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>=,EPA
United States Office of Chemical Safety and
Environmental Protection Agency Pollution Prevention
Draft Risk Evaluation for
1-Bromopropane (1-BP)
1-BP Supplemental File:
Supplemental Information on Occupational Exposure
Assessment
CASRN: 106-94-5
Br
CH
August 2019
NOTICE: This information is distributed solely for the purpose of pre-dissemination peer review under
applicable information quality guidelines. It has not been formally disseminated by EPA. It does not
represent and should not be construed to represent any Agency determination or policy. It is being
circulated for review of its technical accuracy and science policy implications.
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TABLE OF CONTENTS
ABBREVIATIONS 12
1 INTRODUCTION 14
1.1 Background and Scope 14
1.2 General Approach and Methodology for Number of Sites and Workers 14
1.3 General Approach and Methodology for Occupational Exposures 15
1.3.1 Inhalation Exposure Assessment Approach and Methodology 15
1.3.2 Dermal Exposure Assessment Approach and Methodology 15
1.3.3 Respiratory Protection 15
1.4 Peer Review Comments 16
2 ENGINEERING ASSESSMENT 18
2.1 Manufacture 18
2.1.1 Process Description 18
2.1.2 Number of Sites and Potentially Exposed Workers 18
2.1.3 Exposure Assessment 19
2.1.3.1 Worker Activities 19
2.1.3.2 Occupational Exposure Assessment Methodology 19
2.1.3.3 Occupational Exposure Results 20
2.2 Import 21
2.2.1 Process Description 21
2.2.2 Number of Sites and Potentially Exposed Workers 21
2.2.3 Exposure Assessment 22
2.2.3.1 Worker Activities 22
2.2.3.2 Occupational Exposure Assessment Methodology 22
2.2.3.3 Occupational Exposure Results 23
2.3 Processing as a Reactant 23
2.3.1 Process Description 23
2.3.2 Number of Sites and Potentially Exposed Workers 23
2.3.3 Exposure Assessment 24
2.3.3.1 Worker Activities 24
2.3.3.2 Occupational Exposure Assessment Methodology 24
2.4 Processing - Incorporation into Formulation, Mixture, or Reaction Product 25
2.4.1 Process Description 25
2.4.2 Number of Sites and Potentially Exposed Workers 26
2.4.3 Exposure Assessment 27
2.4.3.1 Worker Activities 27
2.4.3.2 Occupational Exposure Assessment Methodology 27
2.4.3.3 Occupational Exposure Results 27
2.5 Processing - Incorporation into Articles 28
2.5.1 Process Description 28
2.5.2 Number of Sites and Potentially Exposed Workers 28
2.5.3 Exposure Assessment 28
2.5.3.1 Worker Activities 29
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2.5.3.2 Occupational Exposure Assessment Methodology 29
2.6 Repackaging 29
2.6.1 Process Description 29
2.6.2 Number of Sites and Potentially Exposed Workers 29
2.6.3 Exposure Assessment 30
2.6.3.1 Worker Activities 30
2.6.3.2 Occupational Exposure Assessment Methodology 30
2.6.3.3 Occupational Exposure Results 30
2.7 Batch Vapor Degreaser (Open-Top) 31
2.7.1 Process Description 31
2.7.2 Number of Sites and Potentially Exposed Workers 34
2.7.3 Exposure Assessment 35
2.7.3.1 Worker Activities 35
2.7.3.2 Occupational Exposure Assessment Methodology 35
2.7.3.3 Occupational Exposure Results 35
2.8 Batch Vapor Degreaser (Closed-Loop) 39
2.8.1 Process Description 39
2.8.2 Number of Sites and Potentially Exposed Workers 41
2.8.3 Exposure Assessment 41
2.8.3.1 Worker Activities 41
2.8.3.2 Occupational Exposure Assessment Methodology 41
2.8.3.1 Occupational Exposure Results 41
2.9 In-line Vapor Degreaser (Conveyorized) 42
2.9.1 Process Description 42
2.9.2 Number of Sites and Potentially Exposed Workers 47
2.9.3 Exposure Assessment 48
2.9.3.1 Worker Activities 48
2.9.3.2 Occupational Exposure Assessment Methodology 48
2.10 Cold Cleaner 50
2.10.1 Process Description 50
2.10.2 Number of Sites Potentially Exposed Workers 50
2.10.3 Exposure Assessment 50
2.10.3.1 Worker Activities 50
2.10.3.2 Occupational Exposure Assessment Methodology 51
2.10.3.3 Occupational Exposure Results 51
2.11 Aerosol Spray Degreaser/Cleaner 53
2.11.1 Process Description 53
2.11.2 Number of Sites and Potentially Exposed Workers 54
2.11.3 Exposure Assessment 55
2.11.3.1 Worker Activities 55
2.11.3.2 Occupational Exposure Assessment Methodology 55
2.11.3.3 Occupational Exposure Results 55
2.12 Dry Cleaning 58
2.12.1 Process Description 58
2.12.2 Number of Sites and Potentially Exposed Workers 58
2.12.3 Exposure Assessment 59
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2.12.3.1 Worker Activities 59
2.12.3.2 Occupational Exposure Assessment Methodology 60
2.12.3.3 Occupational Exposure Results 60
2.13 Spot Cleaner, Stain Remover 65
2.13.1 Process Description 65
2.13.2 Number of Sites and Potentially Exposed Workers 66
2.13.3 Exposure Assessment 66
2.13.3.1 Worker Activities 66
2.13.3.2 Occupational Exposure Assessment Methodology 66
2.13.3.3 Occupational Exposure Results 66
2.14 Adhesive Chemicals (Spray Adhesives) 68
2.14.1 Process Description 68
2.14.2 Number of Sites and Potentially Exposed Workers 69
2.14.3 Exposure Assessment 70
2.14.3.1 Worker Activities 70
2.14.3.2 Occupational Exposure Assessment Methodology 70
2.14.3.3 Occupational Exposure Results 71
2.15 Other Uses 72
2.15.1 Process Description 72
2.15.2 Number of Sites and Potentially Exposed Workers 73
2.15.3 Exposure Assessment 73
2.16 Disposal, Recycling 73
2.16.1 Process Description 73
2.16.2 Number of Sites and Potentially Exposed Workers 76
2.16.3 Exposure Assessment 77
2.16.3.1 Worker Activities 77
2.16.3.2 Occupational Exposure Assessment Methodology 78
2.16.3.3 Occupational Exposure Results 78
2.17 Dermal Exposure Assessment 79
3 DISCUSSION OF UNCERTAINTIES AND LIMITATIONS 84
3.1 Variability 84
3.2 Uncertainties and Limitations 84
3.2.1 Number of Workers 84
3.2.2 Analysis of Exposure Monitoring Data 85
3.2.3 Near-Field / Far-Field Model Framework 85
3.2.3.1 Vapor Degreasing and Cold Cleaning Model 86
3.2.3.2 Aerosol Degreasing Model 87
3.2.3.3 Dry Cleaning Model 88
3.2.3.4 Spot Cleaning Model 88
3.2.4 Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure
Model 89
3.2.5 Modeling Dermal Exposures 89
4 REFERENCES 90
Appendix A Approach for Estimating Number of Workers 97
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Appendix B Equations for Calculating Acute and Chronic Exposures for Non-Cancer and
Cancer 103
Appendix C Summary of Department of Defense Data 106
Appendix D Tank Truck and Railcar Loading and Unloading Release and Inhalation
Exposure Model Approach and Parameter 107
D. 1 Displacement of Saturated Air Inside Tank Trucks and Railcars 107
D.2 Emissions of Saturated Air that Remain in Transfer Hoses/Loading Arm 108
D.3 Emission from Leaks 110
D. 4 Exposure Estimates 112
Appendix E Open-Top Vapor Degreasing Near-Field/Far-Field Inhalation Exposure
Model Approach and Parameter 115
E. 1 Model Design Equations 116
E.2 Model Parameters 119
E.2.1 Far-Field Volume 122
E.2.2 Air Exchange Rate 122
E.2.3 Near-Field Indoor Air Speed 122
E.2.4 Near-Field Volume 123
E.2.5 Exposure Duration 123
E.2.6 Averaging Time 123
E.2.7 Emission Factor 123
E.2.8 Number of Employees 123
E.2.9 Operating Hours 123
Appendix F Cold Cleaning Near-Field/Far-Field Inhalation Exposure Model Approach
and Parameter 124
Appendix G Brake Servicing Near-Field/Far-Field Inhalation Exposure Model Approach
and Parameter 129
G, 1 Model Design Equations 129
G.2 Model Parameters 135
G.2.1 Far-Field Volume 138
G.2.2 Air Exchange Rate 138
G.2.3 Near-Field Indoor Air Speed 138
G.2.4 Near-Field Volume 139
G.2.5 Application Time 139
G.2.6 Averaging Time 139
G.2.7 1-BP Weight Fraction 139
G. 2.8 Volume of Degreaser Used per Brake Job 141
G.2.9 Number of Applications per Brake Job 141
G.2.10 Amount of 1-BP Used per Application 141
G.2.11 Operating Hours per Week 141
G.2.12 Number of Brake Jobs per Work Shift 141
Appendix H Dry Cleaning Multi-Zone Inhalation Exposure Model Approach and
Parameter 143
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H. 1 Model Design Equations 144
H.2 Model Parameters 150
H.2.1 Facility Parameters 153
H.2.1.1 Far-Field Volume 153
H.2.1.2 Air Exchange Rate 153
H.2.1.3 Near-Field Indoor Air Speed 153
H.2.2 Dry Cleaning Machine Parameters 154
H.2.2.1 Machine Door Diameter 154
H.2.2.2 Number of Loads per Day 154
11.2.2.3 Load Time 154
H.2.2.4 Machine Cylinder Concentration 155
H.2.2.5 Cylinder Volume 155
H.2.2.6 Exposure Duration 155
H.2.3 Finishing and Pressing Parameters 155
H.2.3.1 Near-Field Volume 155
H.2.3.2 Residual Solvent 155
11.2.3.3 Load Size 156
H.2.3.4 Exposure Duration 158
H.2.4 Spot Cleaning Parameters 158
H.2.4.1 Near-Field Volume 158
H.2.4.2 Spot Cleaning Use Rate 158
H.2.4.3 Exposure Duration 159
H.2.5 Other Parameters 159
H.2.5.1 Operating Hours 159
H.2.5.2 Operating Days per Year 159
H.2.5.3 Fractional Number of Operating Days that a Worker Works 159
Appendix I Spot Cleaning Near-Field/Far-Field Inhalation Exposure Model Approach
and Parameter 160
I.1 Model Design Equations 160
1.2 Model Parameters 164
I.2.1 Far-Field Volume 167
1.2.2 Near-Field Volume 167
1.2.3 Air Exchange Rate 167
1.2.4 Near-Field Indoor Wind Speed 167
1.2.5 Averaging Time 168
1.2.6 Use Rate 168
1.2.7 Vapor Generation Rate 168
1.2.8 Operating Hours 168
Appendix J Dermal Exposure Assessment Method 170
J. 1 Incorporating the Effects of Evaporation 170
J. 1.1 Modification of EPA/OPPT Models 170
J. 2 Calculation of fabs 170
J.2.1 Small Doses (Case l:Mo Msat) 172
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J. 3 Comparison of fabs to Experimental Values for I -BP 173
J.4 Potential for Occlusion 174
J. 5 Incorporating Glove Protection 175
J.6 Proposed Dermal Dose Equation 176
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LIST OF TABLES
Table 1-1. Assigned Protection Factors for Respirators in OSHA Standard 29 CFR 1910.134 .. 16
Table 2-1. Number of Potentially Exposed Workers at Manufacturing Facilities (2016 CDR)... 19
Table 2-2. Statistical Summary of 8-hr 1-BP TWA Exposures (AC, ADC and LADC) for
Manufacturing Based on Monitoring Data (U.S. Facility, Closed System) 20
Table 2-3. Statistical Summary of 12-hr 1-BP TWA Exposures (AC, ADC and LADC) for
Manufacturing Based on Monitoring Data (Chinese Facility, Open System) 21
Table 2-4. Number of Potentially Exposed Workers at Import Facilities 22
Table 2-5. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Import and
Repackaging Based on Modeling 23
Table 2-6. Estimated Number of Sites and Workers for Industrial Intermediate Uses (2016 CDR)
24
Table 2-7. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Processing as a
Reactant Based on Modeling 25
Table 2-8. Estimated Number of Sites and Workers for Processing - Incorporation into
Formulation, Mixture or Reaction Product (2016 CDR) 26
Table 2-9. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for
Processing/Formulation Based on Monitoring Data 28
Table 2-10. Estimated Number of Workers Potentially Exposed during Incorporation of 1-BP
into Articles for NAICS 326150 28
Table 2-11. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Processing -
Incorporation into Articles Based on Modeling 29
Table 2-12. Number of Sites and Potentially Exposed Workers for Repackaging (2016 CDR).. 30
Table 2-13. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Repackaging
Based on Modeling 31
Table 2-14. Estimated Number of Workers Potentially Exposed to 1-BP in Degreasing Uses ... 34
Table 2-15. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Vapor
Degreasing Based on Monitoring Data 36
Table 2-16. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Vapor
Degreasing Based on Modeling 39
Table 2-17. Estimated Number of Workers Potentially Exposed to 1-BP in Batch Closed-Loop
Degreasing 41
Table 2-18. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Batch
Closed-Loop Vapor Degreasing Based on Modeling 42
Table 2-19. Estimated Number of Workers Potentially Exposed to 1-BP for Conveyorized Vapor
Degreasers 48
Table 2-20. Statistics of OTVD and Conveyorized Degreaser Emissions and Operating Time
Data from 2014 NEI 49
Table 2-21. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Cold
Cleaning Based on Monitoring Data 52
Table 2-22. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Cold
Cleaning Based on Modeling 53
Table 2-23. Estimated Number of Workers Potentially Exposed to 1-BP in Aerosol Degreasing
55
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Table 2-24. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for
Aerosol Degreasing Based on Monitoring Data 56
Table 2-25. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for
Aerosol Degreasing Based on Modeling 57
Table 2-26. Estimated Number of Workers Potentially Exposed to 1-BP in Dry Cleaning Shops
59
Table 2-27. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Dry
Cleaning Based on Monitoring Data 61
Table 2-28. Statistical Summary of 1-BP Dry Cleaning Exposures for Workers and Occupational
Non-users based on Modeling 65
Table 2-29. Statistical Summary of 1-BP Dry Cleaning Exposures for Children based on
Modeling 65
Table 2-30. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Spot Cleaning
Based on Monitoring Data 67
Table 2-31. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Use
of Spot Cleaning at Dry Cleaners Based on Modeling 68
Table 2-32. Estimated Number of Workers Potentially Exposed to 1-BP in Spray Adhesive Use
in Foam Cushion Manufacturing 70
Table 2-33. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Spray
Adhesive on Monitoring Data 72
Table 2-34. Estimated Number of Workers Potentially Exposed to 1-BP during Waste Handling
77
Table 2-35. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Disposal Based
on Modeling 78
Table 2-36. Glove Protection Factors for Different Dermal Protection Strategies 79
Table 2-37. Estimated Dermal Retained Dose (mg/day) for Workers in All Conditions of Use. 83
LIST OF FIGURES
Figure 2-1. Use of Vapor Degreasing in a Variety of Industries 32
Figure 2-2. Batch Open-Top Vapor Degreaser 33
Figure 2-3. Open-Top Vapor Degreaser with Enclosure 34
Figure 2-4. Schematic of the Near-Field/Far-Field Model for Vapor Degreasing 37
Figure 2-5. Closed-loop/Vacuum vapor Degreaser 40
Figure 2-6. Monorail Conveyorized Vapor Degreasing System (U.S. EPA, 1977) 43
Figure 2-7. Cross-Rod Conveyorized Vapor Degreasing System (U.S. EPA, 1977) 44
Figure 2-8. Vibra Conveyorized Vapor Degreasing System (U.S. EPA, 1977) 45
Figure 2-9. Ferris Wheel Conveyorized Vapor Degreasing System (U.S. EPA, 1977) 46
Figure 2-10. Belt/Strip Conveyorized Vapor Degreasing System (U.S. EPA, 1977) 46
Figure 2-11. Continuous Web Vapor Degreasing System 47
Figure 2-12. Typical Batch-Loaded, Maintenance Cold Cleaner (U.S. EPA, 1981) 50
Figure 2-13. Illustration for Use of Cold Cleaner in a Variety of Industries 51
Figure 2-14. The Near-Field/Far-field Model for Cold Cleaning Scenario 53
