data to determine statistical distributions of the
actual exposure parameters. As described in Section 1.4.3, ideally, EPA would like to know 50th and
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95th percentiles for each parameter. However, where these percentiles were unavailable, EPA used
substitutes such as mid-ranges or high-ends. These substitutes were highly uncertain and not ideal
substitutes for the percentiles. EPA could not determine whether these values were suitable to represent
statistical distributions of real-world scenarios.
Parameters were selected for the most sensitive populations: pregnant women, females of reproductive
age who may become pregnant, and males.
1.4.3.2.1 Weight Fraction of NMP
EPA determined the weight fraction of NMP in various products through information provided in the
available literature, previous risk assessments and the 2017 NMP Market Profile (Abt 2017). This
Market Profile was prepared in part by searching Safety Data Sheets (SDSs) of products that contain
NMP and compiling the associated name, use, vendor and NMP concentration associated with each of
these products. Where a data point was provided as range of NMP concentrations for a certain product
(e.g., paints and coatings), EPA utilized the mid-range (middle) and high-end (maximum) weight
fractions to estimate potential exposures. Where multiple data points for a given type of product (e.g.,
paints and coatings) were available, EPA estimated exposures using the central tendency (50th
percentile) and high-end (95th percentile) NMP concentrations.
1.4.3.2.2 Skin Surface Area
EPA has no reasonably available information on actual surface area of contact with liquids. For both
consumer and occupational user dermal exposure for liquid contact, EPA assumed skin surface area
values both for the hands of females and for the hands of males, obtained from the 2011 edition of
EPA's Exposure Factors Handbook (Table 7-13) (U.S. EPA 2011). These values are assumed to
represent adequate surrogates for most uses' central tendency and high-end surface areas of contact with
liquid that may sometimes include exposures to much of the hands and also beyond the hands, such as
wrists, forearms, neck, or other parts of the body. These values overestimate exposures for younger
members of the workforce whose hand surface areas would be smaller. One exception is for the OES
that includes Writing, 1 cm2 was assumed based on a literature estimate for writing inks (Australian
Government Department of Health. 2016). For the remainder of the occupational dermal exposure to
liquid assessment, EPA used the following values:
High-end value, which represents two full hands exposed to a liquid: 890 cm2 (female), 1,070
cm2 (males), and
Central tendency value, which is half of two full hands (equivalent to one full hand) exposed to a
liquid and represents only the palm-side of both hands exposed to a liquid: 445 cm2 (females),
535 (males).
ONUs are not expected to have direct contact with NMP-based liquid products unless an incident (e.g.,
spill) were to occur. However, PBPK modeling of ONU (no liquid contact) used a skin surface area
value of 0.1 cm2 (about 0.1% of values used for occupational users) for liquid exposure to prevent a
division by zero error in model equations.
For dermal exposure to vapor for both occupational users and ONUs, the PBPK modeled up to 25% of
the total skin surface area, corresponding to the face, neck, arms and hands, as exposed to and capable of
absorbing vapors, minus any area covered by personal protection equipment (PPE). This area, which is
programmed into the PBPK model, is not a variable input value. For semiconductor industry fab
workers, additional PBPK modeling was conducted that assumed 2% of total skin surface area exposed.
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1.4.3.2.3 Glove Usage
Glove protection factors (PFs) are also inputs into the PBPK model. Where workers wear gloves,
workers are exposed to NMP-based product that penetrates the gloves, including potential seepage
through the cuff from improper donning of the gloves, permeation of NMP through the glove material,
and the gloves may occlude the evaporation of NMP from the skin. Where workers do not wear gloves,
workers are exposed through direct contact with NMP.
Overall, EPA understands that workers may potentially wear gloves but does not know the likelihood
that workers wear gloves of the proper type and have training on the proper usage of gloves. Some
sources indicate that workers wear chemical-resistant gloves (NIOSH. 2014; Meier et al.. 2013). while
others indicate that workers likely wear gloves that are more permeable than chemical-resistant gloves
(RIVM. 2013). For most occupational exposure scenarios, no information on employee training was
found; if information was found for a scenario, this information is presented in the appropriate
subsection of Section 2. Data on the prevalence of glove use is not available for most uses of NMP. For
semiconductor manufacturing and lithium ion cell manufacturing, public comments provided
information indicating that all employees wear gloves when performing tasks involving NMP, indicating
that the glove material is chosen to be resistant to NMP and that employees receive training on proper
glove usage, donning, and doffing before working with NMP (SIA, EaglePicher Technologies. 2020a;
Intel Corporation. 2019; 2019a). One anecdotal survey of glove usage among workers performing
graffiti removal indicates that 87% of workers wear gloves, although the glove materials varied and
were sometimes not protective; only a small fraction of these workers used gloves made of optimal
material for protection against NMP and some used cloth or leather gloves (Anundi et al.. 2000).
Prior to the initiation of this risk evaluation, EPA had gathered information in support of understanding
glove use for handling pure NMP and for paint and coatings removal using NMP formulations. This
information may be generally useful for a broader range of uses of NMP and is presented for illustrative
purposes in Appendix E of the Risk Evaluation. SDSs found by EPA recommend glove use. Initial
literature review suggests that there is unlikely to be sufficient data to justify a specific probability
distribution for effective glove use for a chemical or industry. Instead, the impact of effective glove use
is explored by considering different protection factors, which are further discussed below and compiled
in Table 1-1.
Gloves only offer barrier protection until the chemical breaks through the glove material. Using a
conceptual model, Cherrie (2004) proposed a glove workplace protection factor (PF) - the ratio of
estimated uptake through the hands without gloves to the estimated uptake though the hands while
wearing gloves: this protection factor is driven by glove usage practices and by flux, which varies with
time. The ECETOC TRA v3 model represents the protection factor of gloves as a fixed, assigned
protection factor equal to 5, 10, or 20 (Marquart et al.. 2017). Given the limited state of knowledge
about the protection afforded by gloves in the workplace, it is reasonable to utilize the PF values of the
ECETOC TRA v3 model (Marquart et al.. 2017). rather than attempt to derive new values. EPA also
considered potential dermal exposure to liquid in cases where exposure is occluded. If occlusion were to
occur, contact duration would be extended and glove protection factors could be reduced, although such
extensions and reductions could not be quantified for this evaluation due to lack of data.
EPA conducted modeling of exposures for the full range of dermal contacts including no glove use, non-
protective glove use, and protective glove use (using PFs of 1, 5, 10, and 20) to determine impacts on
exposures as what-if scenarios. For the purpose of PBPK modeling, PFs were assumed to reduce
workers' surface areas of contact with liquids (i.e., surface areas of contact were divided by PF values).
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Table 1-1. Glove Protection Factors for Different Dermal Protection Strategies from ECETOC
I R A v3
Dermal Protection Characteristics
Setting
Protection Factor,
PF
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
1.4.3.2.4 Duration of Dermal Contact with Liquids
EPA found no reasonably available data on actual duration of dermal contact with liquids. In lieu of
dermal duration data or task-based durations from inhalation monitoring data, EPA assumed a minimum
duration of 1 hour/day, which is a reasonable assumption considering the initial contact time with the
formulation containing NMP plus the time after direct contact when the thin film evaporates from and
absorbs into the skin. EPA assumed a high-end value of 8 hours/day (i.e., a full shift). As a central
tendency estimate, EPA assumed a mid-range value of 4 hours/day (the calculated mid-point of 4.5 was
rounded to 4 hours/day). The low-end and high-end values are consistent with EPA's documented
standard model assumptions for occupational dermal exposure modeling (U.S. EPA. 1991). Where
available, EPA utilized durations from the available task-based inhalation monitoring data and modeling
estimates as well as from estimates of task durations for generating what-if exposure scenarios assuming
that the workers were contacting NMP-containing liquids over only the entire task duration.
1.4.3.2.5 Air Concentration for Inhalation and Vapor-through-Skin Exposure
EPA reviewed workplace inhalation monitoring data collected by government agencies such as OSHA
and NIOSH, and monitoring data found in published literature (i.e., personal exposure monitoring data
and area monitoring data). Data were evaluated using the evaluation strategies laid out in the Application
of Systematic Review in TSCA Risk Evaluations (U.S. EPA. 2018a). Where available, EPA used air
concentration data and estimates found in government or published literature sources to serve as inputs
to the PBPK modeling for occupational exposures to NMP. There is not a known correlation between
weight fraction of NMP in the material being handled / used and the concentration of NMP in air. Where
air concentration data were not available, data for the use of NMP in similar but different work activities
(surrogate approach) or modeling estimates were used. Details on which approaches and models EPA
used are included in Section 2 for the applicable OESs and discussion of the uncertainties associated
with these approaches and models is included in Section 3.2.
Inhalation data sources did not usually indicate whether NMP exposure concentrations were for
occupational users or nearby occupational non-users. In these cases, EPA assumed that inhalation
exposure data were applicable for a combination of users and nearby occupational non-users (ONUs);
EPA used the same air concentration estimates for both occupational users and ONUs. While some
ONUs may have lower inhalation and vapor-through-skin exposure than users, especially when they are
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further away from the source of exposure, EPA assumed that ONUs that may be near workers handling
NMP.
For PBPK modeling, the duration of inhalation and vapor-through-skin exposure must equal the duration
of dermal contact with liquid. Therefore, where these two exposure durations were not equal, EPA
adjusted air concentrations by multiplying by a ratio of duration of the air concentration averaging time
to duration of dermal contact with liquid, which is discussed above. These adjusted air concentrations
are also called "duration-based air concentrations."
Few literature sources indicate the use of respirators for reducing worker exposures to NMP by
inhalation. Therefore, EPA central tendency and high-end scenarios do not incorporate protection factors
for respirator use. Regarding respirator use, only one of the NMP studies containing worker inhalation
data specified the type of respirator used by the workers in the study. This respirator, a half mask air-
purifying respirator with organic vapor cartridges (NIOSH. 19931 is classified as having an assigned
protection factor (APF) of 10. Therefore, EPA conducted additional modeling representing scenarios
below central tendency for the use of respirators providing an APF of 10. This modeling reduces
inhalation concentrations by a factor of 10 as intended when this type of respirator is used in accordance
with OSHA's Respiratory Protection standard (29 CFR 1910.134). While respirators with other APFs
may be used, EPA only included this APF in additional modeling. The results of this additional
modeling are shown in Section 4 of the Risk Evaluation.
1.4.3.2.6 Body Weight
Both the consumer and occupational dermal exposure to liquid assessments used the 50th percentile
body weight value for pregnant women in their first trimester, which is 74 kg, and for males, which is 88
kg, for both the central tendency and high-end exposure scenarios. EPA obtained this value from the
2011 edition of EPA's Exposure Factors Handbook (Table 8-29) (U.S. EPA 2011).
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2 Engineering Assessment
The following sections will contain process descriptions and the specific details (worker activities,
analysis for determining number of workers, exposure assessment approach and results, release sources,
media of release, and release assessment approach and results) from the assessment for each
release/exposure scenario.
2.1 Manufacturing
2.1.1 Process Description
NMP can be manufactured using multiple reaction pathways and relevant different processing steps.
One method involves reaction of butyrolactone with an excess of pure or aqueous methylamine in a
high-pressure tube ( iSDB. 2017; PubC'hem. 2017; Harreus et al.. 20] I; TURI. 1996). This reaction is
shown in Figure 2-1 and is taken from (Anderson and Liu. 2000). This exothermic reaction takes place
under adiabatic conditions and produces a reaction product containing NMP that is subsequently
distilled to purify the produced NMP. This method of manufacturing results in a 97% yield of NMP
(Harreus et al.. 2011).
o
+ CH3NH2 ^ HO(CH2)3CNHCH3 - I I + h2o
0^0 N^O
CH3
Figure 2-1. NMP Manufacturing Under Adiabatic Conditions
Another similar process for manufacturing NMP involves reacting gamma-butyrolactone (GBL) and
monom ethyl amine (MMA), as shown in Figure 2-2 (Johnson Matthev Process Technologies. 2017).
This reaction is non-catalyzed and takes place in two stages. The first stage produces a long-chain amide
that is cyclized, then dehydrated to form NMP during the second stage of the reaction. The reaction
product that contains NMP is then distilled to purify the NMP.
6
H
+ NCH, » Nn^° + H20
J CH,
gamma butyrolactone MMA n-methyl-2-pyrrolidone water
(GBL) (NMP)
Figure 2-2. NMP Manufacturing Using Gamma-Butyrolactone (GBL) and Monomethylamine
(MMA)
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Other methods of NMP manufacturing include high pressure synthesis from acetylene and formaldehyde
(HSDB. 2017; TURI. 1996) carbonylation of allylamine (Harreus et al.. 201 1). and hydrogenation of
maleic anhydride or succinic acid and methylamine (HSDB. 2017; Mitsubishi Chemical 2017).
Methods of manufacturing may depend on the specifications for the end product. For example, higher
purities of NMP are generally required for electronic applications (U.S. EPA. 2017b).
2.1.2 Exposure Assessment
2.1.2.1 Worker Activities
Workers are potentially exposed to NMP during the manufacture of NMP from sampling, equipment
maintenance, cleaning activities, and loading NMP into containers (RIVM. 2013). These activities are
all potential sources of worker exposure through dermal contact to liquid, vapor-through-skin, and
inhalation of NMP vapors.
The 2013 Netherlands' National Institute for Public Health and the Environment (RIVM) Proposal for
Restriction - NMP report indicates that the production, storage, and bulk transfers of NMP are all
conducted within closed systems (RIVM. 2013). In addition, this report indicates that bulk transfers of
NMP may occur with either open or closed transfer lines. Filling of smaller containers is expected to
occur at dedicated filling points equipped with ventilation.
The RIVM Annex XV Proposal for a Restriction - NMP report indicates that sites that manufacture NMP
are expected to implement local exhaust ventilation (LEV) and wear proper chemical-specific personal
protective equipment, including appropriate gloves (RIVM. 2013). Specifically, workers wear gloves
with an assigned protection factor (APF) of 5 (80 percent exposure reduction) (RIVM. 2013). EPA did
not find information that indicates the extent that engineering controls and worker PPE are used at
facilities that manufacture NMP in the United States.
ONUs include employees that work at the sites where NMP is manufactured, but they do not directly
handle the chemical and are therefore expected to have lower inhalation exposures and vapor-through-
skin uptake and are not expected to have dermal exposures by contact with liquids. ONUs for this
scenario include supervisors, managers, and other employees that may be in the production areas but do
not perform tasks that result in the same level of exposures as those workers that engage in tasks related
to the manufacturing of NMP.
2.1.2.2 Number of Potentially Exposed Workers
EPA estimated the number of workers and occupational non-users potentially exposed to NMP at
manufacturing sites using 2016 CDR data (where available), 2016 TRI data (where available), Bureau of
Labor Statistics' OES data (U.S. BLS. 2016) and the U.S. Census' SUSB (U.S. Census Bureau. 2015).
The method for estimating number of workers from the Bureau of Labor Statistics' OES data and U.S.
Census' SUSB data is detailed in Appendix B.l. These estimates were derived using industry- and
occupation-specific employment data from the BLS and U.S. Census.
The 2016 CDR non-CBI results identify a total of 33 sites that manufacture, import, or both manufacture
and import NMP (U.S. EPA. 2016a). Of these 33 sites, five sites report domestic manufacture of NMP
and an additional six sites claim the domestic manufacture/import activity field as either CBI or
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withheld.1 To try to determine whether the remaining six CDR sites were manufacturers or importers,
EPA mapped the sites to 2016 TRI data using the facility names and addresses but did not find these
sites in 2016 TRI (reporting releases of NMP) (U.S. EPA. 2016b). EPA assumed that these six sites for
which the activity could not be determined through CDR or TRI may import or manufacture NMP.
Therefore, there may be up to 11 sites that domestically manufacture NMP.
Of these 11 sites, one site reports that there are at least 50 but fewer than 100 workers potentially
exposed to NMP, three sites report that there are at least 100 but fewer than 500 workers potentially
exposed to NMP, and one site reports that there are at least 500 but fewer than 1,000 workers potentially
exposed to NMP. The remaining sites claim number of worker estimates as CBI. EPA compiled these
worker estimates in Table 2-1.
In addition to worker estimates from the 2016 CDR results, EPA compiled the number of workers and
ONUs for NAICS code 325199 in Table 2-1 using data obtained from the BLS. To determine the
number of workers potentially exposed, EPA used one less than the range of number of workers
reported in the 2016 CDR for the manufacturing sites that reported worker information as non-CBI. For
the CDR submissions that claimed number of workers as CBI and for the additional sites identified per
2016 TRI data, EPA used the number of workers estimate from the BLS data for NAICS code 325199.
To determine the number of ONUs potentially exposed, EPA used the ratio of ONUs to workers from
BLS data multiplied by the total number of workers estimated with BLS and CDR data. Note that these
estimates may be overestimates of the actual number of employees potentially exposed to NMP.
Table 2-1. US Number of Establishments and Employees for Manufacturing
Source
Number of
Establishments
Number of
Workers per Site
Number
of ONUs
per Site
(U.S. BLS. 2016) data for NAICS 325199. All Other
Basic Organic Chemical Manufacturing
Not included in
this estimate
39a
18a
2016 CDR results indicate up to 11 sites manufacture
NMP
1
at least 50 but
fewer than 100 b
Unknown
- used
BLS
estimate
3
at least 100 but
fewer than 500 b
1
at least 500 but
fewer than 1,000 b
6
Unknown - used
BLS estimate
Total establishments and number of potentially exposed
workers and ONUs = c
11
2,800
200d
a Rounded to the nearest whole number.
b EPA uses one less than the upper end of this range for worker calculations (i.e., for "at least 50 but fewer than 100 workers,
EPA assumes 99 workers).
0 Totals may not add exactly due to rounding to two significant figures.
d EPA used the number of ONUs per site from BLS data to calculate the total number of ONUs using CDR estimate for
number of sites.
1 Manufacturers (including importers) are required to report under CDR if they meet certain production volume thresholds,
generally 25,000 lb or more of a chemical substance at any single site. Reporting is triggered if the annual reporting threshold
is met during any of the calendar years since the last principal reporting year. In general, the reporting threshold remains
25,000 lb per site. However, a reduced reporting threshold (2,500 lb) now applies to chemical substances subject to certain
TSCA actions, https://www.epa.gov/chemical-data-reporting/how-report-under-chemical-data-reporting
Page 26 of 292
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2.1.2.3 Occupational Exposure Assessment Methodology
In the occupational exposure assessment for this scenario, EPA assesses potential exposure from the
loading of various containers (i.e., drums, tank trucks, rail cars) with pure NMP. While EPA does expect
that workers may perform additional activities during this scenario, such as sampling or maintenance
work, EPA expects that loading activities present the largest range of potential exposures.
2.1.2.3.1 Inhalation and Vapor-Through-Skin
Due to the lack of monitoring data in the published literature, EPA used modeling estimates, as further
described below.
EPA found no monitoring data specific to the manufacture of NMP. EPA found European modeling
estimates for the manufacturing of NMP in the RIVM Annex Xl^ Proposal for a Restriction - NMP
report (RIVM. 2013). EPA modeled potential NMP air concentrations during the loading of bulk storage
containers (i.e., tank trucks and rail cars) and drums using the Tank Truck andRailcar Loading and
Unloading Release and Inhalation Exposure Model and the Dram Loading and Unloading Release and
Inhalation Exposure Model and compared them to the European modeled exposures. The Tank Truck
and Railcar Loading and Unloading Release and Inhalation Exposure Model involves deterministic
modeling and the Drum Loading and Unloading Release and Inhalation Exposure Model involves
probabilistic modeling. See Appendix B.2 and B.3 for additional details on the bulk container loading
modeling and the drum loading modeling, respectively.
EPA's modeled exposure concentrations for loading NMP into bulk containers are similar in value and
the same order of magnitude as those modeled by RIVM for closed-system NMP transfers. EPA's
modeled exposure concentrations for loading NMP into drums are the same magnitude but higher in
value than those modeled by RIVM for open-system NMP transfers. EPA's modeled concentrations
represent a larger range of potential NMP air concentrations than those presented by RIVM. EPA
assessed the range of NMP air concentrations modeled by EPA for this scenario. The discussed
inhalation monitoring data as well as the RIVM and EPA's modeled exposure concentrations are
summarized and further explained in Appendix A. 1.
The NMP air concentrations modeled by EPA for loading of 100% NMP are summarized into the input
parameters used for the PBPK modeling in Table 2-2. The container loading models used by EPA
calculate what-if (duration-based) concentrations, with the exposure duration equal to the task duration
of the loading event (for bulk containers, central tendency case is 0.5 hours for loading tank trucks and
high-end is 1 hour for loading rail cars; for drums, 20 containers are loaded per hour and the duration
was determined based on the throughput of NMP at a site [refer to Appendix A. 1 for further
explanation]) and number of loading events per day. EPA calculated the 8-hour TWA exposures as the
weighted average exposure during an entire 8-hour shift, assuming zero exposure during the remainder
of the shift.
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Table 2-2. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Manufacturing i
Work
Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hour
TWA)
(mg/m3)
Loading
NMP into
bulk
containers
Central tendency
(50th percentile)
0.047
0.76 (duration =
0.5 hour)
Tank Truck and
Railcar Loading and
Unloading Release
and Inhalation
Exposure Model (U.S.
EPA. 2015b)
Not
applicable3
High-end (95th
percentile)
0.19
1.52 (duration = 1
hour)
Loading
NMP into
drums
Central tendency
(50th percentile)
0.427
1.65 (duration =
2.06 hour)
EPAOAOPS AP-42
Loading Model and
EPA/OPPTMass
Balance Model (U.S.
EPA. 2015b)
High-end (95th
percentile)
1.51
5.85 (duration =
2.06 hour)
" EPA models are standard sources used by RAD for engineering assessments. EPA did not systematically review models that
were developed by EPA.
EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from NMP manufacturing. Since ONUs do not directly handle NMP (otherwise they would
be considered workers), ONU inhalation exposures could be lower than worker inhalation exposures.
Information on activities where ONUs may be present are insufficient to determine the proximity of
ONUs to workers and sources of emissions, so relative exposure of ONUs to workers cannot be
quantified.
2.1.2.3.2 Dermal Exposure to Liquid
Table 2-3 summarizes the parameters used to assess dermal exposure to liquid during the manufacturing
of NMP. EPA assesses dermal exposure to liquid NMP at the specified concentration weight fraction,
skin surface area, and duration of contact with liquid, based on the methodology described below.
During the manufacturing of NMP, workers are potentially exposed during sampling, maintenance, and
loading (packaging) activities. For this scenario, EPA assessed dermal exposures to liquid during the
loading of pure NMP into bulk containers and into drums. See below for additional information.
NMP Weight Fraction
For this scenario, EPA gathered NMP concentration data from the non-CBI 2016 CDR results and
literature, which is summarized in Appendix D. The 2016 CDR results include four submissions with
non-CBI concentration data that indicate NMP is manufactured at least 90 weight percent NMP (U.S.
EPA. 2016a). Because CDR reporting is in ranges, the category for at least 90 weight percent includes
those products that are between 90 and 100 weight percent. The RIVM Annex XV Proposal for a
Restriction - NMP report indicates that manufactured NMP is sold at a purity of at least 80 weight
percent and up to 100 weight percent (RIVM. 2013). Other sources indicate manufactured NMP is sold
at a purity of 99.8 (TURI. 1996) and up to 100 weight percent NMP per 2012 CDR (U.S. EPA. 2012).
All underlying data from these sources have an overall confidence rating of high. Based on this
information, EPA assesses dermal exposures to liquid with 100 weight percent NMP, as a likely
exposure scenario.
Page 28 of 292
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Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (4 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (8 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. For the loading of bulk containers, EPA assesses a what-if duration of contact with
liquid of half an hour and one hour, based on the central tendency and high-end scenarios assessed for
inhalation and vapor-through-skin exposure during the loading of a tank truck and rail car, respectively.
For loading of drums, EPA assesses a what-if task duration of 2.06 hours, based on annual NMP
throughput at each site (determined from the production volume and number of sites from 2016 CDR),
250 days of operation per year, and a loading rate of 20 drums per hour. Refer to Appendix A.l for
additional information on this task duration.
Table 2-3. Summary of Parameters for Worker Dermal Exposure to Liquids During
Manufacturing
Work Activity
Parameter
Characterization
NMP
Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Central Tendency
1
445 (f)
535 (m)
4
Loading NMP into
High-end
1
890 (f)
1,070 (m)
8
74 (f)
bulk containers
What-if (duration-
based)
1
445 (f)
535 (m)
0.5
88 (m)
What-if (duration-
based)
1
890 (f)
1,070 (m)
1
Central Tendency
1
445 (f)
535 (m)
4
Loading NMP into
High-end
1
890 (f)
1,070 (m)
8
74 (f)
drums
What-if (duration-
based)
1
445 (f)
535 (m)
2.06
88 (m)
What-if (duration-
based)
1
890 (f)
1,070 (m)
2.06
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.1.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-4.
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The numeric parameters corresponding to the characterizations presented in Table 2-4 are summarized
in Table 2-5. These are the inputs used in the PBPK model.
Table 2-4. Characterization of PBPK Model Input Parameters
'or Manufacturing of NMP
Scenario
Work
Activity
Air Concentration
Data
Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
Loading of
bulk
containers
Central tendency (50th
percentile)
Half shift (4
hours)
1-hand
N/A - 100% is
assumed
High-end
Loading of
drums
High-end (95th
percentile)
Full shift (8
hours)
2-hand
N/A - 100% is
assumed
What-if
(duration-
based)
Loading of
bulk
containers
Central tendency (50th
percentile
Duration
calculated by
model
1-Hand
N/A - 100% is
assumed
What-if
(duration-
based)
Loading of
drums
High-end (95th
percentile)
Duration
calculated by
model
2-hand
N/A - 100% is
assumed
Table 2-5. PBPK Mode Input Parameters for Manufacturing of NMP
Scenario
Work
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration
of Contact
with
Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2) a,b'c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Loading of
bulk
containers
0.10
4
445 (f)
535 (m)
1
74 (f)
88 (m)
High-end
Loading of
drums
1.51
8
890 (f)
1,070 (m)
1
74 (f)
88 (m)
What-if (duration-based)
Loading of
bulk
containers
0.76
0.5
445 (f)
535 (m)
1
74 (f)
88 (m)
What-if (duration-based)
Loading of
drums
5.85
2.06
890 (f)
1,070 (m)
1
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g., 1, 5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.1.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.2 Repackaging
2.2.1 Process Description
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In general, commodity chemicals are imported into the United States in bulk via water, air, land, and
intermodal shipments (Tomer and Kane. 2015). These shipments take the form of oceangoing chemical
tankers, railcars, tank trucks, and intermodal tank containers. Chemicals shipped in bulk containers may
be repackaged into smaller containers for resale, such as drums or bottles. Domestically manufactured
commodity chemicals may be shipped within the United States in liquid cargo barges, railcars, tank
trucks, tank containers, intermediate bulk containers (IBCs)/totes, and drums. Both imported and
domestically manufactured commodity chemicals may be repackaged by wholesalers for resale; for
example, repackaging bulk packaging into drums or bottles.
The exact shipping and packaging methods specific to NMP are not known. For this risk evaluation,
EPA assesses the repackaging of NMP from bulk packaging to drums at wholesale repackaging sites
(see Figure 2-3).
Figure 2-3. General Process Flow Diagram for Repackaging
This scenario includes the repackaging of both pure NMP and formulations containing NMP.
2.2.2 Exposure Assessment
2.2.2.1 Worker Activities
During repackaging, workers are potentially directly 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). These activities are potential sources of worker exposure through dermal contact to
liquid, vapor-through-skin, and inhalation of NMP vapors. Workers are also potentially directly exposed
through the same pathways to incidental leaks or spills. Workers near loading racks and container filling
stations are potentially exposed to fugitive emissions from equipment leaks and displaced vapor as
containers are filled.
The RIVM Annex XV Proposal for a Restriction - NMP report recommends that workers conducting
repackaging activities wear gloves with an assigned protection factor (APF) of 5 (80 percent exposure
reduction) (RIVM. 2013). This report also indicates that LEV may be employed but is not customary.
EPA did not find information that indicates the extent that engineering controls and worker PPE are used
at facilities that repackage NMP in the United States.
ONUs include employees that work at the site where NMP is repackaged, but they do not directly handle
the chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin
uptake and are not expected to have dermal exposures by contact with liquids. 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.
2.2.2.2 Number of Potentially Exposed Workers
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EPA estimated the number of workers and occupational non-users potentially exposed to NMP at
repackaging sites using 2016 CDR data (where available), 2016 TRI data (where available), Bureau of
Labor Statistics' OES data (U.S. BLS, 2016) and the U.S. Census' SUSB (U.S. Census Bureau. 2015).
The method for estimating number of workers from the Bureau of Labor Statistics' OES data and U.S.
Census' SUSB data is detailed in Appendix B.l. These estimates were derived using industry- and
occupation-specific employment data from the BLS and U.S. Census.
The 2016 CDR non-CBI results identify a total of 33 sites that manufacture, import, or both manufacture
and import NMP (U.S. EPA 2016a). Of these 33 sites, there are at least 22 and up to 29 sites that
manufacture NMP, with the exact number unknown due to CBI claims.2 EPA assumes that the sites
claiming CBI may either import or domestically manufacture NMP. Of these 29 sites, eight submissions
report that NMP is imported and never at the site. EPA assumes that these eight sites do not conduct
repackaging activities. Of the remaining 21 sites, EPA mapped these sites to 2016 TRI data and found
that one of these sites does not repackage NMP, one site does repackage NMP, and the remaining sites
were not identified in TRI (EPA assumes these sites repackage NMP). Thus, EPA assumes 20 sites
import and repackage NMP, per 2016 CDR results. Of the 21 import and repackaging sites, six sites
report that there are fewer than 10 workers potentially exposed to NMP, one site reports at least 10 but
fewer than 25 workers, five sites report at least 50 but fewer than 100 workers, and one site reports that
there are at least 100 but fewer than 500 workers potentially exposed to NMP. The remaining sites claim
number of workers estimates as CBI or not known or reasonably ascertainable. EPA compiled these
worker estimates in Table 2-6.
EPA determined additional sites that potentially repackage NMP using 2016 TRI results. Specifically,
EPA first identified the sites reporting operations under NAICS code 424690, Other Chemical and
Allied Products Merchant Wholesalers, and removed those sites that reported to and are captured in the
2016 CDR results. EPA then identified those sites that report repackaging operations occur, leaving 12
sites.
In addition to worker estimates from the 2016 CDR results, EPA compiled the number of workers and
ONUs for NAICS code 424690 in Table 2-6 using data obtained from the BLS. To determine the
number of workers potentially exposed, EPA used the one less than the range of number of workers
reported in the 2016 CDR for the sites that reported worker information as non-CBI. For the CDR
submissions that claimed number of workers as CBI and for the additional sites identified per 2016 TRI
data, EPA used the number of workers estimate from the BLS data for NAICS code 424690. To
determine the number of ONUs potentially exposed, EPA used the ratio of ONUs to workers from BLS
data multiplied by the total number of workers estimated with BLS and CDR data. Note that these
estimates may be overestimates of the actual number of employees potentially exposed to NMP.
2 Manufacturers (including importers) are required to report under CDR if they meet certain production volume thresholds,
generally 25,000 lb or more of a chemical substance at any single site. Reporting is triggered if the annual reporting threshold
is met during any of the calendar years since the last principal reporting year. In general, the reporting threshold remains
25,000 lb per site. However, a reduced reporting threshold (2,500 lb) now applies to chemical substances subject to certain
TSCA actions, https://www.epa.gov/chemical-data-reporting/how-report-under-chemical-data-reporting
Page 32 of 292
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Table 2-6. US Number of Establishments and Employees for Re
Source
Number of
Establishments
Number of Workers per
Site
Number
of ONUs
per Site
(U.S. BLS. 2016) data for NAICS 424690.
Other Chemical and Allied Products
Merchant Wholesalers
Not included in this
estimate
la
la
Per 2016 CDR results, there are up to 29 sites
that import (21 sites with NMP at the site and
8 with NMP never at site). Per 2016 TRI
data, one of these sites does not repackage,
one site does repackage, and the remaining
sites were not identified in the TRI. EPA
assumes the unidentified sites repackage
NMP. Thus, 20 sites repackage NMP.
6
fewer than 10 b
Unknown
- used
BLS
estimate
1
at least 10 but fewer than
25 b
5
at least 50 but fewer than
100 b
1
at least 100 but fewer
than 500 b
7
Unknown - used BLS
estimate
The 2016 TRI identifies 43 sites reporting
operations under NAICS code 424690.
Excluding those sites included in the 2016
CDR and only including those reporting
repackaging operations results in 12 sites.
12
Unknown - not reported
in TRI - used BLS
estimate
Total establishments and number of
potentially exposed workers and ONUs = c
32 d
1,100
14 e
)ackaging
a Rounded to the nearest whole number. Exact values are 1.3 workers and 0.45 ONUs.
b EPA uses one less than the upper end of this range for worker calculations (i.e., for "at least 50 but fewer than 100 workers,
EPA assumes 99 workers),
c Totals may not add exactly due to rounding to two significant figures.
d EPA assumes the sum of sites reported in 2016 CDR and 2016 TRI.
e EPA used the number of ONUs from BLS data to calculate the total number of ONUs based on the number of sites per
CDR.
2.2.2.3 Occupational Exposure Assessment Methodology
2.2.2.3.1 Inhalation and Vapor-Through-Skin
EPA compiled the same monitoring and modeled exposure concentration data for this scenario as for
manufacturing. These data are summarized in Appendix A.2. As described in the previous scenario,
Section 2.1.2.3.1, due to the lack of monitoring data and modeling estimates found in the published
literature, EPA used modeling estimates with the highest data quality for this use, as further described
below.
EPA summarized in Appendix A.2 the modeled NMP air concentrations during the manufacturing of
NMP, for closed- and open-system transfers of NMP, that were presented in the RIVM Annex XV
Proposal for a Restriction - NMP report (RIVM. 2013).
Consistent with the approach EPA took in Section 2.1.2.3.1 for the manufacture of NMP, EPA modeled
potential NMP air concentrations during the unloading of bulk storage containers and drums using EPA
models. Details on this modeling approach are presented in Appendix A.2. EPA's modeled exposure
concentrations represent a larger range of potential NMP air concentrations than those presented by
RIVM; thus, EPA uses these modeled exposures in lieu of using the monitoring data or modeled
exposure in the RIVM Annex XV Proposal for a Restriction - NMP report. The inhalation monitoring
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data as well as the RIVM and EPA's modeled exposure concentrations are summarized and further
explained in Appendix A.2.
The NMP air concentrations modeled by EPA for unloading of 100% NMP are summarized into the
input parameters used for the PBPK modeling in Table 2-7. The container unloading models used by
EPA calculates what-if (duration-based) concentrations, with the exposure duration equal to the task
duration of the unloading event (for bulk containers, central tendency case is 0.5 hours for unloading
tank trucks and high-end is 1 hour for unloading rail cars; for drums, 20 containers are unloaded per
hour and the duration was determined based on the throughput of NMP at a site [refer to Appendix A.2
for further explanation]) and number of loading events per day. EPA calculated the 8-hour TWA
exposures to as the weighted average exposure during an entire 8-hour shift, assuming zero exposures
during the remainder of the shift.
The Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model involves
deterministic modeling and the Dram Loading and Unloading Release and Inhalation Exposure Model
involves probabilistic modeling. See Appendix B.2 and B.3 for additional details on the bulk container
unloading modeling and the drum unloading modeling, respectively.
Table 2-7. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure Repac
kaging
Work
Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hour
TWA)
(mg/m3)
Unloading
NMP from
bulk
containers
Central tendency
(50th percentile)
0.047
0.76 (duration =
0.5 hour)
Tank Truck and
Railcar Loading and
Unloading Release
and Inhalation
Exposure Model (U.S.
EPA. 2015b)
Not
applicable3
High-end (95th
percentile)
0.19
1.52 (duration = 1
hour)
Unloading
NMP from
drums
Central tendency
(50th percentile)
0.427
1.65 (duration =
2.06 hour)
EPA OAOPS AP-42
Loading Model and
EPA/OPPTMass
Balance Model (U.S.
EPA. 2015b)
High-end (95th
percentile)
1.51
5.85 (duration =
2.06 hour)
a EPA models are standard sources used by RAD for engineering assessments. EPA did not systematically review models that
were developed by EPA.
EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from repackaging of NMP. Since ONUs do not directly handle NMP (otherwise they would
be considered workers), ONU inhalation exposures could be lower than worker inhalation exposures.
Information on activities where ONUs may be present are insufficient to determine the proximity of
ONUs to workers and sources of emissions, so relative exposure of ONUs to workers cannot be
quantified.
2.2.2.3.2 Dermal Exposure to Liquid
Table 2-8 summarizes the parameters used to assess dermal exposure to liquid during the repackaging of
NMP and formulations containing NMP. EPA assesses dermal exposure to liquid NMP at the specified
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liquid weight fraction, skin surface area, and duration of contact with liquid, based on the methodology
described below. During the importation and repackaging of NMP, EPA assessed dermal exposure to
liquid during the unloading of pure NMP from bulk containers and drums. See below for additional
information.
NMP Weight Fraction
For this scenario, EPA gathered NMP concentration data from the non-CBI 2016 CDR results and
literature, which is summarized in Appendix D. The 2016 CDR results include 20 submissions with non-
CBI concentration data that indicate NMP is imported in formulations as low as less than one weight
percent NMP and up to 90 to 100 weight percent NMP (U.S. EPA 2016a). One public comment
indicates that NMP is imported in a primer formulation at five weight percent NMP (Haas. 2017).
Another source indicates NMP is imported at a purity of 100 weight percent NMP (U.S. EPA 2012).
The underlying data from all sources have overall confidence ratings of high. Based on this information,
using the midpoint when concentration data is available in a range, EPA calculated the 50th percentile
weight percent of NMP in imported products to be 95 weight percent. Based on the high 50th percentile
NMP concentration and EPA's expectation that bulk commodity chemicals are more likely to be
repackaged over formulations containing NMP (i.e., pure NMP is more likely to be repackaged than
formulations with lower NMP concentrations), EPA assesses dermal exposure to liquid at 100 weight
percent NMP.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (4 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (8 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. For the unloading of bulk containers, EPA assesses a what-if task duration of half an
hour, based on the central tendency scenario assessed for inhalation and vapor-through-skin exposure
during the unloading of a tank truck and rail car, respectively. For unloading of drums, EPA assesses a
what-if task duration of 2.06 hours, based on annual NMP throughput at each site (determined from the
production volume and number of sites from 2016 CDR), 250 days of operation per year, and an
unloading rate of 20 drums per hour. Refer to Appendix A.2 for additional information on this task
duration.
Table 2-8. Summary of Parameters for Worker Dermal Exposure to Liquids During Re
Work Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Unloading NMP
from bulk
containers
Central Tendency
1
445 (f)
535 (m)
4
74 (f)
High-end
1
890 (f)
1,070 (m)
8
88 (m)
jackaging
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Work Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
What-if (duration-
based)
1
445 (f)
535 (m)
0.1
74 (f)
88 (m)
What-if (duration-
based)
1
890 (f)
1,070 (m)
1
Unloading NMP
from drums
Central Tendency
1
445 (f)
535 (m)
4
74 (f)
88 (m)
High-end
1
890 (f)
1,070 (m)
8
What-if (duration-
based)
1
445 (f)
535 (m)
2.06
74 (f)
88 (m)
What-if (duration-
based)
1
890 (f)
1,070 (m)
2.06
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.2.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-9.
The numeric parameters corresponding to the characterizations presented in Table 2-9 are summarized
in Table 2-10. These are the inputs used in the PBPK model.
Table 2-9. Characterization of PBPK Model Inpu
Scenario
Work
Activity
Air Concentration
Data
Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
Unloading
NMP from
bulk
containers
Central tendency (50th
percentile)
Half shift (4
hours)
1-hand
N/A - 100% is
assumed
High-end
Unloading
NMP from
drums
High-end (95th
percentile)
Full shift (8
hours)
2-hand
N/A - 100% is
assumed
What-if
(duration-
based)
Unloading
NMP from
bulk
containers
Central tendency (50th
percentile)
Duration
calculated by
model
1-hand
N/A - 100% is
assumed
What-if
(duration-
based)
Unloading
NMP from
drums
High-end (95th
percentile)
Duration
calculated by
model
2-hand
N/A - 100% is
assumed
Parameters for Repackaging
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Table 2-10. PBPK Model Input Parameters for Repackaging
Scenario
Work
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration of
Contact
with Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central
Tendency
Unloading
NMP from
bulk
containers
0.10
4
445 (f)
535 (m)
1
74 (f)
88 (m)
High-end
Unloading
NMP from
drums
1.51
8
890 (f)
1,070 (m)
1
74 (f)
88 (m)
What-if
(duration-based)
Unloading
NMP from
bulk
containers
0.76
0.5
445 (f)
535 (m)
1
74 (f)
88 (m)
What-if
(duration-based)
Unloading
NMP from
drums
5.85
2.06
890 (f)
1,070 (m)
1
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g., 1, 5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.2.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.3 Chemical Processing, Excluding Formulation
2.3.1 Process Description
This scenario includes the use of NMP for processing activities other than formulation (i.e., non-
incorporative processing). Specifically, this may include the use of NMP as an intermediate, as a media
for synthesis, extractions, and purifications, or as some other type of processing aid. EPA identified the
following industries that use NMP in this manner (U.S. EPA 2016a; RIVM, 2013):
Agricultural chemical manufacturing,
Petrochemical manufacturing,
Polymer product manufacturing, and
Miscellaneous chemical manufacturing.
2.3.1.1 Agricultural Chemical Manufacturing
NMP is used for the manufacturing of agricultural chemicals, including fertilizers, fungicides,
insecticides, herbicides, and other types of pesticides (Abt, 2017; U.S. EPA 2017b; RIVM, 2013). NMP
is used in the synthesis of active ingredients for agricultural chemicals (Roberts, 2017; RIVM, 2013). A
public comment to the NMP risk evaluation docket from the NMP Producers Group details that NMP is
used as a solvent in the production of a fertilizer additive that prevents the volatilization of urea in
fertilizer formulations (Roberts, 2017). The NMP Producers Group indicates that the amount of NMP in
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the final fertilizer formulation is minimal (<0.1 percent). The RIVM Annex XV Proposal for a
Restriction - NMP report also indicates that, when NMP is used in the synthesis of active ingredients, it
is not expected to be in the final agricultural chemical formulation (RIVM. 2013).
NMP is also used in the formulation of agricultural chemicals such that it is present in the final
agricultural chemical formulation. Formulation activities are assessed in Section 2.4 of this risk
evaluation.
2.3.1.2 Petrochemical Manufacturing
NMP is used as a petrochemical processing aid in a variety of applications including extraction of
aromatic hydrocarbons from lube oils; separation and recovery of aromatic hydrocarbons from mixed
hydrocarbon feedstocks; recovery of acetylenes, olefins and diolefins; removal of sulfur compounds
from and dehydration of natural gas and refinery gases (Anderson and Liu. 2000).
NMP is used both for the extraction of unwanted aromatics from lube oils and the recovery of
hydrocarbons from feedstocks, via extractive distillation (ERM. 2017; HSDB. 2017; MacRov. 2017;
RIVM. 2013; ECHA. 2011). NMP is favorable for the extractive distillation of hydrocarbons because
hydrocarbons are highly soluble in NMP, and the use of NMP for extraction does not lead to the
formation of azeotropes.
Extractive distillation involves distillation in the presence of a solvent (or mixture of solvents) that acts
as a separating agent, displaying both a selectivity for and the capacity to solubilize components in a
mixture to be separated (Dohertv and Knapp. 2004). Solvents interact differently with the components of
the mixture to be separated, thereby altering their relative volatility and allowing them to be separated.
Solvents are added near the top of the extractive distillation column and the mixture to be separated is
added at a second feed point further down the column. The component with the higher volatility in the
presence of a solvent is distilled overhead as the distillate and components with lower volatility are
removed with the solvent in the column bottoms. The solvent is then separated from other components
of the mixture, generally through distillation in a second column, and then recycled back to the
extractive distillation column (Dohertv and Knapp. 2004).
Other uses of NMP in petrochemical processing involve using NMP to absorb specific compounds, then
separating the NMP from the absorbed compounds, similar to the extractive distillation process
(Anderson and Liu. 2000). Examples of absorptive processes include NMP use in the recovery of
acetylenes, olefins and diolefins; removal of sulfur compounds from natural and refinery gases; and the
dehydration of natural gas (HSDB. 2017; MacRov. 2017; RIVM. 2013; Anderson and Liu. 2000).
Absorption using a solvent, such as NMP, generally involves two towers, an absorption tower and a
removal tower. The mixture to be separated and the solvent are first introduced into the absorption
tower. The solvent then absorbs the miscible compound and this heavier stream leaves in the bottoms of
the column. The solvent mixture is then sent to another column where the absorbed compound is
recovered from the solvent. The solvent may undergo further processes, such as scrubbing, to be fully
regenerated before being recycled back into the absorption column (Gannon and Schaffer. 2003).
2.3.1.3 Polymer Manufacturing
NMP is also used the polymer industry as a polymerization media for a variety of polymers.
NMP is used as a polymerization media for the manufacturing of polyphenylene sulfide (PPS) and other
high-temperature polymers such as polyethersulfones, polyamideimides and polyaramids (HSDB. 2017;
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Materials. 2017; U.S. EPA. 2015c; RIVM. 2013). One public comment indicates that NMP is present at
below 17 ppm in produced PPS (Materials. 2017). Another public comment indicates that NMP may be
present at up to 1,500 ppm in resin pellets up to seven percent in resin powders (Roberts. 2017). EPA
expects that these quantities of NMP are driven off in subsequent compounding of the resins, which is
assessed in Section 2.4 of this risk evaluation.
Similarly, NMP is used as a processing aid in the production of polymer membranes (Roberts. 2017;
RIVM. 2013). Polymer membranes are produced by immersion precipitation in which a solution of
polymer, solvents, and other additives is immersed in a water bath to produce a polymer-based film from
which the solvent is removed into the water bath. This film is isolated and solidified to produce the
desired membrane that can be applied in gas separations, filtrations, and desalination processes (RIVM.
2013). Further, a public comment on the NMP risk evaluation docket indicates polymer particles
dispersed in NMP may be imported into the US for the production of polymer film via a gravure process
(Anonymous. 2017). NMP is not present in the produced polymer membranes and films in appreciable
quantities (Anonymous. 2017; Roberts. 2017).
NMP is particularly useful for the dissolving and repolymerization of difficult to dissolve polymers
(ACC. 2017; RIVM. 2013). NMP can be used to dissolve polymers at elevated temperatures and
precipitate them to form beads and pellets (ACC. 2017). Additionally, NMP is used in this capacity to
produce high-performance polymers that are used for ballistic protection by dissolving the polymer and
allowing reaction between an amine group and a carboxylic acid halide group before polymerization
(RIVM. 2013). Again, NMP is not expected to be present above residual quantities in these products
(RIVM. 2013).
Finally, a comment on the NMP risk evaluation docket indicates that NMP can be used in the polymer
manufacturing industry as a polymerization inhibitor (Kemira. 2018). Specifically, NMP is used in
additives containing phenothiazine. According to this public comment, these additives can contain NMP
at 35 or 65 weight percent. In the case of uncontrolled polymerization, these additives are injected into
the reaction vessels to cease the polymerization reaction and prevent vessel ruptures. This comment
indicates that, if these additives are uses, NMP is not expected to be present in the final polymer articles.
2.3.1.4 Miscellaneous
NMP may be used in additional industries as a chemical intermediate. The exact process operations
involved during the use of NMP as a chemical intermediate are dependent on the final product that is
being synthesized. For NMP use as a chemical intermediate, operations would typically involve
unloading NMP from transport containers and feeding it into reaction vessel(s), where the NMP would
either react fully or to a lesser extent. Following completion of the reaction, the produced substance may
or may not be purified further, thus removing unreacted NMP (if present). The reacted NMP is not
expected to be released to the environment or to present a potential for worker exposure. Any unreacted
NMP presents potential sources of release or exposure.
2.3.2 Exposure Assessment
2.3.2.1 Worker Activities
During the use of NMP as a reactant or other processing aid, workers are potentially exposed while
unloading NMP into intermediate storage or processing vessels, quality sampling of the NMP prior to
use, fugitive emissions from equipment leaks, and from maintenance and cleaning activities. These
activities are all potential sources of worker exposure through dermal contact to liquid, vapor-through-
skin, and inhalation of NMP vapors. For polymer processing, workers have further potential inhalation
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and vapor-through-skin exposure to NMP vapors during drying of the polymers as the NMP may
evaporate as the produced polymer is further processed or the NMP may be driven off with elevated
temperatures (RIVM. 2013).
These processes are likely to be partially or fully closed operations, to avoid solvent losses (Roberts.
2017; RIVM. 2013) and due to the nature of the processes (i.e., extractions and other purification
processes are conducted in closed columns). One public comment indicates that workers who handle
solutions containing NMP wear a chemical resistant jacket, gloves, goggles, and a face shield (Kemira.
2018). The RIVM Annex XV Proposal for a Restriction - NMP report recommends that workers within
these chemical processing industries wear gloves with an assigned protection factor (APF) of 5 (80
percent exposure reduction) (RIVM. 2013). EPA did not find additional information on the use of
engineering controls and worker PPE at facilities that use NMP in non-incorporative processing
operations.
ONUs include employees that work at the site where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs 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 workers.
2.3.2.2 Number of Potentially Exposed Workers
The use of NMP for non-incorporative processing operations may occur in many industries. EPA
determined the industries likely to use NMP for non-incorporative processing operations from the
following sources: the non-CBI 2016 CDR results for NMP (U.S. EPA. 2016a). 2016 TRI data (U.S.
EPA. 2016b). and the process descriptions in Section 2.3.1.
In the 2016 CDR, one submission reported processing of NMP as an intermediate in the plastic material
and resin manufacturing and pharmaceutical and medicine manufacturing industries (U.S. EPA. 2016a).
although the pharmaceutical and medicine manufacturing industries are not a TSC A use and are not
assessed in the risk evaluation. EPA identified three additional reported uses that EPA assessed in this
scenario, including the use of NMP as a processing aid in the following industries: petrochemical
manufacturing (reported by two submitters); pesticide, fertilizer, and other agricultural chemical
manufacturing (reported by one submitter); and, plastic material and resin manufacturing (reported by
one submitter). Half of these submissions report fewer than 10 sites that use NMP in non-incorporative
activities, with the remaining half reporting at least 10 but fewer than 25 sites. These submissions report
varying estimates of the number of workers potentially exposed. Due to the variability in the CDR
reported values for number of sites and workers and uncertainty in the basis of the CDR submitter
estimates for downstream processers, EPA estimated sites from 2016 TRI data and workers using data
from the BLS and U.S. Census Bureau.
EPA reviewed the 2016 TRI data for sites that use NMP as a reactant or as a chemical processing aid.
Based on the 2016 TRI data, 94 unique sites use NMP as a reactant and/or chemical processing aid. EPA
compiled the primary NAICS codes for these sites in Table 2-11. EPA determined the number of
workers using the related SOC codes from BLS data that are associated with the primary NAICS codes
listed in Table 2-11. The method for estimating number of workers from the Bureau of Labor Statistics'
OES data and U.S. Census' SUSB data is detailed in Appendix B.l.
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Table 2-11. US Number of Establishments and Employees for Chemical Processing, Excluding Formulation
2016
NAICS
2016 NAICS Title
Number of
Establishments per
2016 TRI
Number of
Workers per Site
per BLS, 2016 and
SUSB, 2015 Data3
Number of ONUs
per Site per BLS,
2016 and SUSB,
2015 data3
313310
Textile and Fabric Finishing Mills
1
7
3
313320
Fabric Coating Mills
1
9
4
322299
All Other Converted Paper Product Manufacturing
1
21
3
323111
Commercial Printing (except Screen and Books)
1
2
1
323120
Support Activities for Printing
1
2
1
324110
Petroleum Refineries
4
170
75
325110
Petrochemical Manufacturing
1
64
30
325130
Synthetic Dye and Pigment Manufacturing
3
26
12
325199
All Other Basic Organic Chemical Manufacturing
7
39
18
325211
Plastics Material and Resin Manufacturing
6
27
12
325212
Synthetic Rubber Manufacturing
1
25
11
325220
Artificial and Synthetic Fibers and Filaments Manufacturing
1
47
21
325320
Pesticide and Other Agricultural Chemical Manufacturing
3
25
7
3254
Pharmaceutical and Medicine Manufacturing b
9
41
25
325510
Paint and Coating Manufacturing
3
14
5
325520
Adhesive Manufacturing
1
18
7
325992
Photographic Film, Paper, Plate, and Chemical Manufacturing
1
19
6
325998
All Other Miscellaneous Chemical Product and Preparation Manufacturing
3
14
5
3261
Plastics Product Manufacturing
7
18
5
331420
Copper Rolling, Drawing, Extruding, and Alloying
3
32
10
332813
Electroplating, Plating, Polishing, Anodizing, and Coloring
2
8
2
333999
All Other Miscellaneous General Purpose Machinery Manufacturing
2
9
4
334400
Semiconductor and Other Electronic Component Manufacturing
12
30
27
334516
Analytical Laboratory Instrument Manufacturing
1
15
16
335911
Storage Battery Manufacturing
1
54
20
336100
Motor Vehicle Manufacturing
11
235
99
336300
Motor Vehicle Parts Manufacturing
3
51
15
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2016
NAICS
2016 NAICS Title
Number of
Establishments per
2016 TRI
Number of
Workers per Site
per BLS, 2016 and
SUSB, 2015 Data3
Number of ONUs
per Site per BLS,
2016 and SUSB,
2015 data8
339112
Surgical and Medical Instrument Manufacturing
1
34
11
339999
All Other Miscellaneous Manufacturing
3
5
1
Total establishments and number of potentially exposed workers and ONUs c=
85
5,000
2,300
a Rounded to the nearest whole number.
b NMP may be used in pharmaceutical manufacturing; however, since this is a non-TSCA use, the number of sites, workers, and ONUs for this NAICS code are not
included in the total values at the end of this table.
0 Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two significant figures.
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2.3.2.3 Occupational Exposure Assessment Methodology
2.3.2.3.1 Inhalation and Vapor-Through-Skin
EPA compiled inhalation monitoring data and modeled exposure concentrations for the use of NMP in
non-incorporative processing activities in Appendix A.3. The monitoring data included in this appendix
lacks data on worker activities, the function of NMP within the industry of use, and the sampling
duration; thus, EPA does not use these monitoring data. Due to limited relevance and quality of
monitoring data and modeling estimates for chemical processing with NMP found in the published
literature, EPA modeled air concentrations for this use, as described below.
In addition to the monitoring data from literature, EPA compiled in Appendix A.3 the modeled NMP air
concentration data that were presented in the RIVM Annex XV Proposal for a Restriction - NMP report
(RIVM. 2013). These modeled NMP air concentrations are for the use of NMP as a process solvent or
reagent in an industrial setting and include scenarios for closed processing systems with various levels
of enclosure as well as the handling of NMP at both ambient and elevated temperatures.
Because the modeled exposure concentrations do not include loading and unloading operations, which
EPA expects to be a significant source of potential worker exposure, EPA modeled potential NMP air
concentrations for the unloading of NMP from bulk containers (i.e., tank trucks and rail cars) and drums.
This modeling is consistent with the methodology described in Section 2.1.2.3.1 for the manufacturing
of NMP. The Dram Loading and Unloading Release and Inhalation Exposure Model involves
probabilistic modeling. Additional details on this modeling approach are presented in Appendix A.3.
EPA used the what-if (duration-based) exposure concentration that EPA modeled during unloading of
drums containing 100% NMP as input to the PBPK model for what-if (duration-based) worker
inhalation and vapor-through-skin exposure. The exposure duration for this what-if (duration-based)
exposure scenario is the task duration of the unloading event (20 drums are unloaded per hour and the
duration was determined based on the throughput of NMP at a site [refer to Appendix A.3 for further
explanation]). These estimates are summarized in Table 2-12. EPA calculated the 8-hour TWA
exposures to as the weighted average exposure during an entire 8-hour shift, assuming zero exposures
during the remainder of the shift. See Appendix B.3 for additional details on the drum unloading
modeling.
Table 2-12. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Chemical Processing, Excluding Formulation i
Work
Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hour
TWA)
(mg/m3)
Unloading
liquid NMP
from drums
Central tendency
(50th percentile)
0.075
1.65 (duration =
0.36 hr)
Drum Loading and
Unloading Release
and Inhalation
Exposure Model
(U.S. EPA. 2015b)
Not
applicable3
High-end (95th
percentile)
0.265
5.85 (duration =
0.36 hr)
EPA models are standard sources used by RAD for engineering assessments. EPA did not systematically review models that
were developed by EPA.
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EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from chemical processing of NMP. Since ONUs do not directly handle NMP (otherwise they
would be considered workers), ONU inhalation exposures could be lower than worker inhalation
exposures. Information on activities where ONUs may be present are insufficient to determine the
proximity of ONUs to workers and sources of emissions, so relative exposure of ONUs to workers
cannot be quantified.
2.3.2.3.2 Dermal Exposure to Liquid
Table 2-13 summarizes the parameters used to assess dermal exposure to liquid during the use of NMP
in non-incorporative processing activities. EPA assesses dermal exposure to liquid NMP at the specified
liquid weight fraction, skin surface area, and duration of contact with liquid, based on the methodology
described below. During the non-incorporative processing of NMP, workers are potentially exposed
during sampling, maintenance, unloading, and loading (packaging) activities. For this scenario, EPA
assessed dermal exposure to liquid during the unloading of pure NMP from drums. See below for
additional information.
NMP Weight Fraction
For this scenario, EPA gathered NMP concentration data from the non-CBI 2016 CDR results, public
comments, and literature, which is summarized in Appendix D. The 2016 CDR results include seven
submissions that indicate NMP is used as an intermediate or non-incorporative processing aid (U.S.
EPA. 2016a). Five of these submissions provide non-CBI concentration data, all indicating that NMP is
used at 90 weight percent or greater. Based on this information, EPA expects that chemical processors
assessed in this scenario are likely to purchase pure NMP and add to various processes in the amounts
needed to achieve the desired concentration for the process operation. Thus, EPA assesses dermal
exposure to liquid for this scenario at 100 weight percent NMP. This data has an overall confidence
rating of high.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (4 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (8 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. For unloading drums, EPA assesses a what-if task duration to be 0.36 hours, based on
the annual NMP throughput at each site (determined by dividing the 2016 CDR production volume by
the number of sites for this and the Incorporation into Formulation, Mixture, or Reaction Product
scenario), 250 days of operation per year, and an unloading rate of 20 drums per hour. Refer to
Appendix A.3 for additional information on this task duration.
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Table 2-13. Summary of Parameters for Worker Dermal Exposure to Liquids During Chemical
Work Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Unloading liquid
NMP from drums
Central Tendency
1
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
1
890 (f)
1,070 (m)
8
What-if (duration-
based)
1
445 (f)
535 (m)
0.36
What-if (duration-
based)
1
890 (f)
1,070 (m)
0.36
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.3.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-14.
The numeric parameters corresponding to the characterizations presented in Table 2-14 are summarized
in Table 2-15. These are the inputs used in the PBPK model.
Table 2-14. Characterization of PBPK Model Input Parameters for Chemical Processing,
Excluding Formulation
Scenario
Work
Activity
Air Concentration
Data
Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
Unloading
drums
Central tendency (50th
percentile)
Half shift (4
hours)
1-hand
N/A - 100% is
assumed
High-end
Unloading
drums
High-end (95th
percentile)
Full shift (8
hours)
2-hand
N/A - 100% is
assumed
What-if
(duration-
based)
Unloading
drums
Central tendency (50th
percentile)
Duration
calculated by
model
1-hand
N/A - 100% is
assumed
What-if
(duration-
based)
Unloading
drums
High-end (95th
percentile)
Duration
calculated by
model
2-hand
N/A - 100% is
assumed
Table 2-15. PBPK Model Input Parameters for Chemical Processing, Excluding Formulation
Scenario
Work
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration
of Contact
with
Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Unloading
drums
0.15
4
445 (f)
535 (m)
1
74 (f)
88 (m)
Page 45 of 292
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Scenario
Work
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration
of Contact
with
Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
High-end
Unloading
drums
0.26
8
890 (f)
1,070 (m)
1
74 (f)
88 (m)
What-if (duration-based)
Unloading
drums
1.65
0.36
445 (f)
535 (m)
1
74 (f)
88 (m)
What-if (duration-based)
Unloading
drums
5.85
0.36
890 (f)
1,070 (m)
1
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g., 1, 5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.3.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.4 Incorporation into Formulation, Mixture, or Reaction Product
2.4.1 Process Description
Incorporation into a formulation, mixture or reaction product refers to the process of mixing or blending
of several raw materials to obtain a single product or preparation. The uses of NMP that may require
incorporation into a formulation include adhesives, sealants, paints, coatings, inks, metal finishing
chemicals, cleaning and degreasing products, agricultural products, and petrochemical products
including lube oils. NMP-specific formulation processes were not identified; however, several ESDs
published by the OECD and Generic Scenarios published by EPA have been identified that provide
general process descriptions for these types of products.
The formulation of coatings and inks typically involves dispersion, milling, finishing and filling into
final packages (OECD. 2010a. c). Adhesive formulation involves mixing together volatile and non-
volatile chemical components in sealed, unsealed or heated processes (OECD. 2009). Sealed processes
are most common for adhesive formulation because many adhesives are designed to set or react when
exposed to ambient conditions (OECD. 2009). Lubricant formulation typically involves the blending of
two or more components, including liquid and solid additives, together in a blending (OECD. 2017).
As described in Section 2.3.1.1, NMP is used in the formulation of agricultural products. While the
majority of these products are liquids, the NMP Producers Group provided a public comment to the
NMP risk evaluation docket indicating that a fertilizer additive is used to produce granular fertilizer
products (Roberts. 2017). According to this public comment, the fertilizer additive containing NMP is
used in both liquid and granular fertilizer products and the blending of both the liquid and granular
fertilizers takes place in enclosed process equipment. The concentration of the NMP in the final fertilizer
product is expected to be less than 0.1 percent (Roberts. 2017). The "Preliminary Information on
Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document and 2017 market profile
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on NMP also identify a granular fungicide product containing less than five weight percent NMP (Abt.
2017; U.S. EPA. 2017b).
As described in Section 2.3.1.3, NMP is used for the production of polymeric resins and may be present
in residual quantities from below 17 ppm (Materials. 2017) up to seven weight percent in the produced
resin (Roberts. 2017). The residual of seven percent is indicated for resin powders (Roberts. 2017). After
production, resins are typically compounded to produce a masterbatch. According to 2016 TRI data on
NMP, the compounding of resins is likely to occur at resin production sites as opposed to separate
compounding sites. In compounding, the polymer resin is blended with additives and other raw materials
to form a masterbatch in either open or closed blending processes (U.S. EPA. 2014). After
compounding, the resin is fed to an extruder where is it converted into pellets, sheets, films or pipes
(U.S. EPA. 2014). These resin pellets and other shapes are then converted into final plastic articles,
generally by melting and forming or extruding, at plastic converting sites.
2.4.2 Exposure Assessment
2.4.2.1 Worker Activities
During the formulation of products containing NMP, workers are potentially exposed to NMP during
unloading of NMP, sampling, maintenance activities, and drumming or loading formulated products
containing NMP (RIVM. 2013). NMP may be unloaded from a variety of container sizes, including rail
cars, tanks, totes, drums, and smaller containers for small-scale operations (FUJIFILM. 2020; Hach
Company. 2020; RIVM. 2013). These activities are all potential sources of worker exposure through
dermal contact to liquid, vapor-through-skin, and inhalation of NMP vapors.
Several public comments to the NMP risk evaluation docket and literature sources report the use of
closed formulation processes. A public comment from FUJIFILM Electronic Materials (FFEM), which
formulates NMP products for the electronics industries, indicates that formulation is completed in an
enclosed process (Fuiifilm. 2017). Another comment by FFEM indicates that NMP may be processed at
elevated temperatures and, where there is potential for vapor generation, local exhaust ventilation is
employed (FUJIFILM. 2020). The NMP Producers Group provided a public comment indicating that the
blending of both liquid and granular fertilizers takes place in enclosed process equipment (Roberts.
2017). Another comment from a coating and adhesive formulator indicates that products are batch
manufactured in an enclosed process (ACC. 2017). However, this comments also indicates that metering
of additives containing NMP may be done from open containers.
The Plastics Compounding GS indicates compounding of plastics may be done in either open or
enclosed vessels (U.S. EPA. 2014). The RIVM Annex Xl^ Proposal for a Restriction - NMP report on
NMP indicates that formulation might or might not occur in closed processes and that formulation may
occur at elevated temperatures (RIVM. 2013). Another source on the formulation of paint stripping
products indicates that formulation of could be open or closed; however, closed processes are preferred
because they prevent solvent loss and mitigate exposures (White and Bardole. 2004).
Public comments indicate that respirators are used to prevent worker exposures to NMP (Hach
Company. 2020; Roberts. 2017). One public comment includes information from a formulator of
coatings and adhesives, which indicates that workers at that site wear full face respirators when handling
NMP (ACC. 2017). Three other formulators specified in public comments that workers wear PPE,
including safety glasses or splash googles, impervious gloves, and protective clothing with respirators, if
needed, or a fume hood (Fujifilm, ACA. 2020; FUJIFILM. 2020; Hach Company. 2020; 2017). with one
comment indicating that workers are required to have chemical hygiene training before handling
Page 47 of 292
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chemicals (FUJIFILM. 2020). Other literature sources indicate that workers generally wear safety
glasses, impervious gloves, and designated work clothes or overalls (Bader et al.. 2006; NICNAS.
2001). The RIVM Annex XV Proposal for a Restriction -NMP report recommends that workers within
these formulation industries wear gloves with an assigned protection factor (APF) of 5 (80 percent
exposure reduction) (RIVM. 2013).
ONUs include employees that work sites where NMP is blended into formulations, but they do not
directly handle the chemical and are therefore expected to have lower exposures. ONUs for formulation
sites include supervisors, managers, and tradesmen that may be in the processing area, but do not
perform tasks that result in the same level of exposures as production workers.
2.4.2.2 Number of Potentially Exposed Workers
Formulation of NMP-based formulations, mixtures, and reaction products is widespread, occurring in
many industries. EPA determined the industries likely to conduct formulation activities using NMP from
the following sources: the non-CBI 2016 CDR results for NMP (U.S. EPA. 2016a). 2016 TRI data (U.S.
EPA. 2016b). the 2017 market profile for NMP (Abt. 2017). the "Preliminary Information on
Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document (U.S. EPA. 2017b). and
public comments on the NMP risk evaluation docket.
In the 2016 CDR, 18 submissions reported processing of NMP by incorporation into a formulation,
mixture, or reaction product (U.S. EPA. 2016a). More than half of these submissions report fewer than
10 sites that use NMP in incorporative activities, with the remaining submissions reporting a higher
estimate of sites or Not Known or Reasonably Ascertainable (NKRA). These submissions report varying
estimates of the number of workers potentially exposed, from fewer than 10 workers up to at least 500
but fewer than 1,000 workers. Due to the variability in the CDR reported values for number of sites and
workers and uncertainty in the basis of the CDR submitter estimates for downstream processers, EPA
estimated sites from 2016 TRI data and workers using data from the BLS and U.S. Census Bureau.
EPA reviewed the 2016 TRI data for sites that use NMP as a formulant. Based on the 2016 TRI data, 94
unique sites use NMP as a formulant. EPA compiled the primary NAICS codes for these sites in Table
2-16. EPA determined the number of workers using the related SOC codes from BLS analysis that are
associated with the primary NAICS codes listed in Table 2-16. The method for estimating number of
workers from the Bureau of Labor Statistics' OES data and U.S. Census' SUSB data is detailed in
Appendix B.l.
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Table 2-16. US Number of Establishments and Employees for Incorporation into Formulation,
Mixture, or Reaction Product
Number of
Establishments per
2016 TRI
Number of
Number of ONUs
2016
NAICS
2016 NAICS Title
Workers per Site
per BLS, 2016 and
per Site per BLS,
2016 and SUSB,
SUSB, 2015 Data3
2015 data3
313320
Fabric Coating Mills
1
9
4
323111
Commercial Printing (except Screen and Books)
1
2
1
324191
Petroleum Lubricating Oil and Grease Manufacturing
1
20
9
325110
Petrochemical Manufacturing
1
64
30
325130
Synthetic Dye and Pigment Manufacturing
1
26
12
325180
Other Basic Inorganic Chemical Manufacturing
1
25
12
325199
All Other Basic Organic Chemical Manufacturing
5
39
18
325211
Plastics Material and Resin Manufacturing
9
27
12
325212
Synthetic Rubber Manufacturing
1
25
11
325220
Artificial and Synthetic Fibers and Filaments Manufacturing
1
47
21
325311
Nitrogenous Fertilizer Manufacturing
1
17
5
325314
Fertilizer (Mixing Only) Manufacturing
1
10
3
325320
Pesticide and Other Agricultural Chemical Manufacturing
9
25
7
325412
Pharmaceutical Preparation Manufacturing b
1
44
27
325510
Paint and Coating Manufacturing
17
14
5
325520
Adhesive Manufacturing
4
18
7
325611
Soap and Other Detergent Manufacturing
2
19
4
325612
Polish and Other Sanitation Good Manufacturing
1
17
4
325910
Printing Ink Manufacturing
2
13
4
325992
Photographic Film, Paper, Plate, and Chemical Manufacturing
4
19
6
325998
All Other Miscellaneous Chemical Product and Preparation Manufacturing
12
14
5
3261
Plastics Product Manufacturing
2
18
5
326291
Rubber Product Manufacturing for Mechanical Use
1
43
7
331300
Alumina and Aluminum Production and Processing
1
33
13
331420
Copper Rolling, Drawing, Extruding, and Alloying
2
32
10
339112
Surgical and Medical Instrument Manufacturing
1
34
11
424690
Other Chemical and Allied Products Merchant Wholesalers
3
1
0
Page 49 of 292
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2016
NAICS
2016 NAICS Title
Number of
Establishments per
2016 TRI
Number of
Workers per Site
per BLS, 2016 and
SUSB, 2015 Data3
Number of ONUs
per Site per BLS,
2016 and SUSB,
2015 data8
562211
Hazardous Waste Treatment and Disposal
7
9
5
562920
Materials Recovery Facilities
1
2
2
Total establishments and number of potentially exposed workers and ONUs c=
93
1,800
690
a Rounded to the nearest whole number.
b NMP may be used in pharmaceutical manufacturing; however, since this is a non-TSCA use, the number of sites, workers, and ONUs for this NAICS code are not
included in the total values at the end of this table.
0 Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two significant figures.
Page 50 of 292
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2.4.2.3 Occupational Exposure Assessment Methodology
2.4.2.3.1 Inhalation and Vapor-Through-Skin
EPA compiled inhalation monitoring data and modeled exposure concentration data for the
incorporation of NMP into a formulation, mixture, or reaction product in Appendix A.4. EPA favors the
use of monitoring data over modeled data, thus EPA used the monitoring data with the highest data
quality to assess exposure for this use, as described below.
Appendix A.4 includes NMP personal monitoring data provided in a public comment to EPA from
FUJIFILM Holdings America Corporation (TUJIFILM. 2020). These data were taken at an industrial
manufacturing site that uses NMP to formulate chemicals used in the electronics industry. In addition,
data were available in the literature for NMP use in the formulation of adhesives for workers engaged in
maintenance, cleaning, and packaging activities (Bader et al.. 2006). These datasets were combined and
used to calculate central tendency and high-end values which are summarized in Table 2-17 (for
Maintenance, analytical, bottling, shipping, loading). EPA used the data in Table 2-17 for inhalation and
vapor-through-skin exposure inputs to the PBPK model, as described in Section 2.4.3. The American
Coatings Association (ACA) additionally provided one full-shift personal breathing zone monitoring
point taken for a worker during paint formulation (ACA. 2020). The NMP concentration for this
monitoring point is reported as less than 0.091 ppm; EPA was unable to determine the level of detection
or if the "less than" implies that the sample was non-detect for NMP. EPA did not include this data point
in the quantitative analysis for this condition of use.
In addition to this monitoring data, EPA compiled in Appendix A.4 the modeled NMP air concentration
data that were presented in the RIVM Annex Xl^ Proposal for a Restriction - NMP report (RIVM. 2013);
however, EPA did not use modeled data from the RIVM Annex Xl^ Proposal for a Restriction - NMP
report because EPA used monitoring data to assess these exposures. Consistent with the modeling EPA
described in Section 2.3.2.3.1 for the chemical processing (excluding formulation) of NMP, EPA
modeled potential NMP air concentrations during the unloading of bulk storage containers and drums
containing 100% NMP. The Dram Loading and Unloading Release and Inhalation Exposure Model
involves probabilistic modeling. EPA used the NMP air concentrations that EPA modeled during
unloading of drums containing pure NMP as input to the PBPK model for central tendency worker
exposure. The exposure duration for this what-if (duration-based) exposure scenario is the task duration
of the unloading event (20 drums are unloaded per hour and the duration was determined based on the
throughput of NMP at a site [refer to Appendix A.4 for further explanation]). EPA calculated the 8-hour
TWA exposures to as the weighted average exposure during an entire 8-hour shift, assuming zero
exposures during the remainder of the shift. See Appendix B.3 for additional details on the drum
unloading modeling.
In addition to the formulation of liquid products, EPA identified formulation activities that may result in
potential worker exposures to particulates containing NMP. Specifically, these include plastics
compounding and blending of granular fertilizers, as described in Section 2.4.1. To determine potential
worker inhalation exposure to solids containing NMP, EPA used the OSHA permissible exposure limit
(PEL) for total particulates not otherwise regulated (PNOR) of 15 mg/m3 as an 8-hour TWA and NMP
concentration data in the products EPA identified as solids containing NMP that undergo formulation.
EPA does not use these exposure concentrations as input to the PBPK model because the PBPK model
does not account for solids, and the range of input parameters for the other exposure scenarios capture
these concentrations. See Appendix A.4 for additional details on this assessment.
Page 51 of 292
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Table 2-17. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Incorporation into Formulation, Mixture, or Reaction Product
Full-Shift NMP
Duration-Based
Parameter
Characterization
Air
NMP Air
Data
Work Activity
Concentration
Concentration
Source
Quality
(mg/m3, 8-hour
TWA)
(mg/m3)
Rating
Liquid
unloading drums
Central tendency
(50th percentile)
0.075
1.65 (duration =
0.36 hr)
Drum Loading
and Unloading
Not
applicable3
High-end (95th
percentile)
0.26
5.85 (duration =
0.36 hr)
Release and
Inhalation
Exposure Model
Liquid - Misc.
(Maintenance,
Central tendency
(50th percentile)
0.344
No data
(FUJIFILM.
2020; Bader et al..
2006)
High
analytical,
loading)
High-end (95th
percentile)
6.28
No data
Solid - loading
Central tendency
(50th percentile)
0.75
No data
OSHA PNOR
PEL and NMP
concentration data
Not
into drums
High-end (95th
percentile)
0.96
No data
applicable
a EPA models are standard sources used by RAD for engineering assessments. EPA did not systematically review models that
were developed by EPA.
The (Bader et al.. 2006) data also included area monitoring data in production and shipping areas, which
is summarized in Table 2-18. However, the representativeness of these data for ONU exposures is not
clear because of uncertainty concerning the intended sample population and the selection of the specific
monitoring location. EPA assumed that the area monitoring data were not appropriate surrogates for
ONU exposure due to lack of necessary metadata, such as monitoring location and distance from worker
activities, to justify its use. Since ONUs do not directly handle formulations containing NMP (otherwise
they would be considered workers), EPA expects ONU inhalation exposures to be lower than worker
inhalation exposures. Information on processes and worker activities is insufficient to determine the
proximity of ONUs to workers and sources of emissions, so relative exposure of ONUs to workers
cannot be quantified using modeling.
Table 2-18. Summary of Area Monitoring During Incorporation into Formulation, Mixture, or
Reaction Product
Full-Shift NMP
Duration-Based
Parameter
Characterization
Air
NMP Air
Data
Scenario
Concentration
Concentration
Source
Quality
(mg/m3, 8-hour
TWA)
(mg/m3)
Rating
Liquid - Misc.
(Maintenance,
Central tendency
0.2
0.2
(Bader et
al.. 2006)
High
analytical, loading)
High-end
3
3
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2.4.2.3.2 Dermal Exposure to Liquid
Table 2-19 summarizes the parameters used to assess dermal exposure to liquid during the incorporation
of NMP into formulations, mixtures, and reaction products. EPA assesses dermal exposure to liquid
NMP at the specified liquid weight fraction, skin surface area, and duration of contact with liquid, based
on the methodology described below. During the formulation of NMP, workers are potentially exposed
during sampling, maintenance, unloading, and loading activities. For this scenario, EPA assessed dermal
exposure to liquid during the unloading of pure NMP from drums. In addition, because NMP may be
formulated into solid products, EPA assessed the loading of solid formulations containing NMP into
drums.
NMP Weight Fraction
NMP is most likely received at formulation sites in pure form (i.e., 100 weight percent NMP), before it
is unloaded by workers and formulated into products with various NMP concentrations. For this
scenario, EPA gathered NMP concentration data in formulated products from the non-CBI 2016 CDR
results, public comments to the NMP risk evaluation docket, the 2017 market profile for NMP, the
"Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document, and literature, which is summarized in Appendix D. The underlying data from these sources
have overall confidence ratings ranging from medium to high. The 2016 CDR results include 36
submissions that indicate NMP is used for formulation in various industries, which formulate product
ranging from at least one weight percent up to at least 90 weight percent NMP (U.S. EPA 2016a). EPA
reviewed the remaining data sources for the concentration of NMP in various formulations, including
the products identified in all subsequent scenarios except recycling and disposal. These products identify
that NMP is present in formulations ranging from 0.06 weight percent NMP up to 100 weight percent
NMP (for industrial cleaning solvents). EPA conservatively assessed dermal exposure to liquid during
the unloading of pure NMP from drums, which is the activity from which workers are potentially
exposed to the highest concentration of NMP. For the assessed scenario of miscellaneous activities (e.g.,
analytical activities, loading), EPA assessed dermal exposure to liquid with 31% (50th percentile) and
99% (95th percentile) NMP, which is based on the NMP concentration in a variety of products.
Note that EPA also determined separate central tendency and high-end NMP concentrations from seven
identified solid formulations (resins and granular agricultural products). EPA calculated the central
tendency (50th percentile) weight percent of NMP in solid formulations to be 5 weight percent and the
high-end (95th percentile) to be 6.4 weight percent NMP.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (4 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (8 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. For unloading of drums containing NMP, EPA assesses a what-if task duration of 0.36
hours, based on the annual NMP throughput at each site (determined by dividing the 2016 CDR
production volume by the number of sites for this and the previous scenario), 250 days of operation per
year, and an unloading rate of 20 drums per hour. Refer to Appendix A.4 for additional information on
Page 53 of 292
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this task duration calculation. EPA did not find task duration data for maintenance, bottling, shipping,
and loading of NMP.
Table 2-19. Summary of Parameters for Worker Dermal Exposure to Liquids During
Incorporation into Formulation, Mixture, or Reaction Product
Work Activity
Parameter
Characterization
NMP
Weight
Fraction
Skin Surface
Area Exposed
a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Liquid - Unloading
drums
Central Tendency
1
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
1
890 (f)
1,070 (m)
8
What-if (duration-
based)
1
445 (f)
535 (m)
0.36
What-if (duration-
based)
1
445 (f)
535 (m)
0.36
Liquid - Misc.
(Maintenance,
analytical, loading)
Central Tendency
0.31
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
0.99
890 (f)
1,070 (m)
8
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.4.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-20.
EPA only presents these scenarios for handling of liquid NMP, to present the most conservative
assessment of potential exposures.
The numeric parameters corresponding to the characterizations presented in Table 2-20 are summarized
in Table 2-21. These are the inputs used in the PBPK model.
Table 2-20. Characterization of PBPK Model Input Parameters for Incorporation into
Formulation, Mixture, or Reaction Product
Scenario
Work Activity
Air Concentration
Data
Characterization
Duration of
Contact
with Liquid
Skin
Surface
Area
Exposed
NMP Weight
Fraction
Characterization
Central
Tendency
Liquid - Drum
unloading
Central tendency
(50th percentile)
Half shift (4
hours)
1-hand
N/A - 100% is
assumed
High-end
Liquid - Drum
unloading
High-end (95th
percentile)
Full shift (8
hours)
2-hand
N/A - 100% is
assumed
What-if
(duration-
based)
Liquid - Drum
unloading
Central tendency
(50th percentile)
Duration
calculated by
model
1-hand
N/A - 100% is
assumed
What-if
(duration-
based)
Liquid - Drum
unloading
High-end (95th
percentile)
Duration
calculated by
model
2-hand
N/A - 100% is
assumed
Page 54 of 292
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Scenario
Work Activity
Air Concentration
Data
Characterization
Duration of
Contact
with Liquid
Skin
Surface
Area
Exposed
NMP Weight
Fraction
Characterization
Central
Tendency
Liquid - Misc.
(Maintenance,
analytical,
loading)
Central tendency
(50th percentile)
Half shift (4
hours)
1-hand
Central tendency
(50th percentile)
High-end
Liquid - Misc.
(Maintenance,
analytical,
loading)
High-end (95th
percentile)
Full shift (8
hours)
2-hand
High-end (95th
percentile)
Table 2-21. PBPK Model Input Parameters for Incorporation into Formulation, Mixture, or
Reaction Product
Duration-
Duration
of
Contact
with
Liquid
(hr)
Skin
Based NMP
Surface
NMP
Body
Scenario
Activity
Air
Concentration
(mg/m3)
Area
Exposed
(cm2)a b c
Weight
Fraction
Weight
(kg)a
Central Tendency
Liquid - Drum
unloading
0.15
4
445 (f)
535 (m)
1
High-end
Liquid - Drum
unloading
0.26
8
890 (f)
1,070 (m)
1
74 (f)
What-if (duration-based)
Liquid - Drum
unloading
1.65
0.36
445 (f)
535 (m)
1
88 (m)
What-if (duration-based)
Liquid - Drum
unloading
5.85
0.36
890 (f)
1,070 (m)
1
Central Tendency
Liquid - Misc.
(Maintenance,
analytical,
loading)
0.69
4
445 (f)
535 (m)
0.31
74 (f)
High-end
Liquid - Misc.
(Maintenance,
analytical,
loading)
6.28
8
890 (f)
1,070 (m)
0.99
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.4.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
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2.5 Metal Finishing
2.5.1 Process Description
EPA's "Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document indicates that NMP is used in metal finishing operations (U.S. EPA. 2017b). Metal finishing
is a broad term used in industry to include a wide variety of processes that alter the surface of metal
substrates, such as cleaning, coating, etching, and invasive quality testing.
Prior to any metal finishing process, the surfaces of metal substrates must first be cleaned to remove
grease and other surface contamination (OECD. 2004). Following cleaning, the substrates may then be
conditioned or activated, which involves the use of a dilute acid to neutralize any remaining alkaline
cleaner used in the cleaning process and to dissolve any tarnish or oxide film on the surface of the metal
substrates. Further, to produce the required surface smoothness or texture, facilities often use polishing
and other abrasive techniques. NMP is expected to be used in these types of surface preparation
processes.
In addition to surface preparation, the Consumer Specialty Products Association (CSPA) submitted a
public comment to EPA's NMP docket indicating that NMP is used as a penetrant for inspection of
metals, specifically on metal parts such as those used in turbines and bridges, among other types of parts
(Brown and Bennett. 2017). Penetrants contain dyes and are used to identify defects in metal parts, such
as those from fatigue and welding cracks. Specifically, once parts are machined and assembled,
penetrant is applied to the surface of the metal, where it migrates into cracks and other surface defects.
The metal parts are then visually inspected for defects, frequently under an ultraviolet light where
fluorescent penetrant dyes are more visible, and then the penetrant is cleaned from the metal part
(Center. 2017).
The specific process steps depend on the type of substrate with application methods including: dip or
immersion, spray, roll, and brush application.
Based on the above information, EPA expects NMP is used in surface preparation and invasive testing
of metal parts. Therefore, EPA assesses the following distinct occupational exposure scenarios for this
scenario:
Spray application,
Dip application, and
Brush application.
NMP may also be used in coatings that are applied to metal parts; however, coating processes with
NMP-based products are covered in Section 2.6.
2.5.2 Exposure Assessment
2.5.2.1 Worker Activities
Workers are potentially exposed to NMP in metal finishing formulations during multiple activities,
including quality testing of formulations, transferring the formulations into application equipment (if
used), applying the formulation to a substrate, and maintenance and cleaning activities. These activities
are all potential sources of worker exposure through dermal contact to liquid, vapor-through-skin, and
inhalation of NMP vapors.
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During application of metal finishing formulations, workers may manually apply the formulation with a
variety of application techniques, including spray application from a handheld spray gun or can, brush
application, and dipping. All types of application are potential exposure points for workers. Some
application methods may be automated, which reduces the potential for worker exposures. For example,
for larger metal parts, machinery may be used to dip these parts into metal finishing formulations. If the
dip application apparatus has an enclosed reservoir, this reduces the potential for NMP vapors to escape
and become available for worker inhalation and vapor-through-skin exposure. The extent of automated
application processes and use of open versus closed systems in the various industries that conduct metal
finishing operations is unknown.
The German Institute for Occupational Safety and Health (IFA) compiled monitoring data for multiple
industries that use NMP, including foundries (TFA 2010). EPA has not identified information describing
how NMP is used at the foundry companies that were included in this monitoring data compilation.
However, EPA believes these operations are most likely to fall within this scenario. These data include
samples from facilities that employ LEV, indicating that this engineering control is sometimes used at
facilities that conduct metal finishing operations. EPA did not find information regarding the frequency
of use of this or other engineering controls nor that for worker PPE in the various industries that may
conduct metal finishing operations.
ONUs include employees that work at the sites where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario include
supervisors, managers, and other employees that may be in the production areas 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
NMP.
2.5.2.2 Number of Potentially Exposed Workers
Application of NMP-based metal finishing products may occur in multiple industries. EPA determined
the industries likely to use NMP for metal finishing from the non-CBI 2016 CDR results for NMP (U.S.
EPA 2016 a). the Scope of the Risk Evaluation for n-Methylpyrrolidone (U.S. EPA 2017c). and the
public comment from the CSPA (Brown and Bennett. 2017).
The exact industries that distinctly perform metal finishing operations are unknown. EPA compiled the
associated NAICS codes for the identified industries in Table 2-22. EPA determined the number of
workers associated with each industry using Bureau of Labor Statistics' OES data (U.S. BLS, 2016) and
the U.S. Census' SUSB (U.S. Census Bureau. 2015). The number of establishments within each industry
that use NMP-based metal finishing products and the number of employees within an establishment
exposed to these NMP-based products are unknown. Therefore, EPA provides the total number of
establishments and employees in these industries as bounding estimates of the number of establishments
that use and the number of employees that are potentially exposed to NMP-based metal finishing
products. These bounding estimates are likely overestimates of the actual number of establishments and
employees potentially exposed to NMP during metal finishing.
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Table 2-22. US Number of Establishments and Employees for Metal Finishing
Industry
Source
2016
NAICS
2016 NAICS Title
Number of
Establishments
Number of
Workers
per Sitea
Number
of ONUs
per Sitea
Primary Metal
Manufacturing
(IFA.
2010)
331100
Iron and Steel Mills and Ferroalloy Manufacturing
603
55
21
331200
Steel Product Manufacturing from Purchased Steel
667
34
10
331300
Alumina and Aluminum Production and Processing
529
37 b
15 b
331400
Nonferrous Metal (except Aluminum) Production and Processing
964
28
10
331500
Foundries
1,770
18
10
Fabricated
Metal Product
Manufacturing
(U.S. EPA.
2016a)
332100
Forging and Stamping
2,467
11
5
332200
Cutlery and Handtool Manufacturing
1,194
8
3
332300
Architectural and Structural Metals Manufacturing
12,309
11
4
332400
Boiler, Tank, and Shipping Container Manufacturing
1,575
21
8
332500
Hardware Manufacturing
599
12
4
332600
Spring and Wire Product Manufacturing
1,196
11
4
332700
Machine Shops; Turned Product; and Screw, Nut, and Bolt
Manufacturing
23,083
2
2
332800
Coating, Engraving, Heat Treating, and Allied Activities
5,732
11
4
332900
Other Fabricated Metal Product Manufacturing
6,612
12
6
Turbine
Manufacturing
(Brown
and
Bennett.
2017)
333600
Engine, Turbine, and Power Transmission Equipment
Manufacturing
1,073
30
17
Total establishments and number of potentially exposed workers and ONUs = c
60,000
530,000
190,000
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016: U.S. Census Bureau. 2015)
a Rounded to the nearest whole number.
b No 2016 BLS data was available for this NAICS. Number of relevant workers per site and ONUs per site within this NAICS were calculated using the ratios of relevant
workers and ONUs to the number of total employees at the 3-digit NAICS level.
0 Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two significant figures.
Page 58 of 292
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2.5.2.3 Occupational Exposure Assessment Methodology
2.5.2.3.1 Inhalation and Vapor-Through-Skin
Appendix A.5 summarizes the inhalation monitoring data for NMP-based metal finishing application
that EPA compiled from published literature sources, including 8-hour TWA, short-term, and partial
shift sampling results. This appendix also includes EPA's rationale for inclusion or exclusion of these
data in the risk evaluation, as well as description of any modeling approaches used by EPA to assess
exposures in this scenario. In summary, where available, EPA used the monitoring data for metal
finishing or surrogate monitoring data for the use of NMP during Application of Paints, Coatings,
Adhesives, and Sealants and Cleaning that had the highest quality rating to assess exposure. Where
monitoring data was unavailable for an application type, EPA used modeling estimates from literature
with the highest data quality to assess exposure. This is further described below.
EPA found limited data on the application of metal finishing chemicals, thus assesses spray application
using the data from Application of Paints, Coatings, Adhesives, and Sealants (refer to Section 2.6) as
surrogate (surrogate work activities using NMP) for this scenario. EPA used data for dip cleaning from
the Cleaning scenario (refer to Section 2.16) as surrogate (surrogate work activities using NMP) for this
scenario. Finally, EPA used a modeled exposure for the brush application of a substance containing
NMP that was presented in the RIVM Annex XV Proposal for a Restriction - NMP report. The personal
breathing zone monitoring data and the modeled exposures are summarized in Table 2-23. EPA used the
data in Table 2-23 for inhalation and vapor-through-skin exposure inputs to the PBPK model, as
described in Section 2.5.3.
Table 2-23. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Work
Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3, 8- hour
TWA)
(mg/m3)
Spray
Application
Low-end (of range)
0.040
0.040 (duration =
4 hr)
(NIOSH. 1998)
High
Mean
0.530
0.530 (duration =
4 hr)
High-end (of
range)
4.51
4.51 (duration = 4
hr)
Dip
Application
Central tendency
(50th percentile)
0.990
No data
Surrogate data
(surrogate work
activities using NMP)
from: (RIVM. 2013;
Nishimura et al.. 2009;
Medium
to high
High-end (95th
percentile)
2.75
No data
Bader et al.. 2006) (IFA.
2010; Xiaofei et al..
2000)
Brush
Application
Single estimate
4.13
No data
(RIVM. 2013)
High
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EPA has not identified personal data on or parameters for modeling potential ONU inhalation exposures.
The available area monitoring data are summarized in Table 2-24. However, the representativeness of
these data for ONU exposures is not clear because of uncertainty concerning the intended sample
population and the selection of the specific monitoring location. EPA assumed that the area monitoring
data were not appropriate surrogates for ONU exposure due to lack of necessary metadata, such as
monitoring location and distance from worker activities, to justify its use. Since ONUs do not directly
handle formulations containing NMP (otherwise they would be considered workers), EPA expects ONU
inhalation exposures to be lower than worker inhalation exposures. Information on processes and worker
activities is insufficient to determine the proximity of ONUs to workers and sources of emissions, so
relative exposure of ONUs to workers cannot be quantified using modeling.
Table 2-24. Summary of Area Monitoring During Metal Finishing
Full-Shift NMP
Air
Concentration
Duration-Based NMP
Data
Quality
Work
Activity
Parameter
Characterization
Air Concentration
Source
(mg/m3, 8-hour
TWA)
(mg/m3)
Rating
Spray
Application
Low-end
0.040
0.040 (duration = 4 hr)
(NIOSH.
Mean
0.140
0.140 (duration = 4 hr)
1998)
High
High-end
0.530
0.530 (duration = 4 hr)
2.5.2.3.2 Dermal Exposure to Liquid
Table 2-25 summarizes the parameters used to assess dermal exposure to liquid during application of
metal finishing formulations containing NMP. EPA assesses dermal exposure to liquid NMP at the
specified liquid weight fraction, skin surface area, and duration of contact with liquid.
NMP Weight Fraction
Neither the 2017 Market Profile for NMP (Abt 2017) nor the "Preliminary Information on
Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document (U.S. EPA 2017b)
identified metal finishing products containing NMP. The 2012 and 2016 CDR results indicate industrial
and commercial categories of use for "metal products not covered elsewhere." These categories of use
indicate that the weight concentration of NMP in formulation is greater than 60 percent but less than 90
percent, as summarized in Appendix D. Due to lack of additional information, EPA assesses a low-end
weight fraction of 0.6 and a high-end weight fraction of 0.9. Because metal finishing products can be
applied with multiple different methods (e.g., spray and brush), EPA assesses these weight fractions for
all application methods in this scenario. These data have overall confidence ratings of high.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (4 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (8 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. EPA did not find data on task durations for a what-if (duration-based) scenario.
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Table 2-25. Summary of Parameters for Worker Dermal Exposure to Liquids During Metal
Finishing i
Work Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
All forms of
application listed
above
Central Tendency
0.6
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
0.9
890 (f)
1,070 (m)
8
" EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.5.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-26.
The numeric parameters corresponding to the characterizations presented in Table 2-26 are summarized
in Table 2-27. These are the inputs used in the PBPK model.
Table 2-26. Characterization of PBPK Model Input Parameters for Metal Finishing
Work
Activity
Air Concentration
Duration of
Skin
Surface
Area
Exposed
NMP Weight
Scenario
Data
Contact with
F raction
Characterization
Liquid
Characterization
Central
Tendency
Spray
application
Mean
Assumed 4
hours
1-hand
Central Tendency
High-end
Spray
application
High-end (of range)
Assumed 8
hours
2-hand
High-end
Central
Tendency
Dip
application
Central tendency (50th
percentile)
Assumed 4
hours
1-hand
Central Tendency
High-end
Dip
application
High-end (95th
percentile)
Assumed 8
hours
2-hand
High-end
Central
Tendency
Brush
application
Single estimate
Assumed 4
hours
1-hand
Central Tendency
High-end
Brush
application
Single estimate
Assumed 8
hours
2-hand
High-end
Table 2-27. PBPK Model Input Parameters for JV
etal Finishing
Scenario
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration of
Contact
with Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Spray
application
0.53
4
445 (f)
535 (m)
0.6
74 (f)
88 (m)
High-end
Spray
application
4.51
8
890 (f)
1,070 (m)
0.9
74 (f)
88 (m)
Page 61 of 292
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Scenario
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration of
Contact
with Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Dip
application
1.98
4
445 (f)
535 (m)
0.6
74 (f)
88 (m)
High-end
Dip
application
2.75
8
890 (f)
1,070 (m)
0.9
74 (f)
88 (m)
Central Tendency
Brush
application
8.26
4
445 (f)
535 (m)
0.6
74 (f)
88 (m)
High-end
Brush
application
4.13
8
890 (f)
1,070 (m)
0.9
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.5.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.6 Application of Paints, Coatings, Adhesives, and Sealants
2.6.1 Process Description
Based on information identified in the "Preliminary Information on Manufacturing, Processing,
Distribution, Use, and Disposal: NMP" document and 2016 CDR reporting, NMP is used as a solvent in
a wide variety of industrial, commercial, and consumer paints, coatings, adhesives, and sealants (U.S.
EPA. 2017b. 2016a). The application methods vary with the specific use.
Several OECD ESDs and EPA generic scenarios provide general process descriptions and worker
activities for industrial and commercial uses. The ESD on Radiation Curable Coatings, Inks, and
Adhesives indicates that, before application onto substrates, paint and coating formulations may be
diluted and are then charged into application equipment (OECD. 2011). Typical coating applications
include manual application with roller or brush, air spray systems, airless and air-assisted airless spray
systems, electrostatic spray systems, electrodeposition/electrocoating and autodeposition, dip coating,
curtain coating systems, roll coating systems, and supercritical carbon dioxide systems (OECD. 2011).
After application, solvent-based coatings typically undergo a drying stage in which the solvent
evaporates from the coating (OECD. 2011).
The OECD ESD for Use of Adhesives (OECD. 2015) provides general process descriptions and worker
activities for industrial adhesive uses. Liquid adhesives are unloaded from containers into the coating
reservoir, applied to a flat or three-dimensional substrate, and the substrates are then joined and allowed
to cure (OECD. 2015). The majority of adhesive applications include spray, roll, curtain, and syringe or
bead application (OECD. 2015). For solvent-based adhesives, the volatile solvent (in this case NMP)
evaporates during the curing stage (OECD. 2015). Based on EPA's knowledge of the industry, EPA
Page 62 of 292
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expects similar process descriptions, worker activities, and application methods for sealant products as
those described above.
Based on the types of paint, coating, adhesive, and sealant products listed in the "Preliminary
Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document (U.S.
EPA. 2017b) and 2017 market profile on NMP (Abt. 2017). EPA could not clearly distinguish the
relevant application methods for these NMP-based products. Due to the potential widespread industrial
and commercial use of NMP-based coating products, EPA expects that the majority of application
methods described above are relevant. Therefore, EPA assesses the following distinct occupational
exposure scenarios for this scenario:
Spray application,
Roll or curtain application,
Dip application,
Brush or roller application, and
Syringe or bead application.
2.6.2 Exposure Assessment
2.6.2.1 Worker Activities
Workers are potentially exposed to NMP in paint, coating, adhesive, and sealant formulations during
quality testing of formulations, transferring the formulations into application equipment, applying the
formulation to a substrate, and maintenance and cleaning activities (Meier et al.. 2013: OECD. 2011:
NICNAS. 2001). These activities are all potential sources of worker exposure through dermal contact to
liquid, vapor-through-skin, and inhalation of NMP vapors or paint, coating, adhesive, and sealant mists
containing NMP. Workers have further potentially inhalation and vapor-through-skin exposure to NMP
vapors during curing or drying of solvent-borne formulations as the NMP evaporates from the applied
formulations.
During application of paints, coatings, adhesives, and sealants, workers may manually apply the
formulation with a variety of application techniques, including spray application from a handheld spray
gun or can, brush or roller application, dipping, or syringe/bead application. All types of application are
potential exposure points for workers. However, the application of the paint, coating, adhesive, and
sealant formulations may be automated using automated spray equipment, roll/curtain equipment, or dip
application equipment. The potential for worker exposure during automated application depends on the
type of system used, specifically whether the system is open or closed. For example, automated spray
application may occur in an enclosed booth equipped with an air filtration or water curtain system to
capture overspray, limiting the potential for worker exposure (NICNAS. 2001). Alternatively, spray
application may be automated but occur in only a semi-enclosed or open space, which increases the
potential for worker exposures. The extent to which closed application systems is used in the various
industries that apply NMP-based paints, coatings, adhesives, and sealants is unknown.
The 2011 ESD on Application of Radiation Curable Coatings, Inks, and Adhesives indicates that typical
PPE may include protective clothing, gloves, safety shoes, and respiratory protection, as needed (OECD.
2011). Additional sources indicate that it is common practice for workers to wear chemical-resistant
gloves (Meier et al.. 2013: OECD. 2009: NICNAS. 2001). The RIVM Annex Xlr Proposal for a
Restriction - NMP report (RIVM. 2013) assesses exposure scenarios that account for the use of local
exhaust ventilation (LEV) (using a 90 percent exposure reduction), gloves (using an 80 percent or a 95
Page 63 of 292
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percent exposure reduction), and, in some cases, a respirator with assigned protection factors (APFs) of
5 (80 percent exposure reduction) or 20 (95 percent exposure reduction).
ONUs include employees that work at the sites where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario include
supervisors, managers, and other employees that may be in the production areas 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
NMP.
2.6.2.2 Number of Potentially Exposed Workers
Application of NMP-based paints, coatings, adhesives, and sealants are widespread, occurring in many
industries. EPA determined the industries likely to use NMP in paints, coatings, adhesives, and sealants
from the following sources: the non-CBI 2016 CDR results for NMP (U.S. EPA. 2016a). the 2017
market profile for NMP (Abt. 2017). and the "Preliminary Information on Manufacturing, Processing,
Distribution, Use, and Disposal: NMP" document (U.S. EPA. 2017b).
In addition, EPA received public comments on the NMP risk evaluation docket indicating NMP is used
in paints, coatings, adhesives, and / or sealants in the following industries:
Aerospace manufacturing industry (Riegle. 2017).
Automotive manufacturing industry (ACC. 2017: Alliance of Automobile Manufacturers. 2017).
Electronics manufacturing (National Electrical Manufacturers Association. 2017: Thomas.
2017),
Semiconductor manufacturing (SIA. 2019a: Fuiifilm. 2017). and
Construction (architectural coatings) (Davis. 2017: NABTU. 2017).
The industries that distinctly perform the various methods of paint, coating, adhesive, and sealant
application (e.g., spray, dip, roll) are unknown. EPA assumes that all industries may perform all
methods of application. EPA compiled the associated NAICS codes for the identified industries in Table
2-28. EPA determined the number of workers associated with each industry using Bureau of Labor
Statistics' OES data (U.S. BLS. 2016) and the U.S. Census' SUSB (U.S. Census Bureau. 2015). The
number of establishments within each industry that use NMP-based paint, coating, adhesive, and sealant
products and the number of employees within an establishment exposed to these NMP-based products
are unknown. Therefore, EPA provides the total number of establishments and employees in these
industries as bounding estimates of the number of establishments that use and the number of employees
that are potentially exposed to NMP-based paint, coating, adhesive, and sealant products. These
bounding estimates are likely overestimates of the actual number of establishments and employees
potentially exposed to NMP during paint, coating, adhesive, and sealant application.
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Table 2-28. US Number of Establishments and Employees for Application of Paints, Coatings, Adhesives, and Sealants
Industry
Industry Source
2016
NAICS
2016 NAICS Title
Number of
Establish-
ments
Number of
Workers
per Sitea
Number of
ONUs per
Site8
Construction
and Flooring
(Abt. 2017; U.S.
EPA. 2017b. 2016a)
238320
Painting and Wall Covering Contractors
31,943
4
0
238330
Flooring Contractors
14,601
4
0
Primary Metal
Manufacturing
(U.S. EPA. 2016a)
331100
Iron and Steel Mills and Ferroalloy Manufacturing
603
53
18
331200
Steel Product Manufacturing from Purchased Steel
667
28
7
331300
Alumina and Aluminum Production and Processing
529
33 b
13 b
331400
Nonferrous Metal (except Aluminum) Production and
Processing
964
22
7
331500
Foundries
1,770
18
10
Fabricated
Metal Product
Manufacturing
(Abt. 2017: U.S.
EPA. 2017b. 2016a)
332100
Forging and Stamping
2,467
10
4
332200
Cutlery and Handtool Manufacturing
1,194
7
3
332300
Architectural and Structural Metals Manufacturing
12,309
10
3
332400
Boiler, Tank, and Shipping Container Manufacturing
1,575
19
6
332500
Hardware Manufacturing
599
12
4
332600
Spring and Wire Product Manufacturing
1,196
10
3
332700
Machine Shops; Turned Product; and Screw, Nut, and Bolt
Manufacturing
23,083
2
1
332800
Coating, Engraving, Heat Treating, and Allied Activities
5,732
8
2
332900
Other Fabricated Metal Product Manufacturing
6,612
12
5
Machinery
Manufacturing
(U.S. EPA. 2017b.
2016a)
333100
Agriculture, Construction, and Mining Machinery
Manufacturing
3,094
20
9
333200
Industrial Machinery Manufacturing
3,262
8
6
333300
Commercial and Service Industry Machinery
Manufacturing
2,014
14
6
333400
Ventilation, Heating, Air-Conditioning, and Commercial
Refrigeration Equipment Manufacturing
1,776
31
8
333500
Metalworking Machinery Manufacturing
6,527
4
4
333600
Engine, Turbine, and Power Transmission Equipment
Manufacturing
1,073
30
17
333900
Other General Purpose Machinery Manufacturing
6,048
13
7
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Industry
Industry Source
2016
NAICS
2016 NAICS Title
Number of
Establish
ments
Number of
Workers
per Sitea
Number of
ONUs per
Site3
Computer and
Electronic
Product
Manufacturing
(Abt. 2017; U.S.
EPA. 2017b. 2016a)
334100
Computer and Peripheral Equipment Manufacturing
1,091
12 b
12 b
334200
Communications Equipment Manufacturing
1,369
13
14
334300
Audio and Video Equipment Manufacturing
486
6 b
6 b
334400
Semiconductor and Other Electronic Component
Manufacturing
3,979
30
27
334500
Navigational, Measuring, Electromedical, and Control
Instruments Manufacturing
5,231
17
18
334600
Manufacturing and Reproducing Magnetic and Optical
Media
521
6 b
6 b
Electrical
Equipment,
Appliance,
and
Component
Manufacturing
(U.S. EPA. 2016a)
335100
Electric Lighting Equipment Manufacturing
1,104
17
5
335200
Household Appliance Manufacturing
303
102
20
335300
Electrical Equipment Manufacturing
2,124
28
12
335900
Other Electrical Equipment and Component
Manufacturing
2,140
23
8
Transportation
Equipment
Manufacturing
(Abt. 2017: U.S.
EPA. 2017b. 2016a)
336100
Motor Vehicle Manufacturing
340
235 b
99 b
336200
Motor Vehicle Body and Trailer Manufacturing
1,917
41
7
336300
Motor Vehicle Parts Manufacturing
5,088
51
15
336400
Aerospace Product and Parts Manufacturing
1,811
75
64
336500
Railroad Rolling Stock Manufacturing
243
35
15
336600
Ship and Boat Building
1,541
36
13
Wholesale and
Retail Trade
(U.S. EPA. 2016a)
424690
Other Chemical and Allied Products Merchant
Wholesalers
9,517
1
0
Total establishments and number of potentially exposed workers and ONUs = c
170,000
2,000,000
910,000
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016: U.S. Census Bureau. 2015)
a Rounded to the nearest whole number.
b No 2016 BLS data was available for this NAICS. Number of relevant workers per site and ONUs per site within this NAICS were calculated using the ratios of relevant
workers and ONUs to the number of total employees at the 3-digit NAICS level.
0 Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two significant figures.
Page 66 of 292
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2.6.2.3 Occupational Exposure Assessment Methodology
2.6.2.3.1 Inhalation and Vapor-Through-Skin
Appendix A.6 summarizes the inhalation monitoring data for NMP-based paint, coating, adhesive, and
sealant application that EPA compiled from published literature sources, including 8-hour TWA, short-
term, and partial shift sampling results. EPA also compile modeled exposure data in this appendix.
Where available for the various types of application, EPA used monitoring data or surrogate monitoring
data for the use of NMP during Cleaning that had the highest quality rating to assess exposure. Where
monitoring data was unavailable for an application type, EPA used modeling estimates to assess
exposure. This is further described below and in Appendix A.6.
EPA used monitoring data presented in Appendix A.6 to determine the PBPK model inputs for
inhalation and vapor-through-skin exposure during spray application. EPA did not find inhalation
monitoring data on roll coating with NMP-containing formulations, thus used data from EPA OPPT's
IIV Roll Coating Model in conjunction with NMP concentration data to determine inputs to the PBPK
model for roll coating in this scenario. The EPA OPPTIIV Roll Coating Model involved deterministic
modeling. EPA found limited data on the dip application of paints, coatings, adhesives, and sealants,
thus EPA used data for dip cleaning with NMP from the Cleaning scenario (refer to Section 2.16) as
surrogate (surrogate work activities using NMP) for this scenario. EPA used a modeled exposure for the
brush application of a substance containing NMP that was presented in the RIVM Annex XV Proposal
for a Restriction - NMP report. The personal breathing zone monitoring data and the modeled exposures
are summarized in Table 2-29. EPA used the data in Table 2-29 for inhalation and vapor-through-skin
exposure inputs to the PBPK model, as described in Section 2.6.3.
Table 2-29. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Application of Paints, Coatings, Adhesives, and Sealants
Full-Shift NMP
Duration-Based
Work
Activity
Parameter
Characterization
Air
NMP Air
Data
Concentration
Concentration
Source
Quality
(mg/m3, 8-hour
TWA)
(mg/m3)
Rating
Low-end (of
0.04 (duration =
range)
0.04
4 hr)
Spray
Application
Mean
0.53
0.53 (duration =
4 hr)
(NIOSH. 1998)
High
High-end (of
4.51 (duration =
range)
4.51
4 hr)
Roll / Curtain
Central tendency
(50th percentile)
0.03
No data
EPA OPPT UV Roll
Not
Application
High-end (95th
percentile)
0.19
No data
Coating Model
applicable3
Page 67 of 292
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Full-Shift NMP
Duration-Based
Work
Activity
Parameter
Characterization
Air
NMP Air
Data
Concentration
Concentration
Source
Quality
(mg/m3, 8-hour
TWA)
(mg/m3)
Rating
Central tendency
(50th percentile)
0.99
No data
Surrogate data
(surrogate work
activities using NMP)
Dip
from: (RIVM. 2013:
Medium to
Application
High-end (95th
percentile)
2.75
No data
IFA. 2010; Nishimura
et al.. 2009: Bader et
al.. 2006: Xiaofei et
al.. 2000)
high
Roller / Brush
and Syringe /
Bead
Single estimate
4.13
No data
(RIVM. 2013)
High
Application
a EPA models are standard sources used by RAD for engineering assessments. EPA did not systematically review models that
were developed by EPA.
EPA has not identified personal data on or parameters for modeling potential ONU inhalation exposures.
The area monitoring data are summarized in Table 2-30. However, the representativeness of these data
for ONU exposures is not clear because of uncertainty concerning the intended sample population and
the selection of the specific monitoring location. EPA assumed that the area monitoring data were not
appropriate surrogates for ONU exposure due to lack of necessary metadata, such as monitoring location
and distance from worker activities, to justify its use. Since ONUs do not directly handle formulations
containing NMP (otherwise they would be considered workers), EPA expects ONU inhalation exposures
to be lower than worker inhalation exposures. Information on processes and worker activities is
insufficient to determine the proximity of ONUs to workers and sources of emissions, so relative
exposure of ONUs to workers cannot be quantified using modeling.
Table 2-30. Summary of Occupational Non-User Inhalation and Vapor-Through-Skin Exposure
6,^, ....w
Full-Shift NMP
Duration-Based
NMP Air
Concentration
Data
Quality
Work Activity
Parameter
Characterization
Air Concentration
Source
(mg/m3, 8-hour
TWA)
(mg/m3)
Rating
Low-end
0.04
0.04 (duration = 4
hr)
Spray Application
Mean
0.14
0.14 (duration = 4
hr)
(NIOSH.
1998)
High
High-end
0.53
0.53 (duration = 4
hr)
Roll / Curtain
No data
No data
No data
No data
Not
applicable
Application
No data
No data
No data
No data
Not
applicable
Dip Application
No data
No data
No data
No data
Not
Page 68 of 292
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Work Activity
Parameter
Characterization
Full-Shift NMP
Air Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hour
TWA)
(mg/m3)
applicable
No data
No data
No data
No data
Not
applicable
Roller / Brush and
Syringe / Bead
Application
No data
No data
No data
No data
Not
applicable
2.6.2.3.2 Dermal Exposure to Liquid
Table 2-31 summarizes the parameters used to assess dermal exposure to liquid during application of
paints, coatings, adhesives, and sealants containing NMP. EPA assesses dermal exposure to liquid NMP
at the specified liquid weight fraction, skin surface area, and duration of contact with liquid, based on
the methodology described below.
NMP Weight Fraction
EPA gathered paint, coating, adhesive, and sealant product concentration from a variety of sources,
including 2017 market profile for NMP (Abt. 20171 the "Preliminary Information on Manufacturing,
Processing, Distribution, Use, and Disposal: NMP" document (U.S. EPA 2017b). public comments to
the NMP risk evaluation docket, and published literature (U.S. EPA 2017b; RIVM. 2013; Muenter and
Blach. 2010; NICNAS. 2001. 1998). which is summarized in Appendix D. The overall confidence rating
of the data from these sources range from medium to high.
EPA identified multiple paint, coating, adhesive, and sealant products containing NMP. Note that some
data points are not for one specific product but are estimated ranges of the expected NMP concentration
in paints, coatings, adhesives, and sealants. Where NMP concentration was provided in a range, EPA
used the midpoint of the range in the distribution of NMP concentrations used for the calculations of
central tendency and high-end NMP concentration described below. NMP concentrations in paints,
coatings, adhesives, and sealants range from 0.06 weight percent NMP up to 90 weight percent NMP.
With these data, EPA determined a central tendency and high-end estimate of NMP concentration in
these products, calculated as the 50th percentile and 95th percentile, respectively. Based on these data, the
central tendency NMP concentration is 2 weight percent and the high-end NMP concentration is 53.4
weight percent.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (4 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (8 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. EPA did not find data on task durations for a what-if (duration-based) scenario.
Page 69 of 292
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Table 2-31. Summary of Parameters for Worker Dermal Exposure to Liquids During Application
of Paints, Coatings, Adhesives, and Sealants
Work Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
All forms of
application listed
above
Central Tendency
0.02
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
0.534
890 (f)
1,070 (m)
8
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.6.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-32.
The numeric parameters corresponding to the characterizations presented in Table 2-32 are summarized
in Table 2-33. These are the inputs used in the PBPK model.
Table 2-32. Characterization of PBPK Model Input Parameters for Application of Paints,
Coatings, Adhesives, and Sealants
Scenario
Work
Activity
Air Concentration
Data
Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
Spray
application
Mean
Half shift (4
hours)
1-hand
Central Tendency
High-end
Spray
application
High-end (of range)
Full shift (8
hours)
2-hand
High-end
Central
Tendency
Roll / curtain
application
Central tendency (50th
percentile)
Half shift (4
hours)
1-hand
Central Tendency
High-end
Roll / curtain
application
High-end (95th
percentile)
Full shift (8
hours)
2-hand
High-end
Central
Tendency
Dip
application
Central tendency (50th
percentile)
Half shift (4
hours)
1-hand
Central Tendency
High-end
Dip
application
High-end (95th
percentile)
Full shift (8
hours)
2-hand
High-end
Central
Tendency
Brush
application
Single estimate
Half shift (4
hours)
1-hand
Central Tendency
High-end
Brush
application
Single estimate
Full shift (8
hours)
2-hand
High-end
Page 70 of 292
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Table 2-33. PBPK Model Input Parameters for Application of Paints, Coatings, Adhesives, and
Sealants
Scenario
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration of
Contact
with Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Spray
application
0.53
4
445 (f)
535 (m)
0.02
74 (f)
88 (m)
High-end
Spray
application
4.51
8
890 (f)
1,070 (m)
0.534
74 (f)
88 (m)
Central Tendency
Roll/
curtain
application
0.06
4
445 (f)
535 (m)
0.02
74 (f)
88 (m)
High-end
Roll/
curtain
application
0.19
8
890 (f)
1,070 (m)
0.534
74 (f)
88 (m)
Central Tendency
Dip
application
1.98
4
445 (f)
535 (m)
0.02
74 (f)
88 (m)
High-end
Dip
application
2.75
8
890 (f)
1,070 (m)
0.534
74 (f)
88 (m)
Central Tendency
Brush
application
8.26
4
445 (f)
535 (m)
0.02
74 (f)
88 (m)
High-end
Brush
application
4.13
8
890 (f)
1,070 (m)
0.534
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
°EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.6.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.7 Recycling and Disposal
2.7.1 Process Description
Each of the conditions of use of NMP may generate waste streams of the chemical that are collected and
transported to third-party sites for disposal, treatment, or recycling. Industrial sites that treat or dispose
onsite wastes that they themselves generate are likely for chemical processing sites (excluding
formulation) and are assessed in Section 2.3. Wastes of NMP that are generated during a scenario and
sent to a third-party site for treatment, disposal, or recycling may include the following:
Wastewater: NMP may be contained in wastewater discharged to POTW or other, non-public
treatment works for treatment. Industrial wastewater containing NMP discharged to a POTW
may be subject to EPA or authorized NPDES state pretreatment programs.
Solid Wastes: Solid wastes are defined under RCRA as any material that is discarded by being:
abandoned; inherently waste-like; a discarded military munition; or recycled in certain ways
(certain instances of the generation and legitimate reclamation of secondary materials are
Page 71 of 292
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exempted as solid wastes under RCRA). Solid wastes may subsequently meet RCRA's definition
of hazardous waste by either being listed as a waste at 40 CFR §§ 261.30 to 261.35 or by
meeting waste-like characteristics as defined at 40 CFR §§ 261.20 to 261.24. Solid wastes that
are hazardous wastes are regulated under the more stringent requirements of Subtitle C of
RCRA, whereas non-hazardous solid wastes are regulated under the less stringent requirements
of Subtitle D of RCRA.
o NMP is not designated as a hazardous substance under federal regulations. However,
three states, Massachusetts, New Jersey and Pennsylvania have designated NMP as a
hazardous substance, thereby regulating NMP disposal ( J.S. EPA, 2018d). The 2016 TRI
results indicate multiple sites reported releases to RCRA Subtitle C Landfills (J.S. EPA
2016b).
Wastes Exempted as Solid Wastes under RCRA: Certain conditions of use of NMP may generate
wastes of NMP that are exempted as solid wastes under 40 CFR § 261.4(a). For example, the
generation and legitimate reclamation of hazardous secondary materials of NMP may be exempt
as a solid waste.
2016 TRI data lists off-site transfers of NMP to land disposal, wastewater treatment, incineration,
recycling facilities, and other off-site transfers. About 51% of off-site transfers were recycled off-site,
26% were incinerated, 12% were sent to land disposal, 7% were sent to wastewater treatment, and 5%
were disposed of via other off-site transfers (J.S. EPA. 2016b). See Figure 2-4 for a diagram of a typical
waste disposal process.
Recycling
Hazardous Waste Hazardous Waste
Generation Transportation
W
Treatment
U i
^ Disposal
Figure 2-4. Typical Waste Disposal Process ( f.S. EPA. 2017a)
Municipal Waste Incineration
Municipal waste combustors (MWCs) that recover energy are generally located at large facilities
comprising an enclosed tipping floor and a deep waste storage pit. Typical large MWCs may range in
capacity from 250 to over 1,000 tons per day. At facilities of this scale, waste materials are not generally
handled directly by workers. Trucks may dump the waste directly into the pit, or waste may be tipped to
the floor and later pushed into the pit by a worker operating a front-end loader. A large grapple from an
overhead crane is used to grab waste from the pit and drop it into a hopper, where hydraulic rams feed
the material continuously into the combustion unit at a controlled rate. The crane operator also uses the
Page 72 of 292
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grapple to mix the waste within the pit, in order to provide a fuel consistent in composition and heating
value, and to pick out hazardous or problematic waste.
Facilities burning refuse-derived fuel (RDF) conduct on-site sorting, shredding, and inspection of the
waste prior to incineration to recover recyclables and remove hazardous waste or other unwanted
materials. Sorting is usually an automated process that uses mechanical separation methods, such as
trommel screens, disk screens, and magnetic separators. Once processed, the waste material may be
transferred to a storage pit, or it may be conveyed directly to the hopper for combustion.
Tipping floor operations may generate dust. Air from the enclosed tipping floor, however, is
continuously drawn into the combustion unit via one or more forced air fans to serve as the primary
combustion air and minimize odors. Dust and lint present in the air is typically captured in filters or
other cleaning devices in order to prevent the clogging of steam coils, which are used to heat the
combustion air and help dry higher-moisture inputs (Kitto, 1992).
Hazardous Waste Incineration
Commercial scale hazardous waste incinerators are generally two-chamber units, a rotary kiln followed
by an afterburner, that accept both solid and liquid waste. Liquid wastes are pumped through pipes and
are fed to the unit through nozzles that atomize the liquid for optimal combustion. Solids may be fed to
the kiln as loose solids gravity fed to a hopper, or in drums or containers using a conveyor (ETC, 2018;
Heritage. 2018).
Incoming hazardous waste is usually received by truck or rail, and an inspection is required for all waste
received. Receiving areas for liquid waste generally consist of a docking area, pumphouse, and some
kind of storage facilities. For solids, conveyor devices are typically used to transport incoming waste
(ETC, 2018; Heritage. 2018V
Smaller scale units that burn municipal solid waste or hazardous waste (such as infectious and hazardous
waste incinerators at hospitals) may require more direct handling of the materials by facility personnel.
Units that are batch-loaded require the waste to be placed on the grate prior to operation and may
involve manually dumping waste from a container or shoveling waste from a container onto the grate.
A typical industrial incineration process is depicted in Figure 2-5 below.
Page 73 of 292
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Disposal Disposal
Figure 2-5. Typical Industrial Incineration Process
Municipal Waste Landfill
Municipal solid waste landfills are discrete areas of land or excavated sites that receive household
wastes and other types of non-hazardous wastes (e.g., industrial and commercial solid wastes).
Standards and requirements for municipal waste landfills include location restrictions, composite liner
requirements, leachate collection and removal system, operating practices, groundwater monitoring
requirements, closure-and post-closure care requirements, corrective action provisions, and financial
assurance. Non-hazardous solid wastes are regulated under RCRA Subtitle D, but states may impose
more stringent requirements.
Municipal solid wastes may be first unloaded at waste transfer stations for temporary storage, prior to
being transported to the landfill or other treatment or disposal facilities.
Hazardous Waste Landfill
Hazardous waste landfills are excavated or engineered sites specifically designed for the final disposal
of non-liquid hazardous wastes. Design standards for these landfills require double liner, double leachate
collection and removal systems, leak detection system, run on, runoff and wind dispersal controls, and
construction quality assurance program (U.S. EPA. 2018b). There are also requirements for closure and
post-closure, such as the addition of a final cover over the landfill and continued monitoring and
maintenance. These standards and requirements prevent potential contamination of groundwater and
nearby surface water resources. Hazardous waste landfills are regulated under Part 264/265, Subpart N.
According to 2016 TRI data, a large portion of land releases are to landfills other than RCRA Subtitle C
hazardous waste landfills. Approximately 150,000 pounds of NMP were reportedly released RCRA
Subtitle C hazardous waste landfills, while 2.4 million pounds of NMP were reported to other landfills
(U.S. EPA. 2016b). EPA expects that NMP wastes sent to municipal landfills are likely to be consumer
and commercial wastes with low potential for NMP to be available for exposure. For example, NMP in
used aerosol cans, paint and coating containers, and other containers that held NMP formulations.
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Recycling
Waste NMP solvent is generated when it becomes contaminated with suspended and dissolved solids,
organics, water, or other substances (U.S. EPA. 1980). Waste solvents can be restored to a condition that
permits reuse via solvent reclamation/recycling (U.S. EPA. 1985. 1980). Waste NMP is shipped to a
solvent recovery site where it is piped or manually loaded into process equipment (U.S. EPA. 1985).
The waste solvent then undergoes a vapor recovery (e.g., condensation, adsorption and absorption) or
mechanical separation (e.g., decanting, filtering, draining, setline and centrifuging) step followed by
distillation, purification and final packaging (U.S. EPA. 1985. 1980).
2.7.2 Exposure Assessment
2.7.2.1 Worker Activities
EPA assumes that any exposures related to on-site waste treatment and disposal are addressed in the
assessments for those uses in this report; therefore, this section assesses exposures to workers for wastes
transferred from the use site to an off-site waste treatment and disposal facility. At waste disposal sites,
workers are potentially exposed via dermal contact with waste containing NMP or via inhalation of
NMP vapor. Depending on the concentration of NMP in the waste stream, the route and level of
exposure may be similar to that associated with container unloading activities.
ONUs include employees that work disposal and recycling sites, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for disposal and recycling
sites include supervisors, managers, and tradesmen that may be in the processing and disposal area but
do not perform tasks that result in the same level of exposures as workers that directly handle NMP
wastes.
Municipal Waste Incineration
At municipal waste incineration facilities, there may be one or more technicians present on the tipping
floor to oversee operations, direct trucks, inspect incoming waste, or perform other tasks as warranted by
individual facility practices. These workers may wear protective gear such as gloves, safety glasses, or
dust masks. Specific worker protocols are largely up to individual companies, although state or local
regulations may require certain worker safety standards be met. Federal operator training requirements
pertain more to the operation of the regulated combustion unit rather than operator health and safety.
Workers are potentially exposed via inhalation to vapors while working on the tipping floor. Potentially-
exposed workers include workers stationed on the tipping floor, including front-end loader and crane
operators, as well as truck drivers. The potential for dermal exposure to liquid is minimized by the use of
trucks and cranes to handle the wastes.
Hazardous Waste Incineration
More information is needed to determine the potential for worker exposures during hazardous waste
incineration and any requirements for personal protective equipment. There is likely a greater potential
for worker exposures for smaller scale incinerators that involve more direct handling of the wastes.
Municipal and Hazardous Waste Landfill
At landfills, worker activities may include operating refuse vehicles to weigh and unload the waste
materials, operating bulldozers to spread and compact wastes, and monitoring, inspecting, and surveying
and landfill site (CalRecvcle. 2018).
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2.7.2.2 Number of Potentially Exposed Workers
As discussed in Section 2.7.1, NMP may be disposed of as hazardous waste at TSDFs, recycled, or
disposed of as municipal waste in used commercial and consumer articles. These operations are covered
by the NAICS codes EPA compiled in Table 2-34. EPA determined the number of workers associated
with each industry identified using Bureau of Labor Statistics' OES data (U.S. BLS. 2016) and the U.S.
Census' SUSB (U.S. Census Bureau. 2015). EPA also searched available 2016 TRI NMP data for the
each NAICS code. The 2016 TRI results indicate that there are 22 sites with operations covered by
NAICS 562211 and two sites with operations covered by NAICS 562920 reporting NMP releases.
The total number of sites that treat and dispose wastes containing NMP is not known. It is possible that
additional hazardous waste treatment facilities treat and dispose NMP but do not meet the TRI reporting
threshold for reporting year 2016. In addition, it is possible that some consumer products containing
NMP may be improperly disposed as municipal solid wastes, and that some amount of NMP is present
in non-hazardous waste streams. Therefore, the total number of workers and ONUs potentially exposed
to NMP may exceed those estimates presented in Table 2-34.