Figure 2-15. Overview of Aerosol degreasing 54
Figure 2-16. Schematic of the Near-Field/Far-Field Model for Aerosol degreasing 57
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Figure 2-17. Overview of Dry Cleaning 60
Figure 2-18. Illustration of the Multi-Zone Model 63
Figure 2-19. Overview of Use of Spot Cleaning at Dry Cleaners 66
Figure 2-20. Schematic of the Near-Field/Far-Field Model for Spot Cleaning 67
Figure 2-21. Overview of Use of Spray Adhesive in the Furniture Industry 69
Figure 2-22. Typical Industrial Incineration Process 75
Figure 2-23. General Process Flow Diagram for Solvent Recovery Processes 76
LIST OF APPENDIX TABLES
Table_Apx A-l. Affected NAICS Codes for Select 1-BP Conditions of Use 98
TableApx A-2. SOCs with Worker and ONU Designations for All Conditions of Use Except
Dry Cleaning 99
Table Apx A-3. SOCs with Worker and ONU Designations for Dry Cleaning Facilities 99
Table_Apx A-4. Estimated Number of Potentially Exposed Workers and ONUs under NAICS
812320 101
Table Apx B-l. Parameter Values for Calculating Acute Concentration 104
Table Apx B-2. Parameter Values for Calculating ADC and LADC 104
Table Apx B-3. Parameter Values for Calculating ADC and LADC for Dry Cleaning 105
Table Apx B-4. Parameter Values for Calculating AC, ADC and LADC using 12-hr TWA
Exposure Concentration 105
Table Apx C-l. Summary of DOD Exposure Monitoring Data 106
Table Apx D-l. Example Dimension and Volume of Loading Arm/Transfer System 109
Table Apx D-2. Default Values for Calculating Emission Rate of 1-BP from Transfer/Loading
Arm 109
Table Apx D-3. Parameters for Calculating Emission Rate of 1-BP from Equipment Leaks... 110
Table_Apx D-4. Default Values for Fa and N Ill
Table Apx D-5. Parameters for Calculating Exposure Concentration Using the EPA/OPPT Mass
Balance Model 113
Table Apx D-6. Calculated 1-BP Emission Rates and Resulting Exposures from the Tank Truck
and Railcar Loading and Unloading Release and Inhalation Exposure Model ..114
TableApx E-l. Summary of Parameter Values and Distributions Used in the Open-Top Vapor
Degreasing Near-Field/Far-Field Inhalation Exposure Model 120
TableApx F-l. Summary of Parameter Values and Distributions Used in the Open-Top Vapor
Degreasing Near-Field/Far-Field Inhalation Exposure Model 125
Table Apx G-l. Summary of Parameter Values and Distributions Used in the Brake Servicing
Near-Field/Far-Field Inhalation Exposure Model 136
Table Apx G-2. Summary of 1-Bromopropane-Based Aerosol Degreaser Formulations 140
Table Apx H-l. Summary of Parameter Values and Distributions Used in the Open-Top Vapor
Degreasing Near-Field/Far-Field Inhalation Exposure Model 151
Table Apx H-2. Composite Distribution of Dry Cleaning Facility Floor Areas 153
Table Apx H-3. Survey Responses of Actual Pounds Washed per Load for Primary Machine (if
more than one machine) from 2010 King County Survey 156
Table Apx H-4. Distribution of Actual Load Sizes from 2010 King County Survey 157
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TableApx 1-1. Summary of Parameter Values and Distributions Used in the Spot Cleaning
Near-Field/Far-Field Inhalation Exposure Model 165
Table Apx 1-2.Composite Distribution of Dry Cleaning Facility Floor Areas 167
Table Apx J-l. Estimated Fraction Evaporated and Absorbed (fabs) using Steady-State
Approximation for Large Doses 173
Table Apx J-2. Exposure Control Efficiencies and Protection Factors for Different Dermal
Protection Strategies from ECETOC TRA v3 176
LIST OF APPENDIX FIGURES
FigureApx D-l. Illustration of Transfer Lines Used During Tank Truck Unloading and
Associated Equipment Assumed by EPA 112
Figure Apx E-l. The Near-Field/Far-Field Model as Applied to the Open-Top Vapor Degreasing
Near-Field/Far-Field Inhalation Exposure Model and the Cold Cleaning Near-
Field/Far-Field Inhalation Exposure Model 116
Figure Apx G-l. The Near-Field/Far-Field Model as Applied to the Brake Servicing Near-
Field/Far-Field Inhalation Exposure Model 130
FigureApx H-l. Illustration of the Dry Cleaning Multi-Zone Inhalation Exposure Model 144
Figure Apx H-2. Fit Comparison of Beta Cumulative Distribution Function to Load Size Survey
Results 158
Figure Apx 1-1. The Near-Field/Far-Field Model as Applied to the Spot Cleaning Near-
Field/Far-Field Inhalation Exposure Model 161
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ABBREVIATIONS
l-BP 1-Bromopropane
AC Acute Concentration
ACGIH American Conference of Government Industrial Hygienists
ADC Average Daily Concentration
APF Assigned Protection Factor
BLS Bureau of Labor Statistics
CARB California Air Resources Board
CBI Confidential Business Information
CDC Centers for Disease Control
CDR Chemical Data Reporting
CEHD Chemical Exposure Health Data
CFR Code of Federal Regulations
COU Conditions of Use
CSHO Chemical Safety and Health Officer
DCM Dichloromethane
DOD Department of Defense
EC Engineering Control
EPA Environmental Protection Agency
ESD Emission Scenario Documents
HHE Health Hazard Evaluation
HSIA Halogenated Solvents Industry Association
IRTA Institute for Research and Technical Assistance
LADC Lifetime Average Daily Concentration
LEV Local Exhaust Ventilation
MassDEP Massachusetts Department of Environmental Protection
MWC Municipal Waste Combustor
NAICS North American Industry Classification System
NEI National Emissions Inventory
NEWMOA Northeast Waste Management Officials' Association
NKRANot Known or Reasonably Ascertainable
NIOSH National Institute of Occupational Safety and Health
OCSPP Office of Chemical Safety and Pollution Prevention
OECD Organisation for Economic Co-operation and Development
OES Occupational Employment Statistics
ONU Occupational Non-User
OPPT Office of Pollution Prevention and Toxics
OSHA Occupational Safety and Health Administration
OTVD Open-Top Vapor Degreaser
PAPR Power Air-Purifying Respirator
PERC Perchloroethylene
PBZ Personal Breathing Zone
PEL Permissible Exposure Limit
PESS Potentially Exposed Susceptible Subpopulation
PPE Personal Protective Equipment
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ppm Part(s) per Million
QC Quality Control
RCRA Resource Conservation and Recovery Act
SAR Supplied-Air Respirator
SCBA Self-Contained Breathing Apparatus
SNAP Significant New Alternatives Policy
SUSB Statistics of US Businesses
TCE Trichloroethylene
TLV Threshold Limit Value
TSCA Toxic Substances Control Act
TWA Time-Weighted Average
U.S. United States
VOC Volatile Organic Compound
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1 INTRODUCTION
This engineering report presents the occupational exposures to 1-Bromopropane (1-BP), and
supplements the draft risk evaluation of 1-BP under the Frank R. Lautenberg Chemical Safety
for the 21st Century Act. The Frank R. Lautenberg Chemical Safety for the 21st Century Act
amended the Toxic Substances Control Act (TSCA), the Nation's primary chemicals management
law, on June 22, 2016. The new law includes statutory requirements and deadlines for actions related
to conducting risk evaluations of existing chemicals.
In December of 2016, EPA published a list of 10 chemical substances that are the subject of the
Agency's initial chemical risk evaluations (81 FR 91927), as required by TSCA § 6(b)(2)(A). EPA's
designation of the first 10 chemical substances constituted the initiation of the risk evaluation process
for each of these chemical substances, pursuant to the requirements of TSCA § 6(b)(4). The scope
documents for all first 10 chemical substances were issued on June 22, 2017, and the problem
formulation documents were issued on May 31, 2018. The risk evaluation for each chemical will be
completed on or before December 2019. This engineering report is being issued separately from the
risk evaluation report for 1-BP.
1.1 Background and Scope
This report addresses all conditions of use and pathways associated with industrial and
commercial activities, as described in EPA's May 2018 Problem Formulation Document for 1-
BP. TSCA § 3(4) defines the conditions of use as "the circumstances, as determined by the
Administrator, under which a chemical substance is intended, known, or reasonably foreseen to be
manufactured, processed, distributed in commerce, used, or disposed of.'' This report assesses
dermal and inhalation exposure in occupational settings.
1.2 General Approach and Methodology for Number of Sites and
Workers
Where possible, EPA determined the number of sites and workers using data reported under the
Chemical Data Reporting (CDR) Rule. The CDR Rule, issued under the TSCA, requires
manufacturers and importers to report certain information on the chemicals they produce
domestically or import into the United States. For the 2016 CDR cycle, manufacturers and
importers of chemicals listed on the TSCA inventory were required to report if their production
volume exceeded 25,000 pounds at a single site during any of the calendar years 2012, 2013,
2014 or 2015.
For conditions of use where CDR data are insufficient, EPA determined the number of sites that
manufacture, process, and use 1-BP using readily available market data and data from Section 3
of the Toxics Release Inventory (TRI), "Activities and Uses of the Toxic Chemical at the
Facility". In addition, EPA determined the number of workers by analyzing Bureau of Labor
Statistics (BLS) and U.S. Census data using the methodology described in Appendix A. This
methodology was previously described in the 2016 draft Risk Assessment of 1-BP.
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1.3 General Approach and Methodology for Occupational Exposures
EPA assessed occupational exposures following the analysis plan published in the May 2018
Problem Formulation Document. Specific assessment methodology is described in further detail
below for each type of assessment.
1.3.1 Inhalation Exposure Assessment Approach and Methodology
To assess inhalation exposure, EPA reviewed available exposure monitoring data and mapped
them to specific conditions of use. The monitoring data used in the assessment include data
collected by government agencies such as OSHA and NIOSH, and data found in published
literature. For each exposure scenario and worker job category ("worker" or "occupational non-
user"), where available, EPA calculated the 95th and 50th percentile exposure levels from the
observed data set. The 95th percentile exposure concentration represents high-end exposure to 1-
BP across the distribution of available exposure data. The 50th percentile exposure concentration
represents a typical exposure level. For this assessment, only personal breathing zone (PBZ)
monitoring data were used to determine the time-weighted average (TWA) exposure
concentration. TWA exposure concentrations are then used to calculate the Acute Concentration
(AC), Average Daily Concentrations (ADC) and Lifetime Average Daily Concentration (LADC)
using the approach and equations described in Appendix B.
For several conditions of use, EPA modeled exposure in occupational settings. The models were
used to either supplement existing exposure monitoring data or to provide exposure estimates
where data are insufficient. For example, EPA used the Tank Truck andRailcar Loading and
Unloading Release and Inhalation Exposure Model to estimate worker exposure during
container and truck unloading activities that occur at industrial facilities. EPA also refined its
exposure models from the 2016 draft Risk Assessment to address peer review comments.
1.3.2 Dermal Exposure Assessment Approach and Methodology
Although inhalation pathway is expected to be the most important route for 1-BP, dermal
exposure may be important in contributing to the overall exposure. During the 2016 peer review
of the draft 1-BP Risk Assessment, peer reviewers recommended that quantitative estimates of
dermal exposure be included to address this pathway. Peer reviewers also noted the possible
occupational exposure scenarios where dermal contact is occluded, and as such, dermal
absorption may be significant.
EPA assessed dermal exposure to workers by modifying the EPA/OPPT 2-HandDermal
Exposure to Liquids Model. The report presents several occupational dermal exposure scenarios,
accounting for the potential for evaporation, glove use, and occlusion. Dermal exposure
assessment is described in more detail in Section 2.17.
1.3.3 Respiratory Protection
OSHA's Respiratory Protection Standard (29 CFR 1910.134) provides a summary of respirator
types by their assigned protection factor (APF). APF means the workplace level of respiratory
protection that a respirator or class of respirators is expected to provide to employees when the
employer implements a continuing, effective respiratory protection program according to the
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requirements of OSHA's Respiratory Protection Standard. Respirators, and any personal
protective equipment, is the last mean of worker protection, and should only be considered when
process design and engineering control cannot reduce workplace exposure to an acceptable level.
Exposure to 1-BP can cause irritation and can damage the nervous system. If respirators are
necessary in atmospheres that are not immediately dangerous to life or health, workers must use
NIOSH-certified air-purifying respirators or NIOSH-approved supplied-air respirators which
have the appropriate APF. Respirators that meet these criteria include air-purifying respirators
with organic vapor cartridges. Respirators must meet or exceed the required level of protection
listed in Table 1-1.
Based on the protection standards, inhalation exposures may be reduced by a factor of 5 to
10,000, assuming workers and occupational non-users are complying with the standard.
Table 1-1. Assigned Protection Factors for Respirators in OSHA Standard 29 CFR
1910.134
Type of Respirator
Quarter
Mask
Half Mask
Full
Facepiece
Helmet/
Hood
Loose-
fitting
Facepiece
1. Air-Purifying Respirator
5
10
50
2. Power Air-Purifying Respirator (PAPR)
50
1,000
25/1,000
25
3. Supplied-Air Respirator (SAR) or
Airline Respirator
• Demand mode
10
50
• Continuous flow mode
50
1,000
25/1,000
25
• Pressure-demand or other positive-
pressure mode
50
1,000
4. Self-Contained Breathing Apparatus
(SCBA)
• Demand mode
10
50
50
• Pressure-demand or other positive-
pressure mode (e.g., open/closed
circuit)
10,000
10,000
Source: 1910.134(d)(3)(i)(A)
1.4 Peer Review Comments
Prior to the Lautenberg Act, EPA completed a draft risk assessment for 1-BP, addressing
occupational and consumer uses in spray adhesives, dry cleaning (including spot cleaning), vapor
degreasing, aerosol degreasing, and cold cleaning. The draft assessment was published in
February 2016 and peer reviewed in May 2016.