Table 2-34. US Number of Establishments and Employees for E
recycling and Disposal
Industry
2016
NAICS
2016 NAICS Title
Number of
Establishments
per 2016 TRI
Number
of
Workers
per Site
per BLS
Dataa
Number
of
ONUs
per Site
per
BLS
Data3
Hazardous waste
disposal and recycling
562211
Hazardous Waste Treatment and
Disposal
22
9
5
Non-hazardous waste
disposal
562212
Solid Waste Landfill
0
3
2
562213
Solid Waste Combustors and
Incinerators
0
13
8
562219
Other Nonhazardous Waste
Treatment and Disposal
0
3
2
Other materials
recovery
562920
Materials Recovery Facilities
2
2
2
Total number of establishments, workers, and ONUs potentially
exposedc
24
200
120
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016: U.S. Census Bureau. 2015)
a Rounded to the nearest worker.
b Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
2.7.2.3 Occupational Exposure Assessment Methodology
2.7.2.3.1 Inhalation and Vapor-Through-Skin
EPA did not find monitoring data on the handling of NMP wastes at disposal and recycling sites. EPA
therefore compiled the same monitoring and modeled exposure concentration data for this scenario as
that for manufacturing. These data are summarized in Appendix A. 1. As described for Manufacturing in
Section 2.1.2.3.1, due to limited relevance and quality of monitoring data and modeling estimates found
in the published literature, EPA modeled air concentrations for this use, as further described below.
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EPA only found one source with monitoring data on the storing and conveying of NMP, which did not
include details on worker activities, sample locations, or sampling times. EPA also summarized in
Appendix A.l the modeled NMP air concentrations during the manufacturing of NMP, for closed- and
open-system transfers of NMP, that were presented in the RIVM Annex XV Proposal for a Restriction -
NMP report (RIVM. 2013).
Consistent with the approach EPA took in Section 2.1.2.3.1 for the manufacture of NMP, EPA modeled
potential NMP air concentrations during the unloading of bulk storage containers and drums using EPA
models. EPA's modeled exposure concentrations represent a larger range of potential NMP air
concentrations than those presented by RIVM; thus, EPA uses these modeled exposures in lieu of using
the monitoring data or modeled exposure in the RIVM Annex Xl^ Proposal for a Restriction - NMP
report. The inhalation monitoring data as well as the RIVM and EPA's modeled exposure concentrations
are summarized and further explained in Appendix A.7.
The NMP air concentrations modeled by EPA for unloading of 100% NMP are summarized into the
input parameters used for the PBPK modeling in Table 2-35. The container unloading models used by
EPA calculate what-if (duration-based) exposure concentrations, with the exposure duration equal to the
task duration of the unloading event (for bulk containers, central tendency case is 0.5 hours for
unloading tank trucks and high-end is 1 hour for unloading rail cars; for drums, 20 containers are
unloaded per hour and the duration was determined based on the throughput of NMP at a site [refer to
Appendix A.l for further explanation]) and number of unloading events per day. EPA calculated the 8-
hour TWA exposures to as the weighted average exposure during an entire 8-hour shift, assuming zero
exposures during the remainder of the shift.
The Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model involves
deterministic modeling and the Dram Loading and Unloading Release and Inhalation Exposure Model
involves probabilistic modeling. See Appendix B.2 and B.3 for additional details on the bulk container
loading modeling and the drum loading modeling, respectively.
Table 2-35. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Work
Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hour
TWA)
(mg/m3)
Unloading
bulk
containers
Central tendency
(50th percentile)
0.048
0.760 (duration =
0.5 hr)
Tank Truck and
Railcar Loading and
Unloading Release
and Inhalation
Exposure Model
(U.S. EPA. 2015b)
Not
applicable3
High-end (95th
percentile)
0.190
1.52 (duration = 1
hr)
Unloading
drums
Central tendency
(50th percentile)
0.125
1.65 (duration =
0.603 hr)
Drum Loading and
Unloading Release
and Inhalation
Exposure Model
(U.S. EPA. 2015b)
Not
applicable3
High-end (95th
percentile)
0.441
5.85 (duration =
0.603 hr)
a EPA models are standard sources used by RAD for engineering assessments. EPA did not systematically review models that
were developed by EPA.
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EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from recycling and disposal NMP. Since ONUs do not directly handle formulations
containing NMP (otherwise they would be considered workers), ONU inhalation exposures could be
lower than worker inhalation exposures. Information on activities where ONUs may be present are
insufficient to determine the proximity of ONUs to workers and sources of emissions, so relative
exposure of ONUs to workers cannot be quantified.
2.7.2.3.2 Dermal Exposure to Liquid
Table 2-36 summarizes the parameters used to assess dermal exposure to liquid during worker handling
of wastes containing NMP. EPA assesses dermal exposure to liquid NMP at the specified liquid weight
fraction, skin surface area, and duration of contact with liquid, based on the methodology described
below. During this scenario, workers are potentially exposed during unloading and loading activities,
waste sorting activities, and equipment maintenance. For this scenario, EPA assessed dermal exposure to
liquid during the unloading of pure NMP from bulk containers and drums. See below for additional
information.
NMP Weight Fraction
EPA found limited information on the concentration of NMP in waste solvents to be recycled and
industrial and commercial wastes containing NMP. The data submitted by SIA for the use of NMP in the
production of semiconductors (discussed in Section 2.10.2) include one inhalation monitoring data point
for the loading of trucks with waste NMP, which is summarized in Appendix D. This data point
indicates that NMP is 92% in the handled waste material (SIA 2019c). EPA uses this concentration for
the central tendency NMP weight fraction. Due to lack of information on the concentration of NMP in
waste solvents, for the high-end NMP concentration value, EPA expects that waste NMP may contain
very little impurities and be up to 100 weight percent NMP.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (6 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (12 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. EPA assessed what-if duration of contact with liquid s of 0.5 and 1 hours for
unloading bulk containers and 0.603 hours for unloading of drums based on the modeled task durations.
Table 2-36. Summary of Parameters for Worker Dermal Exposure to Liquids During Recycling
and Disposal
Work Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Unloading bulk
containers
Central Tendency
0.92
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
1
890 (f)
8
Page 78 of 292
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Work Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
1,070 (m)
What-if (duration-
based)
0.92
445 (f)
535 (m)
0.5
What-if (duration-
based)
1
890 (f)
1,070 (m)
1
Unloading
drums
Central Tendency
0.92
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
1
890 (f)
1,070 (m)
8
What-if (duration-
based)
0.92
445 (f)
535 (m)
0.603
What-if (duration-
based)
1
890 (f)
1,070 (m)
0.603
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.7.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-37.
The numeric parameters corresponding to the characterizations presented in Table 2-37 are summarized
in Table 2-38. These are the inputs used in the PBPK model.
Table 2-37. Characterization of PBPK Model Input Parameters for Recycle and Disposal
Scenario
Work
Activity
Air Concentration
Data
Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
Unloading
bulk
containers
Central tendency (50th
percentile)
Half shift (4
hours)
1-hand
Central tendency
High-end
Unloading
drums
High-end (95th
percentile)
Full shift (8
hours)
2-hand
High-end
What-if
(duration-
based)
Unloading
bulk
containers
Central tendency (50th
percentile)
Duration
calculated by
model
1-hand
Central tendency
What-if
(duration-
based)
Unloading
drums
High-end (95th
percentile)
Duration
calculated by
model
2-hand
High-end
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Table 2-38. PBPK Model Input Parameters for Recycle and Disposal
Scenario
Work
Activity
Duration-
Based NMP
Air
Concentration
(mg/m3)
Duration of
Contact
with Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Unloading
bulk
containers
0.10
4
445 (f)
535 (m)
0.92
74 (f)
88 (m)
High-end
Unloading
drums
0.44
8
890 (f)
1,070 (m)
1
74 (f)
88 (m)
What-if (duration-based)
Unloading
bulk
containers
0.76
0.5
445 (f)
535 (m)
0.92
74 (f)
88 (m)
What-if (duration-based)
Unloading
drums
5.85
0.603
890 (f)
1,070 (m)
1
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.7.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.8 Removal of Paints, Coatings, Adhesives, and Sealants
2.8.1 Process Description
EPA's 2017 market profile of NMP identified that NMP may be used in removers for paints, coatings,
and adhesives (Abt. 2017). Similar to the 2015 EPA Assessment on Paint Stripper Use (U.S. EPA
2015c). this risk evaluation considers two different occupational exposure scenarios within this category
of use: miscellaneous stripping, which is assumed to occur mostly indoors, and graffiti removal, which
is assumed mostly outdoor but may include partially enclosed spaces, such as outdoor escalators and
elevators. EPA makes this distinction based on the specificity of the available monitoring data.
The typical process for removal of paints and coatings, including graffiti removal, from substrates first
includes optional preparation of surfaces via cleaning and sanding (U.S. EPA. 2015c). This preparation
is to ensure that the removal product will stick to the coating to be removed. Following surface
preparation, the paint and coating removal product is applied to the surface of the substrate via hand-
held brush, tank dipping, spray application, pouring, wiping, or rolling. Depending on whether removal
is performed industrially or commercially, users may purchase paint and coating removal products in
55-gallon drums or in common, commercially available containers that range from 1 liter to 5 gallons
(U.S. EPA. 2015c).
Paint stripper application methods can include brushing, spraying, dipping, and wiping (White and
Bardole. 2004). The particular application method is dependent on the size and location of the substrate.
For example, for walls and floors, the removal product is typically applied with a handheld brush. For
furniture, the furniture pieces are generally dipped into a tank containing the removal product, or the
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removal product is applied by brushing or spraying. After application, the stripper is allowed to set and
soften the old coating (U.S. EPA. 2015c). The old coating is then removed by scraping, brushing,
wiping, or mechanically buffering or sanding. Once the old coating is removed, the substrate may be
washed with water or solvent to remove any remaining portions of the old coating and prepare the
surface for a new coating, if one is to be applied.
2.8.2 Exposure Assessment
2.8.2.1 Worker Activities
During paint and coating removal, workers may manually apply the removal product to the surface of
the substrate. Once the paint and coating removal product is applied to the substrate and allowed to set,
workers will likely manually remove the old coating. Both these worker activities are potential sources
of worker exposure, through dermal contact to liquid, vapor-through-skin, and inhalation of NMP
vapors.
EPA did not find information on the customary engineering controls and worker PPE used in the paint,
coating, and graffiti removal industries; however, some resources list suggested engineering controls and
worker PPE that may be used during paint, coating, and graffiti removal. Graffiti removal is typically
performed outdoors, while paint and coating removal may occur indoors or outdoors. Should removal
activities occur indoors, the area may be mechanically ventilated (U.S. EPA 2013). Workers may wear
respirators to reduce potential exposure to NMP vapors. Workers may wear gloves that are resistant to
NMP, which include butyl rubber and laminated polyethylene or ethylene vinyl alcohol (EVOH) gloves.
The 2015 EPA (U.S. EPA 2015 c) for NMP assesses exposures considering the use of gloves that have
an exposure reduction efficiency of 90 percent and the use of respirators with an assigned protection
factor (APF) of 10 (U.S. EPA 2015c). The RA also assesses exposures without consideration for gloves
or respirators, as EPA had not identified information indicating these PPE are generally implemented
across all industries that conduct paint and coating removal.
ONUs include employees that work at the sites where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario include
supervisors, managers, and other employees that may be in the production areas 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
NMP.
2.8.2.2 Number of Potentially Exposed Workers
The 2015 EPA Assessment on Paint Stripper Use (U.S. EPA 2015c) identified the following industries
that are likely to conduct paint stripping activities:
Professional contractors,
Bathtub refinishing,
Automotive refinishing,
Furniture refinishing,
Art restoration and conservation,
Aircraft paint stripping,
Ship paint stripping, and
Graffiti removal.
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EPA's additional research does not indicate that this list of industries has changed since publication of
the 2015 Paint Stripper Risk Assessment. EPA determined the number of workers associated with each
industry using Bureau of Labor Statistics' OES data (U.S. BLS. 2016) and the U.S. Census' SUSB (U.S.
Census Bureau. 2015). These data are summarized in Table 2-39. The number of establishments within
each industry that use NMP-based removal products and the number of employees within an
establishment exposed to NMP-based removal products are unknown. Therefore, EPA provides the total
number of establishments and employees in these industries as bounding estimates of the number of
establishments that use and the number of employees that are potentially exposed to NMP-based
removal products. These bounding estimates are likely overestimates of the actual number of
establishments and employees potentially exposed to NMP during paint and coating removal.
Table 2-39. US Number of Establishments and Employees for Removal of Paints, Coatings,
Adhesives, ant
Sealants
Occupational
Exposure
Scenario
2016
NAICS
2016 NAICS Title
Number of
Establishments
Number of
Workers
per Site a
Number
of ONUs
per Sitea
Miscellaneous
Paint, Coating,
Adhesive, and
Sealant
Removal
238320
Painting and Wall Covering
Contractors
31,943
4
0
238330
Flooring Contractors
14,601
4
0
811121
Automotive Body, Paint and Interior
Repair and Maintenance
33,648
3
0
811420
Reupholstery and Furniture Repair
3,720
1
1
711510
Independent Artists, Writers and
Performers
25,205
1
0
712110
Museums
5,125
1
0
336411
Aircraft Manufacturing
321
187
159
336611
Ship building and repairing
674
62
22
Graffiti
Removal
Unknown
Total number of establishments, workers, and ONUs potentially
exposedb
120,000
410,000
100,000
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016: U.S. Census Bureau. 2015)
a Rounded to the nearest worker.
b Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
2.8.2.3 Occupational Exposure Assessment Methodology
EPA evaluated potential worker exposures through PBPK modeling. The PBPK model was used to
calculate internal doses of NMP using a set of parameters determined from literature or through standard
assumptions, as described below.
2.8.2.3.1 Inhalation and Vapor-Through-Skin
Appendix A.8 summarizes the inhalation monitoring data for NMP-based paint and coating removal that
EPA compiled from published literature sources, including 8-hour TWA, short-term, and partial shift
sampling results. This appendix also includes EPA's rationale for inclusion or exclusion of these data in
the risk evaluation. EPA used the available monitoring data with the highest data quality to assess
exposure for this use.
The available monitoring data for paint and coating removal are summarized into low-end (lowest
Page 82 of 292
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concentration), high-end (highest concentration), and mean or mid-range values in Table 2-40. Note
that, where possible, EPA prefers to present a central tendency (based on 50th percentile) and high-end
(based on 95th percentile) exposure scenario. However, due to lack of data, EPA summarized the data
into low-end, high-end, and mid-range or mean.
EPA's research for this risk evaluation did not result in additional 8-hour TWA data points from the
2015 TSCA Work Plan Chemical Risk Assessment n-Methylpyrrolidone: Paint Stripping Use (U.S. EPA,
2015c). The data presented in Table 2-40 are the input parameters used for the PBPK modeling for
workers and ONUs, respectively. Note that, due to lack of specificity in the monitoring data, EPA
assumes the data are representative of both workers and ONUs.
Table 2-40. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Removal of Paints, Coatings, Adhesives, and Sealants
Work Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hour
TWA)
(mg/m3)
Miscellaneous
paint, coating,
adhesive, and
sealant removal
Low-end (of
range)
1.0
6.1 (duration = 1
hr)
(NMP Producers
Group. 2012;
WHO. 2001;
NIOSH. 1993) as
cited in (U.S.
EPA. 2015c)
High
Mid-range
32.5
13.2 (duration = 1
hr)
High-end (of
range)
64
280 (duration = 1
hr)
Graffiti removal
Low-end
0.03
No data
(Anundi et al..
2000) as cited in
(U.S. EPA.
2015c)
High
Mean
1.01
No data
High-end
4.52
No data
EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from paint, coating, adhesive, and sealant removal. Since ONUs do not directly handle
formulations containing NMP (otherwise they would be considered workers), ONU inhalation exposures
could be lower than worker inhalation exposures. Information on activities where ONUs may be present
are insufficient to determine the proximity of ONUs to workers and sources of emissions, so relative
exposure of ONUs to workers cannot be quantified.
2.8.2.3.2 Dermal Exposure to Liquid
Table 2-41 summarizes the parameters used to assess dermal exposure to liquid during paint and coating
removal. EPA assumed that the skin was exposed dermally to NMP at the specified liquid weight
fraction, skin surface area, and duration of contact with liquid, based on the methodology described
below.
NMP Weight Fraction
The 2015 EPA Assessment on Paint Stripper Use (U.S. EPA 2015c) identified the weight percent of
NMP in paint and coating removal products as ranging from 25 up to 100. EPA identified additional
paint stripping and graffiti removal products in the 2017 market profile on NMP and "Preliminary
Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document (Abt
2017; U.S. EPA 2017b). This data identified multiple commercial and industrial grade paint, coating,
and graffiti removers that contain NMP at weight fractions ranging from 1 to 100 weight percent NMP.
Page 83 of 292
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With these data, which is summarized in Appendix D, EPA determined a central tendency and high-end
estimate of NMP concentration in these products, calculated as the 50th percentile and 95th percentile,
respectively. Where NMP concentration was provided in a range, EPA used the midpoint of the range in
the distribution of NMP concentrations used for the calculations. Based on these data, for miscellaneous
paint, coating, adhesive, and sealant removal, the central tendency NMP concentration is 30.5 weight
percent and the high-end NMP concentration is 69.5 weight percent. For graffiti removal, the central
tendency NMP concentration is 50 weight percent and the high-end NMP concentration is 61.25 weight
percent. The underlying data used for these estimates have overall confidence ratings ranging from
medium to high.
For the remaining dermal parameters, skin surface area, duration of contact with liquid, and body
weight, EPA uses the same methodology for both miscellaneous removal and graffiti removal, as
described below.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (4 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (8 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. For paint and coating removal, EPA assesses a what-if duration of contact with liquid
of one hour based on the available monitoring data. For graffiti removal, EPA did not find data on task
durations for a what-if (duration-based) scenario.
Table 2-41. Summary of Parameters for PBPK Modeling of Worker Dermal Exposure to Liquids
During Removal of Painl
ts, Coatings, Adhesives, and Sealants
Work Activity
Parameter
Characterization
NMP
Weight
Fraction
Skin Surface
Area Exposed
a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Miscellaneous paint,
coating, adhesive, and
sealant removal
Central Tendency
0.305
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
0.695
890 (f)
1,070 (m)
8
What-if (duration-
based)
0.305
445 (f)
535 (m)
1
What-if (duration-
based)
0.695
890 (f)
1,070 (m)
1
Graffiti removal
Central Tendency
0.5
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
0.6125
890 (f)
1,070 (m)
8
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
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2.8.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-42.
The numeric parameters corresponding to the characterizations presented in Table 2-42 are summarized
in Table 2-43. These are the inputs used in the PBPK model.
Table 2-42. Characterization of PBPK Model Input Parameters for Removal of Paints, Coatings,
Adhesives, and Sealants
Scenario
Work
Activity
Air Concentration
Data
Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
Miscellaneous
paint, coating,
adhesive, and
sealant
removal
Mid-range
Half shift (4
hours)
1-hand
Central Tendency
High-end
Miscellaneous
paint, coating,
adhesive, and
sealant
removal
High-end (of range)
Full shift (8
hours)
2-hand
High-end
What-if
(duration-
based)
Miscellaneous
paint, coating,
adhesive, and
sealant
removal
Mid-range
Based on 1-
hour TWA
data
1-hand
Central Tendency
What-if
(duration-
based)
Miscellaneous
paint, coating,
adhesive, and
sealant
removal
High-end (of range)
Based on 1-
hour TWA
data
2-hand
High-end
Central
Tendency
Graffiti
removal
Mean
Half shift (4
hours)
1-hand
Central Tendency
High-end
Graffiti
removal
High-end (of range)
Full shift (8
hours)
2-hand
High-end
Table 2-43. PBPK Model Input Parameters for Removal of Paints, Coatings, Adhesives, and
Sealants
Scenario
Activity
Duration-
Based NMP
Air
Concentration
(mg/m3)
Duration
of
Contact
with
Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Miscellaneous
paint, coating,
adhesive, and
sealant removal
65
4
445 (f)
535 (m)
0.305
74 (f)
88 (m)
Page 85 of 292
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Duration-
Duration
of
Contact
with
Liquid
(hr)
Skin
Based NMP
Surface
NMP
Body
Scenario
Activity
Air
Concentration
(mg/m3)
Area
Exposed
(cm2)a b c
Weight
Fraction
Weight
(kg)a
Miscellaneous
High-end
paint, coating,
adhesive, and
sealant removal
64
8
890 (f)
1,070 (m)
0.695
74 (f)
88 (m)
Miscellaneous
What-if (duration-based)
paint, coating,
adhesive, and
sealant removal
13.2
1
445 (f)
535 (m)
0.305
74 (f)
88 (m)
Miscellaneous
What-if (duration-based)
paint, coating,
adhesive, and
sealant removal
280
1
890 (f)
1,070 (m)
0.695
74 (f)
88 (m)
Central Tendency
Graffiti
removal
2.02
4
445 (f)
535 (m)
0.5
74 (f)
88 (m)
High-end
Graffiti
removal
4.52
8
890 (f)
1,070 (m)
0.6125
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.8.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.9 Other Electronics Manufacturing
2.9.1 Process Description
NMP is used in multiple other electronic industries including:
A solvent in enamels, thinners, and cleaners used in magnet wire coating (National Electrical
Manufacturers Association. 2020).
A component of solder mask removers for printed circuit board manufacturing (Roberts. 2017).
and
A cleaner for other electronic parts (U.S. EPA. 1998b).
Within the magnet wire industry, NMP is used as a solvent in enamels, thinners, and cleaners(National
Electrical Manufacturers Association. 2020). as well as an additive in polymeric coatings that are used
to coat magnet wires, often to give them thermal and solvent resistance (RIVM. 2013). Wires are routed
through an enclosed applicator containing the coating, then are heated, thereby allowing the coating to
cure onto the wire (National Electrical Manufacturers Association. 2020). NMP is evaporated from the
coating during the curing process such that only trace amounts of NMP are present in final coated
magnet wires (National Electrical Manufacturers Association. 2020). The RIVM Annex XV Proposal for
a Restriction - NMP report (RIVM. 2013) indicates that NMP is used particularly for magnet wires that
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require high quality coatings or coatings that are cured at relatively high temperatures. The magnet wires
are used in the manufacturing of products such as motors, generators, transformers, and communications
devices (National Electrical Manufacturers Association. 2020). NMP is also used in maintenance
cleaning activities, such as equipment cleaning (National Electrical Manufacturers Association. 2020).
A public comment to the NMP risk evaluation docket from Elantas Electrical Insulation indicates NMP
is present in residual quantities in electrical insulating films (Thomas. 2017). The NMP Producers
Group, Inc. also indicated that NMP is used to remove solder mask from circuit boards (Roberts. 2017).
NMP is used at up to 99.9 percent purity in an open-topped tank equipped with ventilation. The NMP
can either be used at ambient temperature or heated up to 180°F. Waste NMP containing the removed
solder mask is either treated on-site or disposed off-site as hazardous waste. NMP may also be used to
clean other electronic parts (U.S. EPA. 1998b). EPA did not find additional information on the cleaning
of electronic parts but expects that the processes occur under well-controlled conditions, as is customary
for the electronics industry.
2.9.2 Exposure Assessment
2.9.2.1 Worker Activities
During the uses of NMP in electronics manufacturing, workers are potentially exposed while unloading
NMP from containers and charging it into equipment. If containers are not manually unloaded by
workers, workers may still be potentially exposed when connecting and disconnecting transfer hoses
between the containers and equipment. Workers may also be potentially exposed during dilution,
mixing, or sampling of solutions containing NMP, if these processes occur (Saft, 2017; RIVM. 2013).
All these activities are potential sources of worker exposure through dermal contact to liquid, vapor-
through-skin, and inhalation of NMP vapors.
During magnet wire coating, the applicator and curing oven are enclosed (National Electrical
Manufacturers Association. 2020). The process is also enclosed while equipment is cleaned (National
Electrical Manufacturers Association. 2020). Workers wear gloves, aprons, and goggles (National
Electrical Manufacturers Association. 2020).
As described in Section 2.9.1, NMP may be used at elevated temperatures for solder mask removal from
printed circuit boards, which may increase the generation of NMP vapors and potential worker
inhalation and vapor-through-skin exposures. However, the processes in which heated NMP is used, as
well as many other processes within the electronics industries, are frequently totally or partially enclosed
and equipped with ventilation that reduces the potential for worker exposures (SIA. 2019a; Roberts.
2017; Saft. 2017; RIVM. 2013). The NMP Producers Group, Inc. indicated in a public comment that
worker exposures in the electronics industries are controlled through the use of the appropriate PPE
(Roberts. 2017).
ONUs include employees that work at the sites where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario include
supervisors, managers, and other employees that may be in the production areas 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
NMP.
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2.9.2.2 Number of Potentially Exposed Workers
Based on the processes described in Section 2.9.1, NMP is used primarily in the computer and electronic
product manufacturing sector, which are included in NAICS codes starting with 334, and the electrical
equipment, appliance, and component manufacturing sector, which are included in NAICS codes
starting with 335. In addition to these NAICS codes, EPA expects that NMP may be used in similar
capacities within other electronics manufacturing industries. A public comment submitted to the NMP
risk evaluation docket from the Aerospace Industries Association (AIA) indicates NMP is used for
electronics manufacturing for the aerospace industry (Riegle. 2017). EPA compiled the identified
NAICS codes for these industries in Table 2-44. Because the NAICS codes 334413 and 335910 are
accounted for in Section 2.10.2.2 and Section 2.15.2.2, respectively, EPA subtracted the total number of
sites, workers, and ONUs for these NAICS codes from the totals presented in Table 2-44. The number of
workers associated with each industry were identified using Bureau of Labor Statistics' OES data (U.S.
BLS. 2016) and the U.S. Census' SUSB (U.S. Census Bureau. 2015). The number of establishments
within each industry that use NMP and the number of employees within an establishment exposed to
NMP are unknown. Therefore, EPA provides the total number of establishments and employees in these
industries as bounding estimates of the number of establishments that use and the number of employees
that are potentially exposed to NMP in other electronics manufacturing. These bounding estimates are
likely overestimates of the actual number of establishments and employees potentially exposed to NMP
in the electronics manufacturing industries.
Table 2-44. US Number of Establishments and Employees for
Other Electronics Manufacturing
Occupational
Exposure
Scenario
2016
NAICS
2016 NAICS Title
Number of
Establishments
Number
of
Workers
Site a
Number
of ONUs
per Site a
Other
Electronics
Manufacturing
3341
Computer and Peripheral Equipment
Manufacturing
1,091
12 b
12
3342
Communications Equipment
Manufacturing
1,369
13
14
3343
Audio and Video Equipment
Manufacturing
486
6 b
6
3344
Semiconductor and Other Electronic
Component Manufacturing
3,979
30
27
3345
Navigational, Measuring,
Electromedical, and Control Instruments
Manufacturing
5,231
17
18
3346
Manufacturing and Reproducing
Magnetic and Optical Media
521
6 b
6
3351
Electric Lighting Equipment
Manufacturing
1,104
17
5
3352
Household Appliance Manufacturing
303
102
20
3353
Electrical Equipment Manufacturing
2,124
28
12
3359
Other Electrical Equipment and
Component Manufacturing
2,140
23
8
3364
Aerospace Product and Parts
Manufacturing
1,811
75
64
3391
Medical Equipment and Supplies
Manufacturing
10,767
11
4
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Occupational
Exposure
Scenario
2016
NAICS
2016 NAICS Title
Number of
Establishments
Number
of
Workers
Site a
Number
of ONUs
per Site a
Total number of establishments, workers, and ONUs potentially
exposed (after subtracting the totals for NAICS codes 334413 and
335910) c
29,854
610,000
400,000
Sources: Number of establishments, workers per site, ONUs per site (U.S. BLS. 2016; U.S. Census Bureau. 2015)
a Rounded to the nearest whole number.
b No 2016 BLS data was available for this NAICS. Number of relevant workers per site and ONUs per site within this
NAICS were calculated using the ratios of relevant workers and ONUs to the number of total employees at the 3-digit
NAICS level.
0 Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
2.9.2.3 Occupational Exposure Assessment Methodology
2.9.2.3.1 Inhalation and Vapor-Through-Skin
Appendix A.9 summarizes the inhalation monitoring data for use of NMP in the electronics
manufacturing industry. Based on the available monitoring data, EPA assessed the occupational
exposure scenario for capacitor, resistor, coil, transformer, and other inductor manufacturing (OSHA
2017).
For other electronics manufacturing, EPA only found data from OSHA's Chemical Exposure Health
Data (CEHD). Specifically, the OSHA CEHD includes four NMP data points related to "capacitor,
resistor, coil, transformer, and other inductor manufacturing" (OSHA 2017). These data points are
personal breathing zone, full-shift measurements. These were summarized into the PBPK modeling full-
shift input parameters in Table 2-45.
Table 2-45. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Other Electronics Manufacturing i
Full-Shift NMP
Duration-Based
Parameter
Characterization
Air
NMP Air
Data
Work Activity
Concentration
Concentration
Source
Quality
(mg/m3, 8-hour
TWA)
(mg/m3)
Rating
Capacitor, Resistor,
Coil, Transformer,
Central tendency
(50th percentile)
2.96
No data
(OSHA.
High
and Other Inductor
Mfg.
High-end (95th
percentile)
44.2
No data
2017)
EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from other electronics manufacturing. Since ONUs do not directly handle formulations
containing NMP (otherwise they would be considered workers), ONU inhalation exposures could be
lower than worker inhalation exposures. Information on activities where ONUs may be present are
insufficient to determine the proximity of ONUs to workers and sources of emissions, so relative
exposure of ONUs to workers cannot be quantified.
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2.9.2.3.2 Dermal Exposure to Liquid
Table 2-46 summarizes the parameters used to assess dermal exposure to liquid during use of NMP in
other electronics manufacturing. EPA assumed that the skin was exposed dermally to NMP at the
specified liquid weight fraction, skin surface area, and duration of contact with liquid.
NMP Weight Fraction
EPA identified multiple products and sources containing data on the concentration of NMP used in the
electronics industry, which is summarized in Appendix D. The 2017 market profile on NMP and the
"Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document identified electronics products with NMP concentrations ranging from less than one up to 100
weight percent NMP (Abt 2017; U.S. EPA 2017b). The NMP Producers Group, Inc. submitted a public
comment to the NMP risk evaluation docket that indicates NMP is used up to 100 percent purity in
photoresist removers and up to 99.9 percent purity in a remover solution for solder mask from printed
circuit boards (Roberts. 2017). These data have an overall confidence rating of high. Based on this
information, EPA calculated central tendency (50th percentile) and high-end (95th percentile) weight
percent of NMP to be 60 and 100, respectively. Note that, where NMP concentration was provided in a
range, EPA used the midpoint of the range in the distribution of NMP concentrations used for the
calculations of central tendency and high-end NMP concentration.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (4 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (8 hours). No task duration data were found for other electronics manufacturing for what-if
exposure scenarios.
Table 2-46. Summary of Parameters for Worker Dermal Exposure to Liquids During Other
Electronics Manufacturing ^
Work Activity
Parameter
Characterization
NMP
Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Capacitor, Resistor, Coil,
Transformer, and Other
Inductor Mfg.
Central Tendency
0.6
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
1
890 (f)
1,070 (m)
8
" EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.9.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-47.
The numeric parameters corresponding to the characterizations presented in Table 2-47 are summarized
in Table 2-48. These are the PBPK model inputs determined by EPA.
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Table 2-47. Characterization of PBPK Model Input Parameters for Other Electronics
Manufacturing
Scenario
Work
Activity
Air Concentration
Data Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
Fraction
Characterization
Central
Tendency
All
activities
Central tendency (50th
percentile)
Mid-point of
shift duration
(4 hours)
1-hand
Central tendency
High-end
All
activities
High-end (95th
percentile)
High-end of
shift duration
(8 hours)
2-hand
High-end
Table 2-48. PBPK Model Input Parameters for Other Electronics Manufacturing
Activity
Scenario
Duration-
Based NMP
Air
Concentration
(mg/m3)
Duration
of
Contact
with
Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)
NMP
Weight
Fraction
Body
Weight
(kg)a
Capacitor,
Resistor, Coil,
Transformer, and
Other Inductor
Mfg.
Central tendency
5.92
4
445 (f)
535 (m)
0.6
74 (f)
88 (m)
High-end
44.2
8
890 (f)
1,070 (m)
1
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.9.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.10 Semiconductor Manufacturing
2.10.1^ Process Description
Within the semiconductor manufacturing industry, NMP is used for the cleaning and stripping of silicon
wafers to prepare the wafer surfaces for application of photoresist and other coating formulations (SIA.
2019a; HSDB. 2017; Mitsubishi Chemical. 2017; RIVM. 2013). as well as for the removal of
photoresists and other residues during wafer cleaning and stripping (SIA. 2019a). NMP also functions as
an ingredient for wafer coatings, including photoresists (SIA, 2019a; Mitsubishi Chemical. 2017).
polyimides (SIA, 2019a; RIVM. 2013). anti-reflective coatings (SIA, 2019a; RIVM. 2013). and as a
carrier for other coatings (U.S. EPA. 1998b). NMP may also be used to clean equipment parts during
maintenance activities and in semiconductor analytical laboratories (SIA. 2019a).
NMP is used to strip photoresist resins from wafer surfaces (Roberts. 2017; U.S. EPA. 1998b). The
NMP Producers Group, Inc. provided information on the photoresist stripping process, stating that the
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process can be batch or continuous and is controlled within a closed system equipped with exhaust
ventilation (Roberts. 2017). NMP is used at up to 100 percent concentration and is heated up to 85°F for
use in the stripping process. During stripping, the NMP solution dissolves any photoresist remaining on
the surfaces of the wafers after developing and etching (OECD. 2010b). Waste NMP containing the
photoresist that was removed from the wafers is either treated on-site or disposed off-site as hazardous
waste (Roberts. 2017).
Trade associations indicate that NMP is not present in the final semiconductor wafers (SIA. 2019a).
2.10.2 Exposure Assessment
2.10.2.1 Worker Activities
During the uses of NMP in semiconductor manufacturing, workers are potentially exposed while
unloading NMP from containers and charging it into equipment. If containers are not manually unloaded
by workers, workers may still be potentially exposed when connecting and disconnecting transfer hoses
between the containers and equipment. Workers may also be potentially exposed during dilution,
mixing, or sampling of solutions containing NMP, if these processes occur (Saft, 2017; RIVM. 2013).
All these activities are potential sources of worker exposure through dermal contact to liquid, vapor-
through-skin, and inhalation of NMP vapors.
Public comments from the Semiconductor Industry Association (SIA) and Intel indicate that most
equipment is fully enclosed during operation, fully automated, and equipped with local exhaust
ventilation (SIA, Intel Corporation. 2020; 2019a). PPE varies depending on the task. For activities that
occur inside the semiconductor fab, workers wear cleanroom garments including a suit with a hood and
boots and chemical resistant gloves (SIA, Intel Corporation. 2020. 2019; 2019a). For activities that do
not occur in the fab, PPE typically includes chemical goggles or safety glasses, face shield, chemical
resistant aprons with sleeves, and chemical resistant gloves (SIA, Intel Corporation. 2020. 2019; 2019a).
Workers receiving training on PPE usage, including when PPE is required, what PPE is required, and
the proper donning and doffing of PPE (SIA, Intel Corporation. 2020. 2019; 2019a).
The 2010 ESD on the Use of Photoresist in Semiconductor Manufacturing also indicates that workers in
the semiconductor manufacturing industry are typically required to wear full-body chemical-resistant
clothing with face shields, chemical-resistant gloves, goggles, and respirators, as needed, inside
production areas, including the areas where photoresist supply containers and waste disposal lines are
connected to the equipment (OECD. 2010b).
ONUs include employees that work at the sites where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario include
supervisors, managers, and other employees that may be in the production areas 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
NMP.
2.10.2.2 Number of Potentially Exposed Workers
Based on the processes described in Section 2.10.1, NMP is used in semiconductor manufacturing,
which is included in NAICS code 334413, semiconductor and related device manufacturing, as shown in
Table 2-49. The number of workers associated with this NAICS code was identified using Bureau of
Labor Statistics' OES data (U.S. BLS. 2016) and the U.S. Census' SUSB (U.S. Census Bureau. 2015).
The number of semiconductor manufacturing establishments that use NMP and the number of
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employees within an establishment exposed to NMP are unknown. Therefore, EPA provides the total
number of establishments and employees as bounding estimates of the number of establishments that use
and the number of employees that are potentially exposed to NMP in semiconductor manufacturing.
These bounding estimates are likely overestimates of the actual number of establishments and
employees potentially exposed to NMP in the semiconductor manufacturing industry.
Table 2-49. US
Number of Establishments and Employees for Semiconductor
Manufacturing
Occupational
Exposure
Scenario
2016
NAICS
2016 NAICS Title
Number of
Establishments
Number
of
Workers
Site3
Number
of ONUs
per Site3
Semiconductor
Manufacturing
334413
Semiconductor and Related Device
Manufacturing
864
50
45
Total number of establishments, workers, and ONUs potentially
exposed b
864
43,000
39,000
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016: U.S. Census Bureau. 2015)
a Rounded to the nearest whole number.
b Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
2.10.2.3 Occupational Exposure Assessment Methodology
2.10.2.3.1 Inhalation and Vapor-Through-Skin
Appendix A. 10 summarizes the inhalation monitoring data for use of NMP in semiconductor
manufacturing. Based on the available monitoring data, EPA assessed the following occupational
exposure scenarios (SLA 2019b):
Container handling, small containers,
Container handling, drums,
Fab worker,
Maintenance,
Virgin NMP truck unloading, and
Waste truck loading.
The available monitoring data was summarized into the PBPK modeling full-shift input parameters in
Table 2-50. For semiconductor manufacturing, EPA uses data received from the Semiconductor Industry
Association (SIA), which include full-shift personal breathing zone sampling results at semiconductor
fabrication facilities during container handling of both small containers and drums, workers inside the
fabrication rooms, maintenance workers, workers that unload trucks containing virgin NMP (100%), and
workers that load trucks with liquid waste NMP (92%) (SIA 2019c). The majority (96% of all samples)
of samples for the semiconductor occupational exposure scenarios were non-detect for NMP (SIA
2019b). Because the geometric standard deviation of the data sets were greater than three, EPA used the
limit of detection (LOD) divided by two to calculate central tendency and high-end values where
samples were non-detect for NMP (U.S. EPA 1994b). Due to the high amount of non-detect results, this
method may result in bias. This is further described in Appendix A. 10.
The semiconductor data included samples of both 8-hour TWA and 12-hour TWA values, with the
majority of the data being 12-hour TWA. EPA used the 12-hour TWA values to assess occupational
exposures in these scenarios, as there is more data available for this shift duration, indicating that shifts
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in this industry are generally 12 hours. Note, however, that the single data points available for the
semiconductor two tasks in Table 2-50 are 8-hour TWA values. EPA used the data in Table 2-50 for
inhalation and vapor-through-skin exposure inputs to the PBPK model, as described in Section 2.10.3.
Table 2-50. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Semicont
uctor Manufacturing
Work Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3,12-hour
TWA)
(mg/m3)
Semiconductor
manufacturing -
Container handling,
small containers
Central tendency
(50th percentile)
0.507
No data
(SIA.
2019b)
High
High-end (95th
percentile)
0.608
No data
Semiconductor
manufacturing -
Container handling,
drums
Central tendency
(50th percentile)
0.013
No data
High-end (95th
percentile)
1.54
No data
Semiconductor
manufacturing - Fab
worker
Central tendency
(50th percentile)
0.138
No data
High-end (95th
percentile)
0.405
No data
Semiconductor
manufacturing -
Maintenance
Central tendency
(50th percentile)
0.020
No data
High-end (95th
percentile)
0.690
No data
Semiconductor
manufacturing - Virgin
NMP truck unloading
Single value
4.78 a
No data
Semiconductor
manufacturing - Waste
truck loading
Single value
0.709 a
No data
a These are 8-hour TWA values.
EPA has not identified personal data on or parameters for modeling potential ONU inhalation exposures.
These semiconductor data also include area monitoring data in the fabrication area, which are
summarized in Table 2-51 (SLA 2019b). However, the representativeness of these data for ONU
exposures is not clear because of uncertainty concerning the intended sample population and the
selection of the specific monitoring location. EPA assumed that the area monitoring data were not
appropriate surrogates for ONU exposure due to lack of necessary metadata, such as monitoring location
and distance from worker activities, to justify its use. Since ONUs do not directly handle formulations
containing NMP (otherwise they would be considered workers), EPA expects ONU inhalation exposures
to be lower than worker inhalation exposures. Information on processes and worker activities is
insufficient to determine the proximity of ONUs to workers and sources of emissions, so relative
exposure of ONUs to workers cannot be quantified using modeling.
Page 94 of 292
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Table 2-51. Summary of Area IV
onitoring During Semiconductor Manufacturing
Work
Activity
Parameter
Characterization
NMP Exposure
Concentration
Duration-Based NMP
Air Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hr TWA)
(mg/m3)
Fab area
Central tendency
0.162
No data
(SIA.
2019b)
High
High-end
0.284
No data
2.10.2.3.2 Dermal Exposure to Liquid
Table 2-52 summarizes the parameters used to assess dermal exposure to liquid during use of NMP in
the electronics industries. EPA assumed that the skin was exposed dermally to NMP at the specified
liquid weight fraction, skin surface area, and duration of contact with liquid.
NMP Weight Fraction
The SIA monitoring data and public comments included NMP concentration data for the products
associated with the inhalation monitoring samples (SIA. 2020; SIA 2019b). which is summarized in
Appendix D. These data have an overall confidence rating of high. EPA calculated the 50th percentile
and 95th percentile NMP concentration for use as the central tendency and high-end NMP
concentrations, on a per task basis. These concentrations are summarized in Table 2-52.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (6 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (12 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. For the semiconductor work activities, EPA used task durations from the SIA for
what-if durations of contact with liquids (SIA. 2020; SIA. 2019b). These data have an overall
confidence rating of high.
Table 2-52. Summary of Parameters for Worker Dermal Exposure to Liquids During
Semiconductor Manufacturing
Work Activity
Parameter
Characterization
NMP
Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Semiconductor
manufacturing - Container
handling, small containers
Central Tendency
0.6
445 (f)
535 (m)
6
74 (f)
88 (m)
High-End
0.75
890 (f)
1,070 (m)
12
What-if (duration-
based)
0.6
445 (f)
535 (m)
5 min
What-if (duration-
based)
0.75
890 (f)
1,070 (m)
60 min
Page 95 of 292
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Work Activity
Parameter
Characterization
NMP
Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Semiconductor
manufacturing - Container
handling, drums
Central Tendency
0.5
445 (f)
535 (m)
6
74 (f)
88 (m)
High-End
0.75
890 (f)
1,070 (m)
12
What-if (duration-
based)
0.5
445 (f)
535 (m)
2 min
What-if (duration-
based)
0.75
890 (f)
1,070 (m)
20 min
Semiconductor
manufacturing - Fab
worker
Central Tendency
0.025
445 (f)
535 (m)
6
74 (f)
88 (m)
High-End
0.05
890 (f)
1,070 (m)
12
What-if (duration-
based)
0.025
445 (f)
535 (m)
10.5
What-if (duration-
based)
0.05
890 (f)
1,070 (m)
10.5
Semiconductor
manufacturing -
Maintenance
Central Tendency
0.50
445 (f)
535 (m)
6
74 (f)
88 (m)
High-End
1
890 (f)
1,070 (m)
12
What-if (duration-
based)
0.50
445 (f)
535 (m)
7 min
What-if (duration-
based)
1
890 (f)
1,070 (m)
11
Semiconductor
manufacturing - Virgin
NMP truck unloading
Central Tendency
1
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
1
890 (f)
1,070 (m)
8
What-if (duration-
based)
1
445 (f)
535 (m)
2
What-if (duration-
based)
1
890 (f)
1,070 (m)
2
Semiconductor
manufacturing - Waste
truck loading
Central Tendency
0.92
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
0.92
890 (f)
1,070 (m)
8
What-if (duration-
based)
0.92
445 (f)
535 (m)
2
What-if (duration-
based)
0.92
890 (f)
1,070 (m)
2
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
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2.10.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-53.
The numeric parameters corresponding to the characterizations presented in Table 2-53 are summarized
in Table 2-54. These are the PBPK model inputs determined by EPA. In addition to the PBPK inputs
determined by EPA in Table 2-54, EPA also modeled PBPK input parameters that were proposed by the
SIA in a public comment (SLA 2020). The SIA proposed PBPK inputs are presented in Table 2-55.
Table 2-53. Characterization of PBPK Model Input Parameters for Semiconductor
Manufacturing
Scenario
Work
Activity
Air Concentration
Data
Characterization a
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
All
activities
Central tendency (50th
percentile)
Mid-point of
shift duration (6
or 4 hours)
1-hand
Central tendency
High-end
All
activities
High-end (95th
percentile)
High-end of
shift duration (8
or 12 hours)
2-hand
High-end
What-if
(duration-
based)
All
activities
Central tendency (50th
percentile)
Task-based
duration
1-hand
Central tendency
What-if
(duration-
based)
All
activities
High-end (95th
percentile)
Task-based
duration
2-hand
High-end
a Only a single estimate was available for virgin NMP truck unloading and waste truck loading. This single air concentration
value was used with both central tendency and high-end duration and dermal parameters.
Table 2-54. PBPK Model Input Parameters for Semiconductor Manufacturing
Duration-
Duration
of
Contact
with
Liquid
(hr)
Skin
Based NMP
Surface
NMP
Body
Activity
Scenario
Air
Concentration
(mg/m3)
Area
Exposed
(cm2)a b c
Weight
Fraction
Weight
(kg)a
Semiconductor
manufacturing -
Container
handling, small
containers
Central tendency
0.507
6
445 (f)
535 (m)
0.6
74 (f)
88 (m)
High-end
0.608
12
890 (f)
1,070 (m)
0.75
74 (f)
88 (m)
What-if (duration-
based)
0.507
5 min
445 (f)
535 (m)
0.6
74 (f)
88 (m)
What-if (duration-
based)
0.608
1
890 (f)
1,070 (m)
0.75
74 (f)
88 (m)
Semiconductor
Central tendency
0.013
6
445 (f)
535 (m)
0.5
74 (f)
88 (m)
manufacturing -
Container
High-end
1.54
12
890 (f)
1,070 (m)
0.75
74 (f)
88 (m)
handling, drums
What-if (duration-
based)
0.013
2 min
445 (f)
0.5
74 (f)
Page 97 of 292
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Duration-
Duration
of
Contact
with
Liquid
(hr)
Skin
Based NMP
Surface
NMP
Body
Activity
Scenario
Air
Concentration
(mg/m3)
Area
Exposed
(cm2)a b c
Weight
Fraction
Weight
(kg)a
535 (m)
88 (m)
What-if (duration-
based)
1.54
20 min
890 (f)
1,070 (m)
0.75
74 (f)
88 (m)
Central tendency
0.138
6
445 (f)
535 (m)
0.025
74 (f)
88 (m)
Semiconductor
manufacturing -
Fab Worker
High-end
0.405
12
890 (f)
1,070 (m)
0.05
74 (f)
88 (m)
What-if (duration-
based)
0.138
10.5
445 (f)
535 (m)
0.025
74 (f)
88 (m)
What-if (duration-
based)
0.405
10.5
890 (f)
1,070 (m)
0.05
74 (f)
88 (m)
Central tendency
0.020
6
445 (f)
535 (m)
0.50
74 (f)
88 (m)
Semiconductor
manufacturing -
Maintenance
High-end
0.690
12
890 (f)
1,070 (m)
1
74 (f)
88 (m)
What-if (duration-
based)
0.020
7 min
445 (f)
535 (m)
0.50
74 (f)
88 (m)
What-if (duration-
based)
0.690
11
890 (f)
1,070 (m)
1
74 (f)
88 (m)
Inhalation - Single
value; Dermal -
Central tendency
9.56
4
445 (f)
535 (m)
1
74 (f)
88 (m)
Semiconductor
manufacturing -
Virgin NMP truck
Inhalation - Single
value; Dermal -
High-end
4.78
8
890 (f)
1,070 (m)
1
74 (f)
88 (m)
unloading
What-if (duration-
based)
19.12
2
445 (f)
535 (m)
1
74 (f)
88 (m)
What-if (duration-
based)
19.12
2
890 (f)
1,070 (m)
1
74 (f)
88 (m)
Inhalation - Single
value; Dermal -
Central tendency
0.709
4
445 (f)
535 (m)
0.92
74 (f)
88 (m)
Semiconductor
manufacturing -
Waste truck
Inhalation - Single
value; Dermal -
High-end
0.709
8
890 (f)
1,070 (m)
0.92
74 (f)
88 (m)
loading
What-if (duration-
based)
0.709
2
445 (f)
535 (m)
0.92
74 (f)
88 (m)
What-if (duration-
based)
0.709
2
890 (f)
1,070 (m)
0.92
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
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Table 2-55. Industry Proposed PBPK Model Input Parameters for Semiconductor Manufacturing
(SIA, 2020) |
Activity
Scenario
Duration-
Based NMP
Air
Concentration
(mg/m3)
Duration
of
Contact
with
Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Semiconductor
manufacturing -
Container
handling, small
containers
Central tendency
0.511
0.33
20.03 (f)
24.08 (m)
0.6
74 (f)
88 (m)
High-end
0.613
1
66.75 (f)
80.25 (m)
0.75
74 (f)
88 (m)
Semiconductor
manufacturing -
Container
handling, drums
Central tendency
0.013
0.33
20.03 (f)
24.08 (m)
0.5
74 (f)
88 (m)
High-end
1.557
1
66.75 (f)
80.25 (m)
0.75
74 (f)
88 (m)
Semiconductor
manufacturing -
Fab Worker with
Container
Changeout
Central tendency
0.139
0.33
20.03 (f)
24.08 (m)
0.025
74 (f)
88 (m)
High-end
0.409
1
66.75 (f)
80.25 (m)
0.05
74 (f)
88 (m)
Semiconductor
manufacturing -
Typical Fab
Worker (e.g.,
ONU)
Central tendency
0.139
0d
0d
0d
74 (f)
88 (m)
High-end
0.409
od
0d
0d
74 (f)
88 (m)
Semiconductor
manufacturing -
Maintenance
Central tendency
0.020
0.33
222.5 (f)
267.5 (m)
0.50
74 (f)
88 (m)
High-end
0.696
1
311.5 (f)
374.5 (m)
1
74 (f)
88 (m)
Semiconductor
manufacturing -
Virgin NMP truck
unloading
Inhalation - Single
value; Dermal -
Central tendency
4.822
0.33
66.75 (f)
80.25 (m)
1
74 (f)
88 (m)
Inhalation - Single
value; Dermal -
High-end
4.822
1
222.5 (f)
267.5 (m)
1
74 (f)
88 (m)
Semiconductor
manufacturing -
Waste truck
loading
Inhalation - Single
value; Dermal -
Central tendency
0.715
0.33
66.75 (f)
80.25 (m)
0.92
74 (f)
88 (m)
Inhalation - Single
value; Dermal -
High-end
0.715
1
222.5 (f)
267.5 (m)
0.92
74 (f)
88 (m)
a SIA proposed exposure factors for both females and males. Values associated with females are denoted with (f) and values
associated with males are denoted with (m).
b SIA proposed PF = 20 for all occupational exposure scenarios.
°EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs (except for the Typical Fab Worker scenario, for which EPA assessed PF = 20 per SIA).
d For the Typical Fab Worker scenario, SIA proposed no dermal contact with NMP, corresponding to a duration of contact
with liquid of 0 hours, 0 cm2 of skin exposed, and an NMP weight fraction of 0. Because exposure duration is needed for
the inhalation exposure estimate, EPA assessed a duration equal to a full shift (12 hours). In addition to avoid a model
error, EPA assessed 0.1 cm2for skin surface area exposed.
Page 99 of 292
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2.10.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.11 Printing and Writing
2.11.1 Process Description
There are multiple types of printing technologies, including lithography, rotogravure, flexography,
screen, letterpress, and digital, which encompasses electrophotography and inkjet printing. Facilities
tend to employ one type of printing process exclusively, although some of the larger facilities may use
two or more types. Solvents are used in inks as carriers for colorants and allow the colorants to bind to
the substrate after drying (OECD. 2010c). Solvents also modify the viscosity of the inks, allowing them
to be more easily applied to substrates. Hawley's Condensed Chemical Dictionary indicates that NMP
specifically can be used as a pigment dispersant in printing formulations (Larranaga et al.. 2016).
The "Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document and a public comment submitted to the NMP risk evaluation docket identify three inks,
ranging from one to 10 weight percent NMP, that are used in inkjet printing (Gerber. 2017; U.S. EPA.
2017b). The "Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal:
NMP" document and 2017 market profile for NMP identify two additional ink products that are both
less than five weight percent NMP and have unspecified printing application methods (Abt. 2017: U.S.
EPA. 2017b). The "Preliminary Information on Manufacturing, Processing, Distribution, Use, and
Disposal: NMP" document additionally states that NMP is expected to be used in lithography and screen
printing but did not identify products that specify this type of printing method (U.S. EPA. 2017b).
The fundamental steps in printing are referred to as imaging/film processing, image carrier preparation,
printing, and post-press operations. Printing processes also include cleanup operations, that may occur
continuously during the print run or between runs. The 2010 Draft Scoping Document for an ESD on the
Manufacture and Use of Printing Inks provides information on the various types of printing processes
(OECD. 2010c).
During lithography, an image is transferred from a plate onto paper or another substrate. The image area
on printing plates is treated to absorb an oil-based ink in the image areas and to absorb only water in the
non-image areas (OECD. 2010c). At the printing facility, ink is loaded into the printing machine and
transferred from the plate to the ink rollers and ultimately onto the paper. Depending on the final printed
product, additional roller units may be used to add various colors and layers to the printed image.
During screen printing, an image is transferred to a substrate through a porous mesh (OECD. 2010c).
The mesh is stretched over a frame and a stencil is applied to the mesh to define the image. Ink is
applied to the mesh and pressure is applied to the ink to force it through the mesh and onto the substrate.
Inkjet printing is the most common method used in digital printing (OECD. 2010c). A digital image is
created on a computer and then transferred onto the substrate with a digital printing press. Small drops
of ink are applied to the substrate from a printing press nozzle by first passing the ink drops through an
electrostatic field and then deflecting the charged drops from a oppositely charge printing plate onto the
substrate. Several types of inks can be used for digital printing, including solid ink, wet/dry toner
systems, and liquid ink.
Page 100 of 292
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The "Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document and 2017 market profile for NMP additionally identify one commercial and consumer product
in which NMP is used in the ink within a marker at 10 to 20 weight percent NMP (Abt. 2017; U.S. EPA.
2017b). The safety datasheet (SDS) for this product lists the product use as "weather-resistant marker for
polyurethane tags" (http://www.markal.eom/assets/l/7/aw plastic eartag white medtip.pdf).
2.11.2 Exposure Assessment
2.11.2.1 Worker Activities
Workers are potentially exposed to NMP during multiple activities involved in printing operations,
including unloading volatile inks, transferring inks into printing equipment, operating the printing
process, and subsequent cleaning and maintenance activities. These activities are potential sources of
worker exposure through dermal contact to liquid, vapor-through-skin, and inhalation of NMP mists and
vapors.
EPA did not identify information on the use of engineering controls and worker PPE in the printing
industry. NIOSH conducted a health hazard evaluation (HHE) at a newspaper printing facility and found
that workers may wear hearing protection and gloves, but do not always do so (NIOSH. 1983).
ONUs include employees that work at the sites where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario include
supervisors, managers, and other employees that may be in the printing areas 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
NMP.
2.11.2.2 Number of Potentially Exposed Workers
This section identifies worker population estimates for use of NMP-based printing inks. Application of
these products are expected to fall within the NAICS group 323, Printing and Related Support
Activities. EPA compiled the 6-digit NAICS codes for each industry within this group in Table 2-56.
NAICS 323111, Commercial Printing (except Screen and Books), captures businesses that perform
lithographic, gravure, flexographic, letterpress, engraving, and digital printing. NAICS 323113,
Commercial Screen Printing, capture screen printing activities. NAICS 323117 and 323120 capture
printing of books and support activities for printing, respectively. As discussed in Section 2.11.1, EPA
identified one marker containing NMP, which is a commercial and consumer product. EPA does not
know if this marker is specifically used in certain industries and does not have a way of estimating the
number of commercial workers that use and are potentially exposed to these markers.
The number of workers associated with each identified industry using Bureau of Labor Statistics' OES
data (U.S. BLS. 2016) and the U.S. Census' SUSB (U.S. Census Bureau. 2015). The number of
establishments within each industry that use NMP-based printing inks and the number of employees
within an establishment exposed to these NMP-based products are unknown. Therefore, EPA provides
the total number of establishments and employees in these industries as bounding estimates of the
number of establishments that use and the number of employees that are potentially exposed to NMP-
based printing inks. These bounding estimates are likely overestimates of the actual number of
establishments and employees potentially exposed to NMP during printing activities.
Page 101 of 292
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Table 2-56. US Number of Establishments and Employees
'or Printing and Writing
2016 NAICS
2016 NAICS Title
Number of
Establishments
Number of
Workers
per Sitea
Number
of ONUs
per Sitea
323111
Commercial Printing (except Screen and Books)
18,687
2
1
323113
Commercial Screen Printing
4,956
1
1
323117
Books Printing
447
6
3
323120
Support Activities for Printing
1,598
2
1
Total establishments and number of potentially exposed workers
and ONUs = b
26,000
53,000
25,000
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016: U.S. Census Bureau. 2015)
a Rounded to the nearest whole number.
b Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
2.11.2.3 Occupational Exposure Assessment Methodology
2.11.2.3.1 Inhalation and Vapor-Through-Skin
Appendix A. 11 summarizes methodology for determining potential NMP air concentrations. EPA used
NMP monitoring data for commercial printing (except screen printing) that were identified in OSHA's
Chemical Exposure Health Data (CEHD) (OSHA. 2017). These data include six personal breathing
zone, partial shift measurements. EPA calculated central tendency (50th percentile) and high-end
exposures (95th percentile) with these data. For the calculations, where non-detect values were included
in the dataset, EPA used the limit of detection (LOD) divided by two (U.S. EPA 1994b). Refer to
Appendix A. 11 for additional details.
EPA did not find inhalation monitoring data for the use of writing utensils containing NMP. EPA does
not assess potential inhalation and vapor-through-skin exposures during the use of NMP-based writing
inks based on information indicating these exposures may be negligible from a NICNAS assessment
(Australian Government Department of Health. 2016) and the likely outdoor use of the one writing
product that was identified (weather-resistant marker). See Appendix A. 11 for additional rationale.
The monitoring data presented in Table 2-57 are the input parameters used for the PBPK modeling. EPA
compiled 4-hour exposure concentration data that can be correlated to the associated dermal exposure to
liquid durations in Table 2-58.
Table 2-57. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Printing and Writing i
Full-Shift NMP Air
Duration-Based NMP
Data
Quality
Rating
Work
Parameter
Concentration
Air Concentration
Source
Activity
Characterization
(mg/m3, 8-hour
TWA)
(mg/m3)
Central tendency (50th
0.037
0.037 (duration = 50
Printing
percentile)
mins)
(OSHA.
High
High-end (95th
0.109
0.827 (duration = 50
2017)
percentile)
mins)
Writing
Not assessed
Page 102 of 292
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EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from printing and writing. Since ONUs do not directly handle formulations containing NMP
(otherwise they would be considered workers), ONU inhalation exposures could be lower than worker
inhalation exposures. Information on activities where ONUs may be present are insufficient to determine
the proximity of ONUs to workers and sources of emissions, so relative exposure of ONUs to workers
cannot be quantified.
2.11.2.3.2 Dermal Exposure to Liquid
Table 2-58 summarizes the parameters used to assess dermal exposure to liquid during printing and
writing activities. EPA assesses dermal exposure to liquid NMP at the specified liquid weight fraction,
skin surface area, and duration of contact with liquid, based on the methodology described below.
NMP Weight Fraction
The "Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document (U.S. EPA 2017b). a public comment submitted to the NMP risk evaluation docket (Gerber.
2017). and the 2017 market profile on NMP (Abt. 2017) identify the following printing products:
Inkjet ink, less than five weight percent NMP,
Inkjet ink, one to five weight percent NMP,
Inkjet ink, five to 10 weight percent NMP,
High performance silver ink, up to five weight percent NMP, and
Unspecified printing ink, less than five weight percent NMP.
Based on these data, which is summarized in Appendix D, for printing activities, EPA assumes a central
tendency (50th percentile) of five weight percent NMP and a high-end (95th percentile) weight fraction of
7 percent NMP in printing inks. For use of NMP in writing utensils, the "Preliminary Information on
Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document (U.S. EPA. 2017b) and
2017 market profile on NMP (Abt. 2017) identified one marker containing NMP at 10 to 20 weight
percent. No other writing products containing NMP were identified. Thus, EPA assumes a low-end
composition of 10 weight percent NMP and a high-end composition of 20 weight percent NMP.
Skin Surface Area
For printing, as described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for
females and 1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535
cm2 for males. However, for writing, EPA does not expect that workers get writing inks on a significant
portion of their hands. Thus, based on information from a NICNAS assessment on potential consumer
exposures to writing inks, EPA assesses that 1 cm2 of skin surface area may be exposed to writing inks
(Australian Government Department of Health. 2016). for both females and males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (6 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (12 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. For printing activities, EPA assesses a what-if duration of contact with liquid of 0.83
hours based on the monitoring data in Appendix A. 11.
Page 103 of 292
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For writing, as EPA assumed one dermal contact event as low-end exposure scenario. Thus, the duration
of contact with liquid is assumed to be the approximate time for evaporation of NMP from skin, or half
an hour. EPA does not assess duration of exposure during writing exceeding this time.
Table 2-58. Summary of Parameters for Worker Dermal Exposure to Liquids During Printing
and Writing
Work
Activity
Parameter
Characterization
NMP Weight
Skin Surface
Duration of
Contact with
Liquid
Body
Fraction
Area Exposed a
Weighta
Unitless
cm2
hr/day
kg
Central Tendency
0.05
445 (f)
535 (m)
4
Printing
High-End
0.07
890 (f)
1,070 (m)
8
74 (f)
What-if (duration-
0.05
445 (f)
0.83
88 (m)
based)
535 (m)
What-if (duration-
0.07
890 (f)
0.83
based)
1,070 (m)
Writing
Central Tendency
0.1
1 b
0.5
74 (f)
High-End
0.2
1 b
0.5
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b This surface area was assumed based on (Australian Government Department of Health 2016).
2.11.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-59.
The numeric parameters corresponding to the characterizations presented in Table 2-59 are summarized
in Table 2-60. These are the inputs used in the PBPK model.
Table 2-59. Characterization of PBPK Model Input Parameters for Printing and Writing
Work
Activity
Air Concentration
Duration of
Skin
Surface
Area
Exposed
NMP Weight
Scenario
Data
Contact with
Fraction
Characterization
Liquid
Characterization
Central
Tendency
Printing
Central tendency (50th
percentile)
Half-shift (4
hours)
1-hand
Central Tendency
High-end
Printing
High-end (95th
percentile)
Full shift (8
hours)
2-hand
High-end
What-if
(duration-
based)
Printing
Central tendency (50th
percentile)
Duration based
on monitoring
data (50 mins)
1-hand
Central Tendency
What-if
(duration-
based)
Printing
High-end (95th
percentile)
Duration based
on monitoring
data (50 mins)
2-hand
High-end
Central
Tendency
Writing
Inhalation Exposure
Not Assessed
Based on one
contact event
1 cm2
Central Tendency
High-end
Writing
Inhalation Exposure
Not Assessed
Based on one
contact event
1 cm2
High-end
Page 104 of 292
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Table 2-60. PBPK Model Input Parameters for Printing and Writing
Scenario
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration of
Contact
with Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Printing
0.074
4
445 (f)
535 (m)
0.05
74 (f)
88 (m)
High-end
Printing
0.109
8
890 (f)
1,070 (m)
0.07
74 (f)
88 (m)
What-if (duration-based)
Printing
0.037
0.83
445 (f)
535 (m)
0.05
74 (f)
88 (m)
What-if (duration-based)
Printing
0.827
0.83
890 (f)
1,070 (m)
0.07
74 (f)
88 (m)
Central Tendency
Writing
0
0.5
1
0.1
74 (f)
88 (m)
High-end
Writing
0
0.5
1
0.2
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.11.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
use of NMP in printing. Only dermal exposure to liquid is expected for use of NMP in writing activities.
EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.12 Soldering
2.12.1 Process Description
The 2017 market profile for NMP and the "Preliminary Information on Manufacturing, Processing,
Distribution, Use, and Disposal: NMP" document identifies one soldering flux product with an NMP
concentration ranging from 1.0 to 2.5 weight percent, used in professional applications (Abt. 2017; U.S.
EPA. 2017b).
The North America's Building Trades Unions (NABTU) submitted a public comment to the NMP risk
evaluation docket that indicates solder materials containing NMP may be used in the construction
industry, including in plumbing work (NABTU. 2017). The RIVM Annex XV Proposal for a Restriction
- NMP report indicates that the Finnish product registry identified around four NMP-based welding and
soldering products, the composition and industries of application of which are unknown (RIVM. 2013).
Soldering is a process in which two or more substrates, or parts (usually metal), are joined together by
melting a filler metal material (solder) into the joint and allowing it to cool, thereby joining the
independent parts. The solder has a lower melting point than the adjoining metal substrates. Soldering
differs from welding in that soldering does not involve melting the work pieces. Solder (or soldering
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flux) is applied to the metal substrates in a variety of methods. The manufacturer and distributor of the
solder flux containing NMP that was described above indicates the soldering flux formula is designed to
be used (dispensed) with a rotating disc, a doctor blade, or a drum fluxer
(https://www.kester.com/products/product/tsf-6522). This product may also be dispensed with a syringe
or a dot dispensing system.
2.12.2 Exposure Assessment
2.12.2.1 Worker Activities
Workers are potentially exposed to NMP in soldering formulations during the application of solder flux
onto the substrate to be soldered. This activity is a potential source of worker exposure through dermal
contact to liquid, vapor-through-skin, and inhalation of NMP vapors. Workers are also potentially
exposed to NMP vapors during the soldering process, which occurs at an elevated temperature,
increasing the potential for NMP vapor production and associated worker inhalation and vapor-through-
skin exposure potential. However, some NMP may be destroyed in the process of soldering, reducing
the potential for worker exposure.
EPA did not find information regarding the use of engineering controls or worker PPE during the use of
NMP-based soldering products. The safety datasheet (SDS) for the soldering product identified above
recommends the use of nitrile or natural rubber gloves and safety glasses with side shields
(http://www.kester.com/DesktopModules/Bring2mind/DMX/Download.aspx?Command=Core Downlo
ad&EntrvId=1169&language=en-US&PortalId=0&TabId=96). The SDS also indicates that respiratory
protection is not needed if the room is well ventilated.
ONUs include employees that work at the sites where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario include
supervisors, managers, and other employees that may be in the production areas 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
NMP.
2.12.2.2 Number of Potentially Exposed Workers
As discussed in Section 2.12.1, soldering products containing NMP may be used in the construction
industry, which is covered within the 2-digit NAICS group 23, construction. Within this NAICS group,
EPA identified the 4-digit NAICS groups that are most likely to perform soldering activities. EPA
compiled these identified NAICS codes in Table 2-61. EPA determined the number of workers
associated with each industry identified using Bureau of Labor Statistics' OES data (U.S. BLS. 2016)
and the U.S. Census' SUSB (U.S. Census Bureau. 2015). The number of establishments within each
industry that use NMP-based soldering products and the number of employees within an establishment
exposed to these NMP-based products are unknown. Therefore, EPA provides the total number of
establishments and employees in these industries as bounding estimates of the number of establishments
that use and the number of employees that are potentially exposed to NMP-based soldering products.
These bounding estimates are likely overestimates of the actual number of establishments and
employees potentially exposed to NMP during soldering.
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Table 2-61. US Number of Establishments and Employees
'or Soldering
Industry
2016
NAICS
2016 NAICS Title
Number of
Establishments
Number of
Workers
Site a
Number
of ONUs
per Site b
Construction
2361
Residential Building Construction
164,519
3
1
2362
Nonresidential Building Construction
41,767
11
1
2371
Utility System Construction
19,585
21
2
2373
Highway, Street, and Bridge
Construction
9,804
20
2
2379
Other Heavy and Civil Engineering
Construction
4,331
15
1
2381
Foundation, Structure, and Building
Exterior Contractors
87,703
7
1
2382
Building Equipment Contractors
176,142
8
1
2389
Other Specialty Trade Contractors
66,339
6
1
Total number of establishments, workers, and ONUs potentially
exposedc
570,000
4,000,000
380,000
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016: U.S. Census Bureau. 2015)
a Rounded to the nearest worker. No 2016 BLS data found for this NAICS. EPA determined number of workers per site by
dividing the total number of employees by the total number of establishments from the available SUSB data for the 2-digit
NAICS group.
b Rounded to the nearest worker. No 2016 BLS data found for this NAICS. EPA determined number of ONUs per site by
dividing the total number of employees by the total number of establishments from the available SUSB data for the 2-digit
NAICS group.
0 Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
2.12.2.3 Occupational Exposure Assessment Methodology
2.12.2.3.1 Inhalation and Vapor-Through-Skin
As shown in Appendix A. 12, EPA did not find inhalation monitoring data or modeled data for NMP-
based soldering from published literature sources. Due to the low NMP content in the one identified
soldering production containing NMP (one to 2.5 weight percent NMP), the potential for worker and
ONU inhalation and vapor-through-skin exposures is likely small. While the increased temperature
during soldering may increase the potential for NMP vapor production, some of the NMP may be
destroyed in the soldering process, mitigating the potential for inhalation and vapor-through-skin
exposures.
Due to the lack of data for this occupational exposure scenario, EPA uses a modeled exposure for brush
application of products containing NMP as surrogate for soldering. The modeled exposure is from the
RIVM Annex XV Proposal for a Restriction - NMP report and is presented in Table 2-62 below.
Table 2-62. Summary of Parameters for Soldering
Work
Activity
Parameter
Characterization
Full-Shift NMP Air
Concentration
Duration-Based NMP
Air Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hour
TWA)
(mg/m3)
Brush
Application
Single estimate
4.13
No data
(RIVM.
2013)
High
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EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from soldering. Since ONUs do not directly handle formulations containing NMP (otherwise
they would be considered workers), ONU inhalation exposures could be lower than worker inhalation
exposures. Information on activities where ONUs may be present are insufficient to determine the
proximity of ONUs to workers and sources of emissions, so relative exposure of ONUs to workers
cannot be quantified.
2.12.2.3.2 Dermal Exposure to Liquid
Table 2-63 summarizes the parameters used to assess dermal exposure to liquid during the use of
soldering products containing NMP. EPA assessed dermal exposure to liquid NMP at the specified
liquid weight fraction, skin surface area, and duration of contact with liquid.
NMP Weight Fraction
The 2017 market profile for NMP (Abt 2017) and the 2017 document on the "Preliminary Information
on Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document (U.S. EPA 2017b)
identified one soldering product containing NMP at a concentration of one to 2.5 weight percent, which
is summarized in Appendix D. Due to lack of additional information, EPA assesses a low-end
concentration of one percent and a high-end concentration of 2.5 percent.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (6 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (12 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. EPA did not find information on task durations for a what-if (duration-based) scenario.
Table 2-63. Summary of Parameters for Worker
Jermal Exposure
to Liquids During Soldering
Work
Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Soldering
Central Tendency
0.01
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
0.025
890 (f)
1,070 (m)
8
EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.12.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-64.
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The numeric parameters corresponding to the characterizations presented in Table 2-64 are summarized
in Table 2-65. These are the inputs used in the PBPK model.
Table 2-64. Characterization of PBPK Model Input Parameters for Soldering
Scenario
Work
Activity
Air Concentration
Data Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
Soldering
Single estimate
Half shift (4
hours)
1-hand
Central Tendency
High-end
Soldering
Single estimate
Full shift (8
hours)
2-hand
High-end
Table 2-65. PBPK Model Input Parameters for Soldering
Scenario
Duration-Based NMP
Air Concentration
(mg/m3)
Duration of
Contact with
Liquid (hr)
Skin Surface
Area Exposed
(cm2) a,b'c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
8.26
4
445 (f)
535 (m)
0.01
74 (f)
88 (m)
High-end
4.13
8
890 (f)
1,070 (m)
0.025
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
°EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.12.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.13 Commercial Automotive Servicing
2.13.1^ Process Description
NMP is used in a variety of automotive service operations. The "Preliminary Information on
Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document (U.S. EPA. 2017b). 2017
market profile for NMP (Abt, 2017), and the 2017 Scope of the Risk Evaluation for NMP (U.S. EPA.
2017c) identified multiple automotive servicing products that contain NMP. These products and the
associated methods of use are described further in this section.
The "Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document and 2017 market profile for NMP identified two sealants, with concentrations of less than one
weight percent and 0.1 to one weight percent, respectively (Abt. 2017: U.S. EPA. 2017b). One sealant is
a paste and is thus likely to be manually applied from the package in discrete quantities or using a trowel
or other tool. The other sealant is an aerosol leak sealer that could potentially be used in the automotive
servicing industry. EPA does not have any additional data on these products or potential worker
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exposures during the use of these products. Due to a lack of specific information for this scenario, EPA
does not assess potential exposures during the manual application of paste sealant.
The "Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document and 2017 market profile for NMP identified multiple automotive cleaning products, including
three leather cleaners that contain from 0.1 to four weight percent of NMP, one air intake cleaner that
contains 15 to 40 weight percent NMP, and one automotive headlight cleaner that contains 0.2 weight
percent NMP (Abt. 2017; U.S. EPA. 2017b). The product details do not specify the methods of
application. EPA expects the most applicable methods of application for these products to be spray then
wiping or polishing and aerosol cleaning. EPA assessed potential exposures during spray / wipe cleaning
in Section 2.16, thus does not reassess these exposures in this scenario because EPA did not find
additional monitoring data specific to automotive cleaning.
In addition to the products listed above, the Scope of Risk Evaluation of NMP, which refers to 2016
CDR results as well as public comments on the NMP docket, indicates that NMP is used in the
following automotive products: paints / coatings / adhesives, strippers, anti-freeze and de-icing products,
and lubricants (MacRov. 2017: U.S. EPA 2017c). EPA assessed application of paints, coating, and
adhesives in Section 2.6 and paint stripping in Section 2.8; EPA did not assess these exposures in this
scenario because no new information was found that would result in differing exposure estimates from
those already assessed.
EPA expects that some of the above products may be used as aerosols. Additionally, the California Air
Resources Board (CARB) surveyed automotive brake cleaner manufacturers and automotive repairs
shops as part of a rulemaking to mitigate air releases of certain chlorinated solvents used in aerosol
cleaning products by automotive maintenance and repair shops (CARB. 2000). CARB's survey of
automotive maintenance and repair shops included a compilation of safety data sheets of brake cleaners,
carburetor and air intake cleaners, engine degreasers, and general purpose degreasers used in California
at the time of the survey. NMP was identified as a component of unspecified formulations in this survey.
Thus, it is feasible that NMP is used in aerosol applications during automotive servicing.
Aerosol activities typically involve the application of a solution from pressurized cans or bottles that use
propellant to aerosolize the solution, allowing it to be sprayed onto substrates. Based on identified safety
data sheets (SDS) for cleaning products, NMP-based formulations typically use liquified petroleum gas
(LPG) (i.e., propane and butane) as the propellant (Abt. 2017; U.S. EPA. 2017b).
EPA did not assess aerosol exposures in other conditions of use; thus, EPA presents potential exposures
for the use of aerosols in this scenario.
2.13.2 Exposure Assessment
2.13.2.1 Worker Activities
Workers may be potentially exposed to NMP during multiple activities involved in automotive
servicing, including the application of cleaning, lubricant, and other servicing formulations onto car
parts, as well as any subsequent wiping, polishing, or maintenance activities that occur once the
formulation has been applied to the car parts. These activities are potential sources of worker exposure
through dermal contact to liquid, vapor-through-skin, and inhalation of NMP mists and vapors.
EPA identified limited information on the use of PPE and engineering controls at automotive service
sites. The Draft ESD on Chemical Additives used in Automotive Lubricants indicates that workers in
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automotive servicing shops are likely to wear disposable gloves and protective footwear (OECD. 2017).
Workers may also use protective headwear when working in pits, under lifts, or hoisting machinery. The
ESD did not identify typical PPE used but indicates that breathing protection may include dust masks or
respirators, if workers are handling highly volatile substances.
ONUs include employees that work at the automotive servicing shops where NMP is used, but they do
not directly handle the chemical and are therefore expected to have lower inhalation exposures and
vapor-through-skin uptake and are not expected to have dermal exposures by contact with liquids.
ONUs for this scenario include supervisors, managers, and other mechanics that may be in the
automotive servicing areas 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 NMP.
2.13.2.2 Number of Potentially Exposed Workers
This section identifies worker population estimates for use of NMP-based automotive servicing
formulations. Application of these products are expected to occur at automotive servicing shops, which
fall within the NAICS group 8111, Automotive Repair and Maintenance. The 6-digit NAICS codes
within this group include both automotive servicing and automotive body work. While EPA expects that
the use of aerosols is largely within the automotive servicing sector, workers at automotive body shops
may still be exposed to NMP in paints and sealants. Thus, EPA includes these NAICS in the worker
estimates provided in this section.
Additionally, because EPA is including aerosol cleaning / degreasing within this scenario, EPA included
industries beyond the automotive servicing sector that are expected to perform aerosol degreasing
activities. Specifically, EPA identified additional industries in which aerosol degreasing may occur from
the 2016 Risk Assessment on Spray Adhesives, Dry Cleaning, and Degreasing Uses of 1-BP (U.S. EPA
2016c).
EPA compiled the associated NAICS codes for the identified industries in Table 2-66. The number of
workers associated with each industry using Bureau of Labor Statistics' OES data (U.S. BLS. 2016) and
the U.S. Census' SUSB (U.S. Census Bureau. 2015). The number of establishments within each industry
that use NMP-based aerosol products and the number of employees within an establishment exposed to
these NMP-based products are unknown. Therefore, EPA provides the total number of establishments
and employees in these industries as bounding estimates of the number of establishments that use and
the number of employees that are potentially exposed to NMP-based aerosol products. These bounding
estimates are likely overestimates of the actual number of establishments and employees potentially
exposed to NMP during use of aerosol products.
Table 2-66. US Number of Establishments and Employees for Commercial Automotive Servicing
2016
Number of
Establishments
Number of
Number
Industry
NAICS
a
2016 NAICS Title
Workers
per Site b
of ONUs
per Site b
441110
Automobile Dealers
46,531
6
1
Automotive
Servicing
811111
General Automotive Repair
80,243
2
0
811112
Automotive Exhaust System Repair
1,907
2
0
811113
Automotive Transmission Repair
4,684
2
0
811118
Other Automotive Mechanical and
3,839
0
Electrical Repair and Maintenance
Z
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2016
Number of
Establishments
Number of
Number
Industry
NAICS
a
2016 NAICS Title
Workers
per Site b
of ONUs
per Site b
811121
Automotive Body, Paint, and Interior
Repair and Maintenance
33,648
3
0
811122
Automotive Glass Replacement Shops
6,106
2
0
811191
Automotive Oil Change and Lubrication
Shops
8,380
4
0
811192
Car Washes
15,902
5
0
811198
All Other Automotive Repair and
Maintenance
4,140
2
0
811211
Consumer Electronics Repair and
Maintenance
1,814
3
0
811212
Computer and Office Machine Repair and
Maintenance
5,195
4
0
Other
Industries
Conducting
Aerosol
Degreasing
811213
Communication Equipment Repair and
Maintenance
1,604
5
1
811219
Other Electronic and Precision Equipment
Repair and Maintenance
3,470
6
1
811310
Commercial and Industrial Machinery and
Equipment (except Automotive and
Electronic) Repair and Maintenance
21,721
5
1
811411
Home and Garden Equipment Repair and
Maintenance
1,735
1
1
811490
Other Personal and Household Goods
9,943
1
1
Repair and Maintenance
I
451110
Sporting Goods Stores
21,890
1
0
Total establishments and number of potentially exposed workers
and ONUs =c
270,000
910,000
110,000
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016: U.S. Census Bureau. 2015)
a Source: (U.S. EPA. 2016c)
b Rounded to the nearest whole number.
0 Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
2.13.2.3 Occupational Exposure Assessment Methodology
2.13.2.3.1 Inhalation and Vapor-Through-Skin
EPA did not find monitoring data for the use of NMP products during automotive servicing. Because
EPA did not find relevant monitoring data monitoring data for this use in the published literature, EPA
used modeling estimates to assess exposure for this use, as described below.
In lieu of monitoring data, EPA modeled potential occupational inhalation and vapor-through-skin
exposures for workers and ONUs using EPA's model for Occupational Exposures daring Aerosol
Degreasing of Automotive Brakes. This model involves probabilistic modeling. This model uses a near-
field/far-field approach, where an aerosol application located inside the near-field generates a mist of
droplets, and indoor air movements lead to the convection of the droplets between the near-field and far-
field. Workers are assumed to be exposed to NMP droplet concentrations in the near-field, while ONUs
are exposed at concentrations in the far-field. Appendix A. 13 includes some background information on
this model, EPA's rationale for using this model, and the model results.
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The results of this modeling are summarized for workers in Table 2-67 and for ONUs in Table 2-68.
This model calculates both 8-hour TWA and 1-hour TWA exposure concentrations. For workers, EPA
uses the 50th and 95th percentile model results in Table 2-67 to represent central tendency and high-end
NMP air concentrations, respectively. Consistent with the approach for other OESs, EPA uses the
central tendency worker air concentration to evaluate ONU exposure and further refines this estimate
using far-field modeling or applicable area monitoring data if needed due to risk. Refinement was not
necessary for this OES.
Table 2-67. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Commercial Automotive Servicing i
Work
Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hour
TWA)
(mg/m3)
Aerosol
Degreasing
Central tendency
(50th percentile)
6.39
19.96 (duration =
1 hr)
Occupational
Exposures during
Aerosol Degreasing
of Automotive Brakes
Model
Not
applicable a
High-end (95th
percentile)
43.4
128.8 (duration =
1 hr)
a EPA models are standard sources used by RAD for engineering assessments. EPA did not systematically review models that
were developed by EPA.
Table 2-68. Summary of Occupational Non-User Inhalation and Vapor-Through-Skin Exposure
During Commercial Automotive Servicing
Work
Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hour
TWA)
(mg/m3)
Aerosol
Degreasing
Central Tendency
0.13
0.40 (duration = 1
hr)
Occupational
Exposures during
Aerosol Degreasing
of Automotive Brakes
Model
Not
applicable a
High-end
1.57
4.71 (duration = 1
hr)
" EPA models are standard sources used by RAD for engineering assessments. EPA did not systematically review models that
were developed by EPA.
2.13.2.3.2 Dermal Exposure to Liquid
Table 2-69 summarizes the parameters used to assess dermal exposure to liquid during cleaning
activities. EPA assumed that the skin was exposed dermally to NMP at the specified liquid weight
fraction, skin surface area, and duration of contact with liquid.
NMP Weight Fraction
As discussed in Section 2.13.1, EPA identified two aerosol cleaning products containing NMP at
concentrations of 4.5 weight percent and between 35 and 40 weight percent. EPA identified multiple
additional automotive care products ranging in NMP concentration from 0.1 to 40 weight percent, which
are summarized in Appendix D. Based on this information, EPA calculated central tendency (50th
Page 113 of 292
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percentile) and high-end (95th percentile) weight percent of NMP to be 2.5 and 33, respectively. Note
that, where NMP concentration was provided in a range, EPA used the midpoint of the range in the
distribution of NMP concentrations used for the calculations of central tendency and high-end NMP
concentration. The underlying data used for these estimates have an overall confidence rating of high.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (6 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (12 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. Based on EPA's model for Occupational Exposures daring Aerosol Degreasing of
Automotive Brakes described in Appendix A. 13, EPA assessed a what-if duration of contact with liquid
of 1 hour (based on the length of time for aerosol degreasing of one job).
Table 2-69. Summary of Parameters for Worker Dermal Exposure to Liquids During Commercial
Automotive Servicing
Work Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Central Tendency
0.025
445 (f)
535 (m)
4
Commercial
Automotive
Servicing
High-End
0.33
890 (f)
1,070 (m)
8
74 (f)
What-if (duration-
based)
0.025
445 (f)
535 (m)
1
88 (m)
What-if (duration-
based)
0.33
890 (f)
1,070 (m)
1
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.13.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-70.
The numeric parameters corresponding to the characterizations presented in Table 2-70 are summarized
in Table 2-71. These are the inputs used in the PBPK model.
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Table 2-70. Characterization of PBPK Model Input Parameters for Commercial Automotive
Servicing
Scenario
Work
Activity
Air Concentration
Data
Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
Fraction
Characterization
Central
Tendency
Aerosol
degreasing
Central tendency (50th
percentile)
Half shift (4
hours)
1-hand
Central Tendency
High-end
Aerosol
degreasing
High-end (95th
percentile)
Full shift (8
hours)
2-hand
High-end
What-if
(duration-
based)
Aerosol
degreasing
Central tendency (50th
percentile)
Based on time
for one job
1-hand
Central Tendency
What-if
(duration-
based)
Aerosol
degreasing
High-end (95th
percentile)
Based on time
for one job
2-hand
High-end
Table 2-71. PBPK Model Input Parameters for Commercial Automotive Servicing
Scenario
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration
of Contact
with
Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Aerosol
degreasing
12.78
4
445 (f)
535 (m)
0.025
74 (f)
88 (m)
High-end
Aerosol
degreasing
43.4
8
890 (f)
1,070 (m)
0.33
74 (f)
88 (m)
What-if (duration-based)
Aerosol
degreasing
19.96
1
445 (f)
535 (m)
0.025
74 (f)
88 (m)
What-if (duration-based)
Aerosol
degreasing
128.8
1
890 (f)
1,070 (m)
0.33
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.13.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.14Laboratory Use
2.14.1 Process Description
The 2017 Scope Document for the Risk Evaluation for NMP (U.S. EPA. 2017c) and the "Preliminary
Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document (U.S.
EPA. 2017b) both indicate that NMP is used in laboratories, but do not identify any specific products
that are marketed for laboratory use. Additionally, no NMP-based laboratory chemicals were identified
in the 2017 market profile on NMP (Abt. 2017).
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EPA found limited information on the function of NMP in laboratory chemicals. The Scope Document
(U.S. EPA. 2017c) identifies one public comment to the NMP risk evaluation from the Motor &
Equipment Manufacturers Association (MEMA), which states that NMP is used as a carrier in chemical
analyses for research and development within the automotive industry (Holmes. 2017). One public
comment indicates that NMP is used as an ingredient in a laboratory reagent intended for water quality
analysis (Hach Company. 2020). A health study published in the Journal of Occupational Medicine
indicates NMP was used to dissolve solid samples, which were analyzed in atomic absorption
spectrophotometers, and subsequently discarded as hazardous waste (Solomon et al.. 1996). In this
application, NMP was poured by the laboratory technician from 5-gallon containers through an ion
exchange column for filtering before use.
Based on the information found, NMP is likely used in laboratories largely as a carrier chemical, which
is a media in which samples are prepared for analysis.
2.14.2 Exposure Assessment
2.14.2.1 Worker Activities
Workers may be potentially exposed to NMP in laboratories during multiple activities, including
unloading of NMP from the containers in which they were received, transferring NMP into laboratory
equipment (i.e., beakers, flasks, other intermediate storage containers), dissolving substances into NMP
or otherwise preparing samples that contain NMP, analyzing these samples, and discarding the samples.
In addition, NMP may be used to clean glassware, which is likely done manually by workers. These
activities are potential sources of worker exposure through dermal contact to liquid, vapor-through-skin,
and inhalation of NMP vapors.
The RIVM Annex XV Proposal for a Restriction - NMP report assessed potential worker exposures to
NMP during use in laboratories (RIVM. 2013). While this report does not have information from
industries on the type of engineering controls and worker PPE employed, RIVM does consider the use
of LEV in its assessment of potential worker exposures in laboratories. EPA expects that some
laboratories may use fume hoods.
The health study report at a laboratory that uses NMP to dissolve solid photoresist for quality testing
indicates that the lab uses LEV in some, but not all, areas within the lab (Solomon et al.. 1996). The
report also indicates that workers in the lab typically wear a lab coat, safety goggles, and latex gloves,
and occasionally use a half-face air-purifying respirator.
ONUs include employees that work at the sites where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario 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 NMP.
2.14.2.2 Number of Potentially Exposed Workers
EPA found limited information on the industries that use of NMP-based products in laboratories. The
public comment to the NMP risk evaluation docket from the Motor & Equipment Manufacturers
Association (MEMA) indicates that NMP is used for research and development within the automotive
industry (Holmes. 2017).
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Based on this information, EPA expects the NMP is used in professional laboratories and within the
automotive manufacturing industry. The use of NMP for research and development in other industries is
unknown. EPA compiled the associated NAICS codes for the identified industries in Table 2-72. The
number of workers associated with each industry using Bureau of Labor Statistics' OES data (U.S. BLS.
2016) and the U.S. Census' SUSB (U.S. Census Bureau. 2015). The number of establishments within
each industry that use NMP and the number of employees within an establishment exposed to NMP are
unknown. Therefore, EPA provides the total number of establishments and employees in these industries
as bounding estimates of the number of establishments that use and the number of employees that are
potentially exposed to NMP in a laboratory setting. These bounding estimates are likely overestimates of
the actual number of establishments and employees potentially exposed to NMP in laboratories.
Table 2-72. US Number of Establishments and Employees for Laboratory Use
Industry
2016
NAICS
2016 NAICS Title
Number of
Establishments
Number of
Workers
Site a
Number
of ONUs
per Sitea
Automotive
Research &
Development
336100
Motor Vehicle Manufacturing
340
235
99
336200
Motor Vehicle Body and Trailer
Manufacturing
1,917
41
7
336300
Motor Vehicle Parts Manufacturing
5,088
51
15
Professional
Laboratories
541380
Testing Laboratories
6844
1
9
Total number of establishments, workers, and ONUs potentially
exposed b
14,000
420,000
180,000
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016: U.S. Census Bureau. 2015)
a Rounded to the nearest worker. No 2016 BLS data found for this NAICS. EPA determined number of workers per site by
dividing the total number of employees by the total number of establishments from SUSB data.
b Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
2.14.2.3 Occupational Exposure Assessment Methodology
2.14.2.3.1 Inhalation and Vapor-Through-Skin
Appendix A. 14 summarizes EPA's methodology for determining potential NMP air concentrations
during this scenario. EPA only found one data source that had inhalation monitoring data, representing
the preparation of NMP for use in samples, sample preparation involving the dissolving of solids in
NMP, and sample analysis. This sample result is used as input into the PBPK model for 2-hour task
duration. EPA did not find additional monitoring data, thus used a modeled exposure for the use of NMP
in a laboratory setting from the RIVM Annex Xlr Proposal for a Restriction - NMP report (RIVM. 2013)
to represent 8-hour NMP exposure concentration. As the quality of both the monitoring and
modeled data is acceptable, EPA used all available data to assess this scenario.
The monitoring data and modeled exposure summarized in Table 2-73 are the input parameters used for
the PBPK modeling. Note that EPA assesses full-shift duration and a 2-hour task duration based on the
available monitoring data (Solomon et al.. 1996) (two hours is the duration of the sampled task - sample
preparation and analysis).
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Table 2-73. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Laboratory Use i
Full-Shift NMP
Duration-Based
NMP Air
Concentration
Data
Quality
Work
Activity
Parameter
Characterization
Air Concentration
Source
(mg/m3, 8-hour
TWA)
(mg/m3)
Rating
Laboratory
Central tendency
(unknown statistical
characterization)
2.07
0.200 (duration = 2
hr)
(Solomon et
al.. 1996)
Medium
Use
High-end (unknown
statistical
4.13
No data
(RIVM.
2013)
High
characterization)
EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from laboratory use of NMP. Since ONUs do not directly handle NMP (otherwise they would
be considered workers), ONU inhalation exposures could be lower than worker inhalation exposures.
Information on activities where ONUs may be present are insufficient to determine the proximity of
ONUs to workers and sources of emissions, so relative exposure of ONUs to workers cannot be
quantified.
2.14.2.3.2 Dermal Exposure to Liquid
Table 2-74 summarizes the parameters used to assess dermal exposure to liquid during use of NMP in
laboratories. EPA assumed that the skin was exposed dermally to NMP at the specified liquid weight
fraction, skin surface area, and duration of contact with liquid.
NMP Weight Fraction
EPA found limited information on the concentration of NMP carrier and reagent solutions used in
laboratories, which is summarized in Appendix D. Neither the 2017 market profile on NMP (Abt 2017)
nor the "Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document (U.S. EPA. 2017b) any NMP products that are marketed for laboratory use. Because NMP is
used as a carrier chemical, EPA expects that NMP may be used in pure form (i.e., 100 percent NMP).
This assumption was also used by RIVM in the Proposal for Restriction of NMP report (RIVM. 2013).
While NMP may be used in concentrations below 100 weight percent, EPA did not find additional
information on these potential concentrations.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (6 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (12 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. EPA did not find information on task durations for a what-if (duration-based) scenario.
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EPA assessed a what-if duration of contact with liquid of 2 hours based on the task duration for the
preparation and analysis of a sample containing NMP, as shown in Appendix A. 14.
Table 2-74. Summary of Parameters for Worker Dermal Exposure to Liquids During Laboratory
Use
Work
Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Laboratory
Use
Central tendency
1
445 (f)
535 (m)
4
74 (f)
88 (m)
High-end
1
890 (f)
1,070 (m)
8
What-if (duration-
based)
1
445 (f)
535 (m)
2
What-if (duration-
based)
1
890 (f)
1,070 (m)
2
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.14.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-75.
The numeric parameters corresponding to the characterizations presented in Table 2-75 are summarized
in Table 2-76. These are the inputs used in the PBPK model.
Table 2-75. Characterization of PBPK Model Input Parameters by Laboratory Use
Scenario
Work
Air Concentration
Duration of
Contact with
Liquid
Skin
Surface
NMP Weight
F raction
Characterization
Activity
Data Characterization
Area
Exposed
Central
Tendency
Laboratory
activities
Central tendency
(unknown statistical
characterization)
Half shift (4
hours)
1-hand
N/A - 100% is
assumed
High-end
Laboratory
activities
High-end (unknown
statistical
characterization)
Full shift (8
hours)
2-hand
N/A - 100% is
assumed
What-if
(duration-
based)
Laboratory
activities
Single estimate
Based on 2-
hour TWA
data
1-hand
N/A - 100% is
assumed
What-if
(duration-
based)
Laboratory
activities
Single estimate
Based on 2-
hour TWA
data
2-hand
N/A - 100% is
assumed
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Table 2-76. PBPK Model Input Parameters for Laboratory Use
Scenario
Work
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration
of Contact
with
Liquid
(hr)
Skin
Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Laboratory
activities
0.10
4
445 (f)
535 (m)
1
74 (f)
88 (m)
High-end
Laboratory
activities
4.13
8
890 (f)
1,070 (m)
1
74 (f)
88 (m)
What-if (duration-based)
Laboratory
activities
0.20
2
445 (f)
535 (m)
1
74 (f)
88 (m)
What-if (duration-based)
Laboratory
activities
0.20
2
890 (f)
1,070 (m)
1
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
°EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.14.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.15Lithium Ion Cell Manufacturing
2.15.1 Process Description
NMP is used as a solvent in lithium ion cell manufacturing (Mitsubishi Chemical. 2017). A carrier for
binders used in coatings used in the production of anodes and cathodes for lithium ion battery cells
(EaglePicher Technologies. 2020a; Roberts. 2017). In public comments submitted to the EPA NMP risk
evaluation docket, multiple companies indicated that NMP is first mixed with powder chemicals,
binders, and other substrates, then the slurry is coated onto thin metal foils with an automated coating
process (EaglePicher Technologies. 2020a; LICM. 2020a; Roberts. 2017). The slurry may be mixed on-
site or arrive at lithium ion cell manufacturing sites pre-mixed (EaglePicher Technologies. 2020a). The
slurry is then applied onto a foil substrate in an automated process and thermally dried, which causes the
NMP to evaporate, leaving a plate that is used to make battery cell components. Capture systems capture
the evaporated NMP, which may be vented (EaglePicher Technologies. 2020a). purified for reuse
(LICM. 2020a). or collected for hazardous waste disposal (LICM. 2020a).
2.15.2 Exposure Assessment
2.15.2.1 Worker Activities
During the uses of NMP in lithium ion cell manufacturing, workers are potentially exposed while
unloading NMP from containers and charging it into equipment. If containers are not manually unloaded
by workers, workers may still be potentially exposed when connecting and disconnecting transfer hoses
between the containers and equipment. Workers may also be potentially exposed during dilution,
mixing, or sampling of solutions containing NMP, if these processes occur (Saft, 2017; RIVM. 2013).
All these activities are potential sources of worker exposure through dermal contact to liquid, vapor-
through-skin, and inhalation of NMP vapors.
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Public comments from lithium ion cell manufacturers and trade associations indicate that processes are
semi or fully automated (EaglePicher Technologies. 2020a). In addition, public comments indicate that
operations in the lithium ion cell manufacturing process contain significant engineering controls to
control the moisture content of solutions containing NMP and prevent worker contact with NMP
(EaglePicher Technologies. 2020a; LICM. 2020c). The public comments indicate that workers always
wear PPE, including protective clothing, gloves specifically designed to protect against NMP exposure,
respirators, goggles or face-shields, depending on the task (Saft, EaglePicher Technologies. 2020a;
LICM. 2020a. c; 2017). Public comments also indicated that employees receive training on PPE usage,
which is supplemented with signage in the workplace and dedicated areas to don and doff PPE
(EaglePicher Technologies. 2020a; LICM. 2020c).
ONUs include employees that work at the sites where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario include
supervisors, managers, and other employees that may be in the production areas 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
NMP.
2.15.2.2 Number of Potentially Exposed Workers
Based on the processes described in Section 2.15.1, NMP is used in lithium ion cell manufacturing,
which is included in NAICS code 335910, battery manufacturing, as shown in Table 2-77. The number
of workers associated with this NAICS code was identified using Bureau of Labor Statistics' OES data
(U.S. BLS. 2016) and the U.S. Census' SUSB (U.S. Census Bureau. 2015). The number of lithium ion
cell manufacturing establishments that use NMP and the number of employees within an establishment
exposed to NMP are unknown. Therefore, EPA provides the total number of establishments and
employees as bounding estimates of the number of establishments that use and the number of employees
that are potentially exposed to NMP in lithium ion cell manufacturing. These bounding estimates are
likely overestimates of the actual number of establishments and employees potentially exposed to NMP
in the lithium ion cell manufacturing industry.
Table 2-77. US Number of Establishments and Employees for Lithium Ion Cell Manufacturing
Occupational
Exposure
Scenario
2016
NAICS
2016 NAICS Title
Number of
Establishments
Number of
Workers Site a
Number of
ONUs per Site a
Lithium Ion
Cell
Manufacturing
335910
Battery Manufacturing
208
47
17
Total number of establishments, workers, and ONUs
potentially exposed b
208
9,800
3,500
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016; U.S. Census Bureau. 2015)
a Rounded to the nearest whole number.
b Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
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2.15.2.3 Occupational Exposure Assessment Methodology
2.15.2.3.1 Inhalation and Vapor-Through-Skin
Appendix A. 15 summarizes the inhalation monitoring data for use of NMP in lithium ion cell
manufacturing. Based on the available monitoring data, EPA assessed the following occupational
exposure scenarios (LICM. 2020a):
Container handling, small containers,
Container handling, drums,
Cathode coating,
Cathode mixing,
Research and development, and
Miscellaneous.
For lithium ion cell manufacturing, EPA used data provided by the Lithium Ion Cell Manufacturers'
Coalition (LICM. 2020a). These data include 8-hour TWA personal breathing zone monitoring data for
NMP during cathode coating, cathode mixing, research and development, and miscellaneous activities
(e.g., mix room, maintenance, and cleaning). Information from the Lithium Ion Cell Manufacturers'
Coalition and EaglePicher also indicate that NMP may be unloaded from small containers and drums
and that waste NMP may be loaded into drums (EaglePicher Technologies. 2020b; LICM. 2020b);
therefore, EPA assessed occupational exposure scenarios for both small containers handling and drum
handling. No monitoring data for small container handling or drum handling were available for the
lithium ion cell manufacturing industry. EPA used monitoring data for these occupational exposure
scenarios for semiconductor manufacturing, as described in Section 2.10.2.3.1. These data were
summarized into the PBPK modeling full-shift input parameters in Table 2-78. Where non-detect
measurements exist in the datasets discussed above, EPA used the LOD divided by two for central
tendency and high-end calculations (U.S. EPA 1994b).
Table 2-78. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Lithium Ion Cell Manufact
uring
Work Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3,12-hour
TWA)
(mg/m3)
Lithium ion cell
manufacturing -
Container handling,
small containers
Central tendency
(50th percentile)
0.507
No data
(SIA.
2019b)
High
High-end (95th
percentile)
0.608
No data
Lithium ion cell
manufacturing -
Container handling,
drums
Central tendency
(50th percentile)
0.013
No data
High-end (95th
percentile)
1.54
No data
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Work Activity
Parameter
Characterization
Full-Shift NMP
Air
Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3,12-hour
TWA)
(mg/m3)
Lithium ion cell
manufacturing -
Cathode coating
Central tendency
(50th percentile)
4.87 a
No data
(LICM.
2020a)
High
High-end
(maximum)
39.7 a
No data
Lithium ion cell
manufacturing -
Cathode mixing
Central tendency
(50th percentile)
2.19 a
No data
High-end (95th
percentile)
9.61 a
No data
Lithium ion cell
manufacturing -
Research and
development
Central tendency
(50th percentile)
0.373 a
No data
High-end
(maximum)
4.05 a
No data
Lithium ion cell
manufacturing -
Miscellaneous
additional activities
Central tendency
(50th percentile)
6.08 a
No data
High-end
(maximum)
7.30 a
No data
High-end (95th
percentile)
1.54
No data
High-end (95th
percentile)
44.2 a
No data
a These are 8-hour TWA values.
EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from lithium ion cell manufacturing. Since ONUs do not directly handle formulations
containing NMP (otherwise they would be considered workers), ONU inhalation exposures could be
lower than worker inhalation exposures. Information on activities where ONUs may be present are
insufficient to determine the proximity of ONUs to workers and sources of emissions, so relative
exposure of ONUs to workers cannot be quantified.
2.15.2.3.2 Dermal Exposure to Liquid
Table 2-79 summarizes the parameters used to assess dermal exposure to liquid during use of NMP in
lithium ion cell manufacturing. EPA assumed that the skin was exposed dermally to NMP at the
specified liquid weight fraction, skin surface area, and duration of contact with liquid.
NMP Weight Fraction
Information from the Lithium Ion Cell Manufacturers' Coalition and EaglePicher provided NMP
concentration data for certain occupational exposure scenarios (e.g., small container handling, drum
handling, cathode slurry mixing, cathode coating, and miscellaneous) (EaglePicher Technologies.
2020b; LICM. 2020c). These data were provided as one or two values per occupational exposure
scenario, which are summarized in Appendix D. Where one data point was available, EPA used the one
value for both central tendency and high-end. Where two data points were available, EPA used the lower
value for central tendency and the higher value for high-end. Where there was no NMP concentration
Page 123 of 292
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data for an occupational exposure scenario, EPA used NMP concentrations determined from literature as
described for other electronics manufacturing in Section 2.9.2.3.2.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (4 or 6 hours depending on the available monitoring data) and a high-end
duration of contact with liquid equal to the length of a full shift (8 or hours depending on the available
monitoring data). Where task duration data are available, EPA uses these durations for what-if (duration-
based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to the task
duration. For the lithium ion cell manufacturing work activities, information from the Lithium Ion Cell
Manufacturers' Coalition included duration data for occupational exposure scenarios (e.g., small
container handling, drum handling, cathode slurry mixing, cathode coating, and miscellaneous)
(EaglePicher Technologies. 2020b; LICM. 2020c). For the remaining worker activities, EPA used a
what-if duration of contact with liquid of 2.5 hours based on the estimated time workers use NMP in the
lithium ion cell manufacturing process from (EaglePicher Technologies. 2020a).
Table 2-79. Summary of Parameters for Worker Dermal Exposure to Liquids During Lithium Ion
Cell Manufacturing
Work Activity
Parameter
Characterization
NMP
Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Central Tendency
0.99
445 (f)
535 (m)
6
Lithium ion cell
manufacturing - Container
handling, small containers
High-End
1
890 (f)
1,070 (m)
12
74 (f)
What-if (duration-
based)
0.99
445 (f)
535 (m)
0.5
88 (m)
What-if (duration-
based)
1
890 (f)
1,070 (m)
1
Central Tendency
0.6
445 (f)
535 (m)
6
Lithium ion cell
manufacturing - Container
handling, drums
High-End
1
890 (f)
1,070 (m)
12
74 (f)
What-if (duration-
based)
0.6
445 (f)
535 (m)
0.5
88 (m)
What-if (duration-
based)
1
890 (f)
1,070 (m)
1
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Work Activity
Parameter
Characterization
NMP
Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Lithium ion cell
manufacturing - Cathode
coating
Central Tendency
0.6
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
0.6
890 (f)
1,070 (m)
8
What-if (duration-
based)
0.6
445 (f)
535 (m)
2
What-if (duration-
based)
0.6
890 (f)
1,070 (m)
6
Lithium ion cell
manufacturing - Cathode
slurry mixing
Central Tendency
0.6
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
0.6
890 (f)
1,070 (m)
8
What-if (duration-
based)
0.6
445 (f)
535 (m)
0.5
What-if (duration-
based)
0.6
890 (f)
1,070 (m)
0.5
Lithium ion cell
manufacturing - Research
and development
Central Tendency
0.6
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
1
890 (f)
1,070 (m)
8
What-if (duration-
based)
0.6
445 (f)
535 (m)
2.5
What-if (duration-
based)
1
890 (f)
1,070 (m)
2.5
Lithium ion cell
manufacturing -
Miscellaneous additional
activities
Central Tendency
0.6
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
1
890 (f)
1,070 (m)
8
What-if (duration-
based)
0.6
445 (f)
535 (m)
1
What-if (duration-
based)
1
890 (f)
1,070 (m)
4
High-End
1
890 (f)
1,070 (m)
8
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.15.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-80.
The numeric parameters corresponding to the characterizations presented in Table 2-80 are summarized
in Table 2-81. These are the PBPK model inputs determined by EPA.
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Table 2-80. Characterization of PBPK Model Input Parameters for Lithium Ion Cell
Manufacturing
Scenario
Work
Activity
Air Concentration
Data
Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
All
activities
Central tendency (50th
percentile)
Mid-point of
shift duration (6
or 4 hours)
1-hand
Central tendency
High-end
All
activities
High-end (95th
percentile)
High-end of
shift duration (8
or 12 hours)
2-hand
High-end
What-if
(duration-
based)
All
activities
Central tendency (50th
percentile)
Task-based
duration
1-hand
Central tendency
What-if
(duration-
based)
All
activities
High-end (95th
percentile)
Task-based
duration
2-hand
High-end
Table 2-81. PBPK Model Input Parameters for Lithium Ion Cell Manufacturing
Duration-
Duration
of
Contact
with
Liquid
(hr)
Skin
Based NMP
Surface
NMP
Body
Activity
Scenario
Air
Concentration
(mg/m3)
Area
Exposed
(cm2)a b c
Weight
Fraction
Weight
(kg)a
Lithium ion cell
manufacturing -
Container
handling, small
containers
Central Tendency
0.507
6
445 (f)
535 (m)
0.99
74 (f)
88 (m)
High-End
0.608
12
890 (f)
1,070 (m)
1
74 (f)
88 (m)
What-if (duration-
based)
0.507
0.5
445 (f)
535 (m)
0.99
74 (f)
88 (m)
What-if (duration-
based)
0.608
1
890 (f)
1,070 (m)
1
74 (f)
88 (m)
Central Tendency
0.013
6
445 (f)
535 (m)
0.6
74 (f)
88 (m)
Lithium ion cell
manufacturing -
High-End
1.54
12
890 (f)
1,070 (m)
1
74 (f)
88 (m)
Container
handling, drums
What-if (duration-
based)
0.013
0.5
445 (f)
535 (m)
0.6
74 (f)
88 (m)
What-if (duration-
based)
1.54
1
890 (f)
1,070 (m)
1
74 (f)
88 (m)
Central tendency
9.74
4
445 (f)
535 (m)
0.6
74 (f)
88 (m)
Lithium ion cell
manufacturing -
Cathode coating
High-end
39.7
8
890 (f)
1,070 (m)
0.6
74 (f)
88 (m)
What-if (duration-
based)
23.4
2
445 (f)
535 (m)
0.6
74 (f)
88 (m)
What-if (duration-
based)
191
6
890 (f)
1,070 (m)
0.6
74 (f)
88 (m)
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Duration-
Duration
of
Contact
with
Liquid
(hr)
Skin
Based NMP
Surface
NMP
Body
Activity
Scenario
Air
Concentration
(mg/m3)
Area
Exposed
(cm2)a b c
Weight
Fraction
Weight
(kg)a
Central tendency
4.38
4
445 (f)
535 (m)
0.6
74 (f)
88 (m)
Lithium ion cell
manufacturing -
High-end
9.61
8
890 (f)
1,070 (m)
0.6
74 (f)
88 (m)
Cathode slurry
mixing
What-if (duration-
based)
10.5
0.5
445 (f)
535 (m)
0.6
74 (f)
88 (m)
What-if (duration-
based)
46.1
0.5
890 (f)
1,070 (m)
0.6
74 (f)
88 (m)
Central tendency
0.746
4
445 (f)
535 (m)
0.6
74 (f)
88 (m)
Lithium ion cell
manufacturing -
High-end
4.05
8
890 (f)
1,070 (m)
1
74 (f)
88 (m)
Research and
development
What-if (duration-
based)
1.79
2.5
445 (f)
535 (m)
0.6
74 (f)
88 (m)
What-if (duration-
based)
19.4
2.5
890 (f)
1,070 (m)
1
74 (f)
88 (m)
Lithium ion cell
manufacturing -
Miscellaneous
additional
activities
Central tendency
12.2
4
445 (f)
535 (m)
0.6
74 (f)
88 (m)
High-end
7.30
8
890 (f)
1,070 (m)
1
74 (f)
88 (m)
What-if (duration-
based)
29.2
1
445 (f)
535 (m)
0.6
74 (f)
88 (m)
What-if (duration-
based)
35.0
4
890 (f)
1,070 (m)
1
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.15.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.16 Cleaning
2.16.1^ Process Description
NMP may be used in a variety of cleaning products that can be used in multiple occupational
applications, including industrial facilities and commercial shops. EPA identified the following distinct
NMP-containing cleaning products with expected occupational applications:
Aerosol degreasing,
Dip degreasing and cleaning products, and
Wipe cleaning, including use of spray-applied cleaning products.
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2.16.1.1 Aerosol Degreasing
EPA's 2017 market profile for NMP (Abt 2017) and "Preliminary Information on Manufacturing,
Processing, Distribution, Use, and Disposal: NMP" document (U.S. EPA 2017b) identified three
aerosol cleaning products containing NMP. One product is listed as a bore cleaning foam with 4.5
weight percent NMP (Abt 2017; U.S. EPA 2017b). Another product is listed as an aerosol stainless
polish with an unknown concentration of NMP (U.S. EPA 2017b). The final product is listed as a resin
remover used as an aerosol with a concentration of 35 to 40 weight percent NMP (Abt 2017; U.S. EPA
2017b). A public comment on the NMP risk evaluation docket from CRC Industries, Inc. indicates that
NMP is present at less than 20 weight percent in their gasket removal products (Rudnick. 2017).
EPA did not find monitoring data for the use of the above4isted aerosol cleaners and did not identify
information that clearly defines scenarios in which these aerosol cleaners are used. However, EPA has
identified NMP as a potential ingredient in aerosol brake cleaners (see Section 2.13). Therefore, EPA
assesses potential inhalation and vapor-through-skin exposures during the aerosol cleaning of
automotive brakes and assesses these potential exposures as surrogate for miscellaneous aerosol
cleaning. Section 2.13 presents the assessment of aerosol brake cleaning.
2.16.1.2 Dip Degreasing and Cleaning
NMP has historically been used for the degreasing of optical lenses and metal parts by dipping into a
tank containing NMP (Xiaofei et al.. 2000; BASF. 1993). A public comment to the NMP risk evaluation
docket indicates that NMP is used in the immersive cleaning of wire coating equipment at facilities that
also used NMP-based wire coatings (National Electrical Manufacturers Association. 2017).
In dip cleaning processes, the parts to be cleaned are first placed in a basket. Workers will then open the
lid of a tank containing NMP and submerge the basket into the tank (National Electrical Manufacturers
Association. 2017; Xiaofei et al.. 2000). The cleaning solution in the tank can range from 90 percent up
to 100 percent NMP and may optionally be heated (RIVM. 2013; BASF. 1993). Once the basket of parts
is submerged in the tank, the lid of the tank is closed and the parts soak in the NMP cleaning solution.
Sonication or some other form of agitation of the parts may be used to aid in the cleaning process. The
basket containing the parts is then lifted from the tank and the parts may be air dried or may be
transferred to a tank containing water to rinse the parts of any residual NMP or NMP-solubilized oil
remaining on the surfaces of the parts.
EPA's "Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document (U.S. EPA. 2017b) identified one cleaning product with an NMP concentration of 60 to 80
weight percent. EPA's 2017 market profile identified two additional products that can be used for
immersion cleaning of items such as spray gun heads (Abt. 2017). These products contain 40 to 60
weight percent NMP and >99 weight percent NMP, respectively. Additionally, literature indicates that
some dip cleaning processes use pure NMP (i.e., 100 percent NMP) (BASF. 1993).
2.16.1.3 Wipe Cleaning, Including Use of Spray-Applied Cleaning Products
Wipe cleaning involves first wetting towels or rags with cleaning solution or spraying, pouring, or
brushing the cleaning solution onto the surfaces to be cleaned. Spray products are deployed from non-
pressurized containers, such as bottles, and use a spray nozzle to discharge the liquid at a high velocity
to atomize the liquid into fine droplets. Some spray applications use an atomizing gas, such as air, to aid
in the atomization of the liquid (U.S. EPA. 2016c). Workers then manually wipe surfaces clean with
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towels and rags (Bader et al.. 2006). Any residual cleaning solution on the wiped surfaces is expected to
volatilize. The dirty towels and rags may be disposed of entirely or laundered so they may be reused.
EPA found limited information regarding products that are used for wipe cleaning. The 2017 market
profile for NMP (Abt 2017) identified numerous cleaning products of unknown application type (i.e.,
aerosol, dip, wipe), ranging in NMP concentration of <1 to 100 weight percent. Based on the SDSs for
these products, EPA believes that it is feasible that these products may be spray applied or otherwise
poured onto surfaces or rags and then wiped off.
2.16.2 Exposure Assessment
2.16.2.1 Worker Activities
Worker are potentially exposed to NMP when unloading cleaning solutions from containers, mixing
and/or diluting the solutions before use, performing cleaning activities (i.e., spraying, dipping, wiping),
and associated equipment cleaning and maintenance (RIVM. 2013). These worker activities are potential
sources of worker exposure through dermal contact to liquid, vapor-through-skin, and inhalation of
NMP vapors.
EPA did not find information on the customary engineering controls and worker PPE used in the many
industries that conduct cleaning activities. However, a public comment on the NMP risk evaluation
docket from the National Electrical Manufacturers Association (NEMA) indicates that, at facilities that
use NMP for wire coating and associated equipment cleaning, the cleaning tanks containing NMP are
enclosed and equipped with ventilation (National Electrical Manufacturers Association. 2017). This
comment also indicates that workers utilize PPE such as gloves, aprons and goggles.
ONUs include employees that work at the sites where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario include
supervisors, managers, and other employees that may be in the production areas 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
NMP.
2.16.2.2 Number of Potentially Exposed Workers
This section identifies relevant industries and worker population estimates for NMP-based cleaners.
Cleaning activities are widespread, occurring in many industries. EPA determined the industries likely
to use NMP for cleaning activities from the following sources: the non-CBI 2016 CDR results for NMP
(U.S. EPA. 2016a). the 2017 market profile for NMP (Abt. 2017). process descriptions for the use of
NMP for cleaning purposes (Xiaofei et al.. 2000; BASF. 1993). and the "Preliminary Information on
Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document (U.S. EPA. 2017b). EPA
estimates the number of potentially exposed workers for aerosol cleaning activities in Section 2.13.
In some cases, the industries that distinctly perform dip cleaning and/or spray/wipe cleaning are
unknown. For these cases, EPA conservatively assumes that cleaning within these industries may
involve all cleaning scenarios. EPA compiled the associated NAICS codes for the identified industries in
Table 2-82. EPA determined the number of workers associated with each industry from using Bureau of
Labor Statistics' OES data (U.S. BLS. 2016) and the U.S. Census' SUSB (U.S. Census Bureau. 2015).
The number of establishments within each industry that use NMP-based cleaning products and the
number of employees within an establishment exposed to NMP-based cleaning products are unknown.
Therefore, EPA provides the total number of establishments and employees in these industries as
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bounding estimates of the number of establishments that use and employees potentially exposed to
NMP-based cleaning products. These bounding estimates are likely overestimates of the actual number
of establishments and employees potentially exposed to NMP during cleaning activities.
Table 2-82. US Number of Establishments and Employees for Cleaning
Occupational
Exposure
Scenario
Occupational
Exposure
Scenario
Source
2016
NAICS
2016 NAICS Title
Number of
Establishments
Number of
Workers
per Sitea
Number
of ONUs
per Sitea
Dip Cleaning
(RIVM. 2013:
Commercial and
(Machinery,
Optical
IFA. 2010:
Xiaofei et al..
333300
Service Industry
Machinery
2,014
14
6
Lenses)
2000)
Manufacturing
(U.S. EPA.
Electric Lighting
2016a)
335100
Equipment
Manufacturing
1,104
17
5
Unknown -
assumes all
cleaning
scenarios may
occur in these
industries
(U.S. EPA.
2016a)
335200
Household Appliance
Manufacturing
303
102
20
(U.S. EPA.
2016a)
335300
Electrical Equipment
Manufacturing
2,124
28
12
(U.S. EPA.
Other Electrical
2016a)
335900
Equipment and
Component
Manufacturing
2,140
23
8
(U.S. EPA.
2016c)
811420
Reupholstery and
furniture repair
3,720
1
1
Total establishments and number of potentially exposed workers
and ONUs = b
11,000
190,000
71,000
Sources: Number of establishments, workers per site, ONUs per site - (U.S. BLS. 2016: U.S. Census Bureau. 2015)
a Rounded to the nearest whole number.
b Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
2.16.2.3 Occupational Exposure Assessment Methodology
2.16.2.3.1 Inhalation and Vapor-Through-Skin
Appendix A. 16 summarizes the inhalation monitoring data for NMP-based cleaning activities that EPA
compiled from published literature sources, including full-shift, short-term, and partial shift sampling
results. This appendix also includes EPA's rationale for inclusion or exclusion of these data in the risk
evaluation. EPA used the available monitoring data for use of NMP in cleaning that had the highest
quality rating to assess exposure for this use.
EPA used the available full-shift monitoring data and the modeled exposures for cleaning activities to
calculate central tendency (based on 50th percentile) and high-end (based on 95th percentile) NMP air
concentrations. These values are summarized in Table 2-83. EPA did not find what-if (duration-based)
exposure concentration data. Again, note that EPA did not assess aerosol exposures in this section, but
considers the modeled exposures in Section 2.13 to be the closest representation of these exposures
based on the available information.
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Table 2-83. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Cleaning i
Full-Shift NMP
Duration-Based
Work
Activity
Parameter
Characterization
Air
NMP Air
Data
Concentration
Concentration
Source
Quality
(mg/m3, 8-hour
TWA)
(mg/m3)
Rating
Dip Cleaning
/ Degreasing
Central tendency
(50th percentile)
0.57
No data
(RIVM. 2013: IFA.
2010; Nishimura et
al.. 2009; Bader et
Medium
to high
High-end (95th
percentile)
2.68
No data
al.. 2006; Xiaofei et
al.. 2000)
Spray / Wipe
Central tendency
(50th percentile)
0.49
No data
(OSHA. 2017;
RIVM. 2013; IFA.
2010; Nishimura et
al.. 2009; Bader et
al.. 2006)
Medium
Cleaning
High-end (95th
percentile)
2.70
No data
to high
EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from cleaning with formulations containing NMP. Since ONUs do not directly handle
formulations containing NMP (otherwise they would be considered workers), ONU inhalation exposures
could be lower than worker inhalation exposures. Information on activities where ONUs may be present
are insufficient to determine the proximity of ONUs to workers and sources of emissions, so relative
exposure of ONUs to workers cannot be quantified.
2.16.2.3.2 Dermal Exposure to Liquid
Table 2-84 summarizes the parameters used to assess dermal exposure to liquid during cleaning
activities. EPA assumed that the skin was exposed dermally to NMP at the specified liquid weight
fraction, skin surface area, and duration of contact with liquid.
NMP Weight Fraction
As discussed in Section 2.16.1, EPA identified three immersion cleaning formulations that range
concentrations of 40 to >99 weight percent NMP. Additionally, literature indicates that some dip
cleaning processes use pure NMP (i.e., 100 percent NMP) (BASF. 1993). Based on this information,
which is summarized in Appendix D, EPA calculated central tendency (50th percentile) and high-end
(95th percentile) weight percent of NMP to be 84.5 and 99.9, respectively. Note that, where NMP
concentration was provided in a range, EPA used the midpoint of the range in the distribution of NMP
concentrations used for the calculations of central tendency and high-end NMP concentration. The
underlying data used for these estimates have overall confidence ratings that range from medium to
high.
As discussed in Section 2.16.1, EPA found limited information regarding products that are used for
spray and wipe cleaning. The 2017 market profile for NMP (Abt 2017) identified numerous cleaning
products of unknown application type (i.e., aerosol, dip, wipe), ranging in NMP concentration of 0.1 to
100 weight percent. Based on the SDSs for these products, EPA believes that it is feasible that these
products may be spray applied or otherwise poured onto surfaces or rags and then wiped off. Based on
these data, EPA calculated central tendency (50th percentile) and high-end (95th percentile) weight
percent of NMP to be 31.3 and 98.9, respectively. Note that, where NMP concentration was provided in
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a range, EPA used the midpoint of the range in the distribution of NMP concentrations used for the
calculations of central tendency and high-end NMP concentration. The underlying data used for these
estimates have overall confidence ratings that range from medium to high.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (6 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (12 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. EPA did not find information on task durations for a what-if (duration-based) scenario.
Table 2-84. Summary of Parameters for Worker Dermal Exposure to Liquids During Cleaning
Work Activity
Parameter
Characterization
NMP Weight
Fraction
Skin Surface
Area Exposed a
Duration of
Contact with
Liquid
Body
Weighta
Unitless
cm2
hr/day
kg
Dip Degreasing
Central Tendency
0.845
445 (f)
535 (m)
4
74 (f)
and Cleaning
High-End
0.999
890 (f)
1,070 (m)
8
88 (m)
Spray/Wipe
Central Tendency
0.313
445 (f)
535 (m)
4
74 (f)
Cleaning
High-End
0.989
890 (f)
1,070 (m)
8
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.16.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-85.
The numeric parameters corresponding to the characterizations presented in Table 2-85 are summarized
in Table 2-86. These are the inputs used in the PBPK model.
Table 2-85.
Characterization of PBPK Model Input Parameters for Cleaning
Scenario
Work
Activity
Air Concentration
Data Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
Dip
cleaning
Central tendency (50th
percentile)
Half shift (4
hours)
1-hand
Central Tendency
High-end
Dip
cleaning
High-end (95th
percentile)
Full shift (8
hours)
2-hand
High-end
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Scenario
Work
Activity
Air Concentration
Data Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
F raction
Characterization
Central
Tendency
Spray /
wipe
cleaning
Central tendency (50th
percentile)
Half shift (4
hours)
1-hand
Central Tendency
High-end
Spray /
wipe
cleaning
High-end (95th
percentile)
Full shift (8
hours)
2-hand
High-end
Table 2-86. PBPK Model Input Parameters for Cleaning
Scenario
Activity
Duration-Based
NMP Air
Concentration
(mg/m3)
Duration of
Contact with
Liquid (hr)
Skin Surface
Area
Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
Dip
cleaning
1.14
4
445 (f)
535 (m)
0.845
74 (f)
88 (m)
High-end
Dip
cleaning
2.68
8
890 (f)
1,070 (m)
0.999
74 (f)
88 (m)
Central Tendency
Spray /
wipe
cleaning
0.98
4
445 (f)
535 (m)
0.313
74 (f)
88 (m)
High-end
Spray /
wipe
cleaning
2.70
8
890 (f)
1,070 (m)
0.989
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.16.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
2.17 Fertilizer Application
2.17.1^ Process Description
Based on information identified in the "Preliminary Information on Manufacturing, Processing,
Distribution, Use, and Disposal: NMP" document, NMP is used as a component in a variety of granular
or liquid pesticides, as well as in herbicides, fungicides, and dog flea treatments (U.S. EPA. 2017b). The
2017 Scope Document for the Risk Assessment of NMP and 2016 CDR results indicate that NMP may
also be used in fertilizers (U.S. EPA. 2017c. 2016a). The use of pesticides, including herbicides and
fungicides, is regulated under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) and is
not assessed in this risk evaluation. The use of flea treatments is regulated by the Food and Drug
Administration (FDA). However, the use of fertilizers is under the purview of TSCA and is assessed in
this risk evaluation.
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NMP is used both in the synthesis of and as a co-solvent in the formulation of agricultural chemicals
(U.S. EPA. 2017c; RIVM. 2013). When used for synthesis, NMP may only be present in the final
formulation in residual quantities. When used as a co-solvent, NMP remains in the final formulation,
usually in concentrations ranging from one to 20 weight percent (U.S. EPA. 2017b; RIVM. 2013). The
NMP Producers Group, Inc. submitted a comment to the NMP risk evaluation docket indicating that
NMP is used in a fertilizer additive that prevents the volatilization of urea (Roberts. 2017). The NMP
Producers Group, Inc. states that NMP comprises 15 to 45 weight percent of the fertilizer additive,
which is blended into a final fertilizer formulation at a recommended rate such that the final fertilizer
contains less than 0.1 weight percent NMP. Per the NMP Producers Group, Inc., the final fertilizer
formulations can be liquid or granular.
Fertilizer application is based on the physical form of the fertilizer, which is typically a liquid
solution/suspension or solid (MRI. 1998). Liquid solutions are often applied from a vehicle that houses a
tank containing the fertilizer. The fertilizer is metered from the vehicle and onto fields through a
manifold of spray nozzles. Applicators may adjust these spray nozzles to manipulate the flow of
fertilizer solution. Solid fertilizers are similarly applied from vehicles containing hoppers through which
the solid fertilizers are metered. The metered fertilizer drops onto a belt that feeds into spreading
equipment. The spreaders are usually either fans through which fertilizer is propelled or long booms that
extend from the back of the vehicle that drop fertilizer onto the field.
This information relates to the automated application of fertilizers from vehicles. Fertilizers may also be
applied manually by workers using handheld spray application systems or other types of application
equipment. EPA did not find additional information regarding the extent of automated versus manual
application of NMP-containing fertilizers or other agricultural products.
2.17.2 Exposure Assessment
2.17.2.1 Worker Activities
Workers are potentially exposed to NMP in fertilizers during multiple activities. These activities include
transfers of fertilizers from storage containers into application equipment, any additional mixing
activities that may occur prior to application, application of the fertilizers, and cleaning of application
equipment that may occur after application (NIOSH. 2014; RIVM. 2013). These activities are potential
sources of worker exposure through dermal contact to liquid, vapor-through-skin, and inhalation of
NMP vapors. In addition, if the fertilizers are granular, workers may have potential inhalation exposures
to dusts that contain NMP during the application of these fertilizers.