EPA has reviewed and evaluated public and peer review comments provided on the 2016 draft
risk assessment. Where appropriate, EPA made editorial changes to improve the clarity and flow
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of the assessment. EPA also reviewed additional data and information provided by the
commenters and considered changes to enhance the assessment approach. As part of this process,
EPA updated the dry cleaning (including spot cleaning), vapor degreasing, aerosol degreasing,
and cold cleaning models to address peer review comments and to incorporate latest available
data. Example model updates include truncating the upper-bound of certain model input
parameters (e.g. air speed) to a reasonable high-end value and changing the exposure averaging
period from 8-hr TWA to 12-hr TWA in the dry cleaning model.
This report also includes a quantitative assessment of dermal exposure, including assessment of
potential for occlusion in select conditions of use, in response to the 2016 peer review comments.
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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) from the assessment for each exposure scenario.
2.1 Manufacture
2.1.1 Process Description
1-BP is produced by reacting n-propyl alcohol with hydrogen bromide and then removing the
excess water that forms in the process (N 13). The reaction product may then be distilled,
neutralized with sodium hydrogen carbonate, stored, and packaged (Ichihara et at.. 2004). The
purity of the final product may range from 96 percent (Li et at.. 2010) to over 99.9 percent
(OSHA., 2013a).
The manufacturing process may be either batch or continuous. Based on a site visit in 2013
conducted by PEC, Icarus Environmental, and OSHA representatives, one major U.S.
manufacturer of 1-BP operates a continuous, closed production process for 24 hours per day and
7 days per week (OSHA. 2013a).
2.1.2 Number of Sites and Potentially Exposed Workers
The CDR Rule requires manufacturers and importers to provide EPA information on the
chemicals they produce domestically or import into the United States. Based on CDR data, EPA
identified two domestic 1-BP manufacturers, Albemarle Corporation and Chemtura Corporation,
for calendar year 2015. Table 2-1 below summarizes the number of workers reasonably likely to
be exposed to 1-BP at the two manufacturing facilities, as reported in the 2016 CDR (
2017a). The term "reasonably likely to be exposed", for the purpose of CDR, means "an
exposure to a chemical substance which, under foreseeable conditions of manufacture,
processing, distribution in commerce, or use of the chemical substance, is more likely to occur
than not to occur". These exposures would include activities such as charging reactor vessels,
drumming, bulk loading, cleaning equipment, maintenance operations, materials handling and
transfer, and analytical operations. The estimate also includes persons whose employment
requires them to pass through areas where chemical substances are manufactured, processed, or
used, i.e., those who may be considered "occupational non-users", such as production workers,
foremen, process engineers, and plant managers. There are at least 35 to less than 75 potentially
exposed workers and ONUs at the two manufacturing sites.
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Table 2-1. Number of Potentially Exposed Workers at Manufacturing Facilities (2016
CDR)
Company
Facility
Facility Location
Number of
Workersa
Likely to be
Exposed
Basis for
Manufacturing
Determination
City
State
Albemarle
Corporation
Albemarle Corp South
Plant
Magnolia
AR
25 - <50
2016 CDR (Sec.
2.B.4)
Chemtura
Corporation
Great Lakes Chemical -
Central
El
Dorado
AR
10 - <25
2016 CDR (Sec.
2.B.4)
Total
35-73
Source: (U.S. EPA. 2017a)
a May include both workers and ONUs
2.1.3 Exposure Assessment
2.1.3.1 Worker Activities
Typical worker activities at a manufacturing facility include: 1) collecting and analyzing quality
control (QC) samples; 2) routine monitoring of the process, making process changes, or
responding to process upsets; and 3) loading finished products containing 1-BP into containers
and tank trucks. The specific activity and the potential exposure level may differ substantially
depending on the facility's operation, process enclosure, level of automation, engineering
control, and personal protective equipment (PPE). For example, at a U.S. manufacturing facility,
workers were observed to spend most of their time in a control room monitoring the production
process via a computerized system. QC samples are taken and analyzed inside a laboratory fume
hood, and in some cases, in a nitrogen purge dry box. Product loading is controlled using a
computerized system; smart-hoses and a vent line are used to minimize leaks and to capture
vapors generated during loading. At this facility, employees wear safety glasses, nitrile gloves,
and steel toe shoes when performing product sampling and laboratory analysis. In addition,
operators wear a full chemical suit1 during truck loading, including a full-face respirator
equipped with organic vapor cartridges (OSHA. 2013a). The company has an industrial hygiene
program where all employees are trained on PPE and work practices according to their job
duties.
In contrast, a recent study among three 1-BP manufacturing facilities in China indicate that none
of the workers were observed to wear PPE. These workers manually add chemicals into reaction
pots, pour final product into drums, and adjust the final drum volume with hand scoops (Li et al..
2010).
2.1.3.2 Occupational Exposure Assessment Methodology
1-BP exposure monitoring data were identified for one manufacturing facility in the U.S.
(OSHA. 2013a) and a facility in China. Although the Chinese study may not be representative of
work practices and exposure levels at U.S. facilities, data from this study are presented for
1 Chemical resistant pants and jacket with hood, steel-toed rubber boots, chemical resistant gloves, and full-face
respirator equipped with organic vapor cartridges.
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comparison purposes, and may be indicative of potential exposure levels in the absence of
adequate engineering controls and workplace protection.
2.1.3.3 Occupational Exposure Results
Table 2-2 presents the exposure levels from an OSHA site visit to a U.S. manufacturing facility.
The purpose of the site visit was to collect information on 1-BP production process, engineering
controls, and potential exposures. OSHA performed personal sampling on two operators during
two consecutive shifts and on one laboratory technician; the company also collected
simultaneous samples for result comparison and verification. In the table, the high-end exposure
value represents the maximum TWA exposure among the three workers sampled, and the central
tendency value represents the median exposure. EPA assumed the TWA exposures approximate
8-hr TWA because actual sampling time ranged from 429 to 449 minutes (7.2 to 7.5 hour).
Exposure was highest during truck loading, which occurs once every 24 hours, with the night
shift operator having an exposure of 2.61 ppm during a 78-minute personal breathing zone
sample. The operator wore a full-face respirator during this activity (OSHA. 2013a).
Table 2-3 presents the 95th and 50th percentile exposures surveyed by Ichihara et al. (2004) at a
factory located in Jiangsu province, China. As most employees at this facility also worked 12-
hour shifts, the data are assumed to represent 12-hr TWA. In comparison to the U.S. facility,
exposure levels in China are more than two orders of magnitude higher, and the
authors/investigators themselves complained of nasal and conjunctival irritation following visits
to the facility. Exposure concentration was highest when workers transferred produced solvents
into containers.
Table 2-2. Statistical Summary of 8-hr 1-BP TWA Exposures (AC, ADC and LADC) for
Manufacturing Based on Monitoring Data (U.S. Facility, Closed System) i
Acute and Chronic, Non-Cancer
Exposures (8-Hour TWAs in
Chronic, Cancer Exposures
ppm)
(ppm)
ACl-BP, 8-hr TWA and ADCl-BP, 8-hr
Data
TWA
LADC 1-BP, 8-hr TWA
Points
High-end
Central
High-end
Central
Category
(Maximum)
tendency
(Maximum)
tendency
Workera
0.27
0.09
0.14
0.04
3
Source: (OSHA. 2013a) (U.S. facility)
AC = Acute Concentration; ADC = Average Daily Concentration and LADC = Lifetime Average Daily Concentration,
a - Because OSHA and the company took simultaneous samples, two sets of exposure monitoring data are available
for each worker. For the same worker, EPA used the higher of the two TWA exposure results. For the lab technician
and the day shift operator, EPA used company results (OSHA experienced a pump malfunction while performing
sampling on the lab technician, and OSHA results for the day shift operator were below the reporting limit of 0.007
ppm of OSHA's sampling and analytical method PV2061). For the night shift operator, EPA used OSHA results.
The workers worked 12-hour shifts but were not exposed to 1-BP for the entire shift; exposure data are available as
8-hr TWA exposures.
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Table 2-3. Statistical Summary of 12-hr 1-BP TWA Exposures (AC, ADC and LADC) for
Manufacturing Based on Monitoring Data (Chinese Facility, Open System) i
Acute, Non-Cancer
Chronic, Non-Cancer
Exposures (12-Hour
Exposures (24-Hour
Chronic, Cancer
TWAs in ppm)
TWAs in ppm)
Exposures (ppm)
ACl-BP, 12-hr TWA
ADC 1-BP, 24-hr TWA
LADCl-BP, 24-hr TWA
95th
50th
95th
50th
95th
50th
Data
Category
Percentile
Percentile
Percentile
Percentile
Percentile
Percentile
Points
Worker
167.9
45.2
59.8
16.1
30.7
6.39
26
Source: (Ichihara et al.. 2004)
2.2 Import
2.2.1 Process Description
Commodity chemicals such as 1-BP may be 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. The type and size of container will vary depending on customer requirement. In some
cases, QC samples may be taken at import sites for analyses. Some import facilities may only
serve as storage and distribution locations, and repackaging/sampling may not occur at all import
facilities.
1-BP may be imported neat or as a component in a formulation. In the 2016 CDR, most
companies reported importing 1-BP at concentrations greater than 90 percent; one company
reported importing a formulation containing 1 to 30 percent 1-BP.
The total 1-BP import volume is claimed CBI in the 2016 CDR. However, recent data from other
sources estimate an import volume of 10.3 million pounds of brominated derivatives of acrylic
hydrocarbons, which includes 1-BP and other chemicals. (ATSDR 2016)
2.2.2 Number of Sites and Potentially Exposed Workers
In the 2016 CDR, seven companies reported importing 1-BP into the United States during
calendar year 2015. In addition, Superior Oil Company, Inc. reported to the CDR but withheld its
activity information in Section 2.B.4 of CDR Form U (U.S. EPA. 2017a). Based on its facility
address, it is likely an import office, rather than industrial manufacturing facility.
Table 2-4 below summarizes the number of persons (including workers and ONUs) reasonably
likely to be exposed to 1-BP at the import facilities, as reported in the 2016 CDR (where
available). Of these import facilities, six facilities estimated that fewer than 10 employees per
site are likely to be exposed, and one facility estimated 25 to up to 50 employees are likely to be
exposed.
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Table 2-4. Number of Potentially Exposed Workers at Im
port Facilities
Company
Facility
Facility Location
Number of
Workers a
Likely to be
Exposed
Basis for Import
Determination
City
State
CBI
CBI
CBI
CBI
<10
2016 CDR (Sec.
2.B.4)
Custom Synthesis,
LLC
Custom Synthesis
LLC
Anderson
SC
25 - <50
2016 CDR (Sec.
2.B.4)
Enviro Tech
International Inc
Enviro Tech
International Inc
Melrose
Park
IL
<10
2016 CDR (Sec.
2.B.4)
ICL North America
ICL-IP America Inc.
St. Louis
MO
<10
2016 CDR (Sec.
2.B.4)
MC International, LLC
MC International,
LLC
Miami
FL
<10
2016 CDR (Sec.
2.B.4)
Phoenix Chemical Co
Inc
Phoenix Chemical Co
Calhoun
GA
<10
2016 CDR (Sec.
2.B.4)
Superior Oil Company,
Inc.
Superior Oil
Company, Inc.
Indianapoli
s
IN
Withheld
2016 CDR (Address)
WEGO Chemical
Group
WEGO Chemical &
Mineral Corp
Great Neck
NY
<10
2016 CDR (Sec.
2.B.4)
Total
31 - 103
Source: (U.S. EPA. 2017a)
a - May include both workers and ONUs
2.2.3 Exposure Assessment
2.2.3.1 Worker Activities
Workers are potentially exposed during repackaging and sampling, if these activities occur at
import sites. Workers near loading racks and container filling stations are potentially exposed to
fugitive emissions as containers are filled. They are also potentially exposed via dermal contact
with liquid.
ONUs are employees who work at the facility where 1-BP is handled, but who do not directly
perform the repackaging and sampling activity. ONUs are expected to have lower inhalation
exposures and are not expected to have dermal exposures. ONUs include supervisors, managers,
and tradesmen.
2.2.3.2 Occupational Exposure Assessment Methodology
EPA has not identified exposure monitoring data for import. Therefore, EPA assessed exposure
using the Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure
Model, assuming 1-BP is present at 100 percent concentration when imported or repackaged.
The model provides inhalation exposure estimates to volatile liquid chemicals during outdoor
loading and unloading activities at an industrial facility. The model accounts for the emissions of
saturated air containing the chemical of interest 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. The model assumes industrial facilities use a vapor recovery system to
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minimize air emissions, such that vapor losses from displacement of saturated air inside the
container is mitigated using such systems. See Appendix D for detailed description of this model.
For the high-end scenario, the model assumes the use of an engineered loading system, such as a
loading arm, and that the operation occurs outdoor with a wind speed of 5 miles per hour (mph).
For the central tendency scenario, the model assumes the use of a 12-foot transfer hose with two-
inch diameter, with an average outdoor wind speed of 9 mph. For the purpose of this assessment,
loading/unloading event is assumed to occur once per work shift. Combining published EPA
emission factors and engineering calculations with the EPA OPPTMass Balance Inhalation
Model (peer reviewed), this model estimates central tendency and high-end exposure
concentrations for chemical unloading scenarios at industrial facilities.
2.2.3.3 Occupational Exposure Results
As shown in Table 2-5, the Tank Truck andRailcar Loading and Unloading Release and
Inhalation Exposure Model estimates a high-end and central tendency exposure level of 0.06
ppm and 0.01 ppm as 8-hr TWA, respectively, during container unloading activities. The "high-
end" exposure represents a railcar loading scenario, and the "central tendency" exposure
represents a tank truck loading scenario. Note the model does not estimate separate exposure
levels for workers and ONUs for this activity.
Table 2-5. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Import and
Category
Acute and Chronic, Non-Cancer
Exposures (8-Hour TWAs in
ppm)
ACl-BP, 8-hr TWA and ADCl-BP, 8-hr
TWA
High-end Central tendency
Chronic, Cancer Exposures (ppm)
LADCl-BP, 8-hr TWA
High-end Central tendency
Worker
6.01E-2 1.14E-2
3.08E-2 4.55E-3
2.3 Processing as a Reactant
2.3.1 Process Description
Processing as a reactant or intermediate is the use of 1-BP as a raw material in the production of
another chemical, in which 1-BP is reacted and consumed. In the early to mid-1990s, 1-BP was
used as an intermediate in the production of pesticides, quaternary ammonium compounds,
flavors and fragrances, pharmaceuticals, and other chemicals (HSIA. 2010). In the present day,
1-BP is used as an intermediate in the production of other organic chemicals, inorganic
chemicals, pharmaceuticals, pesticides, fertilizers, and other agricultural chemicals (Enviro Tech
International 2017a). The extent of these uses is not known, as the volumes are claimed CBI in
the 2016 CDR (HSIA. 2010).
2.3.2 Number of Sites and Potentially Exposed Workers
EPA identified the number of sites and workers using downstream industrial processing and use
information reported by manufacturers and importers in Part III, Section A of the CDR Form U.
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As shown in Table 2-6, 1-BP is potentially used as a chemical intermediate at between three and
27 sites, where 30 to 72 workers and ONUs are potentially exposed. CDR does not differentiate
between workers and ONUs. CDR also does not provide the identity of these downstream sites.
Information reported under the TRI program indicates Dow Chemical's Midland, MI facility is a
processing site (U.S. EPA. 2016b).