The 1993 Generic Scenario (GS) on the Application of Agricultural Pesticides indicates that workers
will typically wear boots, gloves, and masks during the application of pesticides on fields (U.S. EPA.
1993). A NIOSH Health Hazard Evaluation (HHE) on the application of sea lamprey pesticides found
that workers wore eye protection (safety glasses, goggles, or face shield) and chemical resistant gloves
when mixing and applying pesticides (NIOSH. 2014). The investigation also included the application of
granular pesticides, for which workers were observed wearing NIOSH-approved full facepiece dual
cartridge (particulate and organic vapor) respirators. EPA expects that similar PPE may be employed for
workers who apply fertilizers.
The RIVM Annex XV Proposal for a Restriction - NMP report recommends that workers who manually
apply agrochemicals by spraying and fogging wear protective coveralls and a respirator (RIVM. 2013).
For workers that apply agrochemicals from an automated vehicle, the report recommends that workers
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do so from a vented cab supplied with filtered air. Additionally, the report indicates that workers should
wear gloves for all work where dermal contact is possible.
EPA did not find information on the extent of use of the above engineering controls and PPE within the
fertilizer application industry.
ONUs include farmers that work at the farms where NMP is used, but they do not directly handle the
chemical and are therefore expected to have lower inhalation exposures and vapor-through-skin uptake
and are not expected to have dermal exposures by contact with liquids. ONUs for this scenario include
farm managers and other farmers that may be near the fields that are receiving fertilizer application, but
do not perform tasks that result in the same level of exposures as those workers that apply fertilizer
containing NMP.
2.17.2.2 Number of Potentially Exposed Workers
Fertilizer products containing NMP are used in the agricultural industry on crop farms (as opposed to
cattle farms). These farms are covered within the 3-digit NAICS group 111, Crop Production.
EPA compiled these identified NAICS codes in Table 2-87. EPA determined the number of workers
associated with each industry from U.S. Department of Agriculture (USD A) Census of Agriculture Data
(USD A 2014). The USD A conducts a census of agriculture instead of the US Census Bureau. Census of
agriculture data were available for 2012 and the number of farms and workers is summarized in Table
2-87. EPA did not find data on the number of workers and occupational non-users on a NAICS level.
Information on the total number of workers is available, but no information on the number of
occupational non-users was found in the census of agriculture.
The number of farms within each industry that use NMP-based fertilizers and the number of employees
at a farm exposed to these NMP-based products are unknown. Therefore, EPA provides the total number
of establishments and employees in these industries as bounding estimates of the number of
establishments that use and the number of employees that are potentially exposed to NMP-based
fertilizers. These bounding estimates are likely overestimates of the actual number of establishments and
employees potentially exposed to NMP during fertilizer application.
Table 2-87. U.S. Number of Establishments and Employees for Fertilizer Application
2016
NAICS
2016 NAICS Title
Number of
Establishments
Number of
Workers
Site a
Number of
ONUs per
Site3
1111
Oilseed and Grain Farming
369,332
NAICS specific data not
found
1112
Vegetable and Melon Farming
43,021
1113
Fruit and Tree Nut Farming
93,020
1114
Greenhouse, Nursery, and Floriculture Production
52,777
1119
Other Crop Farming
496,837
Total number of establishments, workers, and ONUs
potentially exposed b
1,100,000
1,300,000
Unknown
Sources: Number of establishments, workers per site, ONUs per site - (USDA. 2014)
a EPA did not find data on the number of workers and occupational non-users on a NAICS level. EPA determined the number
of total workers for these NAICS codes by multiplying the total number of workers for all farms on the 2012 NAICS by the
fraction of farms that fall within the listed NAICS codes.
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b Unrounded figures were used for total worker and ONU calculations. Totals may not add exactly due to rounding to two
significant figures.
2.17.2.3 Occupational Exposure Assessment Methodology
2.17.2.3.1 Inhalation and Vapor-Through-Skin
EPA did not find inhalation monitoring data for the application of fertilizers containing NMP. The
RIVM Annex XV Proposal for a Restriction -NMP report presented the modeled potential NMP air
concentrations during spray and fog application of agrochemicals (RIVM. 2013). EPA summarized
these modeled exposures in Appendix A. 17. Due to lack of additional information or modeling
approaches, EPA uses the modeled exposures from the RIVM Annex XF Proposal for a Restriction -
NMP report to represent potential NMP air concentrations during this scenario. These data are of
acceptable quality.
The input parameters used for the PBPK modeling based on the modeled exposures are summarized in
Table 2-88. The RIVM Annex XV Proposal for a Restriction - NMP report recommends that manual
application activities should be limited to four hours per shift or less (RIVM. 2013). Application with
more automated equipment and separation of the worker from the sources of exposure can exceed this
recommendation. EPA thus assesses both full-shift 8-hour TWA and half-shift 4-hour TWA NMP air
concentrations. EPA did not find data on what-if (duration-based) exposures.
Table 2-88. Summary of Parameters for PBPK Modeling of Worker Inhalation and Vapor-
Through-Skin Exposure During Fertilizer Application ^
Work Activity
Parameter
Characterization
Full-Shift NMP
Air Concentration
Duration-Based
NMP Air
Concentration
Source
Data
Quality
Rating
(mg/m3, 8-hour
TWA)
(mg/m3)
Manual spray or
boom application
of fertilizers a
Low-end (of range)
2.97
No data
(RIVM.
2013)
High
High-end (of range)
5.27
No data
" These data are from (RIVM. 2013) and are modeled exposures during the manual spray or boom application of
agrochemicals. No data on other forms of application were identified.
EPA has not identified personal or area data on or parameters for modeling potential ONU inhalation
exposures from application of fertilizers containing NMP. Since ONUs do not directly handle
formulations containing NMP (otherwise they would be considered workers), ONU inhalation exposures
could be lower than worker inhalation exposures. Information on activities where ONUs may be present
are insufficient to determine the proximity of ONUs to workers and sources of emissions, so relative
exposure of ONUs to workers cannot be quantified.
2.17.2.3.2 Dermal Exposure to Liquid
Table 2-89 summarizes the parameters used to assess dermal exposure to liquid during the use of
agricultural products containing NMP. EPA assessed dermal exposure to liquid NMP at the specified
liquid weight fraction, skin surface area, and duration of contact with liquid.
NMP Weight Fraction
As described in Section 2.17.1, the NMP Producers Group, Inc. indicated that NMP is present in
fertilizers in very small quantities, less than 0.1 weigh percent (Roberts. 2017). EPA identified multiple
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other agricultural products from the 2017 market profile on NMP and the "Preliminary Information on
Manufacturing, Processing, Distribution, Use, and Disposal: NMP" document; however, these products
are all pesticides and other products that are not regulated under TSCA (Abt. 2017; U.S. EPA. 2017b).
EPA excludes those products from this risk evaluation. The RIVM Annex XV Proposal for a Restriction
- NMP report indicates that NMP is typically less than seven weight percent in agrochemical
formulations (RIVM. 2013). Due to lack of additional information, EPA assesses a low-end
concentration of 0.1 percent and a high-end concentration of seven percent. The underlying data used for
these estimates have overall confidence ratings of high, as shown in Appendix D.
Skin Surface Area
As described in Section 1.4.3.2.2, EPA assessed high-end skin surface areas of 890 cm2 for females and
1,070 cm2 for males and central tendency skin surface areas of 445 cm2 for females and 535 cm2 for
males.
Duration of Contact with Liquid
As discussed in Section 1.4.3.2.4, EPA assessed a central tendency duration of contact with liquid equal
to the length of half a shift (6 hours) and a high-end duration of contact with liquid equal to the length of
a full shift (12 hours). Where task duration data are available, EPA uses these durations for what-if
(duration-based) scenarios, representing if a worker's duration of contact with liquid to NMP is equal to
the task duration. EPA did not find information on task durations for a what-if (duration-based) scenario.
Table 2-89. Summary of Parameters for Worker Dermal Exposure to Liquids During Fertilizer
Application
Work Activity
Parameter
Characterization
NMP
Weight
Fraction
Skin Surface
Area Exposed
b
Duration of
Contact with
Liquid
Body
Weight b
Unitless
cm2
hr/day
kg
Manual spray or boom
application of
fertilizers a
Central Tendency
0.001
445 (f)
535 (m)
4
74 (f)
88 (m)
High-End
0.07
890 (f)
1,070 (m)
8
a These data are from (RIVM. 2013) and are modeled exposures during the manual spray or boom application of
agrochemicals. No data on other forms of application were identified.
b EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
2.17.3 PBPK Inputs
Based on the methodology described in the previous sections, EPA assessed PBPK parameters for
central tendency and high-end exposure scenarios based on the characterizations listed in Table 2-90.
The numeric parameters corresponding to the characterizations presented in Table 2-90 are summarized
in Table 2-91. These are the inputs used in the PBPK model.
Table 2-90. Characterization of PBPK Model Input Parameters for Fertilizer Application
Scenario
Work Activity
Air Concentration
Data
Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
Fraction
Characterization
Central
Tendency
Manual spray or
boom
Low-end (of range)
Half shift (4
hours)
1-hand
Central Tendency
Page 137 of 292
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Scenario
Work Activity
Air Concentration
Data
Characterization
Duration of
Contact with
Liquid
Skin
Surface
Area
Exposed
NMP Weight
Fraction
Characterization
application of
fertilizers
High-end
Manual spray or
boom
application of
fertilizers
High-end (of range)
Full shift (8
hours)
2-hand
High-end
Table 2-91. PBPK Model Input Parameters for Fertilizer Application
Scenario
Duration-Based NMP
Air Concentration
(mg/m3)
Duration of
Contact with
Liquid (hr)
Skin Surface
Area Exposed
(cm2)a b c
NMP
Weight
Fraction
Body
Weight
(kg)a
Central Tendency
5.94
4
445 (f)
535 (m)
0.001
74 (f)
88 (m)
High-end
5.27
8
890 (f)
1,070 (m)
0.07
74 (f)
88 (m)
a EPA assessed these exposure factors for both females and males. Values associated with females are denoted with (f) and
values associated with males are denoted with (m).
b EPA modeled all glove protection factors (e.g. .1.5, 10, and 20) for workers in the "Risk Evaluation for n-
Methylpyrrolidone (2-Pyrrolidinone, 1 Methyl-) (NMP)."
0 EPA assessed a skin surface area exposed of 0.1 cm2for ONUs for each scenario. However, EPA did not assess glove usage
(protection factor = 1) for ONUs.
2.17.4 Summary
In summary, dermal exposure to liquid, inhalation, and vapor-through-skin exposures are expected for
this use. EPA has not identified additional uncertainties for this use beyond those included in Section 3.
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3 Discussion of Results
3.1 Variability
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.
3.2 Uncertainties and Limitations
Uncertainty is "the lack of knowledge about specific variables, parameters, models, or other factors" and
can be described qualitatively or quantitatively (U.S. EPA, 2001). The following sections discuss
uncertainties in each of the assessed NMP use scenarios.
3.2.1 Number of Workers
There are a number of uncertainties surrounding the estimated number of workers potentially exposed to
NMP, as outlined below.
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 NMP for the assessed applications. EPA
addressed this issue by refining the OES estimates using total employment data from the U.S. Census'
SUSB. However, this approach assumes that the distribution of occupation types (SOC codes) in each 6-
digit NAICS is equal to the distribution of occupation types at the parent 5-digit NAICS level. If the
distribution of workers in occupations with NMP exposure differs from the overall distribution of
workers in each NAICS, then this approach will result in inaccuracy. The effects of this uncertainty on
the number of worker estimates are unknown, as the uncertainties may result in either over or
underestimation of the estimates depending on the actual distribution.
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 NMP 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.
3.2.2 PBPK Input Parameters
Key uncertainties in the occupational exposure parameters are summarized below. Most parameters are
related specifically to the route of dermal contact with liquids by workers, while air concentrations are
related to the routes of inhalation and vapor-through-skin exposure. The body weight parameter is
related to all of these routes. The assumed values for human body weight have relatively lower
uncertainties, and the median values used may underestimate exposures at the high-end of PBPK
exposure results.
The dermal exposure to liquid parameters used in this assessment have uncertainties because many
parameters lack data and were therefore based on assumptions. The assumed parameter values with the
greatest uncertainties are glove use and effectiveness (using protection factors based on the ECETOC
TRA model that are what-if type values as described in Section 1.4.3.2.3), durations of contact with
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liquid, and skin surface areas for contact with liquids, and these assumed values may or may not be
representative of actual values. The assumed values for NMP concentrations in formulations have
relatively lower uncertainties. The midpoints of some ranges serve as substitutes for 50th percentiles of
the actual distributions and high ends of ranges serve as substitutes for 95th percentiles of the actual
distributions. However, these substitutes are uncertain and are weak substitutes for the ideal percentile
values. Generally, EPA cannot determine whether most of these assumptions may overestimate or
underestimate exposures. However, high-end duration of dermal contact estimates of 8 hours may be
more likely to overestimate exposure potential to some extent, and some activity-based durations may be
more likely to underestimate exposure potential to some extent. For many OESs, the high-end surface
area assumption of contact over the full area of two hands likely overestimates exposures. Occupational
non-users (ONUs) may have direct contact with NMP-based liquid products due to incidental exposure
at shared work areas with workers who directly work with NMP, and the estimate of zero surface area
contact may underestimate their exposure. The parameter values NMP concentrations are from available
data and are likely to have a relatively low impact on the magnitude (less than an order of magnitude, or
factor of 10) of overestimation or underestimation of exposure. The impact of vapors being trapped next
to the skin during glove use is also uncertain.
Where monitoring data are available, limitations of the data also introduce uncertainties into the
exposures. The principal limitation of the air concentration data is the uncertainty in the
representativeness of the data. EPA identified a limited number of exposure studies and data sets that
provided data for facilities or job sites where NMP was used. Some of these studies primarily focused on
single sites. This small sample pool introduces uncertainty as it is unclear how representative the data
for a specific end use are for all sites and all workers across the US. Differences in work practices and
engineering controls across sites can introduce variability and limit the representativeness of any one site
relative to all sites. Age of the monitoring data can also introduce uncertainty due to differences in work
practices and equipment used at the time the monitoring data were taken and those used currently, so the
use of older data may over- or underestimate exposures. Additionally, some data sources may be
inherently biased. For example, bias may be present if exposure monitoring was conducted to address
concerns regarding adverse human health effects reported following exposures during use. The effects of
these uncertainties on the occupational exposure assessment are unknown, as the uncertainties may
result in either over or underestimation of exposures depending on the actual distribution of NMP air
concentrations and the variability of work practices among different sites. Dermal exposures to NMP
vapor that may penetrate clothing fabrics and the potential for associated direct skin contact with
clothing saturated with NMP vapor are not included in quantifying exposures, which could potentially
result in underestimates of exposures.
The impact of these uncertainties precluded EPA from describing actual parameter distributions. In most
scenarios where data were available, EPA did not find enough data to determine complete statistical
distributions. Ideally, EPA would like to know 50th and 95th percentiles for each exposed population. In
the absence of percentile data for monitoring, the means or midpoint of the range serve as substitutes for
50th percentiles of the actual distributions and high ends of ranges serve as substitutes for 95th
percentiles of the actual distributions. However, these substitutes are uncertain and are weak substitutes
for the ideal percentile values. The effects of these substitutes on the occupational exposure assessment
are unknown, as the substitutes may result in either over or underestimation of exposures depending on
the actual distribution.
Where data were not available, the modeling approaches used to estimate air concentrations also have
uncertainties. Parameter values used in models did not all have distributions known to represent the
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modeled scenario. It is also uncertain whether the model equations generate results that represent actual
workplace air concentrations. Some activity-based modeling does not account for exposures from other
activities. Additional model-specific uncertainties are included below. In general, unless specified
otherwise, the effects of the below model-specific uncertainties on the exposure estimates are unknown,
as the uncertainties may result in either over or underestimation on exposures depending on the actual
distributions of each of the model input parameters.
3.2.2.1 Tank Truck and Railcar Loading and Unloading Release and Inhalation
Exposure Model
For manufacturing; repackaging; and recycling and disposal, the Tank Track and Railcar Loading and
Unloading Release and Inhalation Exposure Model was 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 NMP 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 NMP.
The model estimates fugitive emissions from equipment leaks using total organic compound
emission factors from EPA's Protocol for Equipment Leak Emission Estimates (U.S. EPA.
1995). 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 NMP, and
the accuracy of EPA's assumption on equipment type are not known.
3.2.2.2 Drum Loading and Unloading Release and Inhalation Exposure Model
For chemical processing, excluding formulation and incorporation into formulation, mixture, or reaction
product, the Dram Loading and Unloading Release and Inhalation Exposure Model was used to
estimate the airborne concentration associated with generic chemical loading scenarios at industrial
facilities. Specific uncertainties associated with this model are described below:
The model estimates fugitive emissions using the EPA OAOPS AP-42 Loading Model. The
applicability of the emission factors used in this model to NMP is not known.
EPA assigned statistical distributions based on available literature data or engineering judgment
to address the variability in Ventilation Rate (Q), Mixing Factor (k), Vapor Saturation Factor (f),
and Exposed Working Years per Lifetime (WY). The selected distributions may vary from the
actual distributions.
3.2.2.3 Model for Occupational Exposures during Aerosol Degreasing of Automotive
Brakes
The aerosol degreasing assessment uses a near-field/far-field approach (uncertainties on this approach
are presented below) to model worker exposure. Specific uncertainties associated with the aerosol
degreasing scenario are presented below:
The model references a CARB study (CARB. 2000) 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 degreasing applications involving NMP;
Aerosol formulations were taken from available safety data sheets, and some were provided as
ranges. For each Monte Carlo iteration the model selects an NMP concentration within the range
of concentrations using a uniform distribution. In reality, the NMP concentration in the
formulation may be more consistent than the range provided.
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3.2.2.4
Near-Field/Far-Field Model Framework
The near-field/far-field approach is used as a framework to model NMP air concentrations during
aerosol degreasing. 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 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. 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). A worker may actually walk away
from the near field during part of the process. As such, assuming the worker is exposed at the
near-field concentration for the entire activity duration may overestimate exposure.
The exposure models represent model workplace settings for NMP used in aerosol degreasing of
automotive brakes. The model has not been regressed or fitted with monitoring data.
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assessment. N-Methylpyrrolidone: Paint stripper use (CASRN: 872-50-4). In Office of Chemical
Safety and Pollution Prevention. (740-R1-5002). Washington, DC.
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reporting (May 2017 release). Washington, DC: US Environmental Protection Agency, Office of
Pollution Prevention and Toxics, https://www.epa.gov/chemical-data-reporting
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Year (Version 15). Retrieved from https://www.epa.gov/toxics-release-inventory-tri-program/tri-
basic-plus-data-files-calendar-years-1987-2017
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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 final.pdf
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Available online at https://www.epa.gov/hw/learn-basics-hazardous-waste
U.S. EPA (U.S. Environmental Protection Agency). (2017b). Preliminary information on manufacturing,
processing, distribution, use, and disposal: N-Methylopyrrolidone (NMP) [Comment], (Support
document for Docket EPA-HQ-OPPT-2016-0743). Washington, DC: Office of Pollution
Prevention and Toxics (OPPT), Office of Chemical Safety and Pollution Prevention (OCSPP).
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Methylpyrrolidone (2-Pyrrolidinone, 1-Methyl-). CASRN: 872-50-4 [EPA Report], (EPA-740-
Rl-7005). https://www.epa.gov/sites/production/files/2017-06/documents/nmp scope 6-22-
17 O.pdf "
U.S. EPA (U.S. Environmental Protection Agency). (2018a). 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.
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06/documents/final application of sr in tsca 05-31-18.pdf
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and Units. Available online at https://www.epa.gov/hwpermitting/hazardous-waste-management-
facilities-and-units
U.S. EPA (U.S. Environmental Protection Agency). (2018c). Problem formulation of the risk evaluation
for n-methylpyrrolidone (2-pyrrolidinone, 1-methyl-). (EPA-740-R1-7015). Washington, DC:
Office of Chemical Safety and Pollution Prevention, United States Environmental Protection
Agency, https://www.epa.gov/sites/production/files/2018-06/documents/nmp pf 05-31-18.pdf
U.S. EPA (U.S. Environmental Protection Agency). (2018d). Problem formulation of the risk evaluation
for N-Methylpyrrolidone (2-Pyrrolidinone, 1-Methyl-). CASRN: 872-50-4 [EPA Report], (EPA
Document# 740-R1-7015). United States Environmental Protection Agency , Office of Chemical
Safety and Pollution Prevention, Office of Pollution Prevention and Toxics.
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USD A (U.S. Department of Agriculture). (2014). 2012 census of agriculture. Available online at
https://www.nass.usda.gOv/Publications/AgCensus/2012/#full report
White. PL; Bardole. J A. (2004). Paint and finish removers.
WHO (World Health Organization). (2001). Concise International Chemical Assessment Document 35:
N-Methyl-2-Pyrrolidone. Geneva, Switzerland.
http://www.inchem.org/documents/cicads/cicads/cicad35.htm
Will W: Leuppert. G: Rossbacher. R. (2004). Poster: Dermal and inhalative uptake of N-methyl-2-
pyrrolidone (NMP) during paint stripping of furniture. 6th International Symposium on
Biological Monitoring in Occupational and Environmental Health, Heidelberg, Germany (as
cited in OECD, 2007).
Xiaofei. E; Wada. Y; Nozaki. J: Miyauchi. H; Tanaka. S: Seki. Y; Koizumi. A. (2000). A linear
pharmacokinetic model predicts usefulness of N-methyl-2-pyrrolidone (NMP) in plasma or urine
as a biomarker for biological monitoring for NMP exposure. J Occup Health 42: 321-327.
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APPENDICES
Appendix A Inhalation Data for Each Occupational Scenario
This appendix summarizes the personal monitoring data EPA found for each scenario, as well as EPA's
rationale for inclusion or exclusion in the risk evaluation.
A.l Manufacturing
EPA did not find monitoring data for the manufacture of NMP based on the information searched at the
time of preparation of this report. These data are summarized in TableApx A-l.
EPA identified modeled potential NMP air concentrations during manufacturing of NMP that were
included in the RIVM Annex XV Proposal for a Restriction -NMP report (RIVM. 2013). These modeled
exposures are presented in Rows 1 through 10. Rows 1 through 3 are for closed-system transfers of
NMP, with various degrees of control of the system (i.e., the system in Row 1 is the most well-
controlled, while the system in Row 3 is the least controlled closed system). RIVM modeled and
assessed potential NMP air concentrations during manufacturing for each of these three modeled
scenarios of system control levels. The report indicated closed-system transfers are likely for
manufacturing of NMP.
In addition to these closed systems, RIVM included modeled exposures for the transfer of NMP in open
systems, which the report assesses for conditions of use other than manufacturing (as closed systems are
assumed for manufacturing). These modeled exposures are presented in Rows 4 through 10 of
Table Apx A-l. EPA excludes those points that describe commercial operations, as manufacturing of
NMP is expected to be an industrial process.
EPA modeled potential worker NMP air concentrations during the loading of bulk storage containers
(i.e., tank trucks and rail cars) and drums with pure NMP using common loading models developed by
EPA, to compare to the RIVM modeled exposures. The loading activity during manufacture is expected
to present the highest potential for worker exposure during a shift. EPA assumes NMP is loaded into
transport containers and distributed in bulk as a pure substance (100 percent concentration).
For the loading of bulk containers with NMP, EPA developed the Tank Truck and Railcar Loading and
Unloading Release and Inhalation Exposure Model, which calculates potential exposure concentrations
based on the loading of one tank truck (central tendency case) and one rail car (high-end) assuming a
closed transfer system and accounting for displacement of vapors from the transfer line and from leaks
in equipment such as transfer line seals and valves. The what-if task duration is the time required to load
one container, which is half an hour for tank trucks and one hour for rail cars. For the loading of drums
with NMP, EPA used the EPA OAOPS AP-42 Loading Model and EPA/OPPT Mass Balance Model to
determine NMP volatilization to air and associated potential NMP air concentrations, respectively.
These models use default parameter values and standard assumptions to provide screening level
assessments of inhalation and dermal exposure to liquid for container loading operations.
Note that, to determine a what-if task duration for the loading of drums during the manufacturing
scenario, EPA first determined annual throughput of NMP at manufacturing sites. To do so, EPA
divided the total NMP production volume of 161 million pounds (determined from 2016 CDR results;
(U.S. EPA 2016a) by the 33 sites that reported to 2016 CDR (see Section 2.1.2.2). EPA assumes that
Page 153 of 292
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each of the 33 sites have the same annual throughput, regardless of whether the site manufactures or
imports NMP. Thus, the site throughput for manufacturing and importation sites is the same. To
determine the daily throughput of NMP at these sites, EPA assumed that sites operate 250 days per year.
Based on this throughput information and the model's assumed loading rate of 20 drums/hour, the model
determined a what-if task duration of 2.06 hr/day for the loading of drums with NMP at manufacturing
sites (assuming the site only fills drums and no other container sizes, as a high-end exposure scenario).
For both loading of bulk containers and drums, EPA calculated what-if task durations as discussed
above, and 4-hour and 8-hour TWA exposures to workers during loading activities. The what-if (task
duration based on monitoring data sample time) TWA exposure is the weighted average exposure during
the entire assumed duration of contact with liquid per shift, accounting for the number of loading events
per shift. The 4-hour and 8-hour TWA exposures are the weighted average exposure during half a shift
(4 hours) an entire 8-hour shift, respectively, assuming zero exposures during the remainder of the shift.
TableApx A-l presents a summary of the exposure modeling results in Rows 11 through 14.
EPA's modeled exposure concentrations for loading NMP into bulk containers are similar in value and
the same order of magnitude as those modeled by RIVM for closed-system NMP transfers. EPA's
modeled exposure concentrations for loading NMP into drums are the same magnitude but higher in
value than those modeled by RIVM for open-system NMP transfers. EPA's modeled exposure
concentrations represent a larger range of potential NMP air concentrations than those presented by
RIVM; thus, EPA uses these modeled exposures in lieu of using the monitoring data or modeled
exposure in the RIVM Annex XV Proposal for a Restriction - NMP report. EPA uses the modeled
exposures in these Rows 11 through 14 as inputs for the PBPK model for worker inhalation and vapor-
through-skin exposure over 4 hours, 8-hours, and what-if (duration-based).
Page 154 of 292
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Table Apx A-l. Summary of Inhalation Monitoring Data for Manufacturing
NMP Airborne
Concentration
(mg/m3)
Data Identifier
Overall
Confidence
Rating from
Data Extraction
and Evaluation
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
Number of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
from Data
Extraction and
Evaluation
Rationale for Inclusion
/ Exclusion
Not
applicable -
this is a
modelled
exposure
Excluded - EPA
1
Closed system
transfers
Modelled using
EasyTRA model
Transfer using closed systems
- varying levels of openness.
Most closed system.
0.04
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 106
High
modeled exposures over
using modeled data
from literature, as
shown in Rows 11
through 14
Not
applicable -
this is a
modelled
exposure
Excluded - EPA
2
Closed system
transfers
Modelled using
EasyTRA model
Transfer using closed systems
- varying levels of openness.
Medium closed system.
4.13
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 106
High
modeled exposures over
using modeled data
from literature, as
shown in Rows 11
through 14
Not
applicable -
this is a
modelled
exposure
Excluded - EPA
3
Closed system
transfers
Modelled using
EasyTRA model
Transfer using closed systems
- varying levels of openness.
Least closed system.
12.39
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 106
High
modeled exposures over
using modeled data
from literature, as
shown in Rows 11
through 14
Not
applicable -
this is a
modelled
exposure
Excluded - EPA
4
Open system
transfers - industrial
setting without LEV
Modelled using
EasyTRA model
Loading and unloading from
containers using transfer lines
or a dedicated fill point. No
ventilation. Industrial setting.
17.35
Partial shift
4 hours
(RIVM.
2013)
3809440 - 108
High
modeled exposures over
using modeled data
from literature, as
shown in Rows 11
through 14
Not
applicable -
this is a
modelled
exposure
Excluded - EPA
5
Open system
transfers - industrial
setting without LEV
Modelled using
EasyTRA model
Loading and unloading from
containers using transfer lines
or a dedicated fill point. No
ventilation. Industrial setting.
14.46
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 108
High
modeled exposures over
using modeled data
from literature, as
shown in Rows 11
through 14
6
Open system
transfers -
commercial setting
without LEV
Modelled using
EasyTRA model
Loading and unloading from
containers using transfer lines
or a dedicated fill point. No
ventilation. Commercial
setting.
14.46
Not
applicable -
this is a
modelled
exposure
Partial shift
1 hours
(RIVM.
2013)
3809440 - 108
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 11
through 14
7
Open system
transfers -
commercial setting
without LEV
Modelled using
EasyTRA model
Loading and unloading from
containers using transfer lines
or a dedicated fill point. No
ventilation. Commercial
setting.
17.35
Not
applicable -
this is a
modelled
exposure
Partial shift
4 hours
(RIVM.
2013)
3809440 - 108
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 11
through 14
Page 155 of 292
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Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)
Number of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from
Data Extraction
and Evaluation
Rationale for Inclusion
/ Exclusion
8
Open system
transfers - high
temperature NMP -
industrial setting
with LEV (95%)
Modelled using
EasyTRA model
Loading and unloading from
containers using transfer lines
or a dedicated fill point. NMP
handled at elevated
temperatures. Local exhaust
ventilation (95% efficiency).
Industrial setting.
3.1
Not
applicable -
this is a
modelled
exposure
Partial shift
4 hours
(RIVM.
2013)
3809440 - 108
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 11
through 14
9
Open system
transfers - high
temperature NMP -
industrial setting
with LEV (90%)
Modelled using
EasyTRA model
Loading and unloading from
containers using transfer lines
or a dedicated fill point. NMP
handled at elevated
temperatures. Local exhaust
ventilation (90% efficiency).
Industrial setting.
12.39
Not
applicable -
this is a
modelled
exposure
Partial shift
4 hours
(RIVM.
2013)
3809440 - 108
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 11
through 14
10
Open system
transfers - high
temperature NMP -
industrial setting
without LEV
Modelled using
EasyTRA model
Loading and unloading from
containers using transfer lines
or a dedicated fill point. NMP
handled at elevated
temperatures. No ventilation.
Industrial setting.
12.91
Not
applicable -
this is a
modelled
exposure
Partial shift
1 hour
(RIVM.
2013)
3809440 - 108
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 11
through 14
11
Transferring NMP to
/ from bulk
containers (tank
trucks and rail cars)
Modeled with Tank
Truck and Railcar
Loading and
Unloading Release
and Inhalation
Exposure Model
Manually transferring 100%
NMP to / from tank trucks
(central tendency) and rail cars
(high-end), including
equipment leaks
Central tendency
= 0.76
High-end =1.52
Not
applicable -
this is a
modelled
exposure
TWA (averaged
over exposure
duration)
transfer activity is 0.5
hours (central tendency)
and 1 hour (high-end)
(U.S.
EPA.
2015b)
Not applicable
Not applicable
Included as what-if
(duration based on
monitoring data sample
time) NMP air
concentration for PBPK
model
12
Transferring NMP to
/ from bulk
containers (tank
trucks and rail cars)
Modeled with Tank
Truck and Railcar
Loading and
Unloading Release
and Inhalation
Exposure Model
Manually transferring 100%
NMP to / from tank trucks
(central tendency) and rail cars
(high-end), including
equipment leaks
Central tendency
= 0.047
High-end = 0.19
Not
applicable -
this is a
modelled
exposure
8-hour TWA
8 hours - transfer activity
is 0.5 hours (central
tendency) and 1 hour
(high-end), with zero
exposure the remainder of
the shift
(U.S.
EPA.
2015b)
Not applicable
Not applicable
Included as 8-hour
worker inhalation
exposure concentration
for PBPK model
13
Transferring NMP to
/ from drums
Modeled with
EPA/OAQPS AP-42
Loading Model and
EPA/OPPT Mass
Balance Model
Manually transferring 100%
NMP to / from drums
Central tendency
= 1.65
High-end = 5.85
Not
applicable -
this is a
modelled
exposure
TWA (averaged
over exposure
duration)
Manufacturing & Import
and Repackaging:
2.06 hours
Disposal:
0.603 hours
(U.S.
EPA.
2015b)
Not applicable
Not applicable
Included as what-if
(duration based on
monitoring data sample
time) inhalation
exposure concentration
for PBPK model
Page 156 of 292
-------
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)
Number of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from
Data Extraction
and Evaluation
Rationale for Inclusion
/ Exclusion
14
Transferring NMP to
/ from drums
Modeled with
EPA/OAQPS AP-42
Loading Model and
EPA/OPPT Mass
Balance Model
Manually transferring 100%
NMP to / from drums
Manufacturing &
Import and
Repackaaina:
Central tendency
= 0.427
High-end =1.51
Disposal:
Central tendency
0.125
High-end = 0.441
Not
applicable -
this is a
modelled
exposure
8-hour TWA)
8 hours - transfer activity
duration from the above
cell, with zero exposure
the remainder of the shift
(U.S.
EPA.
2015b)
Not applicable
Not applicable
Included as 8-hour
worker inhalation
exposure concentration
for PBPK model
Page 157 of 292
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A.2 Repackaging
EPA did not find inhalation monitoring data related to the repackaging of NMP. The same data
presented in Appendix A.l for the manufacturing of NMP are also applicable to repackaging of NMP, as
these data apply to the transfers (i.e., loading and unloading) of NMP, which occurs at both
manufacturing and repackaging sites.
EPA uses the calculated PBPK input parameters for full-shift (8-hour TWA), half-shift (4-hour TWA),
and what-if (duration-based) worker inhalation and vapor-through-skin exposures presented in Rows 11
through 14 of Table Apx A-l in Appendix A.l. See Appendix A.l for additional information on the
calculation of these exposure concentrations.
A.3 Chemical Processing, Excluding Formulation
Table Apx A-2 summarizes the inhalation monitoring data that are available in published literature for
the use of NMP in non-incorporative processing activities. Rows 1 through 18 include air monitoring
data that was submitted to EPA from E.I. DuPont De Nemours & Company in response to a proposed
TSCA Section 4 test rule on NMP. These data were submitted in 1990 and were taken from 1983 to
1989, during polymer production using NMP. Some of these data lack information on sample durations
and explanation on what the associated worker activities involve. Due to the age and lack of sample
context, these data were rated of Medium quality. EPA found data that was rated High quality, presented
in Rows 19 through 24 and discussed further below.
EPA summarized modeled NMP air concentrations from the RIVM Annex XV Proposal for a Restriction
- NMP report (RIVM. 2013) in Rows 19 through 24. These modeled NMP air concentrations are for the
use of NMP as a process solvent or reagent in an industrial setting and include scenarios for closed
processing systems with various levels of enclosure as well as the handling of NMP at both ambient and
elevated temperatures. These data are all 8-hour TWA values.
In addition to the modeled exposures compiled from the RIVM Annex XF Proposal for a Restriction -
NMP report, EPA modeled potential NMP air concentrations during the unloading of pure NMP, as
shown in Rows 25 through 28. The unloading activity during this scenario is expected to present a high
potential for worker exposure and is not already covered in the RIVM modeled exposures presented for
this scenario. EPA modeled these exposure concentrations consistent with the methodology presented in
Appendix A. 1 for the manufacturing of NMP. Refer to Appendix A. 1 for additional details on this
modeling.
For the unloading of bulk containers containing pure NMP, EPA developed the Tank Truck andRailcar
Loading and Unloading Release and Inhalation Exposure Model, which calculates potential exposure
concentrations based on the unloading of one tank truck (central tendency case) and one rail car (high-
end). The task duration is the time required to unload one container, which is half an hour for tank trucks
and one hour for rail cars. For the unloading of drums containing NMP, EPA used the EPA OAOPS AP-
42 Loading Model and EPA OPPTMass Balance Model to determine NMP volatilization to air and
associated potential worker inhalation and vapor-through-skin exposures, respectively.
Note that, to determine a task duration for the unloading of drums at processing sites, EPA first
determined throughput of NMP at these sites. NMP processing is assessed in both this scenario and in
Section 2.4, Incorporation into Formulation, Mixture, or Reaction Product. EPA does not expect that
NMP is processed in both conditions of use, but that the production volume of NMP is split between
these conditions of use. EPA assumes that the entire production volume of NMP (161 million pounds
Page 158 of 292
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per 2016 CDR; (U.S. EPA. 2016a) is processed and determined the throughput at processing sites by
dividing the production volume by the total number of sites assessed between the two processing
conditions of use (94 sites each per Sections 2.3.2.2 and 2.4.2.2) and by 250 days of operation per site
per year. Based on this daily site throughput, the capacity of drums, and an assumed unloading rate of 20
drums/hour, the model determined a what-if task duration of 0.362 hours for processing sites (assuming
the site only unloads drums and no other container sizes).
For both unloading of bulk containers and drums, EPA calculated what-if (duration-based, as discussed
above), 4-hour TWA, and 8-hour TWA exposures to workers during unloading activities. The what-if
(shift duration-based) TWA exposure is the weighted average exposure during the entire exposure
duration per shift, accounting for the number of unloading events per shift. The 4-hour TWA and 8-hour
TWA exposures are the weighted average exposure during half a shift (4 hours) and an entire 8-hour
shift, assuming zero exposures during the remainder of the shift. Table Apx A-2 presents a summary of
the exposure modeling results in Rows 25 through 28. EPA used the modeled exposure concentrations
for unloading drums (Rows 27 and 28) as a conservative exposure scenario as input for the PBPK
model.
Page 159 of 292
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Table Apx A-2. Summary of Inhalation Monitoring Data for Chemical Processing, Excluding Formulation
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or Sampling
Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure Duration
Source
Data Identifier
from Data
Extraction
and
Evaluation
Overall
Confidence
Rating from
Data Extraction
and Evaluation
Rationale for
Inclusion / Exclusion
1
Processing - polymer
Personal
Organic polymer prep and solvent
recovery
Mean: 0.02
Maximum: 0.81
21
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100-101
Medium
Excluded - data is not
the highest rated
1990)
2
Processing - polymer
Personal
Manufacture of composite prepreg
0.81
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 102
Medium
Excluded - data is not
the highest rated
1990)
3
Processing - polymer
Personal
Manufacture of composite prepreg
4.05
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 102
Medium
Excluded - data is not
the highest rated
1990)
4
Processing - polymer
Area
Resin heating mill hood
24.33
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 103
Medium
Excluded - data is not
the highest rated
1990)
5
Processing - polymer
Area
Resin heating mill hood
4.05
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 103
Medium
Excluded - data is not
the highest rated
1990)
6
Processing - polymer
Personal
Curing composite article at 800 F
<0.41
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 106
Medium
Excluded - data is not
the highest rated
1990)
7
Processing - polymer
Area
Curing composite article at 800 F
<0.41
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 107
Medium
Excluded - data is not
the highest rated
1990)
8
Processing - polymer
Personal
Devolatilizing composite article in
laboratory hood
<0.41
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 108
Medium
Excluded - data is not
the highest rated
1990)
9
Processing - polymer
Personal
Devolatilizing composite article in
ventilated press
<0.41
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 109
Medium
Excluded - data is not
the highest rated
1990)
10
Processing - polymer
Area
Devolatilizing composite article in
ventilated press
<0.41
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 110
Medium
Excluded - data is not
the highest rated
1990)
11
Processing - polymer
Personal
Impregnating fibers with resin in
laboratory hood
<0.41
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 111
Medium
Excluded - data is not
the highest rated
1990)
12
Processing - polymer
Personal
Cut patterns from prepreg and
devolatilized for 2 hours
<0.41
1
Unknown
2 hours
(DuPont.
4214100 - 112
Medium
Excluded - data is not
the highest rated
1990)
13
Processing - polymer
Area
Cut patterns from prepreg and
devolatilized for 2 hours
<0.41
Unknown
2 hours
(DuPont.
4214100 - 113
Medium
Excluded - data is not
the highest rated
1990)
14
Processing - polymer
Personal
Operator cut patterns from prepreg
wearing skin protective equipment
<0.41
1
Unknown
unknown - greater
than 5.5 hours
(DuPont.
4214100 - 114
Medium
Excluded - data is not
the highest rated
1990)
15
Processing - polymer
Personal
Clean up of 310 F heater plates
21.08
1
Unknown
9 minutes
(DuPont.
4214100 - 115
Medium
Excluded - data is not
the highest rated
1990)
16
Processing - polymer
Personal
Clean up of 310 F heater plates
15.00
1
Unknown
13 minutes
(DuPont.
4214100 - 116
Medium
Excluded - data is not
the highest rated
1990)
17
Processing - polymer
Personal
Clean up of 310 F heater plates
40.55
1
Unknown
17 minutes
(DuPont.
4214100 - 116
Medium
Excluded - data is not
the highest rated
1990)
18
Processing - polymer
Personal
Clean up of 310 F heater plates
48.65
1
Unknown
13 minutes
(DuPont.
4214100 - 117
Medium
Excluded - data is not
the highest rated
1990)
19
Processing - NMP
used as a process
solvent or reagent -
closed system
Modelled using
EasyTRA model
Manufacture of chemicals (NMP
used as a process solvent or
reagent) in a closed system at
ambient temperatures. Most
enclosed system. Industrial setting.
No local exhaust ventilation.
0.04
Not
applicable -
this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 110
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 27 and
28
Page 160 of 292
-------
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or Sampling
Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure Duration
Source
(RIVM.
2013)
Data Identifier
from Data
Extraction
and
Evaluation
3809440 - 110
Overall
Confidence
Rating from
Data Extraction
and Evaluation
Rationale for
Inclusion / Exclusion
20
Processing - NMP
used as a process
solvent or reagent -
closed system
Modelled using
EasyTRA model
Manufacture of chemicals (NMP
used as a process solvent or
reagent) in a closed system at
ambient temperatures. Medium
level of enclosed system. Industrial
setting. No local exhaust
ventilation.
4.13
Not
applicable -
this is a
modelled
exposure
8-hour TWA
8 hours
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 27 and
28
21
Processing - NMP
used as a process
solvent or reagent -
closed system
Modelled using
EasyTRA model
Manufacture of chemicals (NMP
used as a process solvent or
reagent) in a closed system at
ambient temperatures. Least
enclosed system. Industrial setting.
No local exhaust ventilation.
12.39
Not
applicable -
this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 110
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 27 and
28
22
Processing - NMP
used as a process
solvent or reagent -
closed system -
elevated temperature
Modelled using
EasyTRA model
Manufacture of chemicals (NMP
used as a process solvent or
reagent) in a closed system at an
elevated temperature up to 180C.
Most enclosed system. Industrial
setting. No local exhaust
ventilation.
0.04
Not
applicable -
this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 110
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 27 and
28
23
Processing - NMP
used as a process
solvent or reagent -
closed system -
elevated temperature
Modelled using
EasyTRA model
Manufacture of chemicals (NMP
used as a process solvent or
reagent) in a closed system at an
elevated temperature up to 180C.
Medium level of enclosed system.
Industrial setting. Local exhaust
ventilation with 90% capture
efficiency.
10.33
Not
applicable -
this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 110
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 27 and
28
24
Processing - NMP
used as a process
solvent or reagent -
closed system -
elevated temperature
Modelled using
EasyTRA model
Manufacture of chemicals (NMP
used as a process solvent or
reagent) in a closed system at an
elevated temperature up to 180C.
Least enclosed system. Industrial
setting. Local exhaust ventilation
with 90% capture efficiency.
20.65
Not
applicable -
this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 110
High
Excluded - EPA
modeled exposures over
using modeled data
from literature, as
shown in Rows 27 and
28
25
Transferring NMP to
/ from bulk
containers (tank
trucks and rail cars)
Modeled with
Assumed Emission
Rates and EPA/OPPT
Mass Balance Model
Transferring 100% NMP to / from
tank trucks (central tendency) and
rail cars (high-end), including
equipment leaks
Central tendency
= 0.76
High-end =1.52
Not
applicable -
this is a
modelled
exposure
8-hour TWA -
central tendency
8 hours - transfer
activity is 0.5 hours
(central tendency)
and 1 hour (high-
end), with zero
exposure the
remainder of the shift
(U.S.
EPA.
2015b)
Not applicable
Not applicable
Excluded - EPA used
the modeled exposure
from loading drums
(Row 27 and 28) as a
more conservative
exposure scenario
Page 161 of 292
-------
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or Sampling
Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure Duration
Source
(U.S.
EPA.
2015b)
Data Identifier
from Data
Extraction
and
Evaluation
Not applicable
Overall
Confidence
Rating from
Data Extraction
and Evaluation
Rationale for
Inclusion / Exclusion
26
Transferring NMP to
/ from bulk
containers (tank
trucks and rail cars)
Modeled with Tank
Truck and Railcar
Loading and
Unloading Release
and Inhalation
Exposure Model
Transferring 100% NMP to / from
tank trucks (central tendency) and
rail cars (high-end), including
equipment leaks
Central tendency
= 0.047
High-end = 0.19
Not
applicable -
this is a
modelled
exposure
TWA (averaged
over exposure
duration)
transfer activity is 0.5
hours (central
tendency) and 1 hour
(high-end)
Not applicable
Excluded - EPA used
the modeled exposure
from loading drums
(Row 27 and 28) as a
more conservative
exposure scenario
27
Transferring NMP to
/ from drums
Modeled with
EPA/OAQPS AP-42
Loading Model and
EPA/OPPT Mass
Balance Model
Manually transferring 100% NMP
to / from drums
Central tendency
= 1.65
High-end = 5.85
Not
applicable -
this is a
modelled
exposure
TWA (averaged
over exposure
duration)
Transfer activity is
0.362 hours, based on
assumed throughput
(U.S.
EPA.
2015b)
Not applicable
Not applicable
Included as what-if
(duration-based) NMP
air concentration for
PBPK model
28
Transferring NMP to
/ from drums
Modeled with
EPA/OAQPS AP-42
Loading Model and
EPA/OPPT Mass
Balance Model
Manually transferring 100% NMP
to / from drums
Central tendency
= 0.075
High-end = 0.265
Not
applicable -
this is a
modelled
exposure
8-hour TWA -
central tendency
8 hours - transfer
activity is 0.362
hours, with zero
exposure the
remainder of the shift
(U.S.
EPA.
2015b)
Not applicable
Not applicable
Included as full-shift
NMP air concentration
for PBPK model
a Statistics were calculated by the cited source and are presented here as they were presented in the source.
Page 162 of 292
-------
A.4 Incorporation into Formulation, Mixture, or Reaction Product
TableApx A-3 shows inhalation monitoring data and modeled data that are available in published
literature for incorporation of NMP into a formulation, mixture, or reaction product. Rows 1 and 2
include data provided in a public comment to EPA from FUJIFILM Holdings America Corporation
(FUJIFILM. 2020). These data were taken at an industrial manufacturing site that uses NMP to
formulate chemicals used in the electronics industry. The dataset is comprised of 16 full-shift (~8 hours)
personal breathing zone samples for workers who perform analytical laboratory work and workers who
perform loading tote with formulations containing NMP. As shown in Rows 1 and 2, 14 of the 16
samples were non-detect for NMP. Rows 3 through 16 include air monitoring data for NMP at a site that
formulate adhesives (Bader et al.. 2006). These data include both 8-hour TWA exposure concentrations,
as well as short-term exposure concentrations.
For full-shift (8 hours) PBPK inputs, EPA calculated central tendency (50th percentile) and high-end
(95th percentile) values using the data from the FUJIFILM public comment (Rows 1 and 2) and the
adhesive formulation site in literature (Rows 3 through 9). As discussed, the FUJIFILM data is largely
non-detect for NMP. For the central tendency and high-end calculation, where non-detect values were
included in the dataset, EPA used the limit of detection (LOD) divided by the square root of two. EPA
used this method for approximating a concentration for non-detect samples because the geometric
standard deviation of the dataset is less than three (U.S. EPA 1994b). Because greater than 50% of the
monitoring data results are non-detect for NMP, this method for the calculation of statistics will results
in potentially biased estimates. EPA also used these data to calculate half-shift, 4-hour TWA, exposure
values, assuming zero exposures during the remainder of the shift (for detected values only). EPA
excluded the monitoring data in Row 10 through 12, as indicated in Table Apx A-3.
In addition to personal monitoring data, EPA summarized modeled NMP air concentrations from the
RIVM Annex XV Proposal for a Restriction -NMP report (RIVM. 2013) in Rows 18 through 28. These
exposure concentrations were modeled using the EasyTRA model, which is based on the European
Center for Ecotoxicology and Toxicology of Chemicals (ECETOC) Targeted Risk Assessment (TRA)
tool. These modeled NMP air concentrations include all formulation activities and include scenarios for
open and closed processing systems as well as for formulation at both ambient and elevated
temperatures. However, EPA uses NMP monitoring data as described above in lieu of these modeled
data.
In addition to the monitoring data, EPA modeled potential NMP air concentrations during unloading of
pure NMP at formulation sites. The unloading activity during this scenario is expected to present a high
potential for worker exposure and is not already covered in the RIVM modeled exposures presented for
this scenario. EPA modeled these exposure concentrations consistent with the methodology presented in
Appendix A. 1 for the manufacturing of NMP. Refer to Appendix A. 1 for additional details on this
modeling.
For the unloading of bulk containers containing pure NMP, EPA developed the Tank Truck andRailcar
Loading and Unloading Release and Inhalation Exposure Model, which calculates potential exposure
concentrations based on the loading of one tank truck (central tendency case) and one rail car (high-
end). The task duration is the time required to load one container, which is half an hour for tank trucks
and one hour for rail cars. For the unloading of drums containing pure NMP, EPA used the EPA OAOPS
AP-42 Loading Model and EPA OPPTMass Balance Model to determine NMP volatilizations to air and
associated potential worker inhalation and vapor-through-skin exposures, respectively.
Page 163 of 292
-------
Note that, to determine a task duration for the unloading of drums at processing sites, EPA first
determined throughput of NMP at these sites. NMP processing is assessed in both this scenario and in
Section 2.3, Chemical Processing, Excluding Formulation. EPA does not expect that NMP is processed
in both conditions of use, but that the production volume of NMP is split between these conditions of
use. EPA assumes that the entire production volume of NMP (161 million pounds per the (U.S. EPA
2016a) is processed and determined the throughput at processing sites by dividing the production
volume by the total number of sites assessed between the two processing conditions of use (94 sites each
per Sections 2.3.2.2 and 2.4.2.2) and by 250 days of operation per site per year. Based on this daily site
throughput, the capacity of drums, and an assumed unloading rate of 20 drums/hour, the model
determined a what-if task duration of 0.362 hours for processing sites (assuming the site only unloads
drums and no other container sizes).
For both unloading of bulk containers and drums, EPA calculated what-if (duration-based, as discussed
above), half-shift (4-hour TWA), and full-shift (8-hour TWA) exposures to workers during unloading
activities. The what-if (shift duration-based) TWA exposure is the weighted average exposure during the
entire exposure duration per shift, accounting for the number of unloading events per shift. The 4-hour
TWA and 8-hour TWA exposures are the weighted average exposure during a half shift (4 hours) and an
entire 8-hour shift, assuming zero exposures during the remainder of the shift. Table Apx A-3 presents a
summary of the exposure modeling results in Rows 29 through 32. EPA used the exposure
concentrations for unloading drums (Row 19 and Row 20) as the central tendency input for the PBPK
model, in addition to the monitoring data described above.
In addition to the formulation of liquid products, EPA identified formulation activities that may result in
potential worker exposures to particulates containing NMP. Specifically, these include plastics
compounding and blending of granular fertilizers, as described in Section 2.4.1. Due to the lower
volatility of NMP, workers may be potentially exposed to NMP in inhaled dusts. EPA did not find
monitoring data for NMP at sites that compound plastic or blend granular fertilizers.
The Draft 2014 ESD on Use of Additives in Plastics Compounding summarized OSHA monitoring data
for total dust at compounding sites that was compiled in (U.S. EPA 2014). These OSHA data are
personal monitoring samples taken between 2006 and 2010 for particulates not otherwise regulated
(PNOR) at facilities whose operations fall within the NAICS code 325991, Custom Compounding of
Purchased Resins. However, these data are not activity-specific and have varying sample times ranging
from about one to four hours. Thus, consistent with the methodology presented in the Draft 2014 ESD
on Use of Additives in Plastics Compounding, EPA uses the OSHA PEL for Total Dust of 15 mg/m3 to
assess potential worker inhalation exposures to solids in this scenario. EPA identified five solid polymer
resins with residual NMP ranging from 0.0017 to seven weight percent NMP and two granular
agricultural chemicals with NMP content of less than 0.1 and less than five weight percent NMP. EPA
multiplied the OSHA PEL by each of the identified NMP weight fractions to determine the potential
NMP air concentrations, then calculated the central tendency (50th percentile) and high-end (95th
percentile) to be 0.75 and 0.96 mg/m3, respectively, from these seven exposure concentrations. EPA did
not use these values as input to the PBPK model because the model does not account for solid NMP.
Page 164 of 292
-------
Table Apx A-3. Summary of Inhalation Monitoring Data for Incorporation into Formulation, Mixture, or Reaction Product
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
1
Formulation
Personal
Analytical work
Non-detect
13
Full shift
329 to 523 mins
(FUJIFILM.
2020)
6592030-0101
High
Included - EPA calculated
central tendency and high-end
full shift exposure
concentrations for
miscellaneous activities using
data in Rows 1 through 11
2
Formulation
Personal
Insert dip tubes into
totes, fill totes
Non-detect, 3.49,
0.93
3
Full shift
461 to 507 mins
(FUJIFILM.
2020)
6592030-0102
High
Included - EPA calculated
central tendency and high-end
full shift exposure
concentrations for
miscellaneous activities using
data in Rows 1 through 11
3
Formulation of
adhesives
Personal
Maintenance, foreman
1
1
8-hr TWA
8 hours
(Bader et al..
2006)
3539720 - 106
High
Included - EPA calculated
central tendency and high-end
full shift exposure
concentrations for
miscellaneous activities using
data in Rows 1 through 11
4
Formulation of
adhesives
Personal
Maintenance
2.8
1
8-hr TWA
8 hours
(Bader et al..
2006)
3539720 - 106
High
Included - EPA calculated
central tendency and high-end
full shift exposure
concentrations for
miscellaneous activities using
data in Rows 1 through 11
5
Formulation of
adhesives
Personal
Bottling, shipping
0.9
1
8-hr TWA
8 hours
(Bader et al..
2006)
3539720 - 106
High
Included - EPA calculated
central tendency and high-end
full shift exposure
concentrations for
miscellaneous activities using
data in Rows 1 through 11
6
Formulation of
adhesives
Personal
Maintenance, cleaning
2.3
1
8-hr TWA
8 hours
(Bader et al..
2006)
3539720 - 107
High
Included - EPA calculated
central tendency and high-end
full shift exposure
concentrations for
miscellaneous activities using
data in Rows 1 through 11
7
Formulation of
adhesives
Personal
Mixing, stirrer cleaning
3.4
1
8-hr TWA
8 hours
(Bader et al..
2006)
3539720 - 109
High
Included - EPA calculated
central tendency and high-end
full shift exposure
concentrations for
miscellaneous activities using
data in Rows 1 through 11
Page 165 of 292
-------
Data Identifier
from Data
Extraction and
Evaluation
Overall
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure
Duration
Source
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
Included - EPA calculated
8
Formulation of
adhesives
Personal
Mixing, stirrer cleaning
6.6
1
8-hr TWA
8 hours
(Bader et al..
2006)
3539720 - 109
High
central tendency and high-end
full shift exposure
concentrations for
miscellaneous activities using
data in Rows 1 through 11
Included - EPA calculated
9
Formulation of
adhesives
Personal
Vessel cleaning
15.5
1
8-hr TWA
8 hours
(Bader et al..
2006)
3539720 - 111
High
central tendency and high-end
full shift exposure
concentrations for
miscellaneous activities using
data in Rows 1 through 11
10
Formulation of
adhesives
Personal
Maintenance, cleaning
5.9
1
Peak
42 min
(Bader et al..
2006)
3539720 - 108
High
Excluded - EPA did not use
these peak data to estimate full-
shift exposure
11
Formulation of
adhesives
Personal
Mixing, stirrer cleaning
18.7
1
Peak
19 min
(Bader et al..
2006)
3539720 - 110
High
Excluded - EPA did not use
these peak data to estimate full-
shift exposure
12
Formulation of
adhesives
Personal
Vessel cleaning
18
1
Peak
102 min
(Bader et al..
2006)
3539720 - 104
High
Excluded - EPA did not use
these peak data to estimate full-
shift exposure
13
Formulation of
adhesives
Personal
Vessel cleaning
85
1
Peak
5 min
(Bader et al..
2006)
3539720 - 112
High
Excluded - EPA did not use
these peak data to estimate full-
shift exposure
14
Formulation of
adhesives
Personal
manual vessel and
fittings cleaning
Mean: 10.7 to 18.0
Unknown
Short term
NR
(Bader et al..
2006)
3539720 - 104
High
Excluded - sample time is
unknown
15
Formulation of
adhesives
Area
Production area
Mean: 3.0
Unknown
NR
NR
(Bader et al..
2006)
3539720 - 103
High
Excluded - sample time is
unknown
16
Formulation of
adhesives
Area
Bottling and shipping
department
Mean: 0.2
Unknown
NR
NR
(Bader et al..
2006)
3539720 - 105
High
Excluded - sample time is
unknown
Average sample
concentration at a
17
formulation of paste
and liquid printing
inks
Unknown
printing inks
manufacturing site that
produces paste (75%)
and liquid (assumed
25%) inks
2 (concentration of
particulates, not
NMP-specific)
Unknown
8-hour TWA
8 hours
(U.S. EPA.
2001)
Not applicable
Not applicable
Excluded - This sample result is
not for NMP, but for
particulates in general
18
Formulation -
Closed system -
Including all
formulation
activities
Modelled using
EasyTRA model
Formulation of products
at ambient temperature
in a closed system. Most
enclosed system.
Industrial setting. No
local exhaust ventilation.
0.04
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
Page 166 of 292
-------
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
19
Formulation -
Closed system -
Including all
formulation
activities
Modelled using
EasyTRA model
Formulation of products
at ambient temperature
in a closed system.
Medium level of
enclosed system.
Industrial setting. No
local exhaust ventilation.
4.13
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
20
Formulation -
Closed system -
Including all
formulation
activities
Modelled using
EasyTRA model
Formulation of products
at ambient temperature
in a closed system. Least
enclosed system.
Commercial and
industrial settings. No
local exhaust ventilation.
12.39
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
21
Formulation -
Closed system -
Elevated
temperature -
Including all
formulation
activities
Modelled using
EasyTRA model
Formulation of products
at an elevated
temperature up to 120C
in a closed system. Most
enclosed system.
Industrial setting. No
local exhaust ventilation.
0.04
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
22
Formulation -
Closed system -
Elevated
temperature -
Including all
formulation
activities
Modelled using
EasyTRA model
Formulation of products
at an elevated
temperature up to 120C
in a closed system.
Medium level of
enclosed system.
Industrial setting. No
local exhaust ventilation.
20.65
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
23
Formulation -
Closed system -
Elevated
temperature -
Including all
formulation
activities
Modelled using
EasyTRA model
Formulation of products
at an elevated
temperature up to 120C
in a closed system. Least
enclosed system.
Industrial setting. Local
exhaust ventilation with
90% capture efficiency.
4.13
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
24
Formulation - Open
system - Elevated
temperature -
Including all
formulation
activities
Modelled using
EasyTRA model
Mixing and blending
products at an elevated
temperature up to 60C.
Industrial setting. No
local exhaust ventilation.
20.65
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
Page 167 of 292
-------
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
25
Formulation - Open
system - Elevated
temperature -
Including all
formulation
activities
Modelled using
EasyTRA model
Mixing and blending
products at an elevated
temperature up to 120C.
Industrial setting. Local
exhaust ventilation with
90% capture efficiency.
20.65
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
26
Formulation - Open
system - Elevated
temperature -
Including all
formulation
activities
Modelled using
EasyTRA model
Mixing and blending
products at an elevated
temperature up to 60C.
Commercial setting. No
local exhaust ventilation.
17.35
Not applicable
- this is a
modelled
exposure
Partial shift
4 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
27
Formulation -
Loading
Modelled using
EasyTRA model
Filling containers with
final product
(assumed)at ambient
temperatures. Industrial
setting. No local exhaust
ventilation.
14.46
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
28
Formulation -
Loading - Elevated
temperature
Modelled using
EasyTRA model
Filling containers with
final product (assumed)
at an elevated
temperature up to 120C.
Industrial setting. Local
exhaust ventilation with
90% capture efficiency.
20.65
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440 - 110
High
Excluded - EPA uses highest
rated monitoring data,
supplemented with EPA
modeling
29
Transferring NMP
to / from bulk
containers (tank
trucks and rail cars)
Modeled with
Tank Truck and
Railcar Loading
and Unloading
Release and
Inhalation
Exposure Model
Transferring 100% NMP
to / from tank trucks
(central tendency) and
rail cars (high-end),
including equipment
leaks
Central tendency =
0.76
High-end =1.52
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours - transfer
activity is 0.5
hours (central
tendency) and 1
hour (high-end),
with zero
exposure the
remainder of the
shift
(U.S. EPA.
2015b)
Not applicable
Not applicable
Excluded - EPA used the
modeled exposure from loading
drums (Row 31 and 32) as a
more conservative exposure
scenario
30
Transferring NMP
to / from bulk
containers (tank
trucks and rail cars)
Modeled with
Tank Truck and
Railcar Loading
and Unloading
Release and
Inhalation
Exposure Model
Transferring 100% NMP
to / from tank trucks
(central tendency) and
rail cars (high-end),
including equipment
leaks
Central tendency =
0.047
High-end = 0.19
Not applicable
- this is a
modelled
exposure
TWA (averaged
over exposure
duration)
transfer activity
is 0.5 hours
(central
tendency) and 1
hour (high-end)
(U.S. EPA.
2015b)
Not applicable
Not applicable
Excluded - EPA used the
modeled exposure from loading
drums (Row 31 and 32) as a
more conservative exposure
scenario
Page 168 of 292
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Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
31
Transferring NMP
to / from drums
Modeled with
EPA/OAQPS
AP-42 Loading
Model and
EPA/OPPT
Mass Balance
Model
Manually transferring
100% NMP to / from
drums
Central tendency =
1.65
High-end 5.85
Not applicable
- this is a
modelled
exposure
TWA (averaged
over exposure
duration)
Transfer activity
is 0.362 hours,
based on
assumed
throughput
(U.S. EPA.
2015b)
Not applicable
Not applicable
Included as what-if (duration-
based) NMP air concentration
for PBPK model
32
Transferring NMP
to / from drums
Modeled with
EPA/OAQPS
AP-42 Loading
Model and
EPA/OPPT
Mass Balance
Model
Manually transferring
100% NMP to / from
drums
Central tendency =
0.075
High-end = 0.265
Not applicable
- this is a
modelled
exposure
TWA (averaged
over exposure
duration)
8 hours - transfer
activity is 0.362
hours, with zero
exposure the
remainder of the
shift
(U.S. EPA.
2015b)
Not applicable
Not applicable
Included as full-shift NMP air
concentration for PBPK model
a Statistics were calculated by the cited source and are presented here as they were presented in the source.
Page 169 of 292
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A.5 Metal Finishing
EPA did not find inhalation monitoring data specifically related to the use of NMP-based metal finishing
products. TableApx A-4 shows modeled NMP air concentrations from the RIVM Annex XV Proposal
for a Restriction - NMP report (RIVM. 2013). These exposure concentrations were modeled using the
EasyTRA model, which is based on the European Center for Ecotoxicology and Toxicology of
Chemicals (ECETOC) Targeted Risk Assessment (TRA) tool, and the Stoffenmanager risk assessment
software. The ECHA report modeled potential NMP air concentrations during generic application
scenarios, specifically the dip, roll/brush, and spray application of formulations containing NMP. These
modeled NMP air concentrations are presented in Rows 1 to 5 of Table Apx A-4.
While there are no personal monitoring data for spray application of metal formulations, there are data
for the spray application of paints and coatings. EPA summarized and used these data in Section 2.6.
Due to lack of data for this scenario, EPA used the same low-end, mean, and high-end values for spray
application of paints and coatings in Section 2.6 as surrogate (surrogate work activities using NMP) for
this scenario.
EPA also did not find any personal monitoring data for dip application of metal finishing fluids. While
EPA did not find monitoring data for dip application of metal finishing fluids containing NMP, EPA did
find monitoring data for the dip application of cleaning products containing NMP. EPA summarized and
used these data in Section 2.16. Due to lack of data for this scenario, EPA used the same central
tendency and high-end values calculated for dip application of cleaning products in Section 2.16 as
surrogate (surrogate work activities using NMP) for this scenario.
Finally, EPA did not find personal monitoring data on the brush application of metal finishing
formulations. Thus, EPA assesses potential inhalation and vapor-through-skin exposures for this
scenario consistent with the approach used for brush application of paints, coatings, adhesives, and
sealants used in Section 2.6. Specifically, EPA assesses the concentration of the modeled value shown in
Row 3 of Table Apx A-4.
Page 170 of 292
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Table Apx A-4. Summary of Inhalation Monitoring Data
'or Metal Finishing
Row
Occupational
Exposure
Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)
Number of
Samples
Type of
Measurement
Sample
Time
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
1
Dip application
Modelled using EasyTRA model
Dip application of
substrate into NMP-
containing solution
4.13
Not applicable -
this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440- 117
High
Excluded - dip cleaning data is
used as surrogate for this
occupational exposure scenario
2
Dip application
Modelled using EasyTRA model
Dip application of
substrate into NMP-
containing solution
12.4
Not applicable -
this is a
modelled
exposure
Short-term
4 hours
(RIVM.
2013)
3809440- 117
High
Excluded - dip cleaning data is
used as surrogate for this
occupational exposure scenario
3
Brush / Roller
Application
Modelled using EasyTRA model
Roll/brush
application of NMP-
containing solution
4.13
Not applicable -
this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440- 115
High
Included as PBPK input for
roller / brush application
4
Spray application
Modelled using Stoffenmanager model
Spray application of
NMP-containing
solution. With spray
booth.
7.96
Not applicable -
this is a
modelled
exposure
Short-term
4 hours
(RIVM.
2013)
3809440- 113
High
Excluded - Monitoring data for
application of coatings is used
as surrogate for this
occupational exposure scenario
5
Spray application
Modelled using Stoffenmanager model
Spray application of
NMP-containing
solution. Without
spray booth.
18.7
Not applicable -
this is a
modelled
exposure
Short-term
4 hours
(RIVM.
2013)
3809440- 113
High
Excluded - Monitoring data for
application of coatings is used
as surrogate for this
occupational exposure scenario
Page 171 of 292
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A.6 Application of Paints, Coatings, Adhesives, and Sealants
TableApx A-4 shows inhalation monitoring data that are available in published literature for NMP-
based paints, coatings, adhesives and sealants. In addition to personal monitoring data, EPA summarized
modeled NMP air concentrations from the RIVM Annex XF Proposal for a Restriction - NMP report
(RIVM. 2013). These exposure concentrations were modeled using the EasyTRA model, which is based
on the European Center for Ecotoxicology and Toxicology of Chemicals (ECETOC) Targeted Risk
Assessment (TRA) tool, and the Stoffenmanager risk assessment software. The RIVM Annex XV
Proposal for a Restriction - NMP report modeled potential NMP air concentrations during generic
application scenarios, specifically the dip, roll/brush, and spray application of formulations containing
NMP. These modeled NMP air concentrations are presented in Rows 19 to 23 of Table Apx A-4.
In the study by NIOSH, presented in Rows 1-9, samples were taken over two 3.5-hour periods (7 am to
10:30 am and 10:30 am to 2 pm) (totaling 7 hours per day for each monitored worker) (NIOSH. 1998).
Since the NIOSH study authors did not assemble the two 3.5-hour samples for each worker together into
a single 7-hour TWA exposure, nor provide the 3.5-hour TWA exposures for each unique worker, EPA
assumed the distribution of exposures for a given worker in the first half of their shift is equal to the
distribution of exposures in the second-half of their shift. Therefore, the 3.5-hour TWA exposure in the
first-half of the shift equals the 3.5-hour TWA exposure in the second-half of the shift, which is also
equal to the 7-hour TWA exposure.
Further, for spray application, EPA uses the data in Row 1 to represent potential inhalation and vapor-
through-skin exposure to workers. EPA translated these data into 4-hour TWA values by assuming no
exposure during the remaining half hour in the 4 hour exposure duration. EPA translated these data into
8-hour TWA values by assuming workers are exposed to the concentrations in Row 1 for 7 hours, as
described above, and have no exposure for the remaining 1 hour.
EPA did not use the data in Rows 3 to 5 because of the smaller sample size and the potential for the
same workers to be captured in the sample results presented in Row 1. EPA did not use the data in Rows
6 to 11 because these are area samples, which are expected to be less representative of worker and ONU
exposures than personal breathing zone samples.
The DoD provided NMP monitoring data taken during spray painting processes that occur at a weekly
frequency (DOEHRS-IH. 2018). These data are included in Rows 24 and 25. Information on whether an
activity is repeated during a work shift is not provided. Additionally, these data were provided as less
than values and no metadata were provided with which to interpret these data (i.e., less than values are
provided for measurements below the limit of detection). Therefore, EPA did not use these data in this
risk evaluation.
Due to lack of personal monitoring data or modeled exposure data for roll coating, EPA assessed
exposures using the EPA/OPPT t IV Roll Coating Inhalation Model, which assumes a low-end
particulate concentration in air of 0.04 mg/m3 and a high-end particulate concentration of 0.26 mg/m3
(OECD. 2011). To determine the potential worker exposure concentration of NMP, EPA multiplied
these particulate air concentrations by the low, mid-range, and high-end mass fractions of NMP
discussed in Section 2.6.2.3.2. Then, from these six calculated NMP exposure concentrations, EPA
calculated a central tendency (50th percentile) and high-end (95th percentile) exposure concentration to
be 0.03 and 0.19, respectively. Note that th e EPA/OPPT U\T Roll Coating Inhalation Model is intended
for assessing potential exposure concentrations to non-volatile portions of mists. Therefore, these
Page 172 of 292
-------
exposure estimates may underestimate exposure as they do not account for the portion of NMP that
volatilizes. However, NMP's low volatility should mitigate this underestimation.
EPA did not find any personal monitoring data for dip application of paints, coatings, adhesives, and
sealants. The RIVM Annex XV Proposal for a Restriction - NMP report modeled a central tendency 8-
hour TWA NMP exposure concentration of 4.13 mg/m3 for a generic dip application scenario (see Row
19 of Table Apx A-4) (RIVM. 2013). While EPA did not find monitoring data for dip application of
paints, coatings, adhesives, and sealants containing NMP, EPA did find monitoring data for the dip
application of cleaning products containing NMP. EPA summarized and used these data in Section 2.16.
Due to lack of data for this scenario, EPA used the same central tendency and high-end values calculated
for dip application of cleaning products in Section 2.16 as surrogate (surrogate work activities using
NMP) for this scenario.
EPA did not find any personal monitoring data for manual brush / roller or syringe / bead application of
paints, coatings, adhesives, and sealants. The RIVM Annex XV Proposal for a Restriction - NMP report
modeled a central tendency NMP exposure concentration of 4.13 mg/m3 for a generic roller / brush
application scenario (see Row 21 of Table Apx A-4) (RIVM. 2013). EPA expects that these two
application types result in similar exposure potential, as neither are expected to produce mists or
aerosols, thus the main inhalation and vapor-through-skin exposure point is to NMP vapors during the
application and drying of paints, coatings, adhesives and sealants. Due to lack of any additional
information, EPA utilizes this value to assess a central tendency potential worker exposure scenario.
Page 173 of 292
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Table Apx A-5. Summary of Inhalation
Monitoring Data for App
ication of Paints, Coatings, Adhesives, and Sealants
Row
Occupational
Exposure
Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from
Data Extraction
and Evaluation
Rationale for
Inclusion / Exclusion
1
Spray
application
Personal
Workers who entered the
paint booths to adjust the
spray guns and/or to
change the air filters.
Range: 0.04 to 5.15
Mean: 0.61
26
Short-term
3.5 hours
(NIOSH.
1998)
4287129- 101
High
Included in full-shift
PBPK inputs
2
Spray
application
Personal
Workers who did not work
with paint or paint booths
(occupational non-users).
Range: 0.04 to 0.61
Mean: 0.16
19
Short-term
3.5 hours
(NIOSH.
1998)
4287129- 102
High
Included in full-shift
PBPK inputs
3
Spray
application
Personal
Spray equipment operators
(application done in a
spray booth by worker
from outside of booth).
Range: 0.04 to 0.12
Mean: 0.08
3
Short-term
3.5 hours
(NIOSH.
1998)
4287129- 102
High
Excluded - these
workers are expected to
be included in those
samples for the data set
in Row 1
4
Spray
application
Personal
Changing air filters inside
a paint booth.
0.77
1
Short-term, for
duration of task
5 minutes
(NIOSH.
1998)
4287129- 101
High
Excluded - these
workers are expected to
be included in those
samples for the data set
in Row 1
5
Spray
application
Personal
Mixing the paint and
filling the paint booth
canister.
0.024
1
Short-term, for
duration of task
12 minutes
(NIOSH.
1998)
4287129- 102
High
Excluded - these
workers are expected to
be included in those
samples for the data set
in Row 2
6
Spray
application
Area
Inside paint booth.
Range: 18 to 101
Mean: 49
6
Short-term
90 minutes
(NIOSH.
1998)
4287129- 103
High
Excluded - Personal
samples are used over
area samples
7
Spray
application
Area
Area outside paint booth.
Range: 0.04 to 0.47
Mean: 0.20
8
Short-term
90 minutes
(NIOSH.
1998)
4287129- 104
High
Excluded - Personal
samples are used over
area samples
8
Spray
application
Area
Paint mix area.
Range: 0.16 to 0.81
Mean: 0.41
3
Short-term
90 minutes
(NIOSH.
1998)
4287129- 104
High
Excluded - Personal
samples are used over
area samples
9
Spray
application
Area
Lunch area.
Range: 0.04 to 0.12
Mean: 0.08
3
Short-term
90 minutes
(NIOSH.
1998)
4287129- 104
High
Excluded - Personal
samples are used over
area samples
10
Spray
application
Area
Air concentration of
particulates while using a
conventional air-atomized
spray gun
Particulate
concentration: 2.3
(downdraft) and 15
(cross-draft)
Unknown
Unknown
Unknown
(OECD.
2011)
Not applicable
Not applicable
Excluded - Sample
duration is unknown
11
Spray
application
Area
Air concentration of
particulates while high
volume-low pressure
(HVLP) sprav gun
Particulate
concentration: 1.9
(downdraft) and 15
(cross-draft)
Unknown
Unknown
Unknown
(OECD.
2011)
Not applicable
Not applicable
Excluded - Sample
duration is unknown
Page 174 of 292
-------
Row
Occupational
Exposure
Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
(IFA. 2010)
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from
Data Extraction
and Evaluation
Rationale for
Inclusion / Exclusion
12
unknown
application type
Area
Car painting. No
additional details are
provided.
50th percentile: 0.2
90th percentile: 0.5
95th percentile: 2.5
12
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to 6
hours, such that this is
comparable to a shift
measurement
4271620- 108
Medium
Excluded - this is not
the highest rated data
13
unknown
application type
Area
Work group area listed as
"surface coating,
painting." No additional
details are provided.
50th percentile: 0.2
(below analytical
quantification limit
of 0.42)
90th percentile: 3
95th percentile: 5.35
55
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to 6
hours, such that this is
comparable to a shift
measurement
(IFA. 2010)
4271620- 131
Medium
Excluded - this is not
the highest rated data
14
unknown
application type
Personal
Work group area listed as
"surface coating,
painting." No additional
details are provided.
50th percentile: 0.65
90th percentile: 3
95th percentile:
4.865
39
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to 6
hours, such that this is
comparable to a shift
measurement
(IFA. 2010)
4271620- 138
Medium
Excluded - this is not
the highest rated data
15
unknown
application type
Unknown
Work group area listed as
"surface coating,
painting." Samples taken
in the absence of LEV. No
additional details are
provided.
50th percentile:
below analytical
quantification limit
of 0.42
90th percentile: 3.24
95th percentile:
4.055
11
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to 6
hours, such that this is
comparable to a shift
measurement
(IFA. 2010)
4271620- 142
Medium
Excluded - this is not
the highest rated data
16
unknown
application type
Unknown
Work group area listed as
"surface coating,
painting." Samples taken
in the presence of LEV.
No additional details are
provided.
50th percentile: 0.3
(below analytical
quantification limit
of 0.42)
90th percentile: 3.76
95th percentile: 5.46
68
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to 6
hours, such that this is
comparable to a shift
measurement
(IFA. 2010)
4271620- 149
Medium
Excluded - this is not
the highest rated data
17
unknown
application type
Personal
Equipment clean up in
paint shop
Mean: 0.53
Maximum: 0.81
3
Unknown
unknown - greater than 5.5
hours
(DuPont.
1990)
4214100-104
Medium
Excluded - this is not
the highest rated data
18
unknown
application type
Personal
Solvent for spray
application of roll coating
Mean: 8.11
Maximum: 12.16
2
Unknown
25 mins
(DuPont.
1990)
4214100-105
Medium
Excluded - this is not
the highest rated data
19
Dip application
Modelled using
EasyTRA model
Dip application of
substrate into NMP-
containing solution
4.13
Not
applicable -
this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440- 117
High
Excluded - dip cleaning
data is used as
surrogate for this
condition of use instead
of modeled values
Page 175 of 292
-------
Data Identifier
from Data
Extraction and
Evaluation
Overall
Row
Occupational
Exposure
Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Confidence
Rating from
Data Extraction
and Evaluation
Rationale for
Inclusion / Exclusion
20
Dip application
Modelled using
EasyTRA model
Dip application of
substrate into NMP-
containing solution
12.4
Not
applicable -
this is a
modelled
exposure
Short-term
4 hours
(RIVM.
2013)
3809440- 117
High
Excluded - dip cleaning
data is used as
surrogate for this
condition of use instead
of modeled values
Not
21
Brush / Roller
Application
Modelled using
EasyTRA model
Roll/brush application of
NMP-containing solution
4.13
applicable -
this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440- 115
High
Included as PBPK
input for roller / brush
application
Not
22
Spray
application
Modelled using
Stoffenmanager
model
Spray application of
NMP-containing solution.
With spray booth.
7.96
applicable -
this is a
modelled
exposure
Short-term
4 hours
(RIVM.
2013)
3809440- 113
High
Excluded - monitoring
data is used instead of
modeled values
Not
23
Spray
application
Modelled using
Stoffenmanager
model
Spray application of
NMP-containing solution.
Without spray booth.
18.7
applicable -
this is a
modelled
exposure
Short-term
4 hours
(RIVM.
2013)
3809440- 113
High
Excluded - monitoring
data is used instead of
modeled values
Excluded - Air
concentration is a less
24
Spray
application
Personal
Spray paint tending
<5.08
1
Short-term
50 minutes
(DOEHRS-
IH. 2018)
5178607- 101
High
than value and no
metadata were
provided to interpret
this value
Excluded - Air
concentration is a less
25
Spray
application
Personal
Spray paint tending
<5.64
1
Short-term
45 minutes
(DOEHRS-
IH. 2018)
5178607- 102
High
than value and no
metadata were
provided to interpret
this value
a Statistics were calculated by the cited source and are presented here as they were presented in the source.
Page 176 of 292
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A. 7 Recycling and Disposal
EPA did not find inhalation monitoring data related to the handling of wastes containing NMP.
Bulk Shipments of Liquid Hazardous Waste
EPA assumes NMP wastes that are generated, transported, and treated or disposed as hazardous waste
are done so as bulk liquid shipments. For example, a facility that uses NMP as a processing aid may
generate and store the waste processing aid as relatively pure NMP and have it shipped to hazardous
waste TSDFs for ultimate treatment, disposal, or recycling. The same monitoring data and modeled data
presented in Appendix A.l for the manufacturing of NMP are also applicable to handling of wastes
containing NMP, as these data apply to the transfers (i.e., loading and unloading) of NMP, which occurs
at both manufacturing and waste handling sites. These exposure concentrations assume the handling of
pure (100 percent) NMP.
Due to the limitations of the available monitoring data and RIVM modeled data discussed in Appendix
A. 1, EPA modeled exposures for the unloading of NMP from bulk containers (i.e., tank trucks and rail
cars) and drums. Note that EPA used the same methodology in this section as that described in
Appendix A.l. For bulk containers, the task duration is the time required to unload one container, which
is half an hour for tank trucks and one hour for rail cars. For the unloading of drums containing NMP,
EPA used the EPA OAOPS AP-42 Loading Model and EPA/OPPTMass Balance Model to determine
task duration. Note that, to determine a task duration, EPA first determined throughput of NMP at
disposal sites. EPA determined the total production volume for this scenario from 2016 TRI results.
Table Apx A-6 lists the off-site waste transfers reported in the 2016 TRI. EPA uses the total value
reported in this table as the production volume for this assessment, excluding off-site transfers to
wastewater treatment, as these are expected to occur via sanitary sewer pipeline. For the drum unloading
exposure scenario, EPA assumes the waste chemical is typically transported to the non-wastewater
treatment and disposal sites in 55-gallon drums and calculates 74,719 total drums per year. 2016 TRI
reports 24 waste treatment and disposal sites, resulting in an average of 3,113 drums per site per year.
Assuming 250 days of operation per year and the model's assumed unloading rate of 20 drums/hour, the
model determined a what-if task duration of 0.6 hr/day for recycling and disposal sites.
Table Apx A-6. 2016 TRI Off-Site Transfers for NMP
Off-Site Transfer
Mass (lb)
Land Disposal
4,272,199
Wastewater Treatmenta
2,719,984
Incineration
9,571,479
Recycled
18,709,460
Other
1,724,080
Total
34,277,218 b
a Note that EPA does not expect transfers to off-site wastewater treatment to occur via shipped containers but expects these
transfers are done via sanitary sewer pipeline.
b Excluding NMP transferred off-site for wastewater treatment.
EPA uses the calculated PBPK input parameters for full-shift (8-hour TWA), half-shift (4-hour TWA)
and what-if (duration-based) (acute) worker inhalation and vapor-through-skin exposures presented in
Page 177 of 292
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Rows 13 through 16 of Table Apx A-l in Appendix A.l. See Appendix A.l for additional information
on the calculation of these exposure concentrations.
Municipal Solid Wastes
Certain commercial and consumer conditions of use of NMP may generate solid wastes that are sent to
municipal waste combustors or landfills. For example, spent aerosol degreasing cans containing residual
NMP used by mechanics or consumers may be disposed as household hazardous waste, which is
exempted as a hazardous waste under RCRA. While some municipalities may have collections of
household hazardous wastes to prevent the comingling of household hazardous wastes with municipal
waste streams, some users may inappropriately dispose of household hazardous wastes in the municipal
waste stream.
EPA is not able to quantitatively assess worker or ONU exposures to NMP within municipal solid waste
streams. The quantities of NMP are expected to be diluted among the comingled municipal solid waste
stream, and uses of NMP, such as aerosol degreasing, result in waste NMP being contained in a sealed
can. Exposures to NMP in spent pressurized cans are only expected if the can is punctured during waste
handling.
Page 178 of 292
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A.8 Removal of Paints, Coatings, Adhesives, and Sealants
TableApx A-7 shows all inhalation monitoring data for NMP-based paint and coating removal that
EPA compiled from published literature sources, including 8-hour TWA, short-term, and partial shift
sampling results. In addition to personal monitoring data, EPA summarized modeled NMP air
concentrations from the RIVM Annex XV Proposal for a Restriction - NMP report (RIVM. 2013). These
exposure concentrations were modeled using the EasyTRA model, which is based on the European
Center for Ecotoxicology and Toxicology of Chemicals (ECETOC) Targeted Risk Assessment (TRA)
tool, and the Stoffenmanager risk assessment software. The ECHA report modeled potential NMP air
concentrations during generic application scenarios, specifically the dip, roll/brush, and spray
application of formulations containing NMP. These modeled NMP air concentrations are presented in
Rows 22 to 26 of Table Apx A-7.
The available data does not always distinguish the specific circumstances and industries in which paint
and coating removal occurs; however, these data customarily identify graffiti removal separately from
other paint and coating removal activities. Note that, where the literature source did not specify the
industry or location of the removal activities, EPA includes these data in the miscellaneous paint,
coating, adhesive, and sealant removal category.
For the what-if (duration-based) and central tendency (4 hour) scenarios, Rows 1-8 were translated
into 1-hour and 4-hour TWA values, respectively, from which low, mean, and high-end values were
calculated for inputs into the PBPK model. Rows 9 and 10 were used for high-end (8-hour TWA) inputs
into the PBPK model for paint stripping. Rows 11-15 were not considered in the risk evaluation
because the sample times are unknown or are not representative of the assessed exposure durations.
For graffiti removal, the data in Row 19 were used as high-end (8-hour TWA) inputs into the PBPK
model. For the central tendency (4 hour) scenarios, Row 19 data were translated into 4-hour TWA
values for inputs into the PBPK model. The data in Rows 17 and 18 were not used because the results
fall within the range in Row 19. Row 16, 21, and 22 were not used because the sample time is not
representative of the assessed exposure durations. Rows 22 - 26 were not used because actual data are
favorable to modeled data.
The Department of Defense (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 (DOEHRS-IH. 2018). These
data are included in Rows 27 and 28. These measurements all appear to be task-based samples; however,
the work shift duration for workers performing the monitored activities is reported to be eight hours. The
DOD NMP samples were taken during the removal of coatings and adhesives, which occur at a weekly
or occasional frequency. Information on whether an activity is repeated during a work shift is not
provided. One data point was provided as a less than value and no metadata were provided with which
to interpret the data point (i.e., less than values are provided for measurements below the limit of
detection). The overall confidence rating of the DOD data is High; however, the numeric confidence
score is higher than the data from (U.S. EPA 2015c). indicating lower quality. Therefore, EPA did not
use these data in this risk evaluation.
Page 179 of 292
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Table Apx A-7. Summary of Inhalation Monitoring Data for Removal of Paints, Coatings, Adhesives, and Sealants
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time
/ Exposure
Duration
Source b
Data Identifier
from Data
Extraction and
Evaluation
Overall Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
1
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Application of floor
stripping solution
17.4
1
Short-term
93 minutes
(NIOSH. 1993) as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Included in duration based
PBPK input summary
2
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Floor stripping
9.3
1
Short-term
48 minutes
(NIOSH. 1993) as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Included in duration based
PBPK input summary
3
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Floor stripping with
window open
5.7
1
Short-term
64 minutes
(NIOSH. 1993) as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Included in duration based
PBPK input summary
4
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Application of floor
stripping solution
21.1
1
Short-term
46 minutes
(NIOSH. 1993) as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Included in duration based
PBPK input summary
5
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Application of floor
stripping solution.
Windows and doors
closed.
12.6
1
Short-term
47 minutes
(NIOSH. 1993) as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Included in duration based
PBPK input summary
6
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Application of floor
stripping solution.
Windows and doors
closed.
21.1
1
Short-term
52 minutes
(NIOSH. 1993) as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Included in duration based
PBPK input summary
7
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Application of floor
stripping solution.
Windows and doors
closed.
14.2
1
Short-term
43 minutes
(NIOSH. 1993) as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Included in duration based
PBPK input summary
8
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Non-Specific Paint
stripping
280
Unknown
Peak
1 hour
(WHO. 2001) as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Included in duration based
PBPK input summary
9
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Furniture paint
stripping
1.0 to 3.8
Unknown
TWA
125 to 167
minutes
(NMP Producers
Groun. 2012)as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Included in full-shift PBPK
input summary
10
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Non-Specific Paint
stripping
64
Unknown
Maximum
8-hour TWA
(WHO. 2001) as
cited in (U.S. EPA.
2015c)
3827504 - 105
High
Included in full-shift PBPK
input summary
11
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Brush application of
paint stripper
39
1
Consumer
measurement
129 minutes
(U.S. EPA. 1994a)
as cited in (U.S.
EPA. 2015c)
3827504 - 104
High
Excluded - This consumer
measurement may not be
representative of
occupational exposures
12
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Brush application of
paint stripper
37
1
Consumer
measurement
130 minutes
(U.S. EPA. 1994a)
as cited in (U.S.
EPA. 2015c)
3827504 - 104
High
Excluded - This consumer
measurement may not be
representative of
occupational exposures
13
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Brush application of
paint stripper
37
1
Consumer
measurement
143 minutes
(U.S. EPA. 1994a)
as cited in (U.S.
EPA. 2015c)
3827504 - 104
High
Excluded - This consumer
measurement may not be
representative of
occupational exposures
Page 180 of 292
-------
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time
/ Exposure
Duration
Source b
Data Identifier
from Data
Extraction and
Evaluation
Overall Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
14
Miscellaneous paint
coating, adhesive,
and sealant removal
Unknown
Non-Specific Paint
stripping with dip
application
0.01 to 6
Unknown
Unknown
Unknown
(NMP Producers
Group. 2012)as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Excluded - Sample time is
unknown
15
Miscellaneous paint
coating, adhesive,
and sealant removal
Unknown
Non-Specific Paint
stripping
0.82 to 4.1
Unknown
Unknown
Unknown
(Will et al.. 2004)
as cited in (U.S.
EPA. 2015c)
3827504 - 104
High
Excluded - Sample time is
unknown
16
Graffiti removal
Unknown
Graffiti removal.
Unknown worker
activities or
conditions.
0.01 to 30
Unknown
Unknown
Unknown
(NMP Producers
Groun. 2012)as
cited in (U.S. EPA.
2015c)
3827504 - 104
High
Excluded - Sample time is
unknown
17
Graffiti removal
Personal
Graffiti removal in
poorly ventilated,
partially enclosed
spaces
Range: 0 to 1.68
Geometric mean:
0.4
Mean: 0.56
Unknown (data
for 6 workers)
8-hour TWA
8 hours
(Anundi et al..
2000) as cited in
(U.S. EPA. 2015c)
3827504 - 106
High
Excluded - this sample set
falls within the range used
from Row 19
18
Graffiti removal
Personal
Graffiti removal in
poorly ventilated,
partially enclosed
spaces
Range: 0.61 to 2.56
Geometric mean:
1.5
Mean: 1.78
Unknown (data
for 3 workers)
8-hour TWA
8 hours
(Anundi et al..
2000) as cited in
(U.S. EPA. 2015c)
3827504 - 106
High
Excluded - this sample set
falls within the range used
from Row 19
19
Graffiti removal
Personal
Graffiti removal in
poorly ventilated,
partially enclosed
spaces
Range: 0.03 to 4.52
Geometric mean:
0.67
Mean: 1
Unknown (data
for 25 workers)
8-hour TWA
8 hours
(Anundi et al..
2000) as cited in
(U.S. EPA. 2015c)
3827504 - 103
High
Included - this sample set
has the highest range for
graffiti removal and is used
for full-shift PBPK input
20
Graffiti removal
Personal
Graffiti removal in
poorly ventilated,
partially enclosed
spaces
Range: 0.01 to
24.61
Geometric mean:
1.97
Mean: 4.71
Standard deviation:
6.17
Unknown (data
for 40 workers)
Short-term
15 minutes
(Anundi et al..
2000) as cited in
(U.S. EPA. 2015c)
3827504 - 107
High
Excluded - This short-term
sample is not representative
of the assessed time frames
21
Graffiti removal
Personal
Graffiti removal in
partially enclosed
spaces
9.9
1
Short-term
15 minutes
(Anundi et al..
1993) as cited in
(U.S. EPA. 2015c)
3827504 - 107
High
Excluded - This short-term
sample is not representative
of the assessed time frames
22
Miscellaneous paint
coating, adhesive,
and sealant removal
Modelled using
EasyTRA model
Dip application of
substrate into NMP-
containing solution
4.13
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440- 117
High
Excluded - Monitoring data
is used over modeled data
23
Miscellaneous paint
coating, adhesive,
and sealant removal
Modelled using
EasyTRA model
Dip application of
substrate into NMP-
containing solution
12.4
Not applicable
- this is a
modelled
exposure
Short-term
4 hours
(RIVM. 2013)
3809440- 117
High
Excluded - Monitoring data
is used over modeled data
24
Miscellaneous paint
coating, adhesive,
and sealant removal
Modelled using
EasyTRA model
Roll/brush
application of NMP-
containing solution
4.13
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM. 2013)
3809440- 115
High
Excluded - Monitoring data
is used over modeled data
Page 181 of 292
-------
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time
/ Exposure
Duration
Source b
Data Identifier
from Data
Extraction and
Evaluation
Overall Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
25
Miscellaneous paint
coating, adhesive,
and sealant removal
Modelled using
Stoffenmanager
model
Spray application of
NMP-containing
solution. With spray
booth.
7.96
Not applicable
- this is a
modelled
exposure
Short-term
4 hours
(RIVM. 2013)
3809440- 113
High
Excluded - Monitoring data
is used over modeled data
26
Miscellaneous paint
coating, adhesive,
and sealant removal
Modelled using
Stoffenmanager
model
Spray application of
NMP-containing
solution. Without
spray booth.
18.7
Not applicable
- this is a
modelled
exposure
Short-term
4 hours
(RIVM. 2013)
3809440- 113
High
Excluded - Monitoring data
is used over modeled data
27
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Using Safe Strip to
Remove Plastic
Covering
<15.2
1
Short-term
17 minutes
(DOEHRS-IH.
2018)
5178607 - 103
High
Excluded - Air
concentration is a less than
value and no metadata were
provided to interpret this
value
28
Miscellaneous paint
coating, adhesive,
and sealant removal
Personal
Glue removal
11
1
Short-term
78 minutes
(DOEHRS-IH.
2018)
5178607 - 104
High
Excluded - These data have
a lower confidence score
than the data from (U.S.
EPA. 2015c)
a Statistics were calculated by the cited source and are presented here as they were presented in the source.
b Where information is presented in multiple sources all sources are listed. Information was not combined from these sources but was presented in all sources independently.
Page 182 of 292
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A.9 Other Electronics Manufacturing
Table Apx A-8 shows inhalation monitoring data that are available in published literature for the use of
NMP in other electronics manufacturing. Based on data availability, EPA assessed the occupational
exposure scenario for capacitor, resistor, coil, transformer, and other inductor manufacturing (OSHA
2017). These data sources are discussed below.
The data presented in Rows 1 and 2 are from a study conducted by Beaulieu and Schmerber (1991) on
the use of NMP in the microelectronics fabrication industry. These data are rated have an overall
confidence rating of Low from systematic review. EPA did not use these data because other data with
higher ratings is available, as discussed below.
Data related to electronics manufacturing are available in OSHA's CEHD dataset, as shown in Rows 3
and 4 (OSHA 2017). Specifically, the following data are related to NMP use in electronics industries:
Capacitor, Resistor, Coil, Transformer, and Other Inductor Mfg.: OSHA CEHD includes four
NMP data points related to this industry. These data points are personal breathing zone, full-shift
measurements. EPA used these data as PBPK inputs.
Bare Printed Circuit Board Mfg.: OSHA CEHD includes one NMP data point for this industry.
This data point was non-detect for NMP. Therefore, EPA did not use this data point as input to
the PBPK model.
Page 183 of 292
-------
Table Apx A-8. Summary of Inhalation Monitoring Data for Other Electronics Manufacturing
Row
Occupational Exposure
Scenario
Type of
Sample
Worker Activity or Sampling
Location
NMP Airborne
Concentration
(mg/m3)
Number of
Samples
Type of
Measurement
Sample Time
/ Exposure
Duration
Source a
Data Identifier
from Data
Extraction and
Evaluation
Overall Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
Microelectronics
fabrication
Unknown - workers in the
(EC. 2007;
Excluded - this is not the
highest rated data
1
Personal
microelectronics fabrication
industry
Up to 6 mg/m3
Unknown
8-hour TWA
8 hours
WHO.
2001)
3809476 - 102
Low
2
Microelectronics
fabrication
Area
Unknown - workers in the
microelectronics fabrication
industry when warm NMP
(80°C) was being handled
Up to 280 mg/m3
(NMP at a
temperature of 80°C)
Unknown
Full-shift
Unknown
(EC. 2007:
WHO.
2001)
3809476 - 103
Low
Excluded - this is not the
highest rated data
Included - EPA used these
3
Capacitor, Resistor, Coil,
Transformer, and Other
Personal
Unknown
4.65, 1.17, 1.27, and
44.18
4
Full shift
8-hr TWA
(OSHA.
2017)
3827305 - 105
High
data to estimate occupational
exposures for this
Inductor Mfg.
occupational exposure
scenario
Excluded - EPA did not
4
Bare Printed Circuit
Board Mfg.
Personal
Unknown
Non-detect
1
Partial shift
169 mins
(OSHA.
2017)
3827305 - 106
High
assess this occupational
exposure scenario because
this sample is non-detect
a Where information is presented in multiple sources all sources are listed. Information was not combined from these sources but was presented in all sources independently.
Page 184 of 292
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A. 10 Semiconductor Manufacturing
TableApx A-10 shows inhalation monitoring data that are available in published literature for the use
of NMP in the semiconductor manufacturing s. Based on data availability, EPA assessed the following
occupational exposure scenarios (SLA 2019b):
Container handling, small containers,
Container handling, drums,
Fab worker,
Maintenance,
Virgin NMP truck unloading, and
Waste truck loading.
The data provided in Rows 1 through 4 of Table Apx A-10 was provided in a public comment by the
Semiconductor Industry Association (SIA) (SLA 2017). These data were originally provided by the
European Semiconductor Industry Association to the EU commission and ECHA for consideration in
the RIVM Annex XV Proposal for a Restriction - NMP report (RIVM. 2013) and were collected at
various semiconductor fabrication facilities between 2003 and 2012. These samples were taken in
worker personal breathing zones.
SIA provided an additional data submission to EPA in 2019 (SIA 2019b). These data are presented in
Rows 5 through 15. These data are 8-hour and 12-hour TWA values for personal breathing zone samples
of workers involved in handing and changeout of containers, photolithography operations, maintenance
activities, virgin (100%) NMP unloading, and waste NMP (92%) loading. In addition, the SIA data
contains 8-hour and 12-hour TWA area samples taken in the fabrication area. EPA calculated central
tendency and high-end values for this dataset, for each task and 8-hour and 12-hour TWA values. The
majority (i.e., 96% of all sample results) of samples were non-detect for NMP. Where non-detect values
were included in the dataset, EPA calculated the limit of detection (LOD) divided by two. EPA used this
method for approximating a concentration for non-detect samples because the geometric standard
deviation of the dataset is greater than three (U.S. EPA 1994b). Because greater than 50% of the
monitoring data results are non-detect for NMP, the use of the LOD/2 for the calculation of statistics
will results in potentially biased estimates.
EPA calculated the central tendency and high-end values listed in Table Apx A-9, using the LOD/2 for
sample results that were non-detect for NMP. EPA used the SIA (SIA 2019b) data to evaluate
inhalation and vapor-through-skin exposures for this scenario. EPA used these data in place of the 2017
data submitted by SIA (SIA 2017). The SIA (SIA. 2019b) data was rated as High overall confidence
compared to the previous SIA data, which was rated Medium. Additionally, the SIA (SIA. 2019b) data
represents the same worker activities as those in the previous SIA submission, as well as a few
additional worker activities.
Specifically, using the SIA (SIA. 2019b) data, EPA used the calculated 12-hour TWA central tendency
(50th percentile) and high-end (95th percentile) values as inputs in the PBPK modeling. EPA used the 12-
hour TWA data because there are more sample results for 12-hour shifts, indicating this is the more
frequent shift length for this industry. EPA used these 12-hour TWA values in conjunction with dermal
parameters for the PBK modeling. EPA used task durations from SIA (SIA. 2019b) data to determine
what-if task durations for each of the semiconductor occupational exposure scenarios. Note that EPA
used updated NMP concentration values provided in the SIA (SIA. 2019b) dataset to calculate the
central tendency and high-end NMP concentrations to which workers may be dermally exposed.
Page 185 of 292
-------
EPA found one data point in OSHA's CEHD related to semiconductor manufacturing (OSHA. 2017).
However, this data has a lower rating from systematic review than the SIA data. Therefore, EPA did not
use the OSHA CEHD data.
Page 186 of 292
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Table Apx A-9. Summary of SIA Data SIA (SIA, 2019b)
8-hour TWA
12-hour TWA
Central
High-
Central
High-
Task
Number of
samples
Non-
detects
Count
Tendency
(mg/m3)
End
(mg/m3)
Count
Tendency
(mg/m3)
End
(mg/m3)
Notes
Container
handling, small
containers
19
19
5
0.026
0.243
14
0.507
0.608
8-hr: 50th percentile presented as central
tendency and maximum value presented
as high end
12-hr: 50th percentile presented as
central tendency and 95th percentile
presented as high end
Container
handling,
drums
15
15
5
0.026
0.026
10
0.013
1.544
8-hr: 50th percentile presented as central
tendency and maximum value presented
as high end
12-hr: 50th percentile presented as
central tendency and 95th percentile
presented as high end
Fab worker
28
28
0
N/A
28
0.138
0.405
12-hr: 50th percentile presented as
central tendency and 95th percentile
presented as high end
Maintenance
45
41
9
0.026
0.726
36
0.020
0.690
8-hr and 12-hr: 50th percentile
presented as central tendency and 95th
percentile presented as high end
8-hr: Central tendency is the midpoint
value between the two data points; high
end is the higher of the two values
Fab area
samples
9
9
2
0.026
0.026
7
0.162
0.284
12-hr: 50th percentile presented as
central tendency and 95th percentile
presented as high end
Virgin NMP
truck unloading
1
0
1
4.78
0
N/A
Single 8-hr TWA value available
Waste truck
loading
1
1
1
0.709
0
N/A
Single 8-hr TWA value available
Page 187 of 292
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Table Apx A-10. Summary of Inhalation Monitoring Data for Semiconductor Manufacturing
Row
Occupational
Exposure Scenario
Type of
Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number
of
Samples
Type of
Measurement
Sample
Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
1
Wafer stripping and
removing processes
Personal
Wafer stripping ('cleaning") removing
photoresist. Wafer cleaning for organics
removal. Operations are in a closed
processing system.
Range: less than the
detection limit to 0.202
Unknown
Unknown -
likely full-shift
Unknown
(SIA.
2017)
5176409- 101
Medium
Excluded - this is not the
highest rated data
2
Deposition processes
Personal
Photolithography layer spin-on. Polyimide
deposition. Operations are in a closed
processing system.
Range: 0.0247 to 0.857
Unknown
Unknown -
likely full-shift
Unknown
(SIA.
2017)
5176409- 102
Medium
Excluded - this is not the
highest rated data
3
Maintenance
Personal
Preventive maintenance at process
equipment tools in the cleanroom. Invasive
maintenance.
Range: less than the
detection limit to 0.770
Unknown
Unknown -
likely full-shift
Unknown
(SIA.
2017)
5176409- 103
Medium
Excluded - this is not the
highest rated data
4
Chemical storage and
handling
Personal
Chemicals storage and delivery areas open to
ambient air. Canister, bottle and container
change at tools and chemfill stations not in
the cleanroom.
Range: less than the
detection limit to 4.054
Unknown
Unknown -
likely full-shift
Unknown
(SIA.
2017)
5176409- 104
Medium
Excluded - this is not the
highest rated data
5
Semiconductor
manufacturing-
Container handling
Personal
Container handling, small containers: 5-
gallon to 20L
0.0263 - 0.243 (all
samples are non-
detect; values
presented are LOD/2)
5
8-hr TWA
8-hour TWA
(SIA.
2019b)
5161295 - 101 to
105
High
Included - EPA used these
data to estimate occupational
exposures
6
Semiconductor
manufacturing-
Container handling
Personal
Container handling, small containers: 5-
gallon to 20L
0.162-0.608 (all
samples are non-
detect; values
presented are LOD/2)
14
12-hr TWA
12-hour
TWA
(SIA.
2019b)
5161295 - 101 to
105
High
Included - EPA used these
data to estimate occupational
exposures
7
Semiconductor
manufacturing-
Container handling
Personal
Container handling, changeout: 55-gallon
drum
0.0263 (all samples are
non-detect; value
presented is LOD/2)
5
8-hr TWA
8-hr TWA
(SIA.
2019b)
5161295 - 101 to
105
High
Included - EPA used these
data to estimate occupational
exposures
8
Semiconductor
manufacturing-
Container handling
Personal
Container handling, changeout: 55-gallon
drum
0.0020 - 1.544 (all
samples are non-
detect; values
presented are LOD/2)
10
12-hr TWA
12-hour
TWA
(SIA.
2019b)
5161295 - 101 to
105
High
Included - EPA used these
data to estimate occupational
exposures
9
Semiconductor
manufacturing-
Microelectronics
fabrication
Personal
Fab worker: Photolithography maintenance,
production operator, routine operator, wet
station operator
0.0067 - 0.405 (all
samples are non-
detect; values
presented are LOD/2)
28
12-hr TWA
12-hour
TWA
(SIA.
2019b)
5161295 - 110
High
Included - EPA used these
data to estimate occupational
exposures
10
Semiconductor
manufacturing-
Maintenance
Personal
Maintenance activities: filter changeout,
cleaning, preventative maintenance
0.00608 -0.750 (8 of 9
samples are non-
detect; values
presented are LOD/2)
9
8-hr TWA
8-hr TWA
(SIA.
2019b)
5161295 - 106 to
109
High
Included - EPA used these
data to estimate occupational
exposures
11
Semiconductor
manufacturing-
Maintenance
Personal
Maintenance activities: filter changeout,
cleaning, preventative maintenance
0.0020- 1.544 (33 of
36 samples are non-
detect; values
presented are LOD/2)
36
12-hr TWA
12-hour
TWA
(SIA.
2019b)
5161295 - 106 to
109
High
Included - EPA used these
data to estimate occupational
exposures
Page 188 of 292
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Row
Occupational
Exposure Scenario
Type of
Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration
(mg/m3)a
Number
of
Samples
Type of
Measurement
Sample
Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
12
Semiconductor
manufacturing-
Fabrication area
Area
Fab area samples: photolithography,
polyimide cure oven, wet area
0.0263 (all samples are
non-detect; value
presented is LOD/2)
2
8-hr TWA
8-hr TWA
(SIA.
2019b)
5161295 - 111
High
Excluded - EPA used personal
breathing zone samples to
estimate occupational
exposures and did assess risk
from ONU exposures for this
condition of use
13
Semiconductor
manufacturing-
Fabrication area
Area
Fab area samples: photolithography,
polyimide cure oven, wet area
0.130-0.284 (all
samples are non-
detect; values
presented are LOD/2)
7
12-hr TWA
12-hour
TWA
(SIA.
2019b)
5161295 - 111
High
Excluded - EPA used personal
breathing zone samples to
estimate occupational
exposures and did assess risk
from ONU exposures for this
condition of use
14
Semiconductor
manufacturing-
Virgin NMP
unloading
Personal
Virgin NMP truck off-loading: Pull 6
samples for purity analysis; transfer of virgin
NMP from a 10,000-gallon tanker truck to a
10,000-gallon tank in the tank farm. Turn on
pump; stay in enclosure upstairs during ~ 2-
hour transfer.
4.78
1
8-hr TWA
8-hr TWA
(SIA.
2019b)
5161295 - 113
High
Included - EPA used these
data to estimate occupational
exposures
15
Semiconductor
manufacturing- Waste
NMP loading
Personal
Waste truck loading: Transfer of
approximately 5,000 gallons of NMP waste
from a 10,000-gallon tank to a tanker truck.
0.709 (sample is non-
detect; value presented
is LOD/2)
1
8-hr TWA
8-hr TWA
(SIA.
2019b)
5161295 - 112
High
Included - EPA used these
data to estimate occupational
exposures
16
Semiconductor and
Related Device Mfg.
Personal
Unknown
Non-detect
3
Partial shift,
Full shift
60 to 368
minutes
(OSHA.
2017)
3827305 - 107
High
Excluded - this is not the
highest rated data
a Statistics were calculated by the cited source and are presented here as they were presented in the source.
Page 189 of 292
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A. 11 Printing and Writing
EPA identified one source containing NMP monitoring data at a screen-printing shop. However, this
data is presented without any context. This data is presented in Row 1 of Table Apx A-l 1 and is from a
facility that conducts screen printing, but the sample type, sample duration, and associated worker
activities are unknown, thus the data is not used in this risk evaluation.
In addition, EPA compiled data from a NIOSH study on ink mist exposures at a newspaper printing shop
in Row 2 (NIOSH. 1983). The printing shop did not specifically use NMP-based inks; thus, this study
did not monitor for NMP, but rather for ink mists in worker breathing zones. Specifically, NIOSH
conducted personal breathing zone sampling of multiple workers, including printing press operators and
assistants, for ink mist. This study consisted of 43 full shift samples, ranging from around 5 to 8 hours,
and 5 partial shift samples, all between 3 and 4 hours. EPA did not use these data because they did not
have the highest rating from systematic review.
NMP monitoring data for commercial printing (except screen printing) were identified in OSHA's
CEHD (OSHA 2017). These data include six personal breathing zone, partial shift measurements and
are presented in Rows 3 and 4. For samples with detected values, EPA translated these sample results
into 8-hour TWA and 4-hour TWA concentrations, respectively, by assuming that exposure
concentration is zero for the time remaining in the 8- and 4-hour durations. EPA used the sampling
duration for the monitoring data as the what-if (duration-based) exposure duration. EPA then used these
measurements to calculate central tendency (50th percentile) and high-end exposures (95th percentile) for
full-shift (8 hours), half-shift (4 hours), and what-if (duration based on monitoring data sample time).
For the central tendency and high-end calculations, where non-detect values were included in the
dataset, EPA used the limit of detection (LOD) divided by two. EPA used this method for approximating
a concentration for non-detect samples because the geometric standard deviation of the dataset is greater
than three (U.S. EPA 1994b). Because greater than 50% of the monitoring data results are non-detect
for NMP, this method for the calculation of statistics will result in potentially biased estimates.
EPA did not find monitoring data on the use of markers or other writing instruments containing NMP.
One assessment performed by Australia's National Industrial Chemicals Notification and Assessment
Scheme (NICNAS) on the use of consumer products indicates that inhalation exposure from the use of
writing inks is assumed negligible due to the small amount of ink, and therefore NMP, used (Australian
Government Department of Health. 2016). In addition, the one writing product identified in the
"Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: NMP"
document and 2017 market profile for NMP indicate that the marker is a weather-resistant (Abt. 2017;
U.S. EPA. 2017b). The SDS for this product confirms that the marker is weather-resistant and intended
for use on polyurethane tags / labels
(http://www.markal.eom/assets/l/7/aw plastic eartag white medtip.pdf). Because, this product is
weather-resistant, EPA expects that the primary users will use this product outside, which mitigates the
potential for inhalation and vapor-through-skin exposures.
Consistent with the NICNAS assessment approach and the outdoor use of the identified writing product
containing NMP, EPA does not assess inhalation and vapor-through-skin exposures during use of NMP
writing inks.
Page 190 of 292
-------
Table Apx A-ll. Summary of Parameters for Inhalation Monitoring Data for Printing and Writing
Row
Occupational
Exposure Scenario
Type of
Sample
Worker Activity
or Sampling
Location
NMP Airborne
Concentration
(mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure
Duration
Source
Data Identifier from
Data Extraction and
Evaluation
Overall Confidence Rating
from Data Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
1
Screen printing
Unknown
Unknown
7.1 to 22.2
Unknown
Unknown
Unknown
(RIVM.
2013)
3809440 - 119
Unacceptable
Excluded - Rated
unacceptable
2
Printing Press
Operator
Personal
Multiple different
workers
Range: 0.12 to 3.29
48
Partial and Full
Shift
3.3 to 7.9 hours
(NIOSH.
1983)
3101190 - 101
Medium
Excluded - these are not the
highest rated data
3
Commercial Printing,
Except Screen Printing
Personal
unknown
Non-detect
5
Partial Shift
14 to 75 mins
(OSHA.
2017)
3827305 - 104
High
Included - LOD/2 used for
central tendency and high-
end calculations
4
Commercial Printing,
Except Screen Printing
Personal
unknown
1.07 mg/m3 (1
sample)
1
Partial Shift
50 mins
(OSHA.
2017)
3827305 - 104
High
Included
Statistics were calculated by the cited source and are presented here as they were presented in the source.
Page 191 of 292
-------
A. 12 Soldering
EPA did not find inhalation monitoring data or modeled data specifically related to the use of NMP -
based soldering products. Due to lack of additional information and the low NMP content in the one
identified soldering production containing NMP (one to 2.5 weight percent NMP), the potential for
worker and ONU inhalation and vapor-through-skin exposures is likely small. While the increased
temperature during soldering may increase the potential for NMP vapor production, some of the NMP
may be destroyed in the soldering process, mitigating the potential for inhalation and vapor-through-skin
exposures.
Due to the lack of data for this occupational exposure scenario, EPA uses a modeled exposure for brush
application of products containing NMP as surrogate for soldering, which is described in Appendix A.6.
Page 192 of 292
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A. 13 Commercial Automotive Servicing
EPA did not find monitoring data for the use of NMP products during automotive servicing. Further,
EPA did not find any monitoring data for the use of NMP aerosol products in any industry. To estimate
potential worker inhalation and vapor-through-skin exposures during the use of aerosol products that
contain NMP, EPA modeled potential NMP air concentrations for workers and ONUs using EPA's
model for Occupational Exposures daring Aerosol Degreasing of Automotive Brakes. This model was
used because EPA does not have related monitoring data nor throughput parameters (i.e., annual and
daily amounts of NMP products used per servicing site). This model includes default parameters for
throughput based on information that CARB obtained from industry surveys of automotive brake
cleaner manufacturers and automotive repair shops.
EPA used the NMP concentrations of the two aerosol degreasing products identified in Section 2.13.1 as
inputs to the model. The concentrations of these products are 4.5 and 35 to 40 weight percent. The
results of this modeling are near-field and far-field NMP air concentration estimates, which are used as
the input parameters used for the PBPK modeling for workers in and ONUs, respectively. Specifically,
EPA uses the 50th and 95th percentile model results to represent central tendency and high-end inhalation
and vapor-through-skin exposures, respectively. This model calculates both 8-hour TWA and 1-hour
TWA exposure concentrations. EPA used the 1-hour TWA concentrations for the what-if (duration-
based) scenarios and the 8-hour TWA concentrations for the high-end scenarios. For the central
tendency scenarios, EPA used an exposure duration of half a shift (4 hours) and translated the 8-hour
TWA concentrations into 4-hour TWA concentrations.
Table Apx A-12. Aerosol Degreasing Model Results
Statistic
C (mg/m3)
8-hour TWA (high-end)
1-hour TWA (what-if, duration-based)
Near-field (Worker)
Exposure
Far-field (ONU)
Exposure
Near-field (Worker)
Exposure
Far-field (ONU)
Exposure
Maximum
564.36
128.87
1,504.94
331.33
99th Percentile
72.55
4.20
210.89
12.44
95th Percentile
43.44
1.57
128.76
4.71
50th Percentile
6.39
0.13
19.96
0.40
5th Percentile
0.94
0.01
3.07
0.04
Minimum
0.07
0.00
0.42
0.01
Mean
12.95
0.40
39.13
1.20
Page 193 of 292
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A. 14 Laboratory use
Table Apx A-13 shows the inhalation monitoring data that is available in published literature for use of
NMP in a laboratory setting. EPA only found one data source that had inhalation monitoring data, which
is presented in Row 1. This data is for a two-hour task duration at a laboratory that uses NMP as a media
in which to dissolve a photoresist formulation for quality testing (Solomon et al.. 1996). Specifically,
this sample was taken during the preparation of NMP before use (purification), sample preparation
(dissolving of solid photoresist into NMP), and sample analysis (operating atomic absorption
Spectrophotometer). EPA uses this result as an input into the PBPK model for the what-if (duration-
based) 2-hour task duration.
In addition to this data point, EPA presented modeled potential NMP air concentrations during use of
NMP in industrial and commercial laboratory settings that were included in the RIVM Annex XV
Proposal for a Restriction - NMP report (RIVM. 2013). These modeled exposures are presented in
Rows 2 and 3. RIVM included these modeled exposures in the report due to the lack of actual inhalation
monitoring data for NMP. In lieu of additional monitoring data, EPA uses the modeled exposure
concentration in Row 2 for use of NMP in industrial laboratories with 90 percent efficient LEV as the
input into the PBPK model for a central tendency full-shift, 8-hour exposure duration. EPA uses the
modeled exposure in Row 3 for use of NMP in commercial laboratories with 80 percent efficient LVE
as the input for high-end full-shift inhalation and vapor-through-skin exposures. EPA uses Row 3 as
high-end because these data relate to commercial laboratories that use LEV with a lower capture
efficiency than those employed by the industrial laboratories represented in Row 2.
Page 194 of 292
-------
Table Apx A-13. Summary of Inhalation Monitoring Data for Laboratory Use
Row
Occupational
Exposure
Scenario
Type of Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration
(mg/m3)
Number of
Samples
Type of
Measurement
Sample
Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence Rating
from Data
Extraction and
Evaluation
Rationale for Inclusion /
Exclusion
1
Laboratory use
Source notes that
this result was
obtained in both
personal and area
samples
Pouring NMP through an ion-exchange
column under pressure (for purification);
sample preparation and analysis (QC
samples of negative photoresist used in
the electronics industry that were
dissolved in NMP)
0.2
Unknown
Partial Shift
2 hours
(Solomon
et al..
1996)
3043623 - 101
Medium
Included - this
concentration is used for
the duration based PBPK
input
2
Laboratory use
Modelled using
EasyTRA model
Laboratory use in an industrial setting
with local exhaust ventilation (90%
efficiency).
2.07
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 127
High
Included - this
concentration is used as
input into the PBPK
model for a central
tendency full-shift
exposure
3
Laboratory use
Modelled using
EasyTRA model
Laboratory use in a commercial setting
with local exhaust ventilation (80%
efficiency).
4.13
Not applicable
- this is a
modelled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 127
High
Included - this
concentration is used as
input into the PBPK
model for a high-end full-
shift exposure
Page 195 of 292
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A. 15 Lithium Ion Cell Manufacturing
Table Apx A-14 shows inhalation monitoring data that are available in published literature for the use
of NMP in the lithium ion cell manufacturing industries. Based on data availability, EPA assessed the
following occupational exposure scenarios (LICM. 2020a):
Container handling, small containers,
Container handling, drums,
Cathode coating,
Cathode mixing,
Research and development, and
Miscellaneous.
The Lithium Ion Cell Manufacturers' Coalition provided 8-hour TWA personal breathing zone
monitoring data for NMP taken at sites that use NMP in lithium ion cell manufacturing (LICM. 2020a).
These data were taken outside of fume hoods and the public comment indicates that workers wear PPE
such as gowns and respirators, which mitigate inhalation and dermal exposure to liquid potential. These
data were taken from 2012 to 2019 and include multiple work activities. Based on the number of data
points for each work activity, EPA assessed individual occupational exposure scenarios for cathode
coating, cathode mixing, research and development, and miscellaneous activities (e.g., mix room,
maintenance, and cleaning). For each occupational exposure scenario, EPA calculated central tendency
and high-end exposure concentrations for full-shift (8 hours), as well as half-shift (4 hours) and what-if
(duration based, 2.5 hours) by adjusting the full shift concentration (note that non-detect values were not
adjusted for these calculations). Where non-detect measurements exist in a dataset, EPA used the LOD
divided by two for central tendency and high-end calculations (U.S. EPA 1994b). EPA uses a what-if
task duration of 2.5 hours, which is based on a public comment from EaglePicher Technologies, LLC
that indicates the length of time NMP is used is roughly 2.5 hours per batch (EPA assumes one batch per
day) (EaglePicher Technologies. 2020a). EPA does not have data on the length of time of NMP
exposure during use; however, public comments indicate exposure is minimal to non-existent due to
PPE usage (EaglePicher Technologies. 2020a; LICM. 2020a). Because EPA does not assume PPE
usage, EPA uses the length of the tasks using NMP, 2.5 hours, as the what-if task duration.
Information from the Lithium Ion Cell Manufacturers' Coalition and EaglePicher also indicate that
NMP may be unloaded from small containers and drums and that waste NMP may be loaded into drums
(EaglePicher Technologies. 2020b; LICM. 2020b); therefore, EPA assessed occupational exposure
scenarios for both small containers handling and drum handling. No monitoring data for small container
handling or drum handling were available for the lithium ion cell manufacturing industry. EPA used
monitoring data for these occupational exposure scenarios for semiconductor manufacturing, which is
discussed in Appendix A. 10.
Page 196 of 292
-------
Table Apx A-14. Summary of Inhalation Monitoring Data for Lithium Ion Cell Manufacturing
Row
Occupational
Exposure Scenario
Type of
Sample
Worker Activity or
Sampling Location
NMP Airborne
Concentration
(mg/m3)
Number
of
Samples
Type of
Measurement
Sample Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall Confidence
Rating from Data
Extraction and
Evaluation
Rationale for Inclusion / Exclusion
1
Lithium ion cell
manufacturing -
cathode coating
Personal
Cathode coating
Non-detect (1
sample), 1.42, 4.87,
21.1, 39.7
5
Full shift
8 or 12-hour
TWA
LICM,
2020,
6592033
6592033 - 101
High
Included - EPA used these data to
estimate occupational exposures for
this occupational exposure scenario
(EPA uses LOD/2 for non-detects)
2
Lithium ion cell
manufacturing -
cathode mixing
Personal
Cathode mixing
Non-detect (3
samples), 1.74, 2.64,
3.45,4.87, 12.2
8
Full shift
8 or 12-hour
TWA
LICM,
2020,
6592033
6592033 - 102
High
Included - EPA used these data to
estimate occupational exposures for
this occupational exposure scenario
(EPA uses LOD/2 for non-detects)
3
Lithium ion cell
manufacturing -
research and
development
Personal
Research and
development
Non-detect (3
samples), 4.06
4
Full shift
8 or 12-hour
TWA
LICM,
2020,
6592033
6592033 - 103
High
Included - EPA used these data to
estimate occupational exposures for
this occupational exposure scenario
(EPA uses LOD/2 for non-detects)
4
Lithium ion cell
manufacturing -
miscellaneous activities
Personal
Cleaning, fill room,
maintenance, mix
room/large coater
Non-detect (2
samples), 6.08, 6.49,
7.30
5
Full shift
8 or 12-hour
TWA
LICM,
2020,
6592033
6592033 - 104
High
Included - EPA used these data to
estimate occupational exposures for
this occupational exposure scenario
(EPA uses LOD/2 for non-detects)
Page 197 of 292
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A. 16 Cleaning
TableApx A-15 shows inhalation monitoring data that is available in published literature for NMP-
based cleaning products. In addition to personal monitoring data, EPA summarized modeled NMP air
concentrations from the RIVM Annex XV Proposal for a Restriction -NMP report (RIVM. 2013). These
exposure concentrations were modeled using the EasyTRA model, which is based on the European
Center for Ecotoxicology and Toxicology of Chemicals (ECETOC) Targeted Risk Assessment (TRA)
tool, and the Stoffenmanager risk assessment software. The ECHA report modeled potential NMP air
concentrations during generic application scenarios, specifically the dip, roll/brush, and spray
application of formulations containing NMP. These modeled NMP air concentrations are presented in
Rows 21 to 25 of Table Apx A-15.
The available data do not always distinguish the specific circumstances and industries in which cleaning
activities occur. Note that, where the literature source did not specify the type of cleaning, EPA includes
these data in all cleaning occupational exposure scenarios.
For dip cleaning, EPA calculated 8-hour TWA central tendency (based on 50th percentile) and high-end
(based on 95th percentile) estimates for using the mean values listed in Rows 1 - 5, 8 - 13, and 21. For
spray / wipe cleaning, EPA calculated 8-hour TWA central tendency and high-end estimates using the
mean values listed in Rows 1-5, 20, and 23. EPA did not use the remaining data because discrete data
points were not available and only summary statistics were provided.
Page 198 of 292
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Table Apx A-15. Summary of Inhalation Monitoring Data for Cleaning
Row
Occupational Exposure
Scenario
Type of Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall Confidence
Rating from Data
Extraction and
Evaluation
1
Cleaning of metal parts -
assume dip and spray/wipe
Personal
Cleaning of metal parts to remove resin
(unknown cleaner application type)
Mean: 0.57
Max: 3.24
14
Full-shift
(Nishimura et
al.. 2009)
735269 -
101
High
Included in input to
PBPK model for dip
and spray / wipe
cleaning
2
Cleaning of metal parts -
assume dip and spray/wipe
Personal
Cleaning of metal parts to remove resin
(unknown cleaner application type)
Mean: 0.97
14
Full-shift
(Nishimura et
al.. 2009)
735269 -
101
High
Included in input to
PBPK model for dip
and spray / wipe
cleaning
3
Cleaning of metal parts -
assume dip and spray/wipe
Personal
Cleaning of metal parts to remove resin
(unknown cleaner application type)
Mean: 0.69
14
Full-shift
(Nishimura et
al.. 2009)
735269 -
101
High
Included in input to
PBPK model for dip
and spray / wipe
cleaning
4
Cleaning of metal parts -
assume dip and spray/wipe
Personal
Cleaning of metal parts to remove resin
(unknown cleaner application type)
Mean: 1.05
14
Full-shift
(Nishimura et
al.. 2009)
735269 -
101
High
Included in input to
PBPK model for dip
and spray / wipe
cleaning
5
Cleaning of metal parts -
assume dip and spray/wipe
Personal
Cleaning of metal parts to remove resin
(unknown cleaner application type)
Mean: 0.65
14
Full-shift
(Nishimura et
al.. 2009)
735269 -
101
High
Included in input to
PBPK model for dip
and spray / wipe
cleaning
6
Cleaning of metal parts -
assume dip and spray/wipe
Personal
Cleaning of optical and metal parts
(unknown cleaner application type)
Mean: 2.0
Max: 2.8
12
12-hour TWA
(Bader et al..
2006)
3539720
- 101
Medium
Excluded - discrete
data not available
(only summary
statistics)
7
Tank cleaning
Unknown
Industrial tank cleaning
Range: 4.1 to 12.4
Unknown
Unknown
(RIVM. 2013)
3809440
- 124
High
Excluded - discrete
data not available
(only summary
statistics)
8
Dip cleaning
Personal
Full-shift sampling for volunteers who
stayed in the lens cleaning workroom
Range: 0.97 to 1.30
Mean: 1.01 +/-0.12
5 (one per day
for one worker
for a week)
8-hr TWA
(Xiaofei et al..
2000)
3562767
- 101
Medium
Included in input to
PBPK model for dip
cleaning
9
Dip cleaning
Personal
Workers place parts in basket, put basket
in chamber, close chamber, open
chamber, remove basket and allow drying
in ambient conditions, transfer basket to
washing process
Range: 1.14 to 2.80
Mean: 1.70+/-0.57
5 (one per day
for one worker
for a week)
12-hr TWA
(Xiaofei et al..