Table 2-6. Estimated Number of Sites and Workers for Industrial Intermediate Uses (2016
CDR)
Reporting
Company
Type of
Process
NAICS
code
Industrial Sector
Industrial
Function
Category
Number
of Sites
Number of
Workers
Basis for
Processing
Determination
Albemarle
Corporation
Processing as
a reactant
32518
All Other Basic
Inorganic Chemical
Manufacturing
Intermediates
<10
10 - <25
2016 CDR
Chemtura
Corporation
Processing as
a reactant
32519
All Other Basic
Organic Chemical
Manufacturing
Intermediates
<10
10 - <25
2016 CDR
Chemtura
Corporation
Processing as
a reactant
3253
Pesticide, Fertilizer,
and Other Agricultural
Chemical
Manufacturing
Intermediates
<10
10 - <25
2016 CDR
Total
3-27
30-72
Source: (U.S. EPA. 2017a)
2.3.3 Exposure Assessment
2.3.3.1 Worker Activities
At industrial facilities, workers are potentially exposed when unloading 1-BP from transport
containers into intermediate storage tanks and process vessels. Workers may be exposed via
inhalation of vapor or via dermal contact with liquids while connecting and disconnecting hoses
and transfer lines. Once 1-BP is unloaded into process vessels, it is consumed as a chemical
intermediate.
ONUs are employees who work at the facilities that process 1-BP, but who do not directly
handle the material. ONUs may also be exposed to 1-BP but are expected to have lower
inhalation exposures and are not expected to have dermal exposures. ONUs for this condition of
use may include supervisors, managers, engineers, and other personnel in nearby production
areas.
2.3.3.2 Occupational Exposure Assessment Methodology
See Section 2.2.3.2 for the assessment of worker exposure from chemical unloading activities.
EPA assumes the exposure sources, routes, and exposure levels are similar to those at an
import/repackaging facility. The exposure results are presented in Table 2-7.
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Table 2-7. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Processing
Category
Acute and Chrc
Exposures (8-
PI
AC 1-BP, 8-hr TWA
T
High-end
nic, Non-Cancer
Hour TWAs in
>m)
and ADCl-BP, 8-hr
WA
Central
tendency
Chronic, Can
(IT
LADCi-b
High-end
cer Exposures
m)
P, 8-hr TWA
Central
tendency
Worker
6.01E-2
1.14E-2
3.08E-2
4.55E-3
2.4 Processing - Incorporation into Formulation, Mixture, or
Reaction Product
2.4.1 Process Description
After manufacture, 1-BP may be supplied directly to end-users, or may be incorporated into
various products and formulations at varying concentrations for further distribution.
Incorporation into a formulation, mixture, or reaction product refers to the process of mixing or
blending several raw materials to obtain a single product or preparation. For example,
formulators may add stabilizing packages to 1-BP for specialized vapor degreasing uses (Enviro
Tech International 2017a) or mix 1-BP with other additives to formulate adhesives, sealants, and
other products.
In a 2010 study, Hanley et al. describes the process of formulating adhesive products containing
1-BP at one facility:
"...a large variety of glues, sealants, and coatings were manufacturedfor a
multitude of commercial and industrial applications using water-, epoxy-, and
organic solvent-basedformulas. When charging the batch mixers, large volume
solvents (e.g. 1-BP) were dispensed through an enclosed piping manifold system.
Solid chemicals were added manually through hatch openings, which otherwise
remained closed during mixing. After blending, the finished product was pumped
into buckets, drums, or bulk tanks using semi-enclosed methods. Local exhaust
ventilation was not provided for the mixing vessels or packaging locations.
Instead, each bay on the charging and packing floors were serviced with high
volume dilution ventilation consisting of air supply and exhaust system located on
opposite walls to produce directional airflow. A solvent blend containing over 96
percent 1-BP was used as the principal solvent in one product line. This adhesive
was made approximately once every 45 days(Hanley et al.. 2010)
It is not known whether the specific equipment and engineering controls cited by Hanley et al.
(Hanley et al.. 2010) is representative of other facilities. However, the general process activities
(e.g., unloading of raw materials into mixing vessels) are likely similar across different
formulation facilities.
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2.4.2 Number of Sites and Potentially Exposed Workers
EPA identified the number of sites and workers using downstream industrial processing and use
information reported by manufacturers and importers in Part III, Section A of the CDR Form U.
As shown in Table 2-8, the number of 1-BP formulation sites ranges from 33 to 992. This range
is consistent with the estimate provided in the Analysis of Economic Impacts of Final nPB [1-
bromopropane] rulemaking for Cleaning Solvent Sector of the SNAP program, which estimated
that in 2007, there were seven companies that formulated solvent-based products containing 1-
BP, three companies that formulated adhesive products containing 1-BP, an additional 60 small
providers of specialty products3 that contained 1-BP, and approximately 20 or 25 companies that
prepared aerosol formulations with 1-BP (U.S. EPA. 2007a). The number of workers and ONUs
likely exposed ranges from 220 to 1,046. CDR does not differentiate between workers and
ONUs.
Table 2-8. Estimated Number of Sites and Workers for Processing - Incorporation into
Formulation, Mixture or Reaction Product (2016 CDR)
Reporting
Company
Type of Process
NAICS
code
Industrial Sector
Industrial
Function
Category
Number
of Sites
Number
of
Workersa
CBI
Processing -
incorporation into
formulation, mixture,
or reaction product
11
Agriculture,
Forestry, Fishing
and Hunting
Agricultural
chemicals (non
pesticidal)
NKRA
NKRA
Albemarle
Corporation
Processing -
incorporation into
formulation, mixture,
or reaction product
325998
All Other
Chemical Product
and Preparation
Manufacturing
Solvents (for
cleaning or
degreasing)
<10
10 - <25
Chemtura
Corporation
Processing -
incorporation into
formulation, mixture,
or reaction product
3256
Soap, Cleaning
Compound, and
Toilet Preparation
Manufacturing
Solvents (for
cleaning or
degreasing)
10 - <25
100-
<500
Custom
Synthesis,
LLC
Processing -
incorporation into
formulation, mixture,
or reaction product
335
Electrical
Equipment,
Appliance, and
Component
Manufacturing
Solvents (for
cleaning or
degreasing)
10 - <25
100-
<500
ICL
Processing -
incorporation into
formulation, mixture,
or reaction product
334
Computer and
Electronic Product
Manufacturing
Solvents (for
cleaning or
degreasing)
10 - <25
NKRA
2 CDR does not provide the identity of these formulation sites.
3 In a 2017 public comment, Enviro Tech stated that most of these additional companies merely market the same
products produced by one of the seven major solvent manufacturers, sometimes under a private label. Enviro Tech
International is a major supplier of 1-BP and fluorinated solvents. (Enviro Tech International. 2017a)
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Reporting
Company
Type of Process
NAICS
code
Industrial Sector
Industrial
Function
Category
Number
of Sites
Number
of
Workersa
MC
International,
LLC
Processing -
incorporation into
formulation, mixture,
or reaction product
32552
Adhesive
Manufacturing
Solvents (which
become part of
product
formulation or
mixture)
<10
NKRA
Wego
Chemical and
Mineral Corp.
Processing -
incorporation into
formulation, mixture,
or reaction product
51, 52,
53, 54,
55, 56,
61,62,
71, 72,
81, 92
Services
Solvents (for
cleaning or
degreasing)
<10
10 - <25
Total
33-99
220-
1,046
a May include both workers and ONUs
Source: (U.S. EPA. 2017a)
2.4.3 Exposure Assessment
2.4.3.1 Worker Activities
At formulation facilities, workers are potentially exposed when unloading 1-BP into mixing
vessels, taking QC samples, and packaging formulated products into containers and tank trucks.
The exact activities and associated level of exposure will differ depending on the degree of
automation, presence of engineering controls, and use of PPE at each facility.
2.4.3.2 Occupational Exposure Assessment Methodology
For formulation of 1-BP into products, EPA assessed exposure using a Hanley et al. (2010)
exposure study at an adhesive manufacturing facility. Exposure monitoring data are not available
for other types of formulation facilities.
2.4.3.3 Occupational Exposure Results
In a 2010 study, Hanley et al. measured the breathing zone concentration of 1-BP at one adhesive
manufacturing facility. The study did not provide detailed data to allow determination of 95th and
50th percentile exposures, but stated that the geometric mean full-shift (8 to 10 hour) TWA
measurement was 3.79 ppm for those who handled 1-BP products (workers), and 0.33 ppm for
those who did not use 1-BP (i.e., ONUs). The maximum exposure value was 18.9 ppm TWA for
those who directly used 1-BP, and 1.59 ppm TWA for those who did not use 1-BP (Hanley et al..
2010). Table 2-9 presents the maximum and central tendency (geometric mean) exposure levels
reported in this study. Note the maximum exposure value at this single facility may not be the
maximum possible exposure across the distribution of all formulation facilities in the U.S.
Exposure levels at other facilities will differ from those observed by Hanley et al (2010)
depending on the process controls and PPE employed at each workplace.
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Table 2-9. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for
Processing/Formulation Based on Monitoring
)ata
Category
Acute and Chrc
Exposures (8-
PI
ACl-BP, 8-hr TWA
T
Maximum
>nic, Non-Cancer
Hour TWAs in
>m)
and ADC l-BP, 8-hr
WA
Central tendency
Chronic, Cancer
LADCib
Maximum
Exposures (ppm)
P, 8-hr TWA
Central tendency
Data
Points
Worker
18.9
3.79
9.69
1.51
3
ONU
1.59
0.33
0.82
0.13
8
Source: (Hanlev et al.. 2010)
2.5 Processing - Incorporation into Articles
2.5.1 Process Description
According to EPA's Use Dossier, 1-BP is present at less than 5 percent concentration in the
THERMAX™ brand insulation manufactured by Dow Chemical (EPA-HQ-QPPT-2016-0741 -
0003). THERMAX™ is a polyisocyanurate rigid board insulation for interior and exterior
applications, and can be used on walls, ceilings, roofs, and crawl spaces in commercial and
residential buildings. The product is marketed to have superior durability and fire performance
over generic polyisocyanurate insulations.4 EPA does not have information on the exact process
for producing THERMAX™ and the function of 1-BP in the insulation material (Dow. 2018).
2.5.2 Number of Sites and Potentially Exposed Workers
Dow's website indicates insulation products containing 1-BP are produced at its Pennsauken, NJ
facility (Dow. 2018). The number of potentially exposed workers at this specific facility is not
known; however, EPA estimated the number of workers at facilities characterized under NAICS
326150s, "Urethane and Other Foam Product (except Polystyrene) Manufacturing" using Bureau
of Labor Statistics' OES data (2015) and U.S. Census SUSB (2012). The method for estimating
number of workers is detailed in Appendix A. The analysis indicates an average of 15 potentially
exposed workers and 4 ONUs per site.
Table 2-10. Estimated Number of Workers Potentially Exposed during Incorporation of 1-
BP into Articles for NAICS 326150
Exposed
Workers
Exposed
Occupational
Non-Users
Total
Exposed
Estimated
Number of
Establishments
Workers per Site
Occupational
Non-Users per
Site
15
4
19
1
15
4
2.5.3 Exposure Assessment
4 https://www.dow.com/en-us/products/thermaxbrandinsulation#sort=%40gtitle%20ascending
5 The Dow facility reports a primary NAICS of 326150 in the 2016 and 2017 TRI
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2.5.3.1 Worker Activities
The exact process and worker activity at the Dow facility is not known; however, workers at this
site may be potentially exposed when unloading 1-BP from transport containers into mixing
vessels and taking QC samples. Actual levels of exposure will depend on the degree of
automation, presence of engineering controls, and use of PPE.
2.5.3.2 Occupational Exposure Assessment Methodology
EPA did not find monitoring data for this condition of use. EPA modeled exposure using the
Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model, which
estimates high-end and central tendency exposure concentrations for chemical unloading
scenarios at industrial setting. See Section 2.2.3.2 for the assessment of worker exposure from
chemical unloading activities. The exposure results are presented in Table 2-11.
Table 2-11. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Processing
Category
Acute and Chronic, Non-Cancer
Exposures (8-Hour TWAs in
PPm)
ACl-BP, 8-hr TWA and ADCl-BP, 8-hr
TWA
High-end Central tendency
Chronic, Cancer Exposures (ppm)
LADCl-BP, 8-hr TWA
High-end Central tendency
Worker
6.01E-2 1.14E-2
3.08E-2 4.55E-3
2.6 Repackaging
2.6.1 Process Description
Chemicals shipped in bulk containers may be repackaged into smaller containers for resale, such
as drums or bottles. The type and size of container will vary depending on customer requirement.
In some cases, QC samples may be taken at repackaging sites for analyses. Note repackaging
could occur for both domestic and imported shipments of 1-BP; repackaging activities that occur
at import facilities are addressed in Section 2.2.
2.6.2 Number of Sites and Potentially Exposed Workers
EPA identified the number of sites and workers using downstream industrial processing and use
information reported by manufacturers and importers in Part III, Section A of the CDR Form U.
As shown in Table 2-12, one company reported up to 10 downstream repackaging sites with 10
to up to 25 workers. Another company reported downstream repackaging activities but indicated
the number of sites and workers were not known or reasonably ascertainable (U.S. EPA. 2017a).
EPA does not know the identity of these sites. In addition, EPA does not know whether these
sites are exclusive repackaging sites or whether they also fall under other 1-BP conditions of use.
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Table 2-12. Number of Sites and Potentially Exposed Workers for Repackaging (2016
CDR) *
Reporting
Company
Type of Process
NAICS
code
Industrial Sector
Industrial
Function
Category
Number
of Sites
Number
of
Workersa
Albemarle
Corporation
Processing -
repackaging
325998
All other chemical
product and
preparation
manufacturing
Solvents (for
cleaning and
degreasing)
<10
10 - <25
Phoenix
Chemical Co
Inc
Processing -
repackaging
NKRA
NKRA
NKRA
NKRA
NKRA
Total
<10
10 - <25
Source: (U.S. EPA. 2017a)
a - May include both workers and ONUs
NKRA - Not known or reasonably ascertainable
2.6.3 Exposure Assessment
2.6.3.1 Worker Activities
During repackaging, workers are potentially exposed while connecting and disconnecting hoses
and transfer lines to import bulk containers (e.g., railcars, tank trucks, totes), intermediate storage
vessels (e.g., storage tanks, pressure vessels), and final packaging containers (e.g., drums,
bottles). Workers near loading racks and container filling stations are potentially exposed to
fugitive emissions as containers are filled. They are also potentially exposed via dermal contact
with liquid.
ONUs are employees who work at the facility where 1-BP is repackaged, but who do not directly
perform the repackaging activity. ONUs are expected to have lower inhalation exposures and are
not expected to have dermal exposures. ONUs for repackaging include supervisors, managers,
and tradesmen that may be in the repackaging area but do not perform tasks that result in the
same level of exposures as repackaging workers.
2.6.3.2 Occupational Exposure Assessment Methodology
EPA has not identified exposure monitoring data for repackaging. Therefore, EPA assessed
exposure using the Tank Truck and Railcar Loading and Unloading Release and Inhalation
Exposure Model. See Section 2.2.3.2 for the assessment of worker exposure from chemical
unloading activities.
2.6.3.3 Occupational Exposure Results
As shown in Table 2-13, the Tank Truck and Railcar Loading and Unloading Release and
Inhalation Exposure Model estimates a high-end and central tendency exposure level of 0.06
ppm and 0.01 ppm as 8-hr TWA, respectively, during container unloading activities. The "high-
end" exposure represents a railcar loading scenario, and the "central tendency" exposure
represents a tank truck loading scenario. Note the model does not estimate separate exposure
levels for workers and ONUs for this activity.