2000)
3562767
- 101
medium
Included in input to
PBPK model for dip
cleaning
10
Dip cleaning
Personal
Workers place parts in basket, put basket
in chamber, close chamber, open
chamber, remove basket and allow drying
in ambient conditions, transfer basket to
washing process
Range: 0.57 to 1.62
Mean: 0.97 +/- 0.36
5 (one per day
for one worker
for a week)
12-hr TWA
(Xiaofei et al..
2000)
3562767
- 101
medium
Included in input to
PBPK model for dip
cleaning
11
Dip cleaning
Personal
Workers place parts in basket, put basket
in chamber, close chamber, open
chamber, remove basket and allow drying
in ambient conditions, transfer basket to
washing process
Range: 0.36 to 0.85
Mean: 0.57 +/- 0.20
5 (one per day
for one worker
for a week)
12-hr TWA
(Xiaofei et al..
2000)
3562767
- 101
Medium
Included in input to
PBPK model for dip
cleaning
Page 199 of 292
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Row
Occupational Exposure
Scenario
Type of Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall Confidence
Rating from Data
Extraction and
Evaluation
12
Dip cleaning
Personal
Workers place parts in basket, put basket
in chamber, close chamber, open
chamber, remove basket and allow drying
in ambient conditions, transfer basket to
washing process
Range: 0.97 to 1.14
Mean: 0.77 +/- 0.24
5 (one per day
for one worker
for a week)
12-hr TWA
(Xiaofei et al..
2000)
3562767
- 101
Medium
Included in input to
PBPK model for dip
cleaning
13
Dip cleaning
Personal
Dip cleaning of metal parts. Workers
place parts in basket, lower basket, life
basket when cleaning complete, and
transfer to water tank
Range: 0.16 to 2.39
Mean: 1.34+/-0.81
8
12-hr TWA
(Xiaofei et al..
2000)
3562767
- 102
medium
Included in input to
PBPK model for dip
cleaning
14
Dip cleaning
Unknown
Immersion cleaning of metal parts
Mean: 1.26
Unknown
Unknown
(BASF. 1993)
3982074
- 101
Low
Excluded - discrete
data not available
(only summary
statistics)
15
Dip cleaning
Unknown
Immersion cleaning of metal parts
Mean: 7.46
Unknown
Unknown
(BASF. 1993)
3982074
- 102
Low
Excluded - discrete
data not available
(only summary
statistics)
16
Unknown application type
Area
Work group area listed as "cleaning." No
additional details are provided.
50th percentile: 0.7
90th percentile: 15
95th percentile: 90
30
Unknown
(IFA. 2010)
4271620
- 132
Medium
Excluded - discrete
data not available
(only summary
statistics)
17
Unknown application type
Personal
Work group area listed as "cleaning." No
additional details are provided.
50th percentile: 2
90th percentile: 12.35
95th percentile: 18.875
23
Unknown
(IFA. 2010)
4271620
- 139
Medium
Excluded - discrete
data not available
(only summary
statistics)
18
Unknown application type
Unknown
Work group area listed as "cleaning."
Samples taken in the absence of LEV. No
additional details are provided.
50th percentile: 0.4
(below analytical
quantification limit of
0.42)
90th percentile: 79.6
95th percentile: 102.1
11
Unknown
(IFA. 2010)
4271620
- 143
Medium
Excluded - discrete
data not available
(only summary
statistics)
19
Unknown application type
Unknown
Work group area listed as "cleaning."
Samples taken in the presence of LEV.
No additional details are provided.
50th percentile: 0.9
90th percentile: 10.85
95th percentile: 13.125
35
Unknown
(IFA. 2010)
4271620
- 150
Medium
Excluded - discrete
data not available
(only summary
statistics)
20
Janitorial services - assume
spray / wipe cleaning (dip
cleaning/degreasing unlikely)
Personal
Unknown
0.071-0.145
3
8-hour TWA
(OSHA. 2017)
3827305
- 108
Medium
Included in input to
PBPK model for spray
/ wipe cleaning
21
Dip cleaning
Modelled using
EasyTRA model
Dip application of substrate into NMP-
containing solution
4.13
Not applicable -
this is a
modelled
exposure
8-hour TWA
(RIVM. 2013)
3809440
- 117
High
Included in input to
PBPK model for dip
cleaning
22
Dip cleaning
Modelled using
EasyTRA model
Dip application of substrate into NMP-
containing solution
12.4
Not applicable -
this is a
modelled
exposure
4 hours
(RIVM. 2013)
3809440
- 117
High
Excluded - EPA used
data in Row 21
Page 200 of 292
-------
Row
Occupational Exposure
Scenario
Type of Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number of
Samples
Type of
Measurement
Sample Time /
Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall Confidence
Rating from Data
Extraction and
Evaluation
23
Wipe/spray Cleaning
Modelled using
EasyTRA model
Roll/brush application of NMP-containing
solution
4.13
Not applicable -
this is a
modelled
exposure
8-hour TWA
(RIVM. 2013)
3809440
- 115
High
Included in input to
PBPK model for spray
/ wipe cleaning
24
Wipe/spray Cleaning
Modelled using
Stoffenmanager
model
Spray application of NMP-containing
solution. With spray booth.
7.96
Not applicable -
this is a
modelled
4 hours
(RIVM. 2013)
3809440
- 113
High
Excluded - EPA used
data in Row 23
exposure
25
Wipe/spray Cleaning
Modelled using
Stoffenmanager
model
Spray application of NMP-containing
solution. Without spray booth.
18.7
Not applicable -
this is a
modelled
4 hours
(RIVM. 2013)
3809440
- 113
High
Excluded - EPA used
data in Row 23
exposure
a Statistics were calculated by the cited source and are presented here as they were presented in the source.
Page 201 of 292
-------
A. 17 F ertilizer Application
EPA did not find inhalation monitoring data for the application of fertilizers containing NMP. The
RIVM Annex XV Proposal for a Restriction -NMP report presented the modeled potential NMP air
concentrations during spray and fog application of agrochemicals (RIVM. 2013). EPA summarized
these modeled exposures in TableApx A-16. The RIVM Annex XV Proposal for a Restriction - NMP
report recommends that manual application activities should be limited to four hours per shift or less
(RIVM. 2013). Application with more automated equipment and separation of the worker from the
sources of exposure can exceed this recommendation. EPA thus assesses both full-shift 8-hour TWA
and half-shift 4-hour TWA NMP air concentrations. EPA did not find data on what-if (duration-based)
exposures.
Due to lack of additional information or modeling approaches, EPA uses the full-shift modeled
exposures from the RIVM Annex Xl^ Proposal for a Restriction - NMP report to represent potential
inhalation and vapor-through-skin exposures during this scenario. Specifically, EPA uses the exposure
estimate in Row 1 as a central tendency inhalation and vapor-through-skin exposure concentration and
the estimate in Row 2 as a high-end inhalation and vapor-through-skin exposure concentration. These
estimates are both full-shift, 8-hour TWA exposures.
Page 202 of 292
-------
Table Apx A-16. Summary of Inhalation Monitoring Data for Fertilizer Application
Row
Occupational
Exposure Scenario
Type of Sample
Worker Activity or Sampling
Location
NMP Airborne
Concentration
(mg/m3)
Number of
Samples
Type of
Measurement
Sample
Time
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall Confidence
Rating from Data
Extraction and
Evaluation
Rationale for
Inclusion /
Exclusion
1
Spray or fog
application of
agrochemicals
Modeled using EasyTRA model
Spray or fog application of
agrochemicals by a worker
located outside, in a cabin with
supplied air.
2.97
Not applicable -
this is a modeled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440- 131
High
Included - used
for central
tendency estimate
2
Spray or fog
application of
agrochemicals
Modeled using EasyTRA model
Spray or fog application of
agrochemicals by a worker
located inside without the use of
a cabin.
5.27
Not applicable -
this is a modeled
exposure
8-hour TWA
8 hours
(RIVM.
2013)
3809440 - 131
High
Included - used
for high-end
estimate
Page 203 of 292
-------
A. 18 Additional Monitoring Data
EPA found additional NMP monitoring data that did not have sufficient context to determine which, if
any, condition of use and occupational exposure scenario these data are applicable to. These data are
summarized in Table Apx A-17.
The data presented in Rows 1 through 39 are from a compilation of NMP monitoring data prepared by
the German Institute for Occupational Safety and Health (IFA) (TFA 2010). These data list specific
work areas such as "storing and conveying" or industries such as "plastics and plastic foam",
"foundries", or "building industry". However, the function of NMP in these work areas and industries,
associated worker activities, sampling areas, and sampling times associated with these data are
unknown. EPA therefore excluded these data points from this analysis.
The data presented in Rows 40 through 42 are from OSHA CEHD (OSHA 2017). These data include
both personal breathing zone and area sampling for a variety of industries, determined from the NAICS
codes associated with the data. These NAICS codes include industries such as photographic and
photocopying equipment manufacturing, all other converted paper product manufacturing, all other
miscellaneous fabricated metal product manufacturing, and regulation, licensing, and inspection of
miscellaneous commercial sectors, among other industries from which EPA could not determine the
condition of use of NMP. These data also lack metadata such as descriptions of worker activities and
sample areas. Therefore, EPA did not use these data points.
Page 204 of 292
-------
Table Apx A-17. Summary of Inhalation Monitoring Data for Unknown Occupational Exposure Scenarios
Row
Occupational
Exposure
Scenario
Type of
Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number
of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for
Inclusion / Exclusion
1
Unknown
Area
Work area listed as "storing, conveying."
No additional details are provided.
50th percentile: below
analytical quantification
limit of 0.42
90th percentile: 0.64
95th percentile: 1.155
13
Unknown
Unknown - Per source, the
sampling time is greater than
or equal to 1 hour and
exposure duration is greater
than or equal to 6 hours, such
that this is comparable to a
shift measurement
(IFA.
2010)
4271620- 129
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
2
Unknown
Unknown
Work area listed as "storing, conveying."
Samples taken in the presence of LEV.
No additional details are provided.
50th percentile: 0.2
(below analytical
quantification limit of
0.42)
90th percentile: 0.7
95th percentile: 1.35
10
Unknown
Unknown - Per source, the
sampling time is greater than
or equal to 1 hour and
exposure duration is greater
than or equal to 6 hours, such
that this is comparable to a
shift measurement
(IFA.
2010)
4271620- 145
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
3
Unknown
Area
Industry listed as "plastics and plastic
foam, processing and manufacture,
manufacture and processing of rubber
products." No additional details are
provided.
50th percentile: 0.3
(below analytical
quantification limit of
0.42)
90th percentile: 3
95th percentile: 3.5
40
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 102
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
4
Unknown
Personal
Industry listed as "plastics and plastic
foam, processing and manufacture,
manufacture and processing of rubber
products." No additional details are
provided.
50th percentile: 0.35
(below analytical
quantification limit of
0.42)
90th percentile: 2.93
95th percentile: 4.985
61
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 110
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
5
Unknown
Unknown
Industry listed as "plastics and plastic
foam, processing and manufacture,
manufacture and processing of rubber
products." Samples taken in the presence
of LEV. No additional details are
provided.
50th percentile: 0.5
90th percentile: 3.45
95th percentile: 4.775
65
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 117
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
6
Unknown
Unknown
Industry listed as "plastics and plastic
foam, processing and manufacture,
manufacture and processing of rubber
products." Samples taken in the absence
of LEV. No additional details are
provided.
50th percentile: 0.2
(below analytical
quantification limit of
0.42)
90th percentile: 1.92
95th percentile: 2.9
22
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 124
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Page 205 of 292
-------
Row
Occupational
Exposure
Scenario
Type of
Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number
of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for
Inclusion / Exclusion
7
Unknown
Unknown
Industry listed as "plastics and plastic
foam, processing and manufacture,
manufacture and processing of rubber
products." No additional details are
provided.
50th percentile: 0.2
(below analytical
quantification limit of
0.42)
90th percentile: 0.84
95th percentile: 1.72
14
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 160
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
8
Unknown
Unknown
Industry listed as "plastics and plastic
foam, processing and manufacture,
manufacture and processing of rubber
products." No additional details are
provided.
50th percentile: 0.3
(below analytical
quantification limit of
0.42)
90th percentile: 2
95th percentile: 2.6
28
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 161
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
9
Unknown
Personal
Work area listed as "foaming." No
additional details are provided.
50th percentile: below
analytical quantification
limit of 0.42
90th percentile: 0.38
(below analytical
quantification limit of
0.42)
95th percentile: 0.49
11
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 136
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
10
Unknown
Unknown
Work area listed as "foaming." Samples
taken in the presence of LEV. No
additional details are provided.
50th percentile: below
analytical quantification
limit of 0.42
90th percentile: 0.88
95th percentile: 1.84
13
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 147
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
11
Unknown
Area
Industry listed as "chemical industry and
mineral processing". No additional details
are provided.
50th percentile: 0.175
(below analytical
quantification limit of
0.42)
90th percentile: 13.41
95th percentile: 16.93
11
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 101
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
12
Unknown
Personal
Industry listed as "chemical industry and
mineral processing". No additional details
are provided.
50th percentile: 0.45
90th percentile: 6
95th percentile: 9.75
30
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 109
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Page 206 of 292
-------
Data Identifier
from Data
Extraction and
Evaluation
Overall
Row
Occupational
Exposure
Scenario
Type of
Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number
of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for
Inclusion / Exclusion
Unknown - Per source, the
Excluded - based on
13
Unknown
Unknown
Industry listed as "chemical industry and
mineral processing". Samples taken in the
presence of LEV. No additional details
are provided.
50th percentile: 0.45
90th percentile: 12.5
95th percentile: 16.8
30
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 116
Medium
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
14
Unknown
Unknown
Industry listed as "chemical industry and
mineral processing". No additional details
50th percentile: 0.4
(below analytical
quantification limit of
0.42)
90th percentile: 4.5
95th percentile: 6.2
14
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
(IFA.
2010)
4271620- 159
Medium
Excluded - based on
the information
available, EPA cannot
determine the
are provided.
6 hours, such that this is
comparable to a shift
measurement
applicable
occupational exposure
scenario
15
Unknown
Personal
Work area listed as "mixing, pressing
(compacting)." No additional details are
50th percentile: 0.35
(below analytical
quantification limit of
0.42)
90th percentile: 3.45
95th percentile: 5.875
21
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
(IFA.
2010)
4271620- 135
Medium
Excluded - based on
the information
available, EPA cannot
determine the
provided.
6 hours, such that this is
comparable to a shift
measurement
applicable
occupational exposure
scenario
Unknown - Per source, the
Excluded - based on
16
Unknown
Unknown
Work area listed as "mixing, pressing
(compacting)." Samples taken in the
presence of LEV. No additional details
are provided.
50th percentile: below
analytical quantification
limit of 0.42
90th percentile: 3.45
95th percentile: 5.875
21
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 146
Medium
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Unknown - Per source, the
Excluded - based on
17
Unknown
Area
Industry listed as "Foundries". No
additional details are provided.
50th percentile: below
analytical quantification
limit of 0.42
90th percentile: 15.8
95th percentile: 21.1
11
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 134
Unacceptable
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Unknown - Per source, the
Excluded - based on
18
Unknown
Personal
Industry listed as "Foundries". No
additional details are provided.
50th percentile: below
analytical quantification
limit of 0.42
90th percentile: 0.6
95th percentile: 0.75
10
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 152
Unacceptable
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Page 207 of 292
-------
Row
Occupational
Exposure
Scenario
Type of
Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number
of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for
Inclusion / Exclusion
19
Unknown
Unknown
Industry listed as "manufacture and
processing of metals." No additional
details are provided.
50th percentile: 0.7
90th percentile: 3.86
95th percentile: 5.415
37
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 101
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
20
Unknown
Unknown
Industry listed as "manufacture and
processing of metals." Samples taken in
the absence of LEV. No additional details
are provided.
50th percentile: 0.2 below
analytical quantification
limit of 0.42
90th percentile: 13.45
95th percentile: 86.9
19
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 125
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
21
Unknown
Unknown
Industry listed as "manufacture and
processing of metals." Samples taken in
the presence of LEV. No additional
details are provided.
50th percentile: 0.55
90th percentile: 4
95th percentile: 6.5
55
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 119
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
22
Unknown
Personal
Industry listed as "manufacture and
processing of metals." No additional
details are provided.
50th percentile: 0.5
90th percentile: 2.72
95th percentile: 3
44
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 111
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
23
Unknown
Area
Industry listed as "manufacture and
processing of metals." No additional
details are provided.
50th percentile: 0.2 below
analytical quantification
limit of 0.42
90th percentile: 13.41
95th percentile: 24.65
43
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 104
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
24
Unknown
Unknown
Industry listed as "manufacture and
processing of metals." No additional
details are provided.
50th percentile: 1.5
90th percentile: 57
95th percentile: 96.4
14
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 154
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Page 208 of 292
-------
Row
Occupational
Exposure
Scenario
Type of
Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number
of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for
Inclusion / Exclusion
25
Unknown
Area
Industry listed as "Electrical engineering,
fine mechanics, optics". No additional
details are provided.
50th percentile: 0.3
(below analytical
quantification limit of
0.42)
90th percentile: 3.54
95th percentile: 6.2
44
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 106
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
26
Unknown
Personal
Industry listed as "Electrical engineering,
fine mechanics, optics". No additional
details are provided.
50th percentile: below
analytical quantification
limit of 0.42
90th percentile: 9.6
95th percentile: 11.9
21
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 113
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
27
Unknown
Unknown
Industry listed as "Electrical engineering,
fine mechanics, optics". No additional
details are provided.
50th percentile: 0.2
(below analytical
quantification limit of
0.42)
90th percentile: 3
95th percentile: 3.9
40
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 121
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
28
Unknown
Unknown
Industry listed as "Electrical engineering,
fine mechanics, optics". No additional
details are provided.
50th percentile: 0.2
(below analytical
quantification limit of
0.42)
90th percentile: 1.22
95th percentile: 1.965
21
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 157
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
29
Unknown
Unknown
Industry listed as "Electrical engineering,
fine mechanics, optics". No additional
details are provided.
50th percentile: 0.95
90th percentile: 11.9
95th percentile: 12
21
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 158
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
30
Unknown
Area
Industry listed as "Steel construction,
manufacture of machinery and vehicles."
No additional details are provided.
50th percentile: below
analytical quantification
limit of 0.42
90th percentile: 5.02
95th percentile: 7.36
16
Unknown
Unknown - Per source, the
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 105
Medium
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Page 209 of 292
-------
Data Identifier
from Data
Extraction and
Evaluation
Overall
Row
Occupational
Exposure
Scenario
Type of
Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number
of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for
Inclusion / Exclusion
Unknown - Per source, the
Excluded - based on
31
Unknown
Personal
Industry listed as "Steel construction,
manufacture of machinery and vehicles."
No additional details are provided.
50th percentile: 0.3
90th percentile: 1.75
95th percentile: 2.725
15
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 112
Medium
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Unknown - Per source, the
Excluded - based on
32
Unknown
Unknown
Industry listed as "Steel construction,
manufacture of machinery and vehicles."
No additional details are provided.
50th percentile: 0.7
90th percentile: 5.56
95th percentile: 7.36
16
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 156
Medium
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Unknown - Per source, the
Excluded - based on
33
Unknown
Unknown
Industry listed as "Steel construction,
manufacture of machinery and vehicles."
Taken in presence of LEV. No additional
details are provided.
50th percentile: 0.55
90th percentile: 5.8
95th percentile: 7.45
15
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 120
Medium
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Unknown - Per source, the
Excluded - based on
34
Unknown
Unknown
Industry listed as "Steel construction,
manufacture of machinery and vehicles."
Taken in absence of LEV. No additional
details are provided.
all measurements below
analytical quantification
limit of 0.42
10
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 126
Medium
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Unknown - Per source, the
Excluded - based on
35
Unknown
Personal
Industry listed as "Building industry." No
additional details are provided.
50th percentile: 1.5
90th percentile: 6.6
95th percentile: 7.9
11
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 115
Medium
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Unknown - Per source, the
Excluded - based on
36
Unknown
Area
Work area listed as "processing, sanding,
removal." No additional details are
50th percentile: below
analytical quantification
limit of 0.42
24
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
(IFA.
2010)
4271620- 130
Medium
the information
available, EPA cannot
determine the
provided.
90th percentile: 49.8
95th percentile: 149.8
6 hours, such that this is
comparable to a shift
measurement
applicable
occupational exposure
scenario
Page 210 of 292
-------
Data Identifier
from Data
Extraction and
Evaluation
Overall
Row
Occupational
Exposure
Scenario
Type of
Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number
of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for
Inclusion / Exclusion
Unknown - Per source, the
Excluded - based on
37
Unknown
Personal
Work area listed as "processing, sanding,
removal." No additional details are
50th percentile: 0.5
90th percentile: 8.4
13
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
(IFA.
2010)
4271620- 137
Medium
the information
available, EPA cannot
determine the
provided.
95th percentile: 13.9
6 hours, such that this is
comparable to a shift
measurement
applicable
occupational exposure
scenario
Unknown - Per source, the
Excluded - based on
38
Unknown
Unknown
Work area listed as "processing, sanding,
removal." Samples taken in the absence
of LEV. No additional details are
provided.
50th percentile: below
analytical quantification
limit of 0.42
90th percentile: 5.72
95th percentile: 7.8
12
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 141
Medium
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Unknown - Per source, the
Excluded - based on
39
Unknown
Unknown
Work area listed as "processing, sanding,
removal." Samples taken in the presence
of LEV. No additional details are
provided.
50th percentile: below
analytical quantification
limit of 0.42
90th percentile: 1
95th percentile: 1
14
Unknown
sampling time greater than or
equal to 1 hour and exposure
time is greater than or equal to
6 hours, such that this is
comparable to a shift
measurement
(IFA.
2010)
4271620- 148
Medium
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Work activities are unknown. Associated
NAICS codes are: All Other Converted
Paper Product Mfg.; All Other Misc.
Wood Product Mfg.; All Other Plastics
Excluded - based on
Product Mfg.; All Other Rubber Product
the information
40
Unknown
personal
and area
Mfg.; Fabric Coating Mills; Iron
Foundries; Landscaping Services; Metal
Coating, Engraving (Except Jewelry and
Silverware), and Allied Services to
Manufacturers; Metal Kitchen Cookware,
Utensil, Cutlery, and Flatware (Except
Precious) Mfg.; Photographic and
Photocopying Equipment Mfg.
ND -31.4
174
Short-term and
full-shift
Varies
(OSHA.
2017)
3827305 - 101
Medium
available, EPA cannot
determine the
applicable
occupational exposure
scenario
Work activities are unknown. Associated
NAICS codes are: Administration of
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
41
Unknown
personal
and area
Education Programs; Institutional
Furniture Manufacturing; Nonferrous
Metal (Except Copper and Aluminum)
Rolling, Drawing, and Extruding; Other
Industrial Machinery Mfg.; Printing
Machinery and Equipment Mfg.
ND - 6.24
53
Short-term and
full-shift
Varies
(OSHA.
2017)
3827305 - 102
Medium
Page 211 of 292
-------
Row
Occupational
Exposure
Scenario
Type of
Sample
Worker Activity or Sampling Location
NMP Airborne
Concentration (mg/m3)a
Number
of
Samples
Type of
Measurement
Sample Time / Exposure
Duration
Source
Data Identifier
from Data
Extraction and
Evaluation
Overall
Confidence
Rating from Data
Extraction and
Evaluation
Rationale for
Inclusion / Exclusion
42
Unknown
personal
and area
Work activities are unknown. Associated
NAICS codes are: All Other
Miscellaneous Fabricated Metal Product
Manufacturing; Metal Coating, Engraving
(except Jewelry and Silverware), and
Allied Services to Manufacturers;
Regulation, Licensing, and Inspection of
Miscellaneous Commercial Sectors;
Reupholstery and Furniture Repair; Sign
Manufacturing
ND - 10.2
19
Short-term and
full-shift
Varies
(OSHA.
2017)
3827305 - 103
High
Excluded - based on
the information
available, EPA cannot
determine the
applicable
occupational exposure
scenario
a Statistics were calculated by the cited source and are presented here as they were presented in the source.
Page 212 of 292
-------
Appendix B Description of Models used to Estimate Worker and ONU
Exposures
B._l Approaches for Estimating Number of Workers
This appendix summarizes the methods that EPA used to estimate the number of workers who are
potentially exposed to NMP in each of its conditions of use. The method consists of the following steps:
1. Identify the North American Industry Classification System (NAICS) codes for the industry
sectors associated with each scenario.
2. Estimate total employment by industry/occupation combination using the Bureau of Labor
Statistics' Occupational Employment Statistics (OES) data (U.S. BLS. 2016).
3. Refine the OES estimates where they are not sufficiently granular by using the U.S. Census'
(2015) Statistics of U.S. Businesses (SUSB) data on total employment by 6-digit NAICS.
4. Estimate the percentage of employees likely to be using NMP instead of other chemicals (i.e., the
market penetration of NMP in the scenario).
5. Estimate the number of sites and number of potentially exposed employees per site.
6. Estimate the number of potentially exposed employees within the scenario.
Step 1: Identifying Affected NAICS Codes
As a first step, EPA identified NAICS industry codes associated with each scenario. EPA generally
identified NAICS industry codes for a scenario by:
Querying the U.S. Census Bureau's NAICS Search tool using keywords associated with each
scenario to identify NAICS codes with descriptions that match the scenario.
Referencing EPA Generic Scenarios (GS's) and Organisation for Economic Co-operation and
Development (OECD) Emission Scenario Documents (ESDs) for a scenario to identify NAICS
codes cited by the GS or ESD.
Reviewing Chemical Data Reporting (CDR) data for the chemical, identifying the industrial
sector codes reported for downstream industrial uses, and matching those industrial sector codes
to NAICS codes using Table D-2 provided in the CDR reporting instructions.
Each scenario section in the main body of this report identifies the NAICS codes EPA identified for the
respective scenario.
Step 2: Estimating Total Employment by Industry and Occupation
BLS's (2016) OES data provide employment data for workers in specific industries and occupations.
The industries are classified by NAICS codes (identified previously), and occupations are classified by
Standard Occupational Classification (SOC) codes.
Among the relevant NAICS codes (identified previously), EPA reviewed the occupation description and
identified those occupations (SOC codes) where workers are potentially exposed to NMP. TableApx
B-l shows the SOC codes EPA classified as occupations potentially exposed to NMP. These
occupations are classified into workers (W) and occupational non-users (O). All other SOC codes are
assumed to represent occupations where exposure is unlikely.
Table Apx B-l. SOCs with Worker and ONU Designations for All Conditions of Use Except Dry
Cleaning
SOC
Occupation
Designation
11-9020
Construction Managers
O
Page 213 of 292
-------
SOC
Occupation
Designation
17-2000
Engineers
O
17-3000
Drafters, Engineering Technicians, and Mapping Technicians
O
19-2031
Chemists
O
19-4000
Life, Physical, and Social Science Technicians
O
47-1000
Supervisors of Construction and Extraction Workers
O
47-2000
Construction Trades Workers
W
49-1000
Supervisors of Installation, Maintenance, and Repair Workers
O
49-2000
Electrical and Electronic Equipment Mechanics, Installers, and Repairers
W
49-3000
Vehicle and Mobile Equipment Mechanics, Installers, and Repairers
W
49-9010
Control and Valve Installers and Repairers
W
49-9020
Heating, Air Conditioning, and Refrigeration Mechanics and Installers
W
49-9040
Industrial Machinery Installation, Repair, and Maintenance Workers
W
49-9060
Precision Instrument and Equipment Repairers
W
49-9070
Maintenance and Repair Workers, General
W
49-9090
Miscellaneous Installation, Maintenance, and Repair Workers
W
51-1000
Supervisors of Production Workers
O
51-2000
Assemblers and Fabricators
W
51-4020
Forming Machine Setters, Operators, and Tenders, Metal and Plastic
W
51-6010
Laundry and Dry-Cleaning Workers
W
51-6020
Pressers, Textile, Garment, and Related Materials
W
51-6030
Sewing Machine Operators
O
51-6040
Shoe and Leather Workers
O
51-6050
Tailors, Dressmakers, and Sewers
O
51-6090
Miscellaneous Textile, Apparel, and Furnishings Workers
O
51-8020
Stationary Engineers and Boiler Operators
W
51-8090
Miscellaneous Plant and System Operators
W
51-9000
Other Production Occupations
W
W = worker designation
O = ONU designation
For dry cleaning facilities, due to the unique nature of work expected at these facilities and that different
workers may be expected to share among activities with higher exposure potential (e.g., unloading the
dry-cleaning machine, pressing/finishing a dry-cleaned load), EPA made different SOC code worker and
ONU assignments for this scenario. Table Apx B-2 summarizes the SOC codes with worker and ONU
designations used for dry cleaning facilities.
Table Apx B-2. SOCs with Worker and ONU Designations for Dry Cleaning Facilities
SOC
Occupation
Designation
41-2000
Retail Sales Workers
O
49-9040
Industrial Machinery Installation, Repair, and Maintenance Workers
W
49-9070
Maintenance and Repair Workers, General
W
49-9090
Miscellaneous Installation, Maintenance, and Repair Workers
W
51-6010
Laundry and Dry-Cleaning Workers
W
51-6020
Pressers, Textile, Garment, and Related Materials
W
51-6030
Sewing Machine Operators
O
51-6040
Shoe and Leather Workers
O
51-6050
Tailors, Dressmakers, and Sewers
O
51-6090
Miscellaneous Textile, Apparel, and Furnishings Workers
O
W = worker designation
O = ONU designation
Page 214 of 292
-------
After identifying relevant NAICS and SOC codes, EPA used BLS data to determine total employment
by industry and by occupation based on the NAICS and SOC combinations. For example, there are
110,640 employees associated with 4-di git NAICS 8123 (Drycleaning and Laundry Services) and SOC
51-6010 (Laundry andDry-C'leaning Workers).
Using a combination of NAICS and SOC codes to estimate total employment provides more accurate
estimates for the number of workers than using NAICS codes alone. Using only NAICS codes to
estimate number of workers typically result in an overestimate, because not all workers employed in that
industry sector will be exposed. However, in some cases, BLS only provide employment data at the 4-
digit or 5-digit NAICS level; therefore, further refinement of this approach may be needed (see next
step).
Step 3: Refining Employment Estimates to Account for lack of NAICS Granularity
The third step in EPA's methodology was to further refine the employment estimates by using total
employment data in the U.S. Census Bureau's (2015) SUSB. In some cases, BLS OES's occupation-
specific data are only available at the 4-digit or 5-digit NAICS level, whereas the SUSB data are
available at the 6-digit level (but are not occupation-specific). Identifying specific 6-digit NAICS will
ensure that only industries with potential NMP exposure are included. As an example, OES data are
available for the 4-digit NAIC S 8123 Drycleaning and Laundry Services, which includes the following
6-digit NAICS:
NAICS 812310 Coin-Operated Laundries and Dry cleaners,
NAICS 812320 Drycleaning and Laundry Services (except Coin-Operated),
NAICS 812331 Linen Supply, and
NAICS 812332 Industrial Launderers.
In this example, only NAICS 812320 is of interest. The Census data allow EPA to calculate employment
in the specific 6-digit NAICS of interest as a percentage of employment in the BLS 4-digit NAICS.
The 6-digit NAICS 812320 comprises 46 percent of total employment under the 4-digit NAICS 8123.
This percentage can be multiplied by the occupation-specific employment estimates given in the BLS
OES data to further refine our estimates of the number of employees with potential exposure.
Table_Apx B-3 illustrates this granularity adjustment for NAICS 812320.
Table Apx B-3. Estimated Number of Potentially Exposed Workers and ONUs under NAICS
812320
NAICS
SOC
Code
SOC
Description
Occupation
Designation
Employment
by SOC at 4-
digit NAICS
level
% of Total
Employment
Estimated
Employment by
SOC at 6-digit
NAICS level
8123
41-2000
Retail Sales
Workers
O
44,500
46.0%
20,459
8123
49-9040
Industrial
Machinery
Installation,
Repair, and
Maintenance
Workers
W
1,790
46.0%
823
Page 215 of 292
-------
NAICS
SOC
Code
SOC
Description
Occupation
Designation
Employment
by SOC at 4-
digit NAICS
level
% of Total
Employment
Estimated
Employment by
SOC at 6-digit
NAICS level
8123
49-9070
Maintenance and
Repair Workers,
General
W
3,260
46.0%
1,499
8123
49-9090
Miscellaneous
Installation,
Maintenance, and
Repair Workers
W
1,080
46.0%
497
8123
51-6010
Laundry and
Dry-Cleaning
Workers
W
110,640
46.0%
50,867
8123
51-6020
Pressers, Textile,
Garment, and
Related Materials
W
40,250
46.0%
18,505
8123
51-6030
Sewing Machine
Operators
O
1,660
46.0%
763
8123
51-6040
Shoe and Leather
Workers
O
Not Reported for this NAICS Code
8123
51-6050
Tailors,
Dressmakers, and
Sewers
O
2,890
46.0%
1,329
8123
51-6090
Miscellaneous
Textile, Apparel,
and Furnishings
Workers
O
0
46.0%
0
otal Potentially Exposed Employees
206,070
46.0%
94,740
Total Workers
157,020
46.0%
72,190
Total Occupational Non-Users
49,050
46.0%
22,551
Note: numbers may not sum exactly due to rounding.
W = worker
O = occupational non-user
Source: (U.S. BLS. 2016: U.S. Census Bureau. 2015)
Step 4: Estimating the Percentage of Workers Using NMP Instead of Other Chemicals
In the final step, EPA accounted for the market share by applying a factor to the number of workers
determined in Step 3. This accounts for the fact that NMP may be only one of multiple chemicals used
for the applications of interest. EPA did not identify market penetration data for any conditions of use.
In the absence of market penetration data for a given scenario, EPA assumed NMP may be used at up to
all sites and by up to all workers calculated in this method as a bounding estimate. This assumes a
market penetration of 100%. Market penetration is discussed for each scenario in the main body of this
report.
Step 5: Estimating the Number of Workers per Site
EPA calculated the number of workers and occupational non-users in each industry/occupation
combination using the formula below (granularity adjustment is only applicable where SOC data are not
available at the 6-digit NAICS level):
Page 216 of 292
-------
Number of Workers or ONUs in NAICS SOC (Step 2) x Granularity Adjustment Percentage (Step 3) =
Number of Workers or ONUs in the Industry Occupation Combination
EPA then estimated the total number of establishments by obtaining the number of establishments
reported in the U.S. Census Bureau's SUSB (U.S. Census Bureau. 2015) data at the 6-digit NAICS
level.
EPA then summed the number of workers and occupational non-users over all occupations within a
NAICS code and divided these sums by the number of establishments in the NAICS code to calculate
the average number of workers and occupational non-users per site.
Step 6: Estimating the Number of Workers and Sites for an Occupational Exposure Scenario
EPA estimated the number of workers and occupational non-users potentially exposed to NMP and the
number of sites that use NMP in a given scenario through the following steps:
6. A. Obtaining the total number of establishments by:
i. Obtaining the number of establishments from SUSB (U.S. Census Bureau. 2015) at the 6-
digit NAICS level (Step 5) for each NAICS code in the scenario and summing these
values, or
ii. Obtaining the number of establishments from the Toxics Release Inventory (TRI),
Discharge Monitoring Report (DMR) data, National Emissions Inventory (NEI), or
literature for the scenario.
6.B. Estimating the number of establishments that use NMP by taking the total number of
establishments from Step 6. A and multiplying it by the market penetration factor from Step
4.
6.C. Estimating the number of workers and occupational non-users potentially exposed to NMP
by taking the number of establishments calculated in Step 6.B and multiplying it by the
average number of workers and occupational non-users per site from Step 5.
Page 217 of 292
-------
B.2 Tank Truck and Railcar Loading and Unloading Release and
Inhalation Exposure Model Approach and Parameters
This appendix presents the modeling approach and model equations used in the Tank Truck and Railcar
Loading and Unloading Release and Inhalation Exposure Model. The model was developed through
review of relevant literature and consideration of existing EPA exposure models. The model approach is
a generic inhalation exposure assessment at industrial facilities that is applicable for any volatile
chemical with the following conditions of use:
Manufacture (loading of chemicals into containers),
Processing as a reactant/intermediate (unloading of chemicals),
Processing into formulation, mixture, or reaction products,
Repackaging, and
Other similar conditions of use at industrial facilities (e.g., industrial processing aid).
As an example, NMP at a manufacturing facility is expected to be packaged and loaded into a container
before distributing to another industrial processing or use site (e.g., formulation sites and sites using
NMP as a processing aid). At the industrial processing or use site, NMP is then unloaded from the
container into a process vessel before being incorporated into a mixture or otherwise processed/used.
For the model, EPA assumes NMP is unloaded into tank trucks and railcars and transported and
distributed in bulk. EPA also assumes the chemical is handled as a pure substance (100 percent
concentration).
Because NMP is volatile (vapor pressure above 0.01 torr at room temperature), fugitive emissions may
occur when NMP is loaded into or unloaded from a tank truck or railcar. Sources of these emissions
include:
Displacement of saturated air containing NMP as the container/truck is filled with liquid,
Emissions of saturated air containing NMP that remains in the loading arm, transfer hose, and
related equipment, and
Emissions from equipment leaks from processing units such as pumps, seals and valves.
These emissions result in subsequent exposure to workers involved in the transfer activity. The
following subsections address these emission sources.
B.2.1 Displacement of Saturated Air Inside Tank Trucks and Railcars
For screening-level assessments, EPA typically uses the EPA OAOPS AP-42 Loading Model to
conservatively assess exposure during container unloading activities (U.S. EPA 2015b). The model
estimates release to air from the displacement of air containing chemical vapor as a container/vessel is
filled with liquid (U.S. EPA 2015b). The model assumes the unloading activity displaces an air volume
equal to the size of the container, and that displaced air is either 50 percent or 100 percent saturated with
chemical vapor (U.S. EPA 2015b).
Industrial facilities often install and operate a vapor capture system and control device (or vapor
balancing system) for loading/unloading operations. As such, vapor losses from displacement of air is
likely mitigated by the use of such systems. Actual fugitive emissions are likely limited to any saturated
vapor that remain in the hose, loading arm, or related equipment after being disconnected from the truck
or railcar. This emission source is addressed in the next subsection.
Page 218 of 292
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B.2.2 Emissions of Saturated Air that Remain in Transfer Hoses/Loading Arm
After loading is complete, transfer hoses and/or loading arms are disconnected from tank trucks and
railcars. Saturated air containing the chemical of interest that remains in transfer equipment may be
released to air, presenting a source of fugitive emissions. The quantity of NMP released will depend on
concentration in the vapor and the volume of vapor in the loading arm/hose/piping.
TableApx B-4 presents the dimensions for several types of loading systems according to an OPW
Engineered Systems catalog (Systems. 2014). OPW Engineered Systems (2014) specializes in the
engineering, designing, and manufacturing of systems for loading and unloading a wide range of
materials including petroleum products, liquefied gases, asphalt, solvents, and hazardous and corrosive
chemicals. These systems include loading systems, swivel joints, instrumentation, quick and dry-
disconnect systems, and safety breakaways. Based on the design dimensions, the table presents the
calculated total volume of loading arm/system and assumes the volume of vapor containing NMP equals
the volume of the loading arm/system.
Chemical-specific transport container information was not available; therefore, EPA assumed a default
approach with the "central tendency" as tank truck loading/unloading and the "high-end" as railcar
loading/unloading. Central tendency and high-end approaches are based on the expected transfer arm
volume (and therefore, potential exposure concentration). To estimate the high-end transfer arm volume,
EPA calculated the 95th percentile of the OPW Engineered Systems loading arms volumetric data
resulting in a high-end value of 17.7 gallons. For the central tendency tank truck scenario, EPA assumed
a 2-inch diameter, 12-ft long transfer hose. This hose has a volume of 2.0 gallons.
Once the volume is known, the emission rate, Et (g/s), can be calculated as follows:
EquationApx B-l
_fxMWx3,786AxVhxXxVP
T ~ tdtsconnect x T x R x 3,600 x 760
Default values for Equation Apx B-l can be found in Table Apx B-5.
Table Apx B-4. Example Dimension and Volume of Loading Arm/Transfer System
Length of Loading
Arm/Connection (in)a
Volume, Vh (gal) b
OPW Engineered Systems Transfer Arm
2-inch
3-inch
4-inch
6-inch
2-
inch
3-
inch
4-
inch
6-
inch
Unsupported Boom-Type Bottom Loader
149.875
158.5
165.25
191.75
2.0
4.9
9.0
23.5
"A" Frame Loader M-32-F
153.75
159.75
164.5
NA
2.1
4.9
8.9
NA
"A" Frame Hose Loader AFH-32-F
180.75
192.75
197.5
NA
2.5
5.9
10.7
NA
CWH Series Counterweighted Hose Loader
NA
NA
309
NA
NA
NA
16.8
NA
Spring Balanced Hose Loader SRH-32-F
204.75
216.75
221.5
NA
2.8
6.6
12.0
NA
Spring Balanced Hose Loader LRH-32-F
NA
270
277.625
NA
NA
8.3
15.1
NA
Top Loading Single Arm Fixed Reach
201.75
207.75
212.5
NA
2.7
6.4
11.6
NA
Top Loading Scissor Type Arm
197.875
206.5
213.25
NA
2.7
6.3
11.6
NA
Supported Boom Arm B-32-F
327.375
335
341.5
NA
4.5
10.3
18.6
NA
Unsupported Boom Arm GT-32-F
215.875
224.5
231.25
NA
2.9
6.9
12.6
NA
Page 219 of 292
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Length of Loading
Arm/Connection (in)
a
Volume, Vh (gal) b
OPW Engineered Systems Transfer Arm
2-inch
3-inch
4-inch
6-inch
2-
inch
3-
inch
4-
inch
6-
inch
Slide Sleeve Arm A-32F
279
292.5
305.125
NA
3.8
9.0
16.6
NA
Hose without Transfer Arm
Hose (EPA judgment)
120
--
--
--
1.6
--
--
--
Source: (Systems. 2014)
a Total length includes length of piping, connections, and fittings.
b Calculated based on dimension of the transfer hose/connection, Vh = %r2L (converted from cubic inch to gallons).
TableApx B-5. Default Values for Calculating Emission Rate of n-Methylpyrrolidone from
Transfer/Loading Arm
Parameter
Parameter Description
Default Value
Unit
Et
Emission rate of chemical from transfer/loading
system
Calculated from model
equation
g/s
f
Saturation factor3
1
dimensionless
MW
Molecular weight of the chemical
99.1
g/mol
vh
Volume of transfer hose
See Table Apx B-4
gallons
r
Fill rate3
2 (tank truck)
1 (railcar)
containers/hour
tdisconnect
Time to disconnect hose/couplers (escape of
saturated vapor from disconnected hose or transfer
arm into air)
0.25
hour
X
Vapor pressure correction factor
1
dimensionless
VP
Vapor pressure of the pure chemical
0.345
ton-
T
Temperature
298
IC
R
Universal gas constant
82.05
atm-cm3/gmol-
K
a Saturation factor and fill rate values are based on established EPA release and inhalation exposure assessment
methodologies (U.S. EPA. 2015b).
B.2.3 Emission from Leaks
During loading/unloading activities, emissions may also occur from equipment leaks from valves,
pumps, and seals. Per EPA's Chapter 5: Petroleum Industry of AP-42 (U.S. EPA. 2015a) and EPA's
Protocol for Equipment Leak Emission Estimates (U.S. EPA. 19951 the following equation can be used
to estimate emission rate El, calculated as the sum of average emissions from each process unit:
EquationApx B-2
Z 1,000
(^x^racxJV)x
Parameters for calculating equipment leaks using Equation Apx B-2 can be found in Table Apx B-6.
Page 220 of 292
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TableApx B-6. Parameters for Calculating Emission Rate of n-Methylpyrrolidone from
Equipment Leaks
Parameter
Parameter Description
Default Value
Unit
El
Emission rate of chemical from equipment leaks
Calculated from
model equation
g/s
Fa
Applicable average emission factor for the
equipment type
See Table Apx B-7
kg/hour-source
WFtoc
Average weight fraction of chemical in the stream
1
dimensionless
N
Number of pieces of equipment of the applicable
equipment type in the stream
See Table Apx B-7
Source
To estimate emission leaks using this modeling approach, EPA modeled a central tendency loading rack
scenario using tank truck loading/unloading and a high-end loading rack scenario using railcar
loading/unloading as discussed in Appendix A.l. EPA used engineering judgment to estimate the type
and number of equipment associated with the loading rack in the immediate vicinity of the loading
operation. EPA assumes at least one worker will be near the loading rack during the entire duration of
the loading operation.
Table Apx B-7 presents the average emission factor for each equipment type, based on the synthetic
organic chemical manufacturing industry (SOCMI) emission factors as provided by EPA's 1995
Protocol (U.S. EPA 19951 and the likely number of pieces of each equipment used for each chemical
loading/unloading activity, based on EPA's judgment. Note these emission factors are for emission rates
of total organic compound emission and are assumed to be applicable to NMP. In addition, these factors
are most valid for estimating emissions from a population of equipment and are not intended to be used
to estimate emissions for an individual piece of equipment over a short period of time.
Table Apx B-7. Default Values for Fa and N
SOCMI Emission
Number of
Number of
Equipment Type
Service
Factor, Fa (kg/hour-
source) a
Equipment, N
(central tendency)
Equipment, N
(high-end)
Valves
Gas
Light liquid
Heavy liquid
0.00597
0.00403
0.00023
3 (gas)
5 (heavy liquid)
3 (gas)
10 (heavy liquid)
Pump seals b
Light liquid
Heavy liquid
0.0199
0.00862
--
--
Compressor seals
Gas
0.228
--
--
Pressure relief valves
Gas
0.104
1
1
Connectors
All
0.00183
2
3
Open-ended lines
All
0.0017
--
--
Sampling connections
All
0.015
2
3
Source: (U.S. EPA. 1995)
a SOCMI average emission factors for total organic compounds from EPA's 1995 Protocol (U.S. EPA. 1995). "Light liquid"
is defined as "material in a liquid state in which the sum of the concentration of individual constituents with a vapor
pressure over 0.3 kilopascals (kPa) at 20 °C is greater than or equal to 20 weight percent". "Heavy liquid" is defined as "not
in gas/vapor service or light liquid service." Since NMP has a vapor pressure of 0.345 mmHg (0.046 kPa) at 25 °C, EPA
modeled NMP liquid as a light liquid.
b The light liquid pump seal factor can be used to estimate the leak rate from agitator seals.
Page 221 of 292
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EPA assumed the following equipment are used in loading racks for the loading/unloading of tank
trucks and railcars. FigureApx B-l illustrates an example tank truck and unloading rack equipment.
Tank Truck Loading/Unloading:
o Liquid Service:
¦ Four valves (modeled as valves in heavy liquid service),
¦ One safety relief valve (modeled as valve in heavy liquid service),
¦ One bleed valve or sampling connection, and
¦ One hose connector,
o Vapor Service:
¦ Three valves (modeled as valves in gas service),
¦ One pressure relief valve,
¦ One bleed valve (modeled as a sampling connection), and
¦ One hose connector.
Railcar Loading/Unloading:
o Liquid Service: EPA assumed, for the high-end scenario, two parallel liquid service lines,
each using the same equipment as assumed for tank trucks.
¦ Eight valves (modeled as valves in heavy liquid service),
¦ Two safety relief valves (modeled as valve in heavy liquid service),
¦ Two bleed valves or sampling connections, and
¦ Two transfer arm connectors.
o Vapor Service: EPA assumed a single line in vapor service with the same equipment as
assumed for tank trucks.
¦ Three valves (modeled as valves in gas service),
¦ One pressure relief valve,
¦ One bleed valve (modeled as a sampling connection), and
¦ One transfer arm connector.
Vaporservice line
Liquid service line
w
Figure Apx B-l. Illustration of Transfer Lines Used During Tank Truck Unloading and
Associated Equipment Assumed by EPA
Page 222 of 292
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B.2.3.1 Exposure Estimates
The vapor generation rate, G, or the total emission rate over time, can be calculated by aggregating
emissions from all sources:
During the transfer period, emissions are only due to leaks, with emission rate G = EL.
After transfer, during the disconnection of the hose(s), emissions are due to both leaks and
escape of saturated vapor from the hose/transfer arm with emission rate G = ET + EL.
The vapor generation rate can then be used with the EPA/OPPTMass Balance Inhalation Model to
estimate worker exposure during loading/unloading activities (U.S. EPA. 2015b). The EPA/OPPT Mass
Balance Inhalation Model estimates the exposure concentration using EquationApx B-3 and the default
parameters found in TableApx B-8 (U.S. EPA 2015b). TableApx B-9 presents exposure estimates for
NMP using this approach. These estimates assume one unloading/loading event per day and NMP is
loaded/unloaded at 100% concentration. The loading operation occurs in an outdoor area with minimal
structure, with wind speeds of 9 mph (central tendency) or 5 mph (high-end).
Equation Apx B-3
r
_ ^V
m ~ v
vm
Table Apx B-8. Parameters for Calculating Exposure Concentration Using the EPA/OPPT Mass
Balance Model
Parameter
Parameter Description
Default Value
Unit
cm
Mass concentration of chemical in air
Calculated from model equation
mg/m3
Cv
Volumetric concentration of chemical
in air
Calculated as the lesser of:
170,000xTxG 1,000,000 XXXVP
MWxQxk OT 760
ppm
T
Temperature of air
298
K
G
Vapor generation rate
El during transfer period
Et+El after transfer/during
disconnection of hose/transfer arm
g/s
MW
Molecular weight of the chemical
99.1
g/mol
Q
Outdoor ventilation rate
237,600 (central tendency)
26,400 X (60 X 528Q) (high-end)
ft3/min
vz
Air speed
440
ft/min
k
Mixing factor
0.5
dimensionless
X
Vapor pressure correction factor
1
dimensionless
VP
Vapor pressure of the pure chemical
0.345
torr
Vm
Molar volume
24.45 @ 25°C, 1 atm
L/mol
EPA also calculated acute and 8-hour TWA exposures as shown in Equation Apx B-4 and
Equation Apx B-5, respectively. The acute TWA exposure is the weighted average exposure during the
entire exposure duration per shift, accounting for the number of loading/unloading events per shift. The
8-hour TWA exposure is the weighted average exposure during an entire 8-hour shift, assuming zero
exposures during the remainder of the shift. EPA assumed one container is loaded/unloaded per shift:
one tank truck per shift for the central tendency scenario and one railcar per shift for the high-end
scenario.
Page 223 of 292
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EquationApx B-4
(a
Acute TWA =
m(leak only)
X Qlevent tdisconnect) ('pm(leak
and hose) ^ ^disconnect
))
x iV,
cont
h
shift
c..
Equation Apx B-5
8 - /ir 7W4 =
Where:
Cm(leak only)
Cm(leak and hose)
hevent
hshift =
tdisconnect
Ncont =
m(leak only)
X Qlevent ^disconnect) {pm(leak i
and hose) ^ ^disconnect
))
x iV,
cont
Airborne concentration (mass-based) due to leaks during unloading while
hose connected (mg/m3),
Airborne concentration (mass-based) due to leaks and displaced air during
hose disconnection (mg/m3),
Exposure duration of each loading/unloading event (hour/event);
calculated as the inverse of the fill rate, r : 0.5 hour/event for tank trucks
and 1 hour/event for railcars,
Exposure duration during the shift (hour/shift); calculated as hevent X Ncont-
0.5 hour/shift for tank trucks and 1 hour/shift for railcars,
Time duration to disconnect hoses/couplers (during which saturated vapor
escapes from hose into air) (hour/event), and
Number of containers loaded/unloaded per shift (event/shift); assumed one
tank truck per shift for central tendency scenario and one railcar per shift
for high-end scenario.
TableApx B-9. Calculated Emission Rates and Resulting Exposures of n-Methylpyrrolidone
from the Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure
Model
Scenario
El
(g/s)
Et
(g/s)
El +
Et
(g/s)
cm
(leaks
only)
(mg/m3)
cm
(leaks and hose
vapor)
(mg/m3)
Acute
TWA
(mg/m3)a
8-hour
TWA
(mg/m3)
Central Tendency
0.044
1.52E-05
0.044
0.76
0.76
0.76
0.047
High-End
0.049
1.37E-04
0.049
1.52
1.53
1.52
0.19
a Acute TWA exposure is a 0.5-hour TWA exposure for the central tendency scenario and a 1-hour TWA exposure for the
high-end scenario.
B.2.4 Sensitivity of Model Parameters
The NMP weight fraction, average emission factor, volume of transfer hose, and tank truck/ railcar fill
rate have a direct relationship with the 8-hr TWA concentrations. The values used for these parameters
were all fixed based on the available data. The NMP weight fraction, average emission factor, and fill
rate have a greater impact on exposure concentration than the volume of transfer hose.
The time to disconnect the transfer hose and outdoor ventilation rate have an inverse relationship with
the 8-hr TWA concentrations. The values used for these parameters were fixed based on the available
data. The outdoor ventilation rate has a greater impact on exposure concentration than the time to
disconnect the transfer hose.
Page 224 of 292
-------
In summary, NMP weight fraction, average emission factor, fill rate, and the outdoor ventilation rate all
have similar impact on the 8-hr TWA concentrations in terms of magnitude.
Page 225 of 292
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B.3 Drum Loading and Unloading Release and Inhalation Exposure
Model Approach and Parameters
This appendix presents the approach for central tendency and high-end inhalation exposure estimation
for the loading and unloading of pure (100%) NMP from 55-gallon drums. This approach applies a
stochastic modeling approach to the EPA OAOPS AP-42 Loading Model, which estimates air releases
during container loading and unloading, and the EPA OPPTMass Balance Model, which estimates
inhalation exposures resulting from air releases (U.S. EPA. 2015b).
This approach is intended to assess air releases and associated inhalation exposures associated with
indoor container loading scenarios at industrial and commercial facilities. Inhalation exposure to
chemical vapors is a function of the chemical's physical properties, ventilation rate of the container
loading area, type of loading method, and other model parameters. While physical properties are fixed
for a chemical, some model parameters, such as ventilation rate (Q), mixing factor (k), and vapor
saturation factor (f), are expected to vary from one facility to another. This approach addresses
variability for these parameters using a Monte Carlo simulation.
An individual model input parameter could either have a discrete value or a distribution of values. EPA
assigned statistical distributions based on available literature data or engineering judgment to address the
variability in ventilation rate (Q), mixing factor (k), vapor saturation factor (f), and exposed working
years per lifetime (WY). A Monte Carlo simulation (a type of stochastic simulation) was conducted to
capture variability in the model input parameters. The simulation was conducted using the Latin
hypercube sampling method in @Risk Industrial Edition, Version 7.0.0 (Palisade, Ithaca, New York).
The Latin hypercube sampling method is a statistical method for generating a sample of possible values
from a multi-dimensional distribution. Latin hypercube sampling is a stratified method, meaning it
guarantees that its generated samples are representative of the probability density function (variability)
defined in the model. EPA performed 100,000 iterations of the model to capture the range of possible
input values, including values with low probability of occurrence.
From the distribution resulting from the Monte Carlo simulation, EPA selected the 95th and 50th
percentile values to represent a high-end exposure and central tendency exposure level respectively. The
statistics were calculated directly in @Risk. The following subsections detail the model design equations
and parameters used for Inhalation exposure estimates.
B.3.1 Model Air Release and Inhalation Exposure Equations
The average vapor generation rate needed to estimate inhalation exposure concentration with
the EPA OPPT Mass Balance Model is calculated from the following EPA OAOPS AP-42 Loading
Model equation for vapor generation rate.
Page 226 of 292
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EquationApx B-6
VP
f x MW x (3,785.4 xVc)xrxXx^
G ~ 3,600 XT x R
Where:
G = Average vapor generation rate [g/s]
F = Saturation factor [Dimensionless]
MW = Molecular weight of chemical [g/mol]
Vc = Container volume [gallon]
r = Container loading/unloading rate [number of containers/hr]
X = Vapor pressure correction factor [ Dimensionless], assumed equal to weight
fraction of component
VP = Vapor pressure (at temperature, T) [mmHg]
T = Temperature [K]
R = Universal gas constant [atm-cm3/mol-K]
The EPA/OPPTMass Balance Model uses Equation Apx B-7 to calculate the volumetric concentration
of the chemical in air, using the vapor generation rate calculated above.
Equation Apx B-7
170,000 xTxG
Cy ~ MW xQxk
Where:
Cv
= Volumetric concentration of chemical vapor in air [ppm]
T
= Temperature [K]
G
= Average vapor generation rate [g/s]
MW
= Molecular weight of chemical [g/mol]
Q
= Ventilation rate [ft3/min]
K
= Mixing factor [Dimensionless]
The EPA/OPPT Mass Balance Model then uses EquationApx B-8 to estimate mass concentration of the
chemical vapor in air (mg/m3):
Equation Apx B-8
r =
CvxMW
Where:
Cm
Cv
MW
vm
Mass concentration of chemical vapor in air [mg/m3]
Volumetric concentration of chemical vapor in air [ppm]
Molecular Weight of chemical [g/mol]
Molar volume [L/mol]
Page 227 of 292
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The estimated mass concentration in air is the short-term inhalation exposure concentration. This short-
term exposure is subsequently used in EquationApx B-9 to estimate the 8-hour TWA exposure
concentration.
Equation Apx B-9
day
Where:
C 8-hr
Contaminant concentration in air (8-hour TWA) [mg/m3]
Mass concentration of chemical vapor in air [mg/m3]
Total unloading time for all drums per day [hr/day]
r
-unload
B.3.2 Number of Containers and Short-Term Exposure Duration Equations
The short-term exposure duration, tunioad, is the length of time workers spend unloading NMP from
drums in a given day. To determine the exposure duration, the number of drums loaded or unloaded at a
given site per day is first calculated with Equation Apx B-10.
Equation Apx B-10
To calculate the production volume in gallons of NMP per year for Equation Apx B-10, the production
volume in pounds per year (included in Table Apx B-10) is converted with Equation Apx B-l 1.
Equation Apx B-ll
dvinri_sit6_day T/ s/ K1 w nn
vc x l*sites x uu
Where:
Vc
Nsites
OD
N drumsiteday
P V gal/yr
Number of drums loaded / unloaded per site per day [drum/site-day]
Production volume for the scenario in gallons of NMP per year [gal/yr]
Volume of container [gallons/drum]
Number of sites [sites]
Operating days [day/yr]
PVgal/yr ~
PVlb/yr x 453.6 jjj
Where:
P V gal/yr
PVlb/yr
P
Production volume for the scenario in gallons of NMP per year [gal/yr]
Production volume for the scenario in pounds of NMP per year [lb/yr]
density of NMP [g/cm3]
Page 228 of 292
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Finally, EPA determined the short-term exposure duration using the number of drums calculated in
EquationApx B-10.
EquationApx B-12
^ _ N'drum_site_day
tunload ~
r
Where:
tunioad = Total unloading time for all drums per day [hr/site-day]
Ndram site day = Number of drums loaded / unloaded per site per day [drum/site-day]
r = Drum fill rate [drums/hr]
B.3.3 Model Input Parameters
Table Apx B-10 summarizes the model parameters and their values for the Monte Carlo simulation. High-
end and central tendency exposure are estimated by selecting the 50th and 95th percentile values from the
output distribution.
Page 229 of 292
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Table Apx B-10. Summary of Parameter Values and Distributions Used in the Inhalation Exposure Model
Constant Model Parameter Values
Variable Model Parameter Values
Input Parameter
Symbol
Unit
Value
Lower
Bound
Upper
Bound
Mode
Distribution
Type
Rational / Basis
Molecular Weight
MW
g/mol
99.1
Physical property
Vapor Pressure at
298 K
VP
mmHg
0.345
Physical property
Molar Volume at
298 K
Vm
L/mol
24.46
Physical constant
Gas Constant
R
atm-cm3/mol-K
82.05
Temperature
T
K
298
Process parameter
Vapor Pressure
Correction Factor
X
Dimensionless
1
Process parameter
Mole Fraction of
Chemical
Xi
Dimensionless
1
Process parameter,
refer to Appendix A
for additional
information
Production
Volume
PVlb/yr
lb/yr
Manufacture and Repackaging:
161,000,000
Chemical Processing and Formulation:
80,500,000
Recycling and Disposal:
34,227,218
Process parameter,
refer to Appendix A
for additional
information
Number of sites
Nsites
sites
Manufacture and Repackaging:
33
Chemical Processing and Formulation:
94
Recycling and Disposal:
24
Process parameter,
refer to Appendix A
for additional
information
Operating Days
OD
day/yr
250
Process parameter,
based on schedule of
five days per week and
50 weeks per year
Page 230 of 292
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Constant Model Parameter Values
Variable Model Parameter Values
Input Parameter
Symbol
Unit
Value
Lower
Bound
Upper
Bound
Mode
Distribution
Type
Rational / Basis
Value is determined
by the selected
Container Volume
Vc
Gallons/drum
55
container type for
given exposure
scenario (U.S. EPA.
2015b)
Container
Loading/Unloading
Rate
Value is determined
r
Containers / hr
20
by the selected
container type (U.S.
EPA. 2015b)
Ventilation Rate
Q
ft3/min
500
10,000
3,000
Triangular
U.S. EPA (2015b)
Mixing Factor
k
Dimensionless
0.1
1
0.5
Triangular
indicates:
1. General ventilation
rates in industry
ranges from a low of
500 ft3/min to over
10,000 ft3/min; a
central tendency value
is 3,000.
Saturation Factor
f
Dimensionless
0.5
1.45
0.5
Triangular
2. Mixing Factor
ranges from 0.1 to 1.
3. Saturation factor
ranges from 0.5 for
submerged loading to
1.45 for splash
loading.
Page 231 of 292
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Input Parameter
Symbol
Unit
Constant Model Parameter Values
Variable Model Parameter Values
Rational / Basis
Underlying
distribution of these
parameters are not
known, EPA assigned
triangular
distributions, since
triangular distribution
requires least
assumptions and is
completely defined by
range and mode of a
parameter.
Value
Lower
Bound
Upper
Bound
Mode
Distribution
Type
Not Applicable
Page 232 of 292
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B.3.4 Monte Carlo Simulation Results
The probability density function for the short-term exposure concentration values resulting from the
simulation are depicted in FigureApx B-2. Specifically, EPA used the 50th and 95th percentile short-
term exposure concentration values to represent central tendency and high-end inhalation exposure
potential.
Short-Term Concentration
>
<_>
c
0)
3
O"
0)
CD
>
_ro
a;
OL
25%
20%
15%
10%
5%
0%
50th Percentile Value
95th Percentile Value =
1.65 mg/m3
5.85 mg/m3
L
r
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 10
Short-Term Concentration (mg/m3)
Figure Apx B-2. Graphical Probability Density Function of Monte Carlo Simulation Results
The 50th and 95th percentile short-term exposure concentration values are the same for all conditions of
use. However, the 8-hour TWA exposure concentration values vary based on the production volume and
number of sites for each scenario. The short-term and 8-hour TWA inhalation exposure concentrations
are summarized for each scenario for which this model was used in Table Apx B-l 1.
Table Apx B-ll. Drum Loading and Unloading Inhalation Exposure Simulation Results
Occupational
Exposure Scenario
8-hour TWA Exposure
(mg/m3)
Short-Term Exposure
(mg/m3)
Number of Drums
per Site per Day
(drums/site-day)
Short-Term
Exposure
Duration
(hr/day)
50th
Percentile
95th
Percentile
50th
Percentile
95th
Percentile
Manufacturing
0.427
1.510
1.65
5.85
41.3
2.064
Repackaging
0.427
1.510
1.65
5.85
41.3
2.064
Chemical
Processing,
Excluding
Formulation
0.075
0.265
1.65
5.85
7.3
0.362
Formulation
0.075
0.265
1.65
5.85
7.3
0.362
Page 233 of 292
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Occupational
Exposure Scenario
8-hour TWA Exposure
(mg/m3)
Short-Term Exposure
(mg/m3)
Number of Drums
per Site per Day
(drums/site-day)
Short-Term
Exposure
Duration
(hr/day)
50th
Percentile
95th
Percentile
50th
Percentile
95th
Percentile
Recycling and
Disposal
0.125
0.441
1.65
5.85
12.1
0.603
B.3.1 Sensitivity of Model Parameters
The vapor saturation factor, container fill rate, and NMP weight fraction all have direct linear
relationships with the 8-hr TWA concentrations. The values used for container fill rate, NMP weight
fraction, and time to unload a container were fixed based on the available data. EPA used a triangular
distribution based on available literature data or engineering judgment to address the variability in vapor
saturation factor. Generally, these parameters all have a similar impact on the exposure concentrations.