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Table 2-13. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for
Repackaging Based on Modeling
Category
Acute and Chronic, Non-Cancer
Exposures (8-Hour TWAs in
PPm)
ACl-BP, 8-hr TWA and ADCl-BP, 8-hr
TWA
High-end Central tendency
Chronic, Cancer Exposures (ppm)
LADCl-BP, 8-hr TWA
High-end Central tendency
Worker
6.01E-2 1.14E-2
3.08E-2 4.55E-3
2.7 Batch Vapor Degreaser (Open-Top)
2.7.1 Process Description
Vapor degreasing is a process used to remove dirt, grease, and surface contaminants in a variety
of industries, including but not limited to (Enviro Tech International 2017a):
• Electronic and electrical product and equipment manufacturing;
• Metal, plastic, and other product manufacturing, including plating;
• Aerospace manufacturing and maintenance cleaning;
• Cleaning skeletal remains; and
• Medical device manufacturing.
Figure 2-1 is an illustration of vapor degreasing operations, which can occur in a variety of
industries.
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Fabrication
Shops
Metal
Plating
Shops
Electronics
Assembly
Shops
o
V«w D«»iw
« *
°o
- >w
# ad
V«« DiWfUW
I I
V«fwDfS«iSaB
» I
ti*
I . I -*1
* id
Repair
Shops
<3%
H
O
Ya«J© DtMtASiWS
M
:0:
:«>:
a
Figure 2-1. Use of Vapor Degreasing in a Variety of Industries
1-BP is often used to replace chlorinated solvents, especially in applications where flammability
is a concern (CRC Industries Inc.. 2017). 1-BP is also desirable because of its low corrosivity,
compatibility with many metals, and suitability for use in most modern vapor degreasing
equipment. Vapor degreasing may take place in batches or as part of an in-line (i.e., continuous)
system. In batch machines, each load (parts or baskets of parts) is loaded into the machine after
the previous load is completed. With in-line systems, parts are continuously loaded into and
through the vapor degreasing equipment as well as the subsequent drying steps. Vapor
degreasing equipment can generally be categorized into one of the three categories: (1) batch
vapor degreasers, (2) conveyorized vapor degreasers and (3) web vapor degreasers.
In batch open-top vapor degreasers (OTVDs), a vapor cleaning zone is created by heating and
volatilizing the liquid solvent in the OTVD. Workers manually load or unload fabricated parts
directly into or out of the vapor cleaning zone. The tank usually has chillers along the side of the
tank to prevent losses of the solvent to the air. However, these chillers are not able to eliminate
emissions, and throughout the degreasing process significant air emissions of the solvent can
occur. These air emissions can cause i ssues with both worker health and safety as well as
environmental issues. Additionally, the cost of replacing solvent lost to emissions can be
expensive ( 1EWMOA. 2001). Figure 2-2 illustrates a standard OTVD. The use of 1-BP in
OTVD has been previously described in EPA's 2016 Draft Risk Assessment (U.S. EPA. 2016c).
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Condensing Coils
.Water Jacket
O
O
Vapor Zone
T/Water Separator
O
Boiling sump
Heat Source
Figure 2-2. Batch Open-Top Vapor Degreaser
OTVDs with enclosures operate the same as standard OTVDs except that the OTVD is enclosed
on all sides during degreasing. The enclosure is opened and closed to add or remove parts
to/from the machine, and solvent is exposed to the air when the cover is open. Enclosed OTVDs
may be vented directly to the atmosphere or first vented to an external carbon filter and then to
the atmosphere (U.S. EPA; ICF Consulting. 2004). Figure 2-3 illustrates an OTVD with an
enclosure. The dotted lines in Figure 2-3 represent the optional carbon filter that may or may not
be used with an enclosed OTVD.
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—I
Carbon Filter
•vent
Loading/
unloading
lock
[
Boiling su
Heat Sou
np-
ce-
Vapor Zone
¦s
]
Wate
z
Condensing Coils
Jacket
er Separator
Figure 2-3. Open-Top Vapor Degreaser with Enclosure
2.7.2 Number of Sites and Potentially Exposed Workers
EPA estimated the number of workers potentially exposed to 1-BP in vapor degreasing using
Bureau of Labor Statistics' OES data (2015) and U.S. Census SUSB (2012). The method for
estimating number of workers is detailed in Appendix A and the 2016 Draft Risk Assessment
(U.S. EPA, 2016c). Table 2-14 presents the estimated number of workers and occupational non-
users based on industry- and occupational-specific employment data.
The number of businesses that use 1-BP for vapor degreasing is estimated at 500 to 2,500
businesses (CDC. 2016). EPA assumes each business equates to one site and that each site has
one degreasing unit. The total number of potentially exposed workers and occupational non-
users is estimated at 4,712 to 23,558. Because EPA was unable to determine which industry
sectors and occupations perform specific degreasing types (e.g., OTVD, conveyorized vapor
degreasing, cold cleaning), these estimates likely cover a range of degreasing operations and are
not specific to OTVD.
Table 2-14. Estimated Number of Workers Potentially Exposed to 1-BP in Degreasing Uses
Exposed
Workers
Exposed
Occupational
non-users
Total Exposed
Estimated
Number of
Establishments
Workers per
Site
Occupational
non-users per
Site
Low-end
3,245
1,466
4,712
500
6
3
High-end
16,226
7,332
23,558
2,500
6
3
Note: Number of workers and occupational non-users per site are calculated by dividing the exposed number of
workers or occupational non-users by the number of establishments. Values are rounded to the nearest integer.
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2.7.3 Exposure Assessment
2.7.3.1 Worker Activities
When operating a batch vapor degreaser, workers manually load or unload fabricated parts directly
into or out of the vapor cleaning zone. Worker exposure can occur from solvent dragout or vapor
displacement when the substrates enter or exit the equipment, respectively ("Kanegsberg and
Kanegsberg. 2011). Worker exposure is also possible while charging new solvent or disposing spent
solvent.
2.7.3.2 Occupational Exposure Assessment Methodology
For vapor degreasing, EPA assessed exposure using available monitoring data and model results.
2.7.3.3 Occupational Exposure Results
Monitoring Data
Table 2-15 summarizes the 1-BP exposure data for vapor degreasing operations. EPA obtained
exposure monitoring data from several sources, including journal articles (e.g., (Hanlev et at..
2010)). NIOSH Health Hazard Evaluations (HHEs), the OSHA Chemical Exposure Health Data
(CEHD) database, and data submitted to EPA's SNAP program. NIOSH HHEs are conducted at
the request of employees, employers, or union officials, and provide information on existing and
potential hazards present in the workplaces evaluated. OSHA CEHD are workplace monitoring
data from OSHA inspections; EPA SNAP program data are collected as part of the EPA's effort
to identify substitutes for ozone-depleting substances. Some of these data, such as monitoring
data conducted during OSHA inspections, are not intended to be representative of typical
exposure levels.
Data from these sources cover exposure at a variety of industries that conduct vapor degreasing,
including telecommunication device manufacturing, aerospace parts manufacturing, electronics
parts manufacturing, helicopter transmission manufacturing, hydraulic power control component
manufacturing, metal product fabrication, optical prism and assembly, and printed circuit board
manufacturing. It should be noted that sources that only contain a statistical summary of worker
exposure monitoring, but exclude the detailed monitoring results, are not included in EPA's
analysis below.
Most of the gathered data were for batch open-top vapor degreasers, except for data from OSHA
and EPA's SNAP program, where the type of degreaser is typically not specified. EPA included
these data in the analysis despite uncertainty in the degreaser type. Note the 2016 draft Risk
Assessment previously categorized data as either pre- or post-Engineering Control. After further
evaluation, EPA removed these categories because we determined there is insufficient
information on engineering control at all facilities to accurately characterize the dataset.
EPA defined a vapor degreasing "worker" as an employee who operates or performs
maintenance tasks on the degreaser, such as draining, cleaning, and charging the degreaser bath
tank. EPA defined "occupational non-user" as an employee who does not handle 1-BP but
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performs work in the surrounding area. Some data sources do not describe their work activities in
detail, and the exact proximity of these occupational non-users to the degreaser is unknown. As
shown in the table, workers are exposed to significant levels of 1-BP, with 95th and 50th
percentile exposures of 49.4 and 6.70 ppm as 8-hr TWA, respectively. For occupational non-
users, the 95th and 50th percentile exposure levels are below 3 ppm as 8-hr TWA.
Table 2-15. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for
Vapor Degreasing Based on Monitoring Data
Category
Acute and Chrc
Exposures (8-
PI
ACl-BP, 8-hr TWA
T
95th Percentile
>nic, Non-Cancer
Hour TWAs in
>m)
and ADC l-BP, 8-hr
WA
50th Percentile
Chronic, Cancer
LADCib
95th Percentile
Exposures (ppm)
P, 8-hr TWA
50th Percentile
Data
Points
Worker
49.4
6.70
25.3
2.66
153
ONU
2.15
0.02
1.10
0.01
18
Source: (OSHA. 2013b: NIOSH. 2001) (OSHA. 2019) (U.S. EPA. 2006b).
Model Data
The Vapor Degreasing model, including all model input parameters, was previously peer
reviewed as part of the 2016 draft 1-BP Risk Assessment. A more detailed description of the
modeling approach is provided Appendix E.
Figure 2-4 illustrates the near-field / far-field model that can be applied to vapor degreasing
(KeiK 2009). As the figure shows, volatile 1-BP vapors evaporate into the near-field, resulting in
worker exposures at a concentration Cnf. The concentration is directly proportional to the
evaporation rate of 1-BP, G, into the near-field, whose volume is denoted by Vnf. The
ventilation rate for the near-field zone (Qnf) determines how quickly 1-BP dissipates into the far-
field, resulting in occupational non-user exposures to 1-BP at a concentration Cff. Vff denotes
the volume of the far-field space into which the 1-BP dissipates out of the near-field. The
ventilation rate for the surroundings, denoted by Qff, determines how quickly 1-BP dissipates
out of the surrounding space and into the outside air.
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Far-Field
Volatile Source
Figure 2-4. Schematic of the Near-Field/Far-Field Model for Vapor Degreasing
Appendix E presents the equations, model parameters, parameter distributions, and assumptions
for the 1-BP vapor degreasing model. To estimate the 1-BP vapor generation rate, the model
references an emission factor developed by the California Air Resources Board (CARB) for the
California Solvent Cleaning Emissions Inventories (CARB. 2011). CARB surveyed facilities that
conduct solvent cleaning operations and gathered site-specific information for 213 facilities.
CARB estimated a 1-BP emission factor averaging 10.43 lb/employee-yr, with a standard
deviation of 17.24 lb/employee-yr, where the basis is the total number of employees at a facility.
The majority of 1-BP emissions were attributed to the vapor degreasing category.
It should be noted that the "vapor degreasing" category in CARB's study includes the batch-
loaded vapor degreaser, aerosol surface preparation process, and aerosol cleaning process. It is
not known what percentage, if any, of the 1-BP emission factor is derived from aerosol
applications. This modeling approach assumes the 1-BP emission factor is entirely attributed to
vapor degreasing applications. The emission factor is expected to represent emissions from
batch-loaded degreasers used in California at the time of study. It is not known whether these are
specifically open-top batch degreasers, although open-top is expected to be the most common
design. The CARB survey data did not include emissions for conveyorized vapor degreasers.
The CARB emission factor is then combined with U.S. employment data for vapor degreasing
industry sectors from the Economic Census6. The 1-BP RA identified 78 NAICS industry codes
that are applicable to vapor degreasing. For these industry codes, the Census data set indicates a
6 For the purpose of modeling, EPA/OPPT used data from the 2007 Economic Census for the vapor degreasing
NAICS codes as identified in the TCE RA (U.S. EPA. 2014b). The 2012 Economic Census did not have
employment data (average number of employees per establishment) for all vapor degreasing NAICS codes of
interest.
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minimum industry average of 8 employees per site, with a 50th percentile and 90th percentile of
25 and 61 employees per site, respectively. A lognormal distribution is applied to the Census
data set to model the distribution of the industry-average number of employees per site for the
NAICS codes applicable to vapor degreasing.
These nationwide Census employment data are comparable to the 2008 California employment
data cited in CARB's study. According to the CARB study, approximately 90 percent of solvent
cleaning facilities in California had less than 50 employees (whereas the national Census data
estimate 90 percent of facilities have less than or equal to 61 employees). It is important to note
that the Census data report an average number of employees per site for each NAICS code. The
number of employees for each individual site within each NAICS code is not reported.
Therefore, the distribution EPA calculated represents a population of average facility size for
each NAICS code, and not the population of individual facility sizes over all NAICS codes.
The vapor generation rate, G (kg/unit-hr), is calculated in-situ within the model, as follows:
Equation 2-1 for Calculating Vapor Degreasing Vapor Generation Rate
G = EF x EMP / (2.20462 x OH x OD x U)
Where EF = emission factor (lb/employee-yr)
EMP = Number of employees (employee/site)
OH = Operating hours per day (hr/day)
OD = Operating days per year (day/yr)
U = Number of degreasing units (unit/site)
2.20462 = Unit conversion from lb to kg (lb/kg)
Batch degreasers are assumed to operate between two and 24 hours per day, based on NEI data
on the reported operating hours for OTVD using TCE. EPA performed a Monte Carlo simulation
with 100,000 iterations and the Latin Hypercube sampling method in @Risk7 to calculate 8-hour
TWA near-field and far-field exposure concentrations. Near-field exposure represents exposure
concentrations for workers who directly operate the vapor degreasing equipment, whereas far-
field exposure represents exposure concentrations for occupational non-users (i.e., workers in the
surrounding area who do not handle the degreasing equipment). The modeled 8-hr TWA results
and the values in Appendix B are used to calculate 8-hr acute exposure, ADC, and LADC.
Table 2-16 presents a statistical summary of the exposure modeling results. These exposure
estimates represent modeled exposures for the workers and occupational non-users. For workers,
the baseline (pre-engineering control) 50th percentile exposure is 1.89 ppm 8-hr TWA, with a
95th percentile of 23.9 ppm 8-hr TWA. Compared to literature studies:
• Hanley et al. (2010) reported a geometric mean of 2.63 ppm 8-hr TWA exposure with a
range of 0.078 to 21.4 ppm 8-hr TWA among 44 samples;
7 A risk analysis software tool (Microsoft Excel add-in) using Monte Carlo simulation.
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• NIOSH (2001) reported a range of 0.01 to 0.63 ppm 8-hr TWA among 20 samples; and
• A 2003 EPA analysis suggested that 87 percent of the samples were less than 25 ppm 8-
hr TWA among 500 samples at vapor degreasing facilities (U.S. EPA. 2003).
The modeled mean near-field exposure is found to be generally comparable to the exposures
reported in literature. For occupational non-users, the modeled far-field exposure has a 50th
percentile value of 0.99 ppm and a 95th percentile of 13.5 ppm 8-hr TWA. These modeled far-
field results are somewhat higher than reported literature values. (Hanlev et al.. 2010) reported
workers away from the degreasers are exposed at concentrations of 0.077 to 1.69 ppm 8-hr
TWA, with a geometric mean of 0.308 ppm 8-hr TWA. It should be noted that the modeled
exposures represent the potential exposure associated with batch-loaded degreasers, which
could include both 01VI) and batch-loaded, closed-loop vapor degreasers.