The number of operating days, ventilation rate, and mixing factor have indirect linear relationships with
the 8-hr TWA concentrations. The values used for number of operating days were fixed based on the
available data. EPA used triangular distributions based on available literature data or engineering
judgment to address the variability in ventilation rate, mixing factor, and vapor saturation factor.
Generally, these parameters all have a similar impact on the exposure concentrations.
In summary, vapor saturation factor, container fill rate, NMP weight fraction, number of operating days,
ventilation rate, and mixing factor have similar impact on the exposure concentrations in terms of
magnitude.
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B.4 Brake Servicing Near-Field/Far-Field Inhalation Exposure Model
Approach and Parameters
This appendix presents the modeling approach and model equations used in the Brake Servicing Near-
Field/Far-Field Inhalation Exposure Model. The model was developed through review of the literature
and consideration of existing EPA exposure models. This model uses a near-field/far-field approach
(AIHA. 2009). where an aerosol application located inside the near-field generates a mist of droplets,
and indoor air movements lead to the convection of the droplets between the near-field and far-field.
Workers are assumed to be exposed to NMP droplet concentrations in the near-field, while occupational
non-users are exposed at concentrations in the far-field.
The model uses the following parameters to estimate exposure concentrations in the near-field and far-
field:
Far-field size,
Near-field size,
Air exchange rate,
Indoor air speed,
Concentration of NMP in the aerosol formulation,
Amount of degreaser used per brake j ob,
Number of degreaser applications per brake job,
Time duration of brake j ob,
Operating hours per week, and
Number of jobs per work shift.
An individual model input parameter could either have a discrete value or a distribution of values. EPA
assigned statistical distributions based on available literature data. A Monte Carlo simulation (a type of
stochastic simulation) was conducted to capture variability in the model input parameters. The
simulation was conducted using the Latin hypercube sampling method in @Risk Industrial Edition,
Version 7.0.0. The Latin hypercube sampling method is a statistical method for generating a sample of
possible values from a multi-dimensional distribution. Latin hypercube sampling is a stratified method,
meaning it guarantees that its generated samples are representative of the probability density function
(variability) defined in the model. EPA performed the model at 100,000 iterations to capture the range of
possible input values (i.e., including values with low probability of occurrence).
Model results from the Monte Carlo simulation are presented as 95th and 50th percentile values. The
statistics were calculated directly in @Risk. The 95th percentile value was selected to represent high-end
exposure level, whereas the 50th percentile value was selected to represent central tendency exposure
level. The following subsections detail the model design equations and parameters for the brake
servicing model.
B.4.1 Model Design Equations
In brake servicing, the vehicle is raised on an automobile lift to a comfortable working height to allow
the worker (mechanic) to remove the wheel and access the brake system. Brake servicing can include
inspections, adjustments, brake pad replacements, and rotor resurfacing. These service types often
involve disassembly, replacement or repair, and reassembly of the brake system. Automotive brake
cleaners are used to remove oil, grease, brake fluid, brake pad dust, or dirt. Mechanics may occasionally
use brake cleaners, engine degreasers, carburetor cleaners, and general purpose degreasers
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interchangeably (CARB, 2000). Automotive brake cleaners can come in aerosol or liquid form (CARB.
2000): this model estimates exposures from aerosol brake cleaners (degreasers).
FigureApx B-3 illustrates the near-field/far-field modeling approach as it was applied by EPA to brake
servicing using an aerosol degreaser. The application of the aerosol degreaser immediately generates a
mist of droplets in the near-field, resulting in worker exposures at aNMP concentration Cnf. The
concentration is directly proportional to the amount of aerosol degreaser applied by the worker, who is
standing in the near-field-zone (i.e., the working zone). The volume of this zone is denoted by Vnf. The
ventilation rate for the near-field zone (Qnf) determines how quickly NMP dissipates into the far-field
(i.e., the facility space surrounding the near-field), resulting in occupational bystander exposures to
NMP at a concentration Cff. Vff denotes the volume of the far-field space into which the NMP
dissipates out of the near-field. The ventilation rate for the surroundings, denoted by Qff, determines
how quickly NMP dissipates out of the surrounding space and into the outside air.
Figure Apx B-3. The Near-Field/Far-Field Model as Applied to the Brake Servicing Near-
Field/Far-Field Inhalation Exposure Model
In brake servicing using an aerosol degreaser, aerosol degreaser droplets enter the near-field in non-
steady "bursts," where each burst results in a sudden rise in the near-field concentration. The near-field
and far-field concentrations then decay with time until the next burst causes a new rise in near-field
concentration. Based on site data from automotive maintenance and repair shops obtained by CARB
(CARB. 2000) for brake cleaning activities and as explained in Sections B.4.2.5 and B.4.2.9 below, the
model assumes a worker will perform an average of 11 applications of the degreaser product per brake
job with five minutes between each application and that a worker may perform one to four brake jobs
per day each taking one hour to complete. EPA modeled two scenarios: one where the brake jobs
occurred back-to-back and one where brake jobs occurred one hour apart. In both scenarios, EPA
assumed the worker does not perform a brake job, and does not use the aerosol degreaser, during the
first hour of the day.
EPA denoted the top of each five-minute period for each hour of the day (e.g., 8:00 am, 8:05 am, 8:10
am, etc.) as tm.n- Here, m has the values of 0, 1, 2, 3, 4, 5, 6, and 7 to indicate the top of each hour of the
day (e.g., 8 am, 9 am, etc.) and n has the values of 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, and 11 to indicate the top
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of each five-minute period within the hour. No aerosol degreaser is used, and no exposures occur, during
the first hour of the day, to.o to to.ii (e.g., 8 am to 9 am). Then, in both scenarios, the worker begins the
first brake job during the second hour, ti.o (e.g., 9 am to 10 am). The worker applies the aerosol
degreaser at the top of the second 5-minute period and each subsequent 5-minute period during the hour-
long brake job (e.g., 9:05 am, 9:10 am,... 9:55 am). In the first scenario, the brake jobs are performed
back-to-back, if performing more than one brake job on the given day. Therefore, the second brake job
begins at the top of the third hour (e.g., 10 am), and the worker applies the aerosol degreaser at the top
of the second 5-minute period and each subsequent 5-minute period (e.g., 10:05 am, 10:10 am,... 10:55
am). In the second scenario, the brake jobs are performed every other hour, if performing more than one
brake job on the given day. Therefore, the second brake job begins at the top of the fourth hour (e.g., 11
am), and the worker applies the aerosol degreaser at the top of the second 5-minute period and each
subsequent 5-minute period (e.g., 11:05 am, 11:10 am,... 11:55 am).
In the first scenario, after the worker performs the last brake job, the workers and occupational non-users
(ONUs) continue to be exposed as the airborne concentrations decay during the final three to six hours
until the end of the day (e.g., 4 pm). In the second scenario, after the worker performs each brake job,
the workers and ONUs continue to be exposed as the airborne concentrations decay during the time in
which no brake jobs are occurring and then again when the next brake job is initiated. In both scenarios,
the workers and ONUs are no longer exposed once they leave work.
Based on data from CARB (CARB. 2000). EPA assumes each brake job requires one 14.4-oz can of
aerosol brake cleaner as described in further detail below. The model determines the application rate of
NMP using the weight fraction of PCE in the aerosol product. EPA uses a uniform distribution of weight
fractions for NMP based on facility data for the aerosol products in use (CARB. 2000).
The model design equations are presented below in EquationApx B-13 through EquationApx B-33.
Near-Field Mass Balance
Equation Apx B-13
dCjyp
Vnf ^ = CffQnf ~ CnfQnf
Far-Field Mass Balance
Equation Apx B-14
dCFF
^FF~dt~ = ^NF^NF ~ ^ffQnf ~ CffQff
Where:
Vnf =
Near-field volume
Vff =
Far-field volume
Qnf =
Near-field ventilation rate
Qff =
Far-field ventilation rate
Cnf =
Average near-field concentration
Cff =
Average far-field concentration
t
Elapsed time
Solving Equation Apx B-13 and Equation Apx B-14 in terms of the time-varying concentrations in the
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near-field and far-field yields EquationApx B-15 and EquationApx B-16, which EPA applied to each
of the 12 five-minute increments during each hour of the day. For each five-minute increment, EPA
calculated the initial near-field concentration at the top of the period (tm,n), accounting for both the burst
of NMP from the degreaser application (if the five-minute increment is during a brake job) and the
residual near-field concentration remaining after the previous five-minute increment (tm,n-i; except
during the first hour and tm,o of the first brake job, in which case there would be no residual NMP from a
previous application). The initial far-field concentration is equal to the residual far-field concentration
remaining after the previous five-minute increment. EPA then calculated the decayed concentration in
the near-field and far-field at the end of the five-minute period, just before the degreaser application at
the top of the next period (tm,n+i). EPA then calculated a 5-minute TWA exposure for the near-field and
far-field, representative of the worker's and ONUs' exposures to the airborne concentrations during each
five-minute increment using Equation Apx B-25 and Equation Apx B-26. The k coefficients
(Equation Apx B-17 through Equation Apx B-20) are a function of the initial near-field and far-field
concentrations, and therefore are re-calculated at the top of each five-minute period. In the equations
below, where the subscript "m, n-1" is used, if the value of n-1 is less than zero, the value at "m-1, 11"
is used and where the subscript "m, n+1" is used, if the value of n+1 is greater than 11, the value at
"m+1, 0" is used.
Equation Apx B-15
Equation Apx B-16
Equation Apx B-17
/Cl £
1>Lm,n
CNf t ±1 C^l t ky t
iyir>Lm,n+1 v z>Lm,n J
Cff t X1 =fet eXlt-k4t e^2t)
rr>Lm,n+1 v 3,im,n ^>Lm,n J
QnF {^FF.O^m.n) ~ CnF,0 (*771,71)) ^¦2^NF^NF,o(j:m,n}
m'n Vnf(A1 A2)
Equation Apx B-18
QnF (CwF,o(tm,7i) CfF,0 + ^l^NF^NF.oiSm.n)
2,tm'n VNF(Xl A2)
Equation Apx B-19
(QnF + ^1 Vnf)(.QnF (CFF,o(tm,n) ~ ^NF,0 (*771,71)) ~ ^2 ^NF^NF.O
3,tm'n Qnf^nf(^i ^2)
Equation Apx B-20
(.QnF + ^2Vnf)(.QnF (CjVF,o(*77i,7i) ~ ^FF.O (*m,7i)) + ^1 ^NfCjVF.O (*m,7i))
4'tm'n Qnf^nf(^i ^2)
EquationA
= 0.5
px B-21
/Qnf^ff + Vnf(Qnf + Qff)\ 1/Qnf^ff + Vnf(Qnf + Qff)\ _ . {QnfQff\
\ ^NF^FF ) J \ VnF^FF J ^ ^NF^FF '
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EquationA
X2 = 0.5
px B-22
(Qnf^ff + Vnf(Qnf + Qff)\ 1/Qnf^ff + Vnf(Qnf + Qff)\ _ . /Q/vfQff\
\ ^/VF^FF / J\ ^/VF^FF / V ^/VF^FF '
EquationApx B-23
( 0, m = 0
CNF,o{pm,n) j Z'1,000+ CWF(tm n_1) , n > 0 /or all m where brake job
V wVF ^ 9 '
Equation Apx B-24
r 0, m = 0
FF,o\tm,n) {CFF(trriin^1), for all n where m > 0
occurs
Equation Apx B-25
C,
NF, 5-min TWA, tn
fk fc \ (k k N
1-tm,n-l CX,U | ^t-, j _ / Um.n-l £Aiti | 2tm,n-l
K K h J \ ^ 1
^2
Equation Apx B-26
l ^t-, | _ (^,tm,n-l £A1t1 | \
_\ ^2 ) \ h h J
CfF, 5-min TWA, tm 7 7
r2 rl
After calculating all near-field/far-field 5-minute TWA exposures (i.e., CWF 5.min TWA tmn and
Cpp 5.min TWA tmn) for each five-minute period of the work day, EPA calculated the near-field/far-field
8-hour TWA concentration and 1-hour TWA concentrations following the equations below:
Equation Apx B-27
n Sm=0 2n=o[^NF,5-min TWA,tmn X 0.0833 hr\
^NF, 8-hr TWA = !
Equation Apx B-28
1jm=o1jn=o[^FF,5-mmTWA,tmn X 0.0833 /ir]
NF, 8-hr TWA =
8 hr
Equation Apx B-29
1m=o[^NF,5-min TWA,tmiTl X 0.0833 hr]
NF, 1-hr TWA =
1 hr
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EquationApx B-30
n _ Tm=o[^FF,5-mmTWA,tmin X 0-0^33 hr\
CFF, 1-hr TWA =
EPA calculated rolling 1-hour TWA's throughout the workday and the model reports the maximum
calculated 1-hour TWA.
To calculate the mass transfer to and from the near-field, the free surface area (FSA) is defined to be the
surface area through which mass transfer can occur. The FSA is not equal to the surface area of the
entire near-field. EPA defined the near-field zone to be a hemisphere with its major axis oriented
vertically, against the vehicle, and aligned through the center of the wheel (see FigureApx 7). The top
half of the circular cross-section rests against, and is blocked by, the vehicle and is not available for
mass transfer. The FSA is calculated as the entire surface area of the hemisphere's curved surface and
half of the hemisphere's circular surface per EquationApx B-31, below:
Equation Apx B-31
FSA = x 4tcRnf^ + x tcR^f^
Where: Rnf is the radius of the near-field.
The near-field ventilation rate, Qnf, is calculated in Equation Apx B-32 from the indoor wind speed,
vnf, and FSA, assuming half of the FSA is available for mass transfer into the near-field and half of the
FSA is available for mass transfer out of the near-field:
Equation Apx B-32
1
Qnf vnfFSA
The far-field volume, Vff, and the air exchange rate, AER, is used to calculate the far-field ventilation
rate, Qff, as given by Equation Apx B-33:
Equation Apx B-33
Qff = V ffAER
Using the model inputs described in Appendix B.4.2, EPA estimated NMP inhalation exposures for
workers in the near-field and for occupational non-users in the far-field. EPA then conducted the Monte
Carlo simulations using @Risk (Version 7.0.0). The simulations applied 100,000 iterations and the Latin
Hypercube sampling method.
B.4.2 Model Parameters
Table Apx B-12 summarizes the model parameters and their values for the Brake Servicing Near-
Field/Far-Field Inhalation Exposure Model. Each parameter is discussed in detail in the following
subsections.
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TableApx B-12. Summary of Parameter Values and Distributions Used in the Brake Servicing Near-Field/Far-Field Inhalation
Exposure Model
Input
Parameter
Symbol
Unit
Constant Model
Parameter Values
Variable Model Parameter Values
Comments
Value
Basis
Lower
Bound
Upper
Bound
Mode
Distribution
Type
Far-field
volume
Vff
m3
206
70,679
3,769
Triangular
Distribution based on data
collected bv CARB (CARB.
2006).
Air exchange
rate
AER
hr1
1
20
3.5
Triangular
(Demou et al.. 2009) identifies
central tendency AERs of 1 hr"
1 and 3 to 20 hr-1 for
occupational settings without
and with mechanical
ventilation systems,
respectively. (Hcllwce et al..
2009) identifies averaae AERs
for occupational settings
utilizing mechanical
ventilation systems to be
between 3 and 20 hr1.
(Golsteiin et al.. 2014)
indicates a characteristic AER
of 4 hr"1. Peer reviewers of
EPA's 2013 TCE draft risk
assessment commented that
values around 2 to 5 hr"1 may
be more likelv (U.S. EPA.
2015b). in agreement with
(Golsteiin et al.. 2014). A
triangular distribution is used
with the mode equal to the
midpoint of the range provided
by the peer reviewer (3.5 is the
midpoint of the range 2 to 5 hr"
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Input
Parameter
Symbol
Unit
Constant Model
Parameter Values
Variable Model Parameter Values
Comments
Value
Basis
Lower
Bound
Upper
Bound
Mode
Distribution
Type
Near-field
indoor wind
speed
Vnf
ft/hr
1,037
50th
percentil
e
Lognormal
Lognormal distribution fit to
commercial-type workplace
data from Baldwin and
Mavnard (1998).
cm/s
8.78
50th
percentil
e
Lognormal
Near-field
radius
Rnf
m
1.5
Constant
Value
Constant.
Starting time
for each
application
period
ti
hr
0
Constant
Value
Constant.
End time for
each
application
period
t2
hr
0.0833
Constant
Value
Assumes aerosol degreaser is
applied in 5-minute increments
during brake job.
Averaging
Time
tavg
hr
8
Constant
Value
Constant.
NMP weight
fraction
wtfrac
wt frac
0.045
0.40
Discrete
Discrete distribution of NMP-
based aerosol product
formulations based on
products identified in EPA
(U.S. EPA. 2017b).
Degreaser Used
per Brake Job
wd
oz/job
14.4
Constant
Value
Based on data from CARB
(CARB. 2000).
Number of
Applications
per Job
Na
Applications
/job
11
Constant
Value
Calculated from the average of
the number of applications per
brake and number of brakes
per job.
Amount Used
per Application
Amt
g NMP/
application
1.7
14.8
Calculated
Calculated from wtfrac, Wd,
and Na.
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Input
Parameter
Symbol
Unit
Constant Model
Parameter Values
Variable Model Parameter Values
Comments
Value
Basis
Lower
Bound
Upper
Bound
Mode
Distribution
Type
Operating
hours per week
OHpW
hr/week
40
82.5
Lognormal
Lognormal distribution fit to
the operating hours per week
observed in CARB (CARB.
2000) site visits.
Number of
Brake Jobs per
Work Shift
Nj
jobs/site-
shift
2
4
Calculated from the average
number of brake jobs per site
per year, OHpW, and
assuming 52 operating weeks
per year and 8 hours per work
shift.
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B.4.2.1 Far-Field Volume
The far-field volume is based on information obtained from CARB (2000) from site visits of 137
automotive maintenance and repair shops in California. CARB (2000) indicated that shop volumes at the
visited sites ranged from 200 to 70,679 m3 with an average shop volume of 3,769 m3. Based on this data
EPA assumed a triangular distribution bound from 200 m3 to 70,679 m3 with a mode of 3,769 m3 (the
average of the data from CARB (2000).
CARB measured the physical dimensions of the portion of the facility where brake service work was
performed at the visited facilities. CARB did not consider other areas of the facility, such as customer
waiting areas and adjacent storage rooms, if they were separated by a normally closed door. If the door
was normally open, then CARB did consider those areas as part of the measured portion where brake
servicing emissions could occur (CARB. 2000). CARB's methodology for measuring the physical
dimensions of the visited facilities provides the appropriate physical dimensions needed to represent the
far-field volume in EPA's model. Therefore, CARB's reported facility volume data are appropriate for
EPA's modeling purposes.
B.4.2.2 Air Exchange Rate
The air exchange rate (AER) is based on data from (Golsteiin et al.. 2014; Demou et al.. 2009; Hellweg
et al.. 2009). and information received from a peer reviewer during the development of the 2014 TSCA
Work Plan Chemical Risk Assessment Trichloroethylene: Deceasing, Spot Cleaning and Arts & Crafts
Uses (U.S. EPA. 2015b). (Demou et al.. 2009) identifies AERs of 1 hr"1 and 3 to 20 hr"1 for occupational
settings without and with mechanical ventilation systems, respectively. Similarly, (Hellweg et al.. 2009)
identifies average AERs for occupational settings using mechanical ventilation systems to vary from 3 to
20 hr"1. (Golsteiin et al.. 2014) indicates a characteristic AER of 4 hr"1. The risk assessment peer
reviewer comments indicated that values around 2 to 5 hr"1 are likely (U.S. EPA. 2015b). in agreement
with Golsteijn, et al. (2014) and the low end reported by (Demou et al.. 2009) and (Hellweg et al.. 2009).
Therefore, EPA used a triangular distribution with the mode equal to 3.5 hr"1, the midpoint of the range
provided by the risk assessment peer reviewer (3.5 is the midpoint of the range 2 to 5 hr"1), with a
minimum of 1 hr"1, per (Demou et al.. 2009) and a maximum of 20 hr"1 per (Demou et al.. 2009) and
(Hellweg et al.. 2009).
B.4.2.3 Near-Field Indoor Air Speed
Baldwin and Maynard (1998) measured indoor air speeds across a variety of occupational settings in the
United Kingdom. Fifty-five work areas were surveyed across a variety of workplaces.
EPA analyzed the air speed data from Baldwin and Maynard (1998) and categorized the air speed
surveys into settings representative of industrial facilities and representative of commercial facilities.
EPA fit separate distributions for these industrial and commercial settings and used the commercial
distribution for facilities performing aerosol degreasing.
EPA fit a lognormal distribution for both data sets as consistent with the authors observations that the air
speed measurements within a surveyed location were lognormally distributed and the population of the
mean air speeds among all surveys were lognormally distributed. Since lognormal distributions are
bound by zero and positive infinity, EPA truncated the distribution at the largest observed value among
all of the survey mean air speeds from Baldwin and Maynard (1998).
EPA fit the air speed surveys representative of commercial facilities to a lognormal distribution with the
following parameter values: mean of 10.853 cm/s and standard deviation of 7.883 cm/s. In the model,
the lognormal distribution is truncated at a maximum allowed value of 202.2 cm/s (largest surveyed
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mean air speed observed in Baldwin and Maynard (1998) to prevent the model from sampling values
that approach infinity or are otherwise unrealistically large.
Baldwin and Maynard (1998) only presented the mean air speed of each survey. The authors did not
present the individual measurements within each survey. Therefore, these distributions represent a
distribution of mean air speeds and not a distribution of spatially-variable air speeds within a single
workplace setting. However, a mean air speed (averaged over a work area) is the required input for the
model.
B.4.2.4 Near-Field Volume
EPA defined the near-field zone to be a hemisphere with its major axis oriented vertically, against the
vehicle, and aligned through the center of the wheel (see FigureApx 1). The near-field volume is
calculated per EquationApx B-34. EPA defined a near-field radius (Rnf) of 1.5 meters, approximately
4.9 feet, as an estimate of the working height of the wheel, as measured from the floor to the center of
the wheel.
Equation Apx B-34
1 4
VNF = 2 X g
B.4.2.5 Application Time
EPA assumed an average of 11 brake cleaner applications per brake job (see Section B.4.2.9). CARB
observed, from their site visits, that the visited facilities did not perform more than one brake job in any
given hour (CARB. 2000). Therefore, EPA assumed a brake job takes one hour to perform. Using an
assumed average of 11 brake cleaner applications per brake job and one hour to perform a brake job,
EPA calculates an average brake cleaner application frequency of once every five minutes (0.0833 hr).
EPA models an average brake job of having no brake cleaner application during its first five minutes
and then one brake cleaner application per each subsequent 5-minute period during the one-hour brake
job.
B.4.2.6 Averaging Time
EPA was interested in estimating 8-hr TWAs for use in risk calculations; therefore, a constant averaging
time of eight hours was used.
B.4.2.7 NMP Weight Fraction
EPA reviewed the Use and Market Profile for n-Methylpyrrolidone (NMP) report (Abt, 2017) for
aerosol degreasers that contain NMP. EPA (U.S. EPA, 2017b) identifies two aerosol cleaners that
overall range in NMP content from 4.5 to 40 weight percent. The identified aerosol cleaners are a gun
bore cleaner and a resin remover. EPA includes these aerosol cleaners in the estimation of NMP content
as EPA uses this brake servicing model as an exposure scenario representative of all commercial-type
aerosol degreaser applications.
EPA used a discrete distribution to model the NMP weight fraction based on the number of occurrences
of each product type. EPA modeled a 50% probability of occurrence for each of the two aerosol cleaner
products. The gun bore cleaner (Break-Free bore cleaning foam) contains 4.5 weight percent NMP and
the resin remover (Slide resin remover) contains 35 to 40 weight percent. EPA used a uniform
distribution to model the NMP weight fraction within the resin remover.
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B.4.2.8 Volume of Degreaser Used per Brake Job
CARB (2000) assumed that brake jobs require 14.4 oz of aerosol product. EPA did not identify other
information to estimate the volume of aerosol product per job; therefore, EPA used a constant volume of
14.4 oz per brake job based on CARB (2000).
B.4.2.9 Number of Applications per Brake Job
Workers typically apply the brake cleaner before, during, and after brake disassembly. Workers may
also apply the brake cleaner after brake reassembly as a final cleaning process (CARB. 2000).
Therefore, EPA assumed a worker applies a brake cleaner three or four times per wheel. Since a brake
job can be performed on either one axle or two axles (CARB. 2000). EPA assumed a brake job may
involve either two or four wheels. Therefore, the number of brake cleaner (aerosol degreaser)
applications per brake job can range from six (3 applications/brake x 2 brakes) to 16 (4
applications/brake x 4 brakes). EPA assumed a constant number of applications per brake job based on
the midpoint of this range of 11 applications per brake job.
B.4.2.10 Amount of NMP Used per Application
EPA calculated the amount of NMP used per application using EquationApx B-35. The calculated
mass of perchloroethylene used per application ranges from 1.7 to 14.8 grams.
Equation Apx B-35
Where:
Amt
Wd
Wtfrac
Na
Amt =
Wd x wtfrac x 28.3495^-
oz
Na
Amount of NMP used per application (g/application)
Weight of degreaser used per brake job (oz/job)
Weight fraction of NMP in aerosol degreaser (unitless)
Number of degreaser applications per brake job (applications/job)
B.4.2.11 Operating Hours per Week
CARB (2000) collected weekly operating hour data for 54 automotive maintenance and repair facilities.
The surveyed facilities included service stations (fuel retail stations), general automotive shops, car
dealerships, brake repair shops, and vehicle fleet maintenance facilities. The weekly operating hours of
the surveyed facilities ranged from 40 to 122.5 hr/week. EPA fit a lognormal distribution to the surveyed
weekly operating hour data. The resulting lognormal distribution has a mean of 16.943 and standard
deviation of 13.813, which set the shape of the lognormal distribution. EPA shifted the distribution to
the right such that its minimum value is 40 hr/week and set a truncation of 122.5 hr/week (the truncation
is set as 82.5 hr/week relative to the left shift of 40 hr/week).
B.4.2.12 Number of Brake Jobs per Work Shift
CARB (2000) visited 137 automotive maintenance and repair shops and collected data on the number of
brake jobs performed annually at each facility. CARB calculated an average of 936 brake jobs
performed per facility per year. EPA calculated the number of brake jobs per work shift using the
average number of jobs per site per year, the operating hours per week, and assuming 52 weeks of
operation per year and eight hours per work shift using Equation Apx B-36 and rounding to the nearest
integer. The calculated number of brake jobs per work shift ranges from one to four.
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EquationApx B-36
93642^£_xa !ism
site-year shift
Where:
Nj
OHpW
Number of brake jobs per work shift (jobs/site-shift)
Operating hours per week (hr/week)
B.4.3 Sensitivity of Model Parameters
The far-field volume, AER, and near-field indoor air speed exhibit inverse relationships with the
calculated NF and FF 8-hr TWA concentrations, with concentrations increasing exponentially at
progressively lower VFF and AER values. EPA used triangular distributions for the far-field volume and
AER, and a lognormal distribution for the near-field indoor air speed, as discussed in Sections B.4.2.1,
B.4.2.2, and B.4.2.3 , respectively. Generally, the AER value has a greater impact on exposure
concentration than the far-field volume and indoor air speed.
Near-field volume also exhibits an inverse relationship with near-field (worker) exposure
concentrations. However, this parameter was fixed as a single value within the model framework, based
on the available data. Similarly, to far-field volume, AER and near-field indoor air speed, smaller
nearfield volume values would result in calculated exposure concentrations increasing exponentially,
while larger values would result in relatively small reductions in near-field exposure concentrations. Far
field exposure concentrations are largely unaffected.
The amount of NMP, which is based on the NMP weight fraction and the amount of degreaser used, has
a linear relationship with both the NF and FF 8-hr TWA concentrations. The amount of degreaser used
was fixed, based on the available data, while the NMP weight fractions were varied based on a
distribution as discussed in Section B.4.2.7.
Page 247 of 292
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Appendix C Data Integration Strategy for Occupational Exposure
and Release Data/Information
General Approach
Data integration is the stage following the data extraction and evaluation step discussed in the
Application of Systematic Review in TSCA Risk Evaluations (U.S. EPA. 2018a). Data integration is
where the analysis, synthesis and integration of data/ information takes place. For integration of
occupational exposure and environmental release data/information, EPA will normally use the highest
rated quality data among the higher level of the hierarchy of preferences as described below. TableApx
C-l and Table Apx C-2 below present the hierarchy of preferences among the primary types of data/
information to be analyzed, synthesized and integrated for the occupational exposure and release
assessments in the TSCA risk evaluations. EPA will provide rationale when deviations from the
hierarchy occur.
Selection of Data and Approaches
EPA will select data for use from the data extraction and evaluation phase of systematic review. EPA
will only use data/information rated as High, Medium, or Low in the environmental release and
occupational exposure assessments; data/ information rated as unacceptable will not be used. If need be,
data of lower rated quality or approaches in lower levels of the hierarchy may be used to supplement the
analysis. For example, data/ information of high quality could be determined to be sufficient such that
lower quality data may not be included or integrated with the higher quality data. Also, data/ information
of high quality could be determined to be sufficient such that approaches assigned lower preference
levels in the hierarchy may not be pursued even if they are available and possible. In many cases, EPA
does not have robust and or representative monitoring data and will augment such data with modeled
estimates of exposure.
Assessment Data and Results
EPA will typically provide occupational exposure and environmental release data and results
representative of central tendency conditions and high-end conditions. A central tendency is assumed to
be representative of occupational exposures and environmental releases in the center of the distribution
for a given condition of use. For risk evaluation, EPA may use the 50th percentile (median), mean
(arithmetic or geometric), mode, or midpoint values of a distribution as representative of the central
tendency scenario. EPA's preference is to provide the 50th percentile of the distribution. However, if the
full distribution is not known, EPA may assume that the mean, mode, or midpoint of the distribution
represents the central tendency depending on the statistics available for the distribution.
A high-end is assumed to be representative of occupational exposures and environmental releases that
occur at probabilities above the 90th percentile but below the exposure of the individual with the highest
exposure (U.S. EPA, 1992) or the highest release. For risk evaluation, EPA plans to provide high-end
results at the 95th percentile. If the 95th percentile is not available, EPA may use a different percentile
greater than or equal to the 90th percentile but less than or equal to the 99.9th percentile, depending on
the statistics available for the distribution. If the full distribution is not known and the preferred statistics
are not available, EPA may estimate a maximum or bounding estimate in lieu of the high-end.
Page 248 of 292
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EPA typically defines occupational exposure (and environmental release) scenarios (OESs) as the most
granular level that EPA will generate results within each condition of use. For some conditions of use,
EPA may define only a single OES (e.g., a manufacturing condition of use for multiple manufacturing
sites may be defined by a single manufacturing OES). Other conditions of use have multiple OES (e.g.,
the use of chemical X (not NMP) in vapor degreasing has OESs for open-top batch vapor degreasing,
conveyorized degreasing, web degreasing, and closed-system degreasing). EPA will typically attempt to
provide a single set of results (central tendency and high-end) for each release or exposure assessed for
an OES. For NMP, the uniqueness of PBPK modeling prevents provision of single sets of workers and
ONU PBPK results due to aggregation of routes of exposure and to the importance but high uncertainty
of glove PF impacts on worker exposures. Therefore, EPA has generated sets of results for a variety of
work activities within some OESs and for the full range of glove PF impacts for all OESs. For releases
of NMP to water, sites with the highest releases reported in TRI were screened for aquatic risk as
reported in the NMP Problem Formulation (U.S. EPA 2018c). and a broader distribution of water
releases were not required.
Integration of Data Sets
To provide the occupational results at the central tendency and high-end descriptors, EPA may integrate
data sets representative of different sites, job descriptions, or process conditions to develop a distribution
representative of the entire population of workers and sites involved in the given OES in the United
States. Ideally, the distribution would account for inter-site variability (variability in operations among
different sites) and intra-site variability (variability in operations within a single site).
To integrate data sets together, EPA will review the available metadata for each data set to ensure the
data sets are representative of the same OES. EPA will document any uncertainties in the metadata or if
EPA used a data set of a similar scenario as surrogate for the OES being assessed.
For NMP, air concentration monitoring data and NMP weight fractions in liquids were the only
occupational PBPK input parameter with adequate robustness to allow data set integration. Other
occupational parameters had no data (e.g., duration of contact with liquid, surface area of skin contact
with liquid), and these parameters did not require data set integration.
Overall Confidence Statements
For each use, EPA considered the strengths such as assessment approach, the quality of the data and
models, and the limitations such as uncertainties in data, models, and parameter assumptions, to
qualitatively determine an overall level of confidence for the PBPK input parameter sets. Generally,
input parameters related to dermal contact with liquids have a higher potential contribution to internal
exposures and are given more weight than parameters related to inhalation and vapor-through-skin
exposures for workers.
For the input parameters related to dermal contact with liquids, strength of confidence is improved by
the following factors:
Data on NMP weight fraction in relevant products for the OES,
Information on task durations and shift lengths, and
Higher systematic review data quality ratings.
Page 249 of 292
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For the input parameters related to dermal contact with liquids, strength of confidence is reduced by the
following factors:
Minimal or no data on NMP weight fraction in relevant products for the OES,
Uncertainty of the representativeness of task durations and shift durations toward actual exposure
durations,
Lack of data on skin surface area potentially exposed to NMP, and
Lack of information on glove usage for the industries and sites covered by the use.
For the air concentration monitoring data related to inhalation and vapor-through-skin exposures,
strength of confidence is improved by the following factors:
Higher approaches in the inhalation approach hierarchy,
Larger number of sites monitored,
Larger broadness of worker population groups included in monitoring, and
Higher systematic review data quality ratings.
Strength of confidence in monitoring data related to inhalation and vapor-through-skin exposures is
reduced by:
Uncertainty of the representativeness of these data toward the true distribution of inhalation
concentrations for the industries and sites covered by the use.
For modeled air concentrations related to inhalation and vapor-through-skin exposures, strength of
confidence is improved by the following factors:
Higher approaches in the inhalation approach hierarchy,
Model validation, and
Full distributions of input parameters.
Strength of confidence in modeled air concentration estimates related to inhalation and vapor-through-
skin exposures is reduced by:
Uncertainty of the representativeness of the model or parameter inputs toward the true
distribution of inhalation concentrations for the industries and sites covered by the use.
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Table Apx C-l. Hierarchy Guiding Integration of Occupational Exposure Data/Information
For occupational exposures, the generic hierarchy of preferences, listed from highest to lowest levels, is as
follows (and may be modified based on the assessment):
Highest
Preferred
1.
Monitoring data:
a. Personal and directly applicable
b. Area and directly applicable
c. Personal and potentially applicable or similar
d. Area and potentially applicable or similar
2.
Modeling approaches:
a. Surrogate monitoring data: Modeling exposure for chemical "X" and condition of
use 'A" based on observed monitoring data for chemical "Y" and condition of use
'A", assuming a known relationship (e.g., a linear relationship) between observed
exposure and physical property (e.g., vapor pressure).
b. Fundamental modeling approaches: Modeling exposure for chemical ""X" for
condition of use 'A" based on fundamental mass transfer, thermodynamic, and
kinetic phenomena for chemical "X" and data for condition of use 'A"
c. Fundamental modeling approaches (with surrogacy): A modeling approach
following item 2.b, but using surrogate data in the model, such as data for condition
of use "ET judged to be similar to condition of use 'A"
d. Statistical regression modeling approaches: Modeling exposure for chemical "X"
in condition of use 'A" using a statistical regression model developed based on:
i.Observed monitoring data for chemical "X" statistically correlated
with observed data specific for condition of use "ET judged to
be similar to condition of use 'A" such that replacement of input
values in the model can extrapolate exposure results to condition of
use 'A"
ii.Observed monitoring data for chemical "Y" statistically correlated
with physical properties and/or molecular structure such that an
exposure prediction for chemical "X" can be made (e.g., QSAR
techniques)
Lowest
Preferred
3.
Occupational exposure limits (OELs):
a. Company-specific OELs (for site-specific exposure assessments, e.g., there is
only one manufacturer who provides to EPA their internal OEL but does not provide
monitoring data)
b. OSHA PEL
c. Voluntary limits (ACGIH TLV, NIOSH REL, OARS WEEL [formerly by
AIHA])
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Table Apx C-2. Hierarchy Guiding Integration of Environmental Release Data/Information
For environmental releases, the generic hierarchy of preferences, listed from highest to lowest levels, is as follows
(and may be modified based on the assessment):
1. Monitoring and measured data:
a. Releases calculated from site-specific concentration in medium and flow rate data
(e.g., concentration in and flow rate of wastewater effluent discharged through outfall)
b. Releases calculated from mass balances or emission factor methods using site-
specific measured data (e.g., process flow rates and concentrations)
2. Modeling approaches:
a. Surrogate monitoring data: Modeling release for chemical "X" and condition of
use "A" based on observed monitoring data for chemical "Y" and condition of use
"A", assuming a known relationship (e.g., a linear relationship) between observed
release and physical property (e.g., vapor pressure).
b. Fundamental modeling approaches: Modeling release for chemical ""X" for
condition of use 'A" based on fundamental mass transfer, thermodynamic, and kinetic
phenomena for chemical "X" and data for condition of use 'A"
c. Fundamental modeling approaches (with surrogacy): A modeling approach
following item 2.b, but using surrogate data in the model, such as data for condition of
use "ET judged to be similar to condition of use "A"
d. Statistical regression modeling approaches: Modeling release for chemical "X" in
condition of use 'A" using a statistical regression model developed based on:
iii.Observed monitoring data for chemical "X" statistically correlated
with observed data specific for condition of use "ET judged to
be similar to condition of use 'A" such that replacement of input
values in the model can extrapolate exposure results to condition of
use 'A"
iv.Observed monitoring data for chemical "Y" statistically correlated
with physical properties and/or molecular structure such that a release
prediction for chemical "X" can be made (e.g., QSAR techniques)
3. Release limits:
a. Company-specific limits (for site-specific exposure assessments, e.g., there is only
one manufacturer who provides to EPA their internal limits (e.g., point-source permits)
but does not provide monitoring data)
b. NESHAP or effluent limitations/ requirements
Highest
Preferred
Lowest
Preferred
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Appendix D NMP Weight Fraction Data
Table Apx D-l summarizes data on the NMP weight fraction in various formulations/products that EPA
found for each occupational exposure scenario. EPA used these data to calculate NMP weight fraction
PBPK inputs. Specifically, EPA calculated the central tendency (50th percentile) and high-end (95th
percentile) weight fraction of NMP for each occupational exposure scenario. Note that, where NMP
concentration was provided in a range, EPA used the midpoint of the range in the distribution of NMP
concentrations for the calculations of central tendency and high-end.
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Table Apx D-l. Summary NMP Weight Fraction Data for All Occupational Exposure Scenarios
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Manufacturing
N/A - EPA assumed
100%
Manufactured NMP
90 - 100%
(U.S. EPA
2016a)
Data Quality
Evaluation of
Common
Sources
High
Manufacturing
N/A - EPA assumed
100%
Manufactured NMP
90 - 100%
(U.S. EPA
2016a)
Data Quality
Evaluation of
Common
Sources
High
Manufacturing
N/A - EPA assumed
100%
Manufactured NMP
90 - 100%
(U.S. EPA
2016a)
Data Quality
Evaluation of
Common
Sources
High
Manufacturing
N/A - EPA assumed
100%
Manufactured NMP
90 - 100%
(U.S. EPA
2016a)
Data Quality
Evaluation of
Common
Sources
High
Manufacturing
N/A - EPA assumed
100%
Manufactured NMP
80 to 100%
(RIVM. 2013)
3809440 - 004
High
Manufacturing
N/A - EPA assumed
100%
Manufactured NMP
99.8%
(TURI. 1996)
3982071 -001
High
Manufacturing
N/A - EPA assumed
100%
Manufactured NMP
90 - 100%
(U.S. EPA. 2012)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
60 - 90%
(U.S. EPA
2016a)
Data Quality
Evaluation of
Common
Sources
High
Page 254 of 292
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Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Page 255 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Repackaging
N/A - EPA assumed
100%
Imported NMP
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
<1%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
1 - 30%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
>1 to <30
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Page 256 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported NMP
90 - 100%
(U.S. EPA. 2012)
Data Quality
Evaluation of
Common
Sources
High
Repackaging
N/A - EPA assumed
100%
Imported primer
containing NMP
<5%
(Haas. 2017)
3986804 - 001
High
Chemical
Processing,
Excluding
Formulation
Unloading liquid
NMP from drums
NMP used as a
processing aid in
pesticide, fertilizer, and
other agricultural
chemical manufacturing
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Chemical
Processing,
Excluding
Formulation
Unloading liquid
NMP from drums
NMP used as a
processing aid in
petroleum production
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Chemical
Processing,
Excluding
Formulation
Unloading liquid
NMP from drums
NMP used as a
processing aid in
petroleum production
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Chemical
Processing,
Excluding
Formulation
Unloading liquid
NMP from drums
NMP used for polymer
membrane
manufacturing
>50%
(Roberts. 2017)
3986796 - 003
High
Page 257 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Chemical
Processing,
Excluding
Formulation
Unloading liquid
NMP from drums
NMP used in plastic
material and resin
manufacturing
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Chemical
Processing,
Excluding
Formulation
Unloading liquid
NMP from drums
NMP used in plastic
material and resin
manufacturing
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Chemical
Processing,
Excluding
Formulation
Unloading liquid
NMP from drums
NMP used in polymer
synthesis
>99%
(Roberts. 2017)
3986796 - 003
High
Chemical
Processing,
Excluding
Formulation
Unloading liquid
NMP from drums
NMP used in polymer
synthesis
35%
(Kemira. 2018)
5176404-001
High
Chemical
Processing,
Excluding
Formulation
Unloading liquid
NMP from drums
NMP used in polymer
synthesis
65%
(Kemira. 2018)
5176404-001
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Additive for coatings
75%
(Davis. 2017)
3986800 - 001
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Additive for coatings
48%
(Davis. 2017)
3986800 - 001
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Additive for coatings
<1%
(Davis. 2017)
3986800 - 001
High
Page 258 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Additive for coatings
45%
(NICNAS. 1997)
3978356 - 001
Medium
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Additive for coatings
48%
(Davis. 2017)
3986800 - 001
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Additive for fertilizer
15 - 45%
(Roberts. 2017)
3986796 - 004
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Adhesive s
30 - 50%
(ACC. 2017)
5176412-001
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Coatings
< 1.5%
(Davis. 2017)
3986800 - 001
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Curable polyurethane
formulation
0.13%
(Abt. 2017)
Not rated
Not rated
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Formulations for
electronics
10 - 100%
(FUJIFILM.
2017)
5176406-001
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Formulations for
electronics
10%
(FUJIFILM.
2020)
6592030-001
High
Page 259 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Formulations for
electronics
100%
(FUJIFILM.
2020)
6592030-001
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Page 260 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Page 261 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Page 262 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Page 263 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
1 - 30%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
NMP used for unknown
liquid formulations
90 - 100%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Paints and coatings
<1%
(U.S. EPA. 2012)
Data Quality
Evaluation of
Common
Sources
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Unknown liquid
formulations
5 - 100%
(Roberts. 2017)
3986796 - 005
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Liquid - Misc.
(Maintenance,
analytical, loading)
Unknown liquid
formulations
<1%
(U.S. EPA. 2012)
Data Quality
Evaluation of
Common
Sources
High
Page 264 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Incorporation into
Formulation,
Mixture, or Reaction
Product
Solid - loading into
drums
NMP in cast nylon
(solid)
<5%
(Abt. 2017)
Not rated
Not rated
Incorporation into
Formulation,
Mixture, or Reaction
Product
Solid - loading into
drums
NMP in cast nylon
(solid)
<5%
(Abt. 2017)
Not rated
Not rated
Incorporation into
Formulation,
Mixture, or Reaction
Product
Solid - loading into
drums
NMP in fertilizer (solid)
<0.1%
(Roberts. 2017)
3986796 - 003
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Solid - loading into
drums
NMP in granular
fungicide (solid)
<5%
(U.S. EPA.
2017b)
Not rated
Not rated
Incorporation into
Formulation,
Mixture, or Reaction
Product
Solid - loading into
drums
Residual NMP in linear
polyphenylene sulfide
(solid)
0.0017%
(Materials. 2017)
5176410-001
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Solid - loading into
drums
Residual NMP in
polymer pellets (solid)
0.15%
(Roberts. 2017)
3986796 - 003
High
Incorporation into
Formulation,
Mixture, or Reaction
Product
Solid - loading into
drums
Residual NMP in
polymer powders (solid)
7%
(Roberts. 2017)
3986796 - 003
High
Metal Finishing
All forms of
application
Metal products not
covered elsewhere
60 - 90%
(U.S. EPA. 2012)
Data Quality
Evaluation of
Common
Sources
High
Page 265 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Metal finishing
All forms of
application
Metal products not
covered elsewhere
60 - 90%
(U.S. EPA.
2016a)
Data Quality
Evaluation of
Common
Sources
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Adhesive
>85%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Adhesive
<0.3%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Adhesive
1%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Adhesive
1 - 10%
(RIVM. 2013)
3809440 - 004
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Adhesive
0.3 - 85%
(U.S. EPA.
2017b)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Adhesive
60 - 90%
(U.S. EPA. 2012)
Data Quality
Evaluation of
Common
Sources
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Adhesive
<5%
(ACC. 2017)
5176412-001
High
Page 266 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Adhesive
<0.1%
(ACC. 2017)
5176412-001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Antistatic coatings
0.5%
(ACC. 2017)
5176412-001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Architectural coatings
0.1 - 1%
(Davis. 2017)
3986800 - 001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Automotive seam sealant
<1.5%
(ACC. 2017)
5176412-001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
<2.5%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
<0.3%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
<0.3%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
3%
(Abt. 2017)
Not rated
Not rated
Page 267 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
<1%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
48 - 49%
(U.S. EPA.
2017b)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
1 - 2.5%
(U.S. EPA.
2017b)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
3 - 7%
(U.S. EPA.
2017b)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
<5%
(U.S. EPA.
2017b)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
60 - 63%
(U.S. EPA.
2017b)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
0 - 1%
(U.S. EPA.
2017b)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
0.129%
(U.S. EPA.
2017b)
Not rated
Not rated
Page 268 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
10 - 30%
(NICNAS. 1998)
3978358 - 001
Medium
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
5 - 10%
(NICNAS. 1998)
3978358 - 002
Medium
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
0-7.1%
(Muenter and
Blach. 2010)
3577026-001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
1 - 5%
(Davis. 2017)
3986800 - 001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating
0.45 - 1.35%
(NICNAS. 1997)
3978356 - 002
Medium
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coating for auto parts
2.5 - 10%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coatings
<1.5%
(Davis. 2017)
3986800 - 001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coatings
<0.2%
(Davis. 2017)
3986800 - 001
High
Page 269 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coatings, inks,
adhesives, and sealants
<2%
(Davis. 2017)
3986800 - 001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Coatings, paints, and
sealants
0.1-63%
(U.S. EPA.
2017b)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Enamel coating
80 - 85%
(National
Electrical
Manufacturers
Association.
3986803 - 001
High
2017)
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Enamel coating
45 - 60%
(Davis. 2017)
3986800 - 001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Fire protection sealant
<0.5%
(ACC. 2017)
5176412-001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Floor finish
<4%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Floor finish
1 - 2.5%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Floor finish
1 - 5%
(Davis. 2017)
3986800 - 001
High
Page 270 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Gloss sealant
0.1 - 1%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Latex coating
0.3 - 1%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Leak sealant
0.1 - 1%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Leather finish
2 - 5%
(U.S. EPA.
2017b)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Non-skid coating
0.25 - 0.5%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paint
4 - 7%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paint
1 - 5%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paint
2%
(Abt. 2017)
Not rated
Not rated
Page 271 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paint
0.36%
(U.S. EPA.
2017b)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paint
0.06 - 13%
(RIVM. 2013)
3809440 - 004
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paint
0.1 - 1%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paint
0.2 - 2%
(Davis. 2017)
3986800 - 001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paint primer
1 - 2.5%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paints, stains, and
coatings
9 - 10%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paints, stains, and
coatings
0 - 5%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paints, stains, and
coatings
1 - 5%
(Abt. 2017)
Not rated
Not rated
Page 272 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paints, stains, and
coatings
30 - 60%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Paints, stains, and
coatings
0.28%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Polyacrylic protective
finish
1.6%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Polymeric adhesive for
leather coating
5%
(NICNAS. 2001)
3978357 - 001
Medium
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Polyurethane coating
1 - 2.5%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Polyurethane coating
2.5 - 10%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Polyurethane coating
10 - 50%
(Davis. 2017)
3986800 - 001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Primer
<5%
(Haas. 2017)
3986804 - 001
High
Page 273 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Protective clear coatings
<14%
(ACC. 2017)
5176412-001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Roof coating
1 - 2%
(Davis. 2017)
3986800 - 001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Sanding sealant
2 - 3%
(Davis. 2017)
3986800 - 001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Sealant
1 - 3%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Sealant
0.1 - 1%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Sealant
<1%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Sealant
0.1 - 1%
(Abt. 2017)
Not rated
Not rated
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Shutter coating
1 - 3%
(MacRov. 2017)
3986795 - 002
High
Page 274 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Stain for wood
0.1 - 1%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Stainless steel paint
5 - 10%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Urethane coatings
5 - 15%
(ACC. 2017)
5176412-001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Vinyl coating
1 - 3%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Wood finish
0.8-2.1%
(Davis. 2017)
3986800 - 001
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Wood floor finish
5 - 7%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Wood floor finish
8 - 12%
(MacRov. 2017)
3986795 - 002
High
Application of
Paints, Coatings,
Adhesives, and
Sealants
All forms of
application
Wood floor finish
1 - 2.5%
(MacRov. 2017)
3986795 - 002
High
Page 275 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Recycling and
disposal
All
Waste NMP at a
semiconductor
manufacturing site
92%
(SIA. 2019b)
5161295 -001
High
Removal of Paints,
Coatings,
Adhesives, and
Graffiti removal
Graffiti remover
40 - 60%
(Abt. 2017)
Not rated
Not rated
Sealants
Removal of Paints,
Coatings,
Adhesives, and
Graffiti removal
Spray graffiti remover
25 - 30%
(Abt. 2017)
Not rated
Not rated
Sealants
Removal of Paints,
Coatings,
Adhesives, and
Miscellaneous paint,
coating, adhesive, and
sealant removal
Biodegradable paint
remover
40 - 45%
(Abt. 2017)
Not rated
Not rated
Sealants
Removal of Paints,
Coatings,
Adhesives, and
Sealants
Miscellaneous paint,
coating, adhesive, and
sealant removal
Glue remover
10 - 20%
(MacRov. 2017)
3986795 - 005
High
Removal of Paints,
Coatings,
Adhesives, and
Sealants
Miscellaneous paint,
coating, adhesive, and
sealant removal
Ink remover
1 - 60%
(U.S. EPA.
2017b)
Not rated
Not rated
Removal of Paints,
Coatings,
Adhesives, and
Miscellaneous paint,
coating, adhesive, and
sealant removal
Paint and varnish
remover
20 - 40%
(Abt. 2017)
Not rated
Not rated
Sealants
Removal of Paints,
Coatings,
Adhesives, and
Miscellaneous paint,
coating, adhesive, and
sealant removal
Paint and varnish
remover
9%
(Abt. 2017)
Not rated
Not rated
Sealants
Page 276 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Removal of Paints,
Coatings,
Adhesives, and
Sealants
Miscellaneous paint,
coating, adhesive, and
sealant removal
Paint remover
<5%
(Abt. 2017)
Not rated
Not rated
Removal of Paints,
Coatings,
Adhesives, and
Sealants
Miscellaneous paint,
coating, adhesive, and
sealant removal
Paint stripper
<80%
(Abt. 2017)
Not rated
Not rated
Removal of Paints,
Coatings,
Adhesives, and
Sealants
Miscellaneous paint,
coating, adhesive, and
sealant removal
Paint stripper
25 - 30%
(Abt. 2017)
Not rated
Not rated
Removal of Paints,
Coatings,
Adhesives, and
Sealants
Miscellaneous paint,
coating, adhesive, and
sealant removal
Paint stripper
5 - 20%
(EC. 2004)
3982358 - 001
Medium
Removal of Paints,
Coatings,
Adhesives, and
Sealants
Miscellaneous paint,
coating, adhesive, and
sealant removal
Paint stripper
2.5 - 63%
(EU. 2007)
3808951 - 001
High
Removal of Paints,
Coatings,
Adhesives, and
Sealants
Miscellaneous paint,
coating, adhesive, and
sealant removal
Paint stripper
12 - 80%
(U.S. EPA.
1998b)
3827493 - 002
High
Removal of Paints,
Coatings,
Adhesives, and
Sealants
Miscellaneous paint,
coating, adhesive, and
sealant removal
Paint stripper for
industrial applications
(removing powder coat
and acrylic coating from
metal)
50%
(MacRov. 2017)
3986795 - 005
High
Removal of Paints,
Coatings,
Adhesives, and
Sealants
Miscellaneous paint,
coating, adhesive, and
sealant removal;
Graffiti remover
Paint and graffiti remoer
25 - 100%
(U.S. EPA.
2015c)
3827504 - 002
High
Page 277 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Aid in battery
manufacturing
>90%
(U.S. EPA. 2012)
Data Quality
Evaluation of
Common
Sources
High
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Battery
0 - 1%
(U.S. EPA.
2017b)
Not rated
Not rated
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Battery
0 - 1%
(Abt. 2017)
Not rated
Not rated
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Battery
0 - 1%
(Abt. 2017)
Not rated
Not rated
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Battery
0 - 1%
(Abt. 2017)
Not rated
Not rated
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Cleaner (electronics)
5 - 7%
(U.S. EPA.
2017b)
Not rated
Not rated
Page 278 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Electronic products
30 - 60%
(U.S. EPA. 2012)
Data Quality
Evaluation of
Common
Sources
High
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Ink for 3D printable
electronics
<15%
(U.S. EPA.
2017b)
Not rated
Not rated
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Photoresist Remover
>99%
(Abt. 2017)
Not rated
Not rated
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Photoresist Remover
>99%
(U.S. EPA.
2017b)
Not rated
Not rated
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Photoresist remover
100%
(Roberts. 2017)
3986796-001
High
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Polyimide coating
<1%
(U.S. EPA.
2017b)
Not rated
Not rated
Page 279 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Other Electronics
Manufacturing;
Lithium Ion Cell
Manufacturing b
Capacitor, Resistor,
Coil, Transformer,
and Other Inductor
Mfg.; Research and
Development
Solder mask remover
100%
(Roberts. 2017)
3986796 - 002
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
50%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
50%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
30 - 60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
30 - 60%
(SIA. 2019b)
5161295 -001
High
Page 280 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
65%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
drums
NMP in drums at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
40 - 60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
40 - 60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
40 - 60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
<60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
<60%
(SIA. 2019b)
5161295 -001
High
Page 281 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
<60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
<60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
<60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
<60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
<60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
<60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
50 - 75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
50 - 75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
50 - 75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
50 - 75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Page 282 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Container handling,
small containers
NMP in small containers
at semiconductor
fabrication site
<60%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Fab worker
Semiconductor fab
workers with container
changeout
2.5%
(SIA. 2020)
6592032-001
High
Semiconductor
Manufacturing
Fab worker
Semiconductor fab
workers with container
changeout
5%
(SIA. 2020)
6592032-001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
1 - 5%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
18-22%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
18-22%
(SIA. 2019b)
5161295 -001
High
Page 283 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
18-22%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Page 284 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
20%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
45 - 65%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
45 - 65%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
50%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
50%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
50%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
50%
(SIA. 2019b)
5161295 -001
High
Page 285 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
50%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
50%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
65%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
65%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
65%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
65%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Page 286 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
75%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
100%
(SIA. 2019b)
5161295 -001
High
Page 287 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
100%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
100%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
100%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
100%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Maintenance
NMP used for
maintenance activities at
semiconductor
fabrication site
100%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Virgin NMP truck
unloading
Virgin NMP in trucks at
semiconductor
manufacturing site
100%
(SIA. 2019b)
5161295 -001
High
Semiconductor
Manufacturing
Waste truck loading
Waste NMP at a
semiconductor
manufacturing site
92%
(SIA. 2019b)
5161295 -001
High
Printing and Writing
Printing
Ink
<5%
(Abt. 2017)
Not rated
Not rated
Printing and Writing
Printing
Inkjet printing ink
<5%
(U.S. EPA.
2017b)
Not rated
Not rated
Printing and Writing
Printing
Inkjet printing ink
5 - 10%
(Gerber. 2017)
3986797 - 002
High
Printing and Writing
Printing
Printing ink
1 - 5%
(U.S. EPA.
2017b)
Not rated
Not rated
Page 288 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Printing and Writing
Printing
Silver ink
0 - 5%
(U.S. EPA.
2017b)
Not rated
Not rated
Printing and Writing
Writing
Ink in marker
10 - 20%
(U.S. EPA.
2017b)
Not rated
Not rated
Soldering
Brush application
Soldering flux
1 - 2.5%
(Abt. 2017)
Not rated
Not rated
Commercial
Automotive
Servicing
Aerosol degreasing
Aerosol gasket remover
<20%
(Rudnick. 2017)
3986802 - 001
High
Commercial
Automotive
Servicing
Aerosol degreasing
Aerosol resin remover
35 - 40%
(Abt. 2017)
Not rated
Not rated
Commercial
Automotive
Servicing
Aerosol degreasing
Air intake system cleaner
15 - 40%
(U.S. EPA.
2017b)
Not rated
Not rated
Commercial
Automotive
Servicing
Aerosol degreasing
Automotive headlight
sealant and cleaner
0.2%
(U.S. EPA.
2017b)
Not rated
Not rated
Commercial
Automotive
Servicing
Aerosol degreasing
Automotive seam sealer
<1%
(U.S. EPA.
2017b)
Not rated
Not rated
Commercial
Automotive
Servicing
Aerosol degreasing
Bore cleaning foam
4.5%
(Abt. 2017)
Not rated
Not rated
Commercial
Automotive
Servicing
Aerosol degreasing
Leak sealer used in cars
0.1 - 1%
(Abt. 2017)
Not rated
Not rated
Commercial
Automotive
Servicing
Aerosol degreasing
Leather cleaner used in
cars
<1%
(U.S. EPA.
2017b)
Not rated
Not rated
Commercial
Automotive
Servicing
Aerosol degreasing
Leather cleaner used in
cars
4%
(Abt. 2017)
Not rated
Not rated
Page 289 of 292
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Commercial
Automotive
Servicing
Aerosol degreasing
Leather cleaner used in
cars
0.1 - 1%
(Abt. 2017)
Not rated
Not rated
Laboratory Use
Laboratory Use
Laboratory solvent
100%
(RIVM. 2013)
3809440 - 004
High
Lithium Ion Cell
Manufacturing
Cathode coating
Batch coating of
cathodes
99%
(LICM. 2020c)
6592044- 101
High
Lithium Ion Cell
Manufacturing
Container handling,
small containers
NMP in small containers
at lithium ion cell
manufacturing site
>99%
(LICM. 2020c)
6592044- 101
High
Lithium Ion Cell
Manufacturing
Miscellaneous
additional activities
Parts washing,
equipment adjustments
and repairs, and other
non-routine tasks at
lithium ion cell
manufacturing site
-------
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
Data Identifier
from Data
Extraction and
Evaluation a
Overall
Confidence
Rating from
Data Extraction
and Evaluation a
Lithium Ion Cell
Manufacturing
Miscellaneous
additional activities
Parts washing,
equipment adjustments
and repairs, and other
non-routine tasks at
lithium ion cell
manufacturing site
>99%
(LICM. 2020c)
6592044- 101
High
Cleaning
Dip degreasing and
cleaning
Immersion cleaner
60 - 80%
(Abt. 2017)
Not rated
Not rated
Cleaning
Dip degreasing and
cleaning
Immersion cleaner for
metal parts
100%
(BASF. 1993)
3982074-001
Medium
Cleaning
Dip degreasing and
cleaning
Polyurethane remover
40 - 60%
(Abt. 2017)
Not rated
Not rated
Cleaning
Dip degreasing and
cleaning
Remover
>99%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Air intake system cleaner
15 - 40%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Cleaning solution
30 - 60%
(RIVM. 2013)
3809440 - 005
High
Cleaning
Spray/wipe cleaning
Cleaning solvent
100%
(MacRov. 2017)
3986795 - 004
High
Cleaning
Spray/wipe cleaning
Cleaning solvent
100%
(MacRov. 2017)
3986795 - 004
High
Cleaning
Spray/wipe cleaning
Coating remover pen
5 - 7%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Commerical cleaning
products
30 - 60%
(U.S. EPA. 2012)
Data Quality
Evaluation of
Common
High
Sources
Cleaning
Spray/wipe cleaning
Cured sealant cleaner
20 - 30%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Epoxy grout film
remover
30 - 60%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Foam and resin cleaner
41%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Gasket remover
10 - 20%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Gun cleaner
5 - 10%
(MacRov. 2017)
3986795 - 004
High
Cleaning
Spray/wipe cleaning
Heavy duty parts cleaner
2%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Industrial strength bio-
based gel cleaner
25 - 50%
(Abt. 2017)
Not rated
Not rated
Page 291 of 292
-------
Data Identifier
Overall
Confidence
Rating from
Data Extraction
Condition of Use
Occupational
Exposure Scenario
Product Description
NMP
Concentration
Source
from Data
Extraction and
Evaluation a
and Evaluation a
Cleaning
Spray/wipe cleaning
Industrial strength
cleaning wipes
15 - 25%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Leather cleaner
4%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Leather cleaner
0.1 - 1%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Leather cleaner
<1%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Oven cleaner
1 - 5%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Resin remover and mold
cleaner
30 - 50%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Screen printer cleaning
35%
(U.S. EPA.
1998a)
3982072-001
Medium
Cleaning
Spray/wipe cleaning
Stainless steel cleaner
1 - 5%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Ultrasonic liquid cleaner
90 - 95%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Unspecified cleaner
60 - 100%
(Abt. 2017)
Not rated
Not rated
Cleaning
Spray/wipe cleaning
Wipe and brush cleaner
for parts at an adhesive
formulation site
65%
(Bader et al..
2006)
3539720 - 001
Medium
Fertilizer
Application
Manual spray or
boom application of
fertilizers
Agrochemicals
<7%
(RIVM. 2013)
3809440 - 004
High
Fertilizer
Application
Manual spray or
boom application of
fertilizers
NMP in fertilizer (solid)
<0.1%
(Roberts. 2017)
3986796 - 004
High
Fertilizer
Application
Manual spray or
boom application of
fertilizers
NMP in granular
fungicide (solid)
<5%
(U.S. EPA.
2017b)
Not rated
Not rated
a Sources listed as not rated are documents that were developed in support of this risk evaluation.
b To develop comprehensive high-end and central tendency weight fractions for these OES, EPA used data for all electronics manufacturing OES (Other Electronics
Manufacturing, Semiconductor Manufacturing, and Lithium Ion Cell Manufacturing).
Page 292 of 292
------- |