The model also presents a "post-Engineering Control" (post-EC) scenario by applying a 90
percent emission reduction factor to the baseline, pre-EC scenario. The estimate is based on a
Wadden et al. (1989) study, which indicates a LEV system for an open-top vapor degreaser
(lateral exhaust hoods installed on two sides of the tank) can be 90 percent effective (Wadden et
al.. 1989). This assumption is likely an overestimate because the study covered only reductions
in degreaser machine emissions due to LEV and did not address other sources of emissions such
as dragout, fresh and waste solvent storage and handling. Furthermore, a caveat in the study is
that most LEV likely do not achieve ACGIH design exhaust flow rates, indicating that the
emission reductions in many units may not be optimized. Actual exposure reductions from added
engineering controls can be highly variable and can only be verified by monitoring studies.
Table 2-16. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for
Vapor Degreasing Based on Modeling
Acute and Chronic, Non-Cancer Exposures
(8-Hour TWAs in ppm)
AC1-BP, 8-hr TWA and ADC 1-BP, 8-hr TWA
Chronic, Cancer Exposures (ppm)
LADC 1-BP, 8-hr TWA
Category
95th Percentile
50th Percentile
95th Percentile
50th Percentile
Worker, Pre EC
23.9
1.89
9.19
0.70
Worker, Post EC 90%
2.39
0.19
0.92
0.07
ONU, Pre EC
13.5
0.99
5.23
0.37
ONU, Post EC 90%
1.35
0.10
0.52
0.04
Pre-EC: refers to modeling where no reduction due to engineering controls was assumed
Post-EC: refers to modeling where engineering controls with 90% efficiency were implemented
2.8 Batch Vapor Degreaser (Closed-Loop)
2.8.1 Process Description
In closed-loop degreasers, parts are placed into a basket, which is then placed into an airtight
work chamber. The door is closed, and solvent vapors are sprayed onto the parts. Solvent can
also be introduced to the parts as a liquid spray or liquid immersion. When cleaning is complete,
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vapors are exhausted from the chamber and circulated over a cooling coil where the vapors are
condensed and recovered. The parts are dried by forced hot air. Air is circulated through the
chamber and residual solvent vapors are captured by carbon adsorption. The door is opened
when the residual solvent vapor concentration has reached a specified level (Kanegsberg and
Kanegsberg. 2011). Figure 2-5 illustrates a standard closed-loop vapor degreasing system.
Vent
Distillation
Solvent Abatement Loop
Solvent Tank(s)
Working Chamber
Workload
Solvent Sump
Refrigeration
2
Electric Heat
Figure 2-5. Closed-loop/Vacuum vapor Degreaser
Airless degreasing systems are also sealed, closed-loop systems, but remove air at some point of
the degreasing process. Removing air typically takes the form of drawing vacuum but could also
include purging air with nitrogen at some point of the process (in contrast to drawing vacuum, a
nitrogen purge operates at a slightly positive pressure). In airless degreasing systems with
vacuum drying only, the cleaning stage works similarly as with the airtight closed-loop
degreaser. However, a vacuum is generated during the drying stage, typically below 5 torr (5
mmHg). The vacuum dries the parts and a vapor recovery system captures the vapors
(Kanegsberg and Kanegsberg. 2011) CNEWMOA, 2001) (U.S. EPA. 2001a).
Airless vacuum-to-vacuum degreasers are true "airless" systems because the entire cycle is
operated under vacuum. Typically, parts are placed into the chamber, the chamber sealed, and
then vacuum drawn within the chamber. The typical solvent cleaning process is a hot solvent
vapor spray. The introduction of vapors in the vacuum chamber raises the pressure in the
chamber. The parts are dried by again drawing vacuum in the chamber. Solvent vapors are
recovered through compression and cooling. An air purge then purges residual vapors over an
optional carbon adsorber and through a vent. Air is then introduced in the chamber to return the
chamber to atmospheric pressure before the chamber is opened (Durkee. 2014) (NEWMOA.
2001). The general design of vacuum vapor degreasers and airless vacuum degreasers is similar
as illustrated in Figure 2-5 for closed-loop systems except that the work chamber is under
vacuum during various stages of the cleaning process.
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2.8.2 Number of Sites and Potentially Exposed Workers
According to IRTA, there may be as many as 2,000 vacuum degreasers in the U.S., of which
approximately 100 systems use 1-BP (IRTA, 2016)8. Table 2-17 presents the estimated number
of workers and ONUs at 100 facilities, assuming one unit per facility. It is unclear whether these
approximately 100 facilities are a subset of those facilities presented in Section 2.7.2.
Table 2-17. Estimated Number of Workers Potentially Exposed to 1-BP in Batch Closed-
Loop Degreasing
Exposed
Workers
Exposed
Occupational
non-users
Total Exposed
Estimated
Number of
Establishments
Workers per
Site
Occupational
non-users per
Site
649
293
942
100
6
3
Note: Number of workers and occupational non-users per site are calculated by dividing the exposed number of
workers or occupational non-users by the number of establishments. Values are rounded to the nearest integer.
2.8.3 Exposure Assessment
2.8.3.1 Worker Activities
For closed-loop vapor degreasing, worker activities can include placing or removing parts from
the basket, as well as general equipment maintenance. Workers can be exposed to residual vapor
as the door to the degreaser chamber opens after the cleaning cycle is completed.
2.8.3.2 Occupational Exposure Assessment Methodology
There are no 1-BP monitoring data specific to closed-loop degreasers. A NEWMOA study states
air emissions can be reduced by 98 percent or more when a closed-loop degreaser is used instead
of an open-top vapor degreaser (NEWMOA. 2001). This reduction factor is applied to the vapor
degreasing model results presented in Section 2.7.3.3 to estimate exposure to batch closed-loop
vapor degreasers. The approach assumes the CARB emission factor primarily represents
emissions from OTVDs, rather than other types of batch-loaded degreasers.
2.8.3.1 Occupational Exposure Results
Table 2-18 presents the exposure model results for batch closed-loop vapor degreasers. For
workers, the 95th and 50th percentile exposure levels are 0.48 and 0.04 ppm as 8-hr TWA. For
occupational non-users, the 95th and 50th percentile exposure levels are 0.27 and 0.02 ppm as 8-
hr TWA, respectively.
8 It is unclear whether the IRTA estimate includes other types of closed-loop degreasers.
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Table 2-18. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for
Batch Closed-Loop Vapor Degreasing Based on Modeling
Category
Acute and Chronic,
(8-Hour T
ACl-BP, 8-hr TWA a
95th Percentile
Non-Cancer Exposures
WAs in ppm)
id ADCl-BP, 8-hr TWA
50th Percentile
Chronic, Cancer
LADCii
95th Percentile
Exposures (ppm)
P, 8-hr TWA
50th Percentile
Worker
0.48
0.04
0.18
0.01
ONU
0.27
0.02
0.10
0.01
2.9 In-line Vapor Degreaser (Conveyorized)
2.9.1 Process Description
In conveyorized systems, an automated parts handling system, typically a conveyor,
continuously loads parts into and through the vapor degreasing equipment and the subsequent
drying steps. Conveyorized degreasing systems are usually fully enclosed except for the
conveyor inlet and outlet portals. Conveyorized degreasers are likely used in shops where large
number of parts need to be cleaned. There are seven major types of conveyorized degreasers:
monorail degreasers; cross-rod degreasers; vibra degreasers; ferris wheel degreasers; belt
degreasers; strip degreasers; and circuit board degreasers (U.S. EPA. 1977).
• Monorail Degreasers - Monorail degreasing systems are typically used when parts are
already being transported throughout the manufacturing areas by a conveyor (U.S. EPA).
They use a straight-line conveyor to transport parts into and out of the cleaning zone. The
parts may enter one side and exit and the other or may make a 180° turn and exit through
a tunnel parallel to the entrance (U.S. EPA. 1977). Figure 2-6 illustrates a typical
monorail degreaser.
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Monorail
Conveyoj
Path
Spray
Pump
Water
Jacket
Figure 2-6. Monorail Conveyorized Vapor Decreasing System (U.S. EPA, 1977)
• Cross-rod Degreasers - Cross-rod degreasing systems utilize two parallel chains
connected by a rod that support the parts throughout the cleaning process. The parts are
usually loaded into perforated baskets or cylinders and then transported through the
machine by the chain support system. The baskets and cylinders are typically manually
loaded and unloaded (U.S. EPA, 1977). Cylinders are used for small parts or parts that
need enhanced solvent drainage because of crevices and cavities. The cylinders allow the
parts to be tumbled during cleaning and drying and thus increase cleaning and drying
efficiency. Figure 2-7 illustrates a typical cross-rod degreaser.
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Conveyor Path
Work Basket
Water
Jacket
Boiling Chamber
Figure 2-7. Cross-Rod Conveyorized Vapor Degreasing System (U.S. EPA, 1977)
• Vibra Degreasers - In vibra degreasing systems, parts are fed by conveyor through a
chute that leads to a pan flooded with solvent in the cleaning zone. The pan and the
connected spiral elevator are continuously vibrated throughout the process causing the
parts to move from the pan and up a spiral elevator to the exit chute. As the parts travel
up the elevator, the solvent condenses, and the parts are dried before exiting the machine
(U.S. EPA. 1977). Figure 2-8 illustrates atypical vibra degreaser.
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Workload Discharger Chute
Ascending
Vibrating
Trough —
Condensers
Distillate
Trough
Workload
Entry Chute
G9
Distillate Return
For Counter-
flow Wash
Steam Coils
Figure 2-8. Vibra Conveyorized Vapor Decreasing System ( .S. EPA, 1977)
• Ferris wheel degreasers - Ferris wheel degreasing systems are generally the smallest of
all the conveyorized degreasers. In these systems, parts are manually loaded into
perforated baskets or cylinders and then rotated vertically through the cleaning zone and
back out ( S. EPA. 1977). Figure 2-9 illustrates a typical ferris wheel degreaser.
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Basket
Boll irig
Chamber
Work
Sear to
baskets
tumble
Figure 2-9. Ferris Wheel Conveyorized Vapor Degreasing System ( .S. EPA, 1977)
• Belt degreasing systems (similar to strip degreasers; see next bullet) are used when
simple and rapid loading and unloading of parts is desired. Parts are loaded onto a mesh
conveyor belt that transports them through the cleaning zone and out the other side (U.S.
EPA. 1977). Figure 2-10 illustrates a typical belt or strip degreaser.
Conveyor.
Path
Boiling
Chamber
Figure 2-10. Belt/Strip Conveyorized Vapor Degreasing System (U.S. EPA, 1977)
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• Strip degreasers - Strip degreasing systems operate similar to belt degreasers except that
the belt itself is being cleaned rather than parts being loaded onto the belt for cleaning
(U.S. EPA. 1977). Figure 2-10 illustrates a typical belt or strip degreaser.
• Circuit board cleaners - Circuit board degreasers use any of the conveyorized designs.
However, in circuit board degreasing, parts are cleaned in three different steps due to the
manufacturing processes involved in circuit board production (U.S. EPA, 1977).
Continuous web cleaning machines are a subset of conveyorized degreasers but differ in that
they are specifically designed for cleaning parts that are coiled or on spools such as films, wires,
and metal strips (Kanegsberg and Kanegsberg. 2011) (U.S. EPA. 2006a). In continuous web
degreasers, parts are uncoiled and loaded onto rollers that transport the parts through the cleaning
and drying zones at speeds greater than 11 feet per minute (U.S. EPA. 2006a). The parts are then
recoiled or cut after exiting the cleaning machine (Kanegsberg and Kanegsberg. 2011) (U.S.
EPA. 2006a). Figure 2-11 illustrates a typical continuous web cleaning machine.
Figure 2-11. Continuous Web Vapor Degreasing System
2.9.2 Number of Sites and Potentially Exposed Workers
According to IRTA, there are likely 1,000 conveyorized systems in use, of which 80 percent
(800 systems) use 1-BP (IRTA. 2016). Table 2-19 presents the estimated number of workers and
ONUs for these systems, based on the average number of worker and ONU per site from the
BLS data analysis.
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Table 2-19. Estimated Number of Workers Potentially Exposed to 1-BP for Conveyorized
Vapor Degreasers
Exposed
Workers
Exposed
Occupational
non-users
Total Exposed
Estimated
Number of
Establishments
Workers per
Site
Occupational
non-users per
Site
5,192
2,346
7,538
800
6
3
Note: Number of workers and occupational non-users per site are calculated by dividing the exposed number of
workers or occupational non-users by the number of establishments. Values are rounded to the nearest integer.
2.9.3 Exposure Assessment
2.9.3.1 Worker Activities
For conveyorized vapor degreasing, worker activities can include placing or removing parts from
the basket, as well as general equipment maintenance. Depending on the level of enclosure and
specific conveyor design, workers can be exposed to vapor emitted from the inlet and outlet of
the conveyor portal.
2.9.3.2 Occupational Exposure Assessment Methodology
There are no monitoring data specific to conveyorized degreasers that use 1-BP. Additionally,
there is not sufficient data to model exposure to 1-BP from these degreasers.
Table 2-20 compares the emission rates and operating hours for OTVD and conveyorized vapor
degreasers from the 2014 NEI. While NEI does not contain data specific to 1-BP, data for
dichloromethane (DCM), perchloroethylene (PERC), and trichloroethylene (TCE) show that
emissions from conveyorized vapor degreasers are generally similar to that from OTVDs. EPA
assumed the associated worker exposure for conveyorized degreasers may be similar to the
exposure levels presented in Section 2.7.3.3.
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Table 2-20. Statistics of OTVD and Conveyorized Degreaser Emissions and Operating Time Data from 2014 NEI
OTVD
Conveyor
DCM
PERC
TCE
DCM
PERC
TCE
kg/unit
-hr
Operating
hr/yr
kg/unit-
hr
Operating
hr/yr
kg/unit-
hr
Operating
hr/yr
kg/unit-
hr
Operating
hr/yr
kg/unit-
hr
Operating
hr/yr
kg/unit-
hr
Operating
hr/yr
Max
2.72
3,600
18.05
8,760
46.72
8,760
2.63
2,080
1.85
4,335
32.88
8,736
95th pet
2.49
3,360
11.47
8,760
5.16
8,736
2.61
2,028
29.66
8,736
50th pet
1.44
1,560
0.18
2,080
0.49
2,080
2.42
1,560
0.69
8,736
Mean
1.34
1,827
2.22
4,463
1.99
3,562
2.42
1,560
11.31
8,224
25th pet
0.81
1,176
0.02
1,000
0.05
1,028
2.31
1,300
0.52
7,968
Min
0.00
500
0.00
1
0.00
1
2.20
1,040
0.36
7,200
Count
9
9
15
15
87
87
2
2
1
1
3
3
Number of
Units
18
-
23
-
149
-
3
1
8
Number of
Sites
12
-
19
-
115
-
3
1
8
Avg Units/Site
1.50
-
1.21
-
1.30
-
1
1
1
Source: (U.S. EPA. 2018a).
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2.10 Cold Cleaner
2.10.1 Process Description
Cold cleaners are non-boiling solvent degreasing units. Cold cleaning operations include spraying,
brushing, flushing, and immersion. Figure 2-12 shows the design of a typical batch-loaded maintenance
cold cleaner, where dirty parts are cleaned manually by spraying and then soaking in the tank. After
cleaning, the parts are either suspended over the tank to drain or are placed on an external rack that
routes the drained solvent back into the cleaner. Batch manufacturing cold cleaners could vary widely
but have two basic equipment designs: the simple spray sink and the dip tank. The dip tank design
typically provides better cleaning through immersion, and often involves an immersion tank equipped
with agitation (U.S. EPA, 1981). Emissions from batch cold cleaning machines typically result from (1)
evaporation of the solvent from the solvent-to-air interface, (2) "carry out" of excess solvent on cleaned
parts, and (3) evaporative losses of the solvent during filling and draining of the machine (U.S. EPA.
2006a). Emissions from cold in-line (conveyorized) cleaning machines result from the same
mechanisms, but with emission points only at the parts entry and exit ports (U.S. EPA. 2006a).
Spray
Figure 2-12. Typical Batch-Loaded, Maintenance Cold Cleaner (U.S. EPA, 1981)
2.10.2 Number of Sites Potentially Exposed Workers
There is no information to determine the number of sites that operate 1-BP cold cleaners, and the
number of potentially exposed workers and occupational non-users. It is possible that some of the
degreasing facilities presented in Section 2.7.2 also use 1-BP as a cold cleaning solvent.
2.10.3 Exposure Assessment
2.10.3.1 Worker Activities
The general worker activities for cold cleaning include placing the parts that require cleaning into a
vessel. The vessel is usually something that will hold the parts but not the liquid solvent (i.e., a wire
basket). The vessel is then lowered into the machine, where the parts could be sprayed, and then
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completely immersed in the solvent. After a short time, the vessel is removed from the solvent and
allowed to drip or air dry. Depending on the industry and/or company, these operations may be
performed manually (i.e., by hand) or mechanically. Sometimes parts require more extensive cleaning;
in these cases, additional cleaning is performed including directly spraying, agitation, wiping or
brushing ( IOSI1. 2001; U.S. EPA. 1997).
Fabrication
Shops
> #
M *
Metal
Plating
Shops
Electronics
Assembly
Shops
Repair
Shops
I
o
V
e
J *
Q
V
« »
:0:
i i
V'
* V
1 t
I 1
Figure 2-13. Illustration for Use of Cold Cleaner in a Variety of Industries
2.10.3.2 Occupational Exposure Assessment Methodology
Occupational exposure to 1-BP used in cold cleaning is assessed using both monitoring data and
modeling results.
2.10.3.3 Occupational Exposure Results
Monitoring Data
Table 2-21 presents OSHA CEHD for two facilities. The first facility uses 1-BP to clean parts in an
immersion process in an area with general ventilation. The second facility uses 1-BP in a degreasing
tank equipped with a spray nozzle. The degreasing operation is conducted in an area with local exhaust
ventilation. Based on available process description, EPA assumes these facilities operate a cold cleaner,
even though the equipment is not described in detail in the OSHA CEHD. Among the five available data
points for workers, the maximum and central tendency exposures are 7.40 and 4.30 ppm 8-hr TWA,
respectively. For occupational non-users, the exposure value is based on a single data point for a
Chemical Safety and Health Officer (CSHO), who is an official from OSHA or a state plan occupational
safety and health program. The exposure for this individual measured 2.60 ppm 8-hr TWA. EPA
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presents this data point as what-if exposure for an occupational non-user; the exposure level may not be
representative because the CSHO is not regularly present in the production area. It should be further
noted that CEHD are obtained from OSHA inspections, and not intended to be representative of typical
worker exposure. Due to uncertainty in the data quality and the low number of available data points, the
assessed exposure may not be representative of the full range of cold cleaning exposure scenarios.
Table 2-21. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Cold
Cleaning Based on Monitoring Data
Category
Acute and Chrc
Exposures (8-Ho
AC l-BP, 8-hr twa ar
High-end (max)
>nic, Non-Cancer
ur TWAs in ppm)
d ADC 1-BP, 8-hr TWA
Central tendency
Chronic, Cancer
LADCib
High-end (max)
Exposures (ppm)
P, 8-hr TWA
Central tendency
Data
Points
Worker
7.40
4.30
3.79
1.71
5
ONU
2.60 (what-if)
1.33
1.0
1
Source: (OSHA. 2013b).
What-if: Represents a what-if inhalation exposure level for occupational non-user based on a single data point.
Model Data
The Cold Cleaning model, including all model input parameters, was previously peer reviewed as part of
the 2016 draft 1-BP Risk Assessment. A more detailed description of the modeling approach is provided
in Appendix F.
The EPA AP-42, Compilations of Air Pollution Emission Factors contains emission factors and process
information developed and compiled from source test data, material balance studies, and engineering
estimates (U.S. EPA. 1981). Chapter 4.6 provides generic, non-methane VOC emission factors for
several solvent cleaning operations, including cold cleaning and vapor degreasing. These emission
factors suggest that cold cleaning emissions range from 3.2 to 57.1 percent of the emissions from a
traditional open-top vapor degreaser (U.S. EPA, 1981). It is not known whether the emission factors
derived using VOC data would be representative of 1-BP emissions, or whether the emission reduction
when switching from vapor degreasing to cold cleaning would be similar across different chemicals. To
model exposures during 1-BP cold cleaning, an exposure reduction factor, RF, with uniform distribution
from 0.032 to 0.571 is applied to the vapor generation rate in the vapor degreasing model.
Figure 2-14 presents the model approach for cold cleaning. Except for the exposure reduction factor, the
model approach and input parameters for cold cleaning are identical to those previously presented for
batch vapor degreasing. EPA performed a Monte Carlo simulation with 100,000 iterations and the Latin
Hypercube sampling method in @Risk to estimate 8-hr TWA near-field and far-field exposures, acute
exposures, ADCs, and LADCs. Note the cold cleaning model approach and the underlying data used
(i.e. EPA AP-42) do not differentiate between a spray versus immersion cold cleaner.
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NF
Far-Field
Near-Field
NF
Volatile Source
> Q,
NF
Figure 2-14. The Near-Field/Far-field Model for Cold Cleaning Scenario
Table 2-22 presents a statistical summary of the exposure modeling results. For workers, the 95th and
50th percentile exposures are 11.91 ppm and 0.55 ppm 8-hr TWA. These exposure levels are
substantially lower than monitoring data. For occupational non-users, the 95th and 50th percentile
exposures are 6.83 ppm and 0.29 ppm 8-hr TWA.
Table 2-22. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Cold
Cleaning Based on
Modeling
Acute and Chronic, Non-Cancer Exposures
(8-Hour TWAs in ppm)
Chronic, Cancer Exposures (ppm)
AC1-BP, 8-hr TWA and ADC 1-BP, 8-hr TWA
LADCi
-BP, 8-hr TWA
Category
95th Percentile
50th Percentile
95th Percentile
50th Percentile
Worker
11.91
0.55
4.59
0.21
ONU
6.83
0.29
2.63
0.11
2.11 Aerosol Spray Degreaser/Cleaner
2.11.1 Process Description
Aerosol degreasing is a process that uses an aerosolized solvent spray, typically applied from a
pressurized can, to remove residual contaminants from fabricated parts. Based on identified safety data
sheets (SDS), 1-BP-based formulations typically use carbon dioxide, liquified petroleum gas (LPG) (i.e.,
propane and butane), 1,1,1,2-tetrafluoroethane, 1,1-difluoroethane, and pentafluorobutane as the carrier
gas (U.S. EPA. 2017b). The aerosol droplets bead up on the fabricated part and then drip off, carrying
away any contaminants and leaving behind a clean surface.
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Figure 2-15 illustrates the typical process of using aerosol degreasing to clean components in
commercial settings. One example of a commercial setting with aerosol degreasing operations is repair
shops, where service items are cleaned to remove any contaminants that would otherwise compromise
the service item's operation. Internal components may be cleaned in place or removed from the service
item, cleaned, and then re-installed once dry (U.S. EPA. 2014a). Example uses of aerosol products
containing 1-BP include brake cleaning, cable cleaning, aircraft degreasing, general purpose degreasing,
and metal product cleaning applications.
Figure 2-15. Overview of Aerosol degreasing
2.11.2 Number of Sites and Potentially Exposed Workers
NAICS industry sectors relevant to aerosol degreasing and BLS occupation codes where workers are
potentially exposed to degreasing solvents are detailed in the 2016 draft Risk Assessment. EPA assumed
the types of occupation with potential solvent exposure are similar between vapor degreasing and
aerosol degreasing.
There are 222,940 establishments among the industry sectors represented in Table 2-23. The EPA
market report on 1-BP estimated that "7,000 to 5,000 businesses used 1-BP-based aerosol solvents in
2002 (U.S. EPA. 2007b). as cited in (U.S. EPA. 2013b)". This translates to a market penetration of
approximately 0.4 percent to 2.2 percent. Based on these estimates, approximately 2,466 to 12,329
workers and occupational non-users are potentially exposed to 1-BP as an aerosol degreasing solvent. It
is unclear whether the number of establishments using 1-BP-based aerosol solvents has changed
substantially since 2002.
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Table 2-23. Est
imated Number of Workers Potentially Exposet
to 1-BP in Aerosol Degreasing
Exposed
Workers
Exposed
Occupational
non-users
Total Exposed
Estimated
Number of
Establishments
Workers per Site
Occupational non-
users per Site
Low-end
2,227
238
2,465
1,000
2
0.2
High-end
11,137
1,192
12,329
5,000
2
0.2
Note: Number of workers and occupational non-users per site are calculated by dividing the exposed number of workers or
occupational non-users by the number of establishments. The number of workers per site is rounded to the nearest integer.
The number of occupational non-users per site is shown as 0.2, as it rounds down to zero.
2.11.3 Exposure Assessment
2.11.3.1 Worker Activities
For aerosol degreasing, worker activities involve manual spraying of 1-BP products from an aerosol can
onto a substrate, and then subsequently wiping of that substrate. The same worker may also perform
other types of degreasing activities, if those process operations are present at the same facility.
2.11.3.2 Occupational Exposure Assessment Methodology
For aerosol degreasing, EPA assessed exposure using available exposure monitoring data and modeling
results.
2.11.3.3 Occupational Exposure Results
Monitoring Data
Table 2-24 summarizes 8-hr TWA PBZ monitoring data for aerosol degreasing obtained from (Stewart,
1998) and (Tech Spray. 2003). The Stewart (1998) study measured 1-BP worker PBZ during an aerosol
spray can application on a test substrate consisting of a small electric motor; the scenario was intended
to simulate workers performing typical repair and maintenance work. The (Tech Spray. 2003) study
measured worker exposure in a test scenario that simulated cleaning of printed circuit boards for the
repair of computers and electrical systems. Among the two test studies, the 95th and 50th percentile
worker exposures were 31.6 and 16.1 ppm, respectively.
The Tech Spray study tested an exposure scenario where the 1-BP aerosol degreasing occurred inside a
non-vented booth. Subsequently, the company tested the same scenario in a vented booth. With a non-
vented booth, worker exposure ranged from 13 to 32 ppm 8-hr TWA. With the vented booth, worker
exposure was reduced to 5.50 ppm 8-hr TWA based on a single data point. The vented booth scenario
has a constant draw of 0.9 cubic meters per second during the 8-hour test. The data suggest the
significance of ventilation and its impact on worker exposure. The single data point for worker exposure
in a vented booth represents a "what-if' exposure level for a post-EC scenario. The representativeness of
this exposure level is unknown.
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Table 2-24. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Aerosol
Degreasing Based on Monitoring Data
Categorya
Acute and Chrc
Exposures (8-Ho
AC l-BP, 8-hr twa ar
95th Percentile
>nic, Non-Cancer
ur TWAs in ppm)
d ADC 1-BP, 8-hr TWA
50th Percentile
Chronic, Cancer
LADCib
95th Percentile
Exposures (ppm)
P, 8-hr TWA
50th Percentile
Data
Points
Worker, Pre EC
31.6
16.1
16.18
6.4
6
Worker, Post EC
5.50 (what-if)
2.82
2.2
1
Source: Stewart (1998): Tech Spray (2003). as cited in (U.S. EPA. 2006b). The vented booth scenario from Tech Spray is
used as the post-EC scenario, and the remaining data points are used as the pre-EC scenario.
What-if: Represents a what-if inhalation exposure level based on a single data point.
a Worker includes operators, technicians, mechanics, and maintenance supervisor. Data are not available for occupational
non-users.
In addition to the data summarized above, the Tech Spray study included a test scenario that measured
short-term worker exposure that simulated an automotive repair shop. In this test, 1-BP was sprayed
continuously over a 15-minute period. In reality, workers are only expected to spray 1-BP for a few
minutes at a time; as such, the test was intended to simulate a "worst-case" scenario with heavy 1-BP
usage. The 15-min short term exposure for operators ranged from 190 to 1,100 ppm. Further, the 15-
minute short term exposure for a worker in an adjacent room measured 11 ppm ((Tech Spray, 2003). as
cited in (U.S. EPA, 2006b)). The presence of 1-BP in the adjacent room suggests the infiltration of
contaminated air into other work areas.
Model Data
As previously discussed in Section 2.11.1, a variety of workplaces can use aerosol degreaser containing
1-BP. For the purpose of modeling, EPA modeled worker exposure to 1-BP during brake servicing as a
representative exposure scenario. EPA chose to model this scenario because the process of brake
servicing is well understood and there is sufficient data to construct such a model. EPA believes brake
servicing and engine degreasing at automotive maintenance and repair shops is a common application
for products containing 1-BP, and the process is a representative aerosol degreasing scenario.
Figure 2-16 illustrates the Brake Servicing Near-Field/Far-Field Inhalation Exposure Model. The
general model framework was previously peer reviewed as part of the 2016 draft 1-BP Risk Assessment;
however, specific model parameters have been updated with data from a recent CARB study. As the
figure shows, 1-BP in aerosolized droplets immediately volatilizes into the near-field, resulting in
worker exposures at a 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 1-BP dissipates into the far-field (i.e., the facility space surrounding the near-field),
resulting in occupational non-user exposures to 1-BP at a concentration Cff. Vff denotes the volume of
the far-field space into which the 1-BP dissipates out of the near-field. The ventilation rate for the
surroundings, denoted by Qff, determines how quickly 1-BP dissipates out of the surrounding space and
into the outside air.
In this scenario, 1-BP vapors enter the near-field in non-steady "bursts," where each burst results in a
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sudden rise in the near-field concentration, followed by a more gradual rise in the far-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. The product application rate is based on a 2000 CARB
report for brake servicing, which estimates that each facility performs on average 936 brake jobs per
year, and that each brake job requires approximately 14.4 ounces of product. For each model iteration,
EPA determined the concentration of 1-BP by assuming the formulation could be one of 25 possible
aerosol degreasing products identified in the Use Dossier. Detailed model parameters and assumptions
are presented in Appendix G. EPA did not model a "post-EC" scenario because there is not sufficient
information to determine the type and effectiveness of engineering control at automotive and other
commercial degreasing facilities.
nf c
Non-
volatile Source
Figure 2-16. Schematic of the Near-Field/Far-Field Model for Aerosol degreasing
EPA performed a Monte Carlo simulation with 100,000 iterations and the Latin hypercube sampling
method to model near-field and far-field exposure concentrations in the aerosol degreasing scenario.
Table 2-25 presents a statistical summary of the exposure modeling results. The 95th and 50th percentile
exposures are 22.53 ppm and 6.37 ppm 8-hr TWA for workers, and 0.93 ppm and 0.11 ppm 8-hr TWA
for occupational non-users.
Table 2-25. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Aerosol
Degreasing Based on Modeling
Category
Acute and Chr
Exposures (8-H(
ACl-BP, 8-hr TWA a
95th Percentile
onic, Non-Cancer
)ur TWAs in ppm)
id ADCl-BP, 8-hr TWA
50th Percentile
Chronic, Cane
LAD(
95th Percentile
er Exposures (ppm)
> 1-BP, 8-hr TWA
50th Percentile
Worker
22.53
6.37
9.05
2.38
ONU
0.93
0.11
0.36
0.04
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2.12 Dry Cleaning
2.12.1 Process Description
1-BP is a solvent used in dry cleaning machines. There are two known 1-BP based dry cleaning
formulations, DrySolv® and Fabrisolv™ XL, which were introduced beginning in 2006. These
formulations are often marketed as "drop-in" replacements for perchloroethylene (PERC), which
indicates they can be used in third generation or higher PERC equipment (TLIRI, 2012). Third
generation equipment, introduced in the late 1970s and early 1980s, are non-vented, dry-to-dry machines
with refrigerated condensers. These machines are essentially closed systems and are only open to the
atmosphere when the machine door is opened. In third generation machines, heated drying air is
recirculated back to the drying drum through a vapor recovery system (CDC. 1997).
Fourth generation dry cleaning equipment are essentially third-generation machines with added
secondary vapor control. These machines "rely on both a refrigerated condenser and carbon adsorbent to
reduce the PERC concentration at the cylinder outlet below 300 ppm at the end of the dry cycle", and
are more effective at recovering solvent vapors. Fifth generation equipment have the same features as
fourth generation machines, but also have a monitor inside the machine drum and an interlocking system
to ensure that the concentration is below approximately 300 ppm before the loading door can be opened
(CDC. 1997).
Dry cleaners who opt to use 1-BP can either convert existing PERC machines or purchase a new dry
cleaning machine specifically designed for 1-BP. To convert existing PERC machines to use 1-BP,
machine settings and components must be changed to prevent machine overheating and solvent leaks
(Blando et at., 2010). 1-BP is known to damage rubber gaskets and seals. It can also degrade cast
aluminum, which is sometimes used on equipment doors and other dry cleaning machine components. In
addition, 1-BP is not compatible with polyurethane and silicone (TLIRI. 2012).
While conversion of a PERC machine to 1-BP is no longer recommended by the manufacturer, 1-BP
remains the only drop-in replacement that does not require buying a new machine. In some cases, the
shop owners may elect to do the conversion themselves to avoid the high cost of paying for a
professional company for the conversion (U.S. EPA. 2016a).
2.12.2 Number of Sites and Potentially Exposed Workers
EPA estimated the number of workers and occupational non-users potentially exposed to 1-BP at dry
cleaners using Bureau of Labor Statistics" OES data (2015) and the U.S. Census" SUSB (2012). The
method for estimating number of workers is detailed in Appendix A. These estimates were derived using
industry- and occupation-specific employment data from the BLS and U.S. Census. EPA anticipates that
dry cleaners are categorized under NAICS 812320, "Drycleaning and Laundry Services (except Coin-
Operated).
According to a public comment submitted by Enviro Tech International, Inc. (Enviro Tech), a major 1-
BP supplier, approximately 28 machines (nine converted PERC machines and 19 DrySolv machines)
were known to be in service in 2016. The number of machines was reduced to 23 (nine converted PERC
machines and 14 DrySolv machines) in 2017, after Enviro Tech ceased selling DrySolv to users of
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converted PERC machines (Enviro Tech International. 2017b). More recent communication with Enviro
Tech indicates only eight dry cleaning establishments are using 1-BP in 2019 (Enviro Tech
International 2019). Assuming one machine per facility, EPA estimates a total of 32 workers and
occupational non-users are exposed to 1-BP (Table 2-26).
Table 2-26. Estimated Number of Workers Potentially Exposed to 1-BP in Dry Cleaning Shops
Exposed
Workers
Exposed
Occupational
non-users
Total Exposed
Estimated
Number of
Establishments
Workers per Site
Occupational non-
users per Site
24
8
32
8
3
1
Source: (U.S. BLS. 2016) (U.S. Census Bureau. 2015) (Enviro Tech International. 2017b) (Enviro Tech International. 2019)
2.12.3 Exposure Assessment
2.12.3.1 Worker Activities
Figure 2-17 provides an overview of the dry cleaning process. Worker activities at dry cleaning shops
can include:
• Receiving garments and tagging garments for identification;
• Inspecting and sorting garments by color, weight, finish;
• Pre-treating any visible stain on the garment with a spotter, typically from a spray or squeeze
bottle;
• Loading garments into the machine, running the wash cycle, and unloading the cleaned
garments;
• Post-spotting any stain that was not already removed during the dry cleaning process; and
• Pressing and finishing, after which the pressed garment is returned to an overhead rack and
wrapped in plastic for customer pickup (NIOSH. 1997a).
At dry cleaning facilities, workers are primarily exposed when 1) adding makeup solvent to the
machine, typically by manually dumping it through the front hatch, 2) opening the machine door during
the wash cycle, and 3) removing garments from the machines (Blando et al., 2010). Workers can also be
exposed during maintenance activities, such as cleaning the machine lint trap, button trap and still,
changing solvent filters, and disposing hazardous wastes. However, these maintenance activities occur
on a much less frequent basis (NIOSH. 1997a).
Engineering controls such as local exhaust ventilation (LEV) located at or near the machine door can
reduce worker exposure during machine loading, machine unloading, and maintenance activities
(NCDOL. 2013). However, there are currently no regulatory requirements for installing such controls to
reduce 1-BP emissions and associated worker exposures at dry cleaning facilities. In addition,
engineering controls may not be economically feasible for dry cleaning shops.
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Finishing
o
•••
Receiving Garments Pre-Spotting Dry Cleaning
Post-Spotting
Figure 2-17. Overview of Dry Cleaning
2.12.3.2 Occupational Exposure Assessment Methodology
For dry cleaning, EPA assessed exposure using available exposure monitoring data and modeling
results.
2.12.3.3 Occupational Exposure Results
Monitoring Data
Table 2-27 presents an analysis of the 8-hr TWA PBZ monitoring data from literature. The data were
obtained from two literature studies covering four dry cleaning shops in New Jersey. The studies noted
significant variability in 1-BP exposure among different dry cleaning shops, different job titles, and in
some cases on different days when the exposure monitoring was conducted. The exposure data were also
impacted by the willingness of individual shops to participate in exposure monitoring. Note the study
(NIOSH, 2010) contains additional partial-shift exposure data that are not summarized here. For those
data, an 8-hr TWA value was not obtained because owners of the shop requested that NIOSH remove
the sampling equipment once they had finished running the dry cleaning machines (NIOSH, 2010).
All shops included in the studies used converted 3rd generation machines. Across the two studies, the
shops dry cleaned one to 14 loads of garments per day. Some shops that converted the machines
themselves "cooked" the solvent, a practice that had been performed widely for PERC but is no longer
recommended by the manufacturers for 1-BP operation (NIOSH, 2010). Only one shop added make-up
solvent during the study. This shop added make-up solvent due to leaks and evaporative losses on
Sample Day 1 and Sample Day 2 by manually dumping a 5-gallon can of solvent product through the
front hatch of the machine, but did not perform this activity on the remaining two sampling days
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(Blando et al.. 2010). The facilities had general building ventilation, ceiling-mounted or wall-mounted
fans, but lacked controls specifically designed to reduce exposure to the dry cleaning solvent.
EPA defined workers as dry cleaning machine operators. For workers, the 95th and 50th percentile
exposures are 50.2 and 29.4 ppm 8-hr TWA, respectively. The exposure level is impacted by the number
of loads cleaned, the number of solvent cooking cycles used, and whether any "make-up" solvent was
added in that particular shop and on that particular day when the monitoring was conducted (Blando et
al.. 2010). These activities can result in a larger release of solvent vapors into the work environment,
contributing to higher worker exposure to 1-BP. The studies also noted that work load and work
practices varied greatly among the shops (NIOSH. 2010). Further, NIOSH (NIOSH. 2010) noted that the
highest 1-BP concentration in air was found when a facility with a converted PERC machine cooked the
solvent, a practice that "had been performed widely for PERC but is no longer recommended by the
manufacturers for 1-BP operation" (NIOSH. 2010).
EPA defined occupational non-users as employees who work in the dry cleaning shops but do not
operate the machine. For occupational non-users, the 95th and 50th percentile exposures are 20.6 and 12.1
ppm 8-hr TWA, respectively. The data suggest that 1-BP exposure for cashiers, clerks, and other
employees at the shop can still be significant. In addition to occupational non-users, children may also
be present at some small, family-owned dry cleaning shops, and thereby be exposed to 1-BP. The
monitoring studies do not contain information on exposure to children.
Table 2-27. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Dry
Cleaning Based on Monitoring Data i
Category
Acute and Chrc
Exposures (8-Ho
AC l-BP, 8-hr twa ar
95th Percentile
>nic, Non-Cancer
ur TWAs in ppm)
d ADC 1-BP, 8-hr TWA
50th Percentile
Chronic, Cancer
LADCib
95th Percentile
Exposures (ppm)
P, 8-hr TWA
50th Percentile
Data
Points
Workera
50.2
29.4
25.75
11.7
8
ONUb
20.6
12.1
10.58
4.8
6
Source: (Blando et al.. 2010: NIOSH. 2010).
a Worker refers to dry cleaning machine operators.
b Occupational non-user refers to cashiers and clerks.
Model Data
Because there are multiple activities with potential 1-BP exposure at a dry cleaner, a multi-zone
modeling approach is used to account for 1-BP vapor generation from multiple sources. This model
framework was peer reviewed as part of the 2016 draft 1-BP Risk Assessment. The model has been
updated to address public and peer review comments. The model also reflects additional information
that became available since 2016; specifically, several model input parameters have been refined. Figure
2-18 illustrates this multi-zone approach, which considers the following worker activities:
• Spot cleaning of stains on both dirty and clean garments: On receiving a garment, dry
cleaners inspect for stains or spots they can remove as much of as possible before cleaning the
garment in a dry cleaning machine. Spot cleaning may also occur after dry cleaning if the stains
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or spots were not adequately removed. Spot cleaning occurs on a spotting board and can involve
the use of a spotting agent containing various solvents, such as 1-BP. Workers are exposed to 1-
BP when applying it via squeeze bottles, hand-held spray bottles, or even from spray guns
connected to pressurized tanks. Once applied, the worker may come into further contact with the
1-BP if using a brush, spatula, pressurized air or steam, or their fingers to scrape or flush away
the stain (Young. 2012; NIOSH. 1997a). For modeling, EPA assumed the near-field is a
rectangular volume covering the body of a worker.
• Unloading garments from dry cleaning machines: At the end of each dry cleaning cycle,
workers manually open the machine door to retrieve cleaned garments. During this activity,
workers are exposed to 1-BP vapors remaining in the dry cleaning machine cylinder. For
modeling, EPA assumed that the near-field consists of a hemispherical area surrounding the
machine door, and that the entire cylinder volume of air containing 1-BP exchanges with the
workplace air, resulting in a "spike" in 1-BP concentration in the near-field, Cd, during each
unloading event. This concentration is directly proportional to the amount of residual 1-BP in the
cylinder when the door is opened. The near-field concentration then decays with time until the
next unloading event occurs.
• Finishing and pressing: The cleaned garments taken out of the cylinder after each dry clean
cycle contain residual solvents and are not completely dried (Von Grote. 2003). The residual
solvents are continuously emitted into the workplace during pressing and finishing, where
workers manually place the cleaned garments on the pressing machine to be steamed and ironed.
EPA assumed any residual solvent is entirely evaporated during pressing, resulting in an increase
in the near-field 1-BP concentration during this activity. Workers are exposed to 1-BP vapors
while standing in vicinity of the press machine. For modeling, EPA assumed the near-field is a
rectangular volume covering the body of a worker.
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Dry Cleaning
Machine
Vr
Cn
Far-field (background)
LI-
LI-
a
FF
Figure 2-18. Illustration of the Multi-Zone Model
As the figure shows, 1-BP vapor is generated in each of the three near-fields, resulting in worker
exposures at concentrations Cs, Cd, and Cf. The volume of each zone is denoted by Vs, Vd, and Vf. The
ventilation rate for the near-field zone (Qs, Qd, Qf) determines how quickly 1-BP dissipates into the far-
field (i.e., the facility space surrounding the near-fields), resulting in occupational non-user exposures to
1-BP at a concentration Cff. Vff denotes the volume of the far-field space into which the 1-BP
dissipates out of the near-field. The ventilation rate for the surroundings, denoted by Qff, determines
how quickly 1-BP dissipates out of the surrounding space and into the outside air. Appendix H
summarizes the parameters and equations for the multi-zone model. The far-field volume, air exchange
rate, and near-field indoor wind speed are identical to those used in the 1-BP Spot Cleaning Model (see
Section 2.13). These values were selected using engineering judgment and literature data that EPA
believed to be representative of a typical dry cleaner.
The dry cleaning industry is characterized by a large number of small businesses, many are family-
owned and operated. EPA assumed small dry cleaners operate up to 12 hours a day and up to 6 days a
week. In addition, EPA assumed each facility has a single machine. The assumption of a single machine
per facility is supported by a recent industry study conducted in King County, Washington, where 96
percent of 151 respondents reported having only one machine at their facility. Four reported having two
machines, and two reported having three machines (Whittaker and Johanson. 2011). Based on the survey
results, this assumption is presumably representative of the majority of small dry cleaning shops.
EPA modeled the baseline scenario assuming the facility operates a converted third generation machine,
the machine type observed at all three New Jersey dry cleaners in the Blando et al. (2010) study. For the
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engineering control scenario, EPA modeled a facility with a fourth generation machine. EPA believes
facilities using 1 -BP are unlikely to own fifth generation machines (ERG. 2005).
EPA assessed three types of workers within the modeled dry cleaning facility: 1) a worker who performs
spot cleaning; 2) a worker who unloads the dry cleaning machine and finishes and presses the garments;
and 3) an occupational non-user. Each worker type is described in further detail below. EPA assumed
each worker activity is performed over the full 12-hour operating day.
• EPA assumed spot cleaning occurs for a duration varying from two to five hours in the middle of
the twelve-hour day. The worker is exposed at the spot cleaning near-field concentration during
this time, and at the far-field concentration for the remainder of the day. Spot cleaning can be
performed for both dry cleaned loads and for laundered loads.
• EPA assumed a separate worker unloads the dry cleaning machine, and finishes and presses the
garments. After each load, EPA assumed this worker spends five minutes unloading the machine,
during which he or she is exposed at the machine near-field concentration. After unloading, the
worker spends five minutes in the finishing near-field to prepare the garments. Then, the worker
spends another 20 minutes finishing and pressing the cleaned garments. During this 20-minute
period of finishing and pressing, the residual 1-BP solvent is off-gassed into the finishing near-
field. The amount of residual 1-BP solvent is estimated using measured data presented in (Von
Grote. 2003). These unloading and finishing activities are assumed to occur at regular intervals
throughout the twelve-hour day. The frequency of unloading and finishing depends on the
number of loads dry cleaned each day, which varies from one to 14, where 14 was the maximum
number of loads observed in the NIOSH (2010) and Blando (2010) studies. When this worker is
not unloading the dry cleaning machine or finishing and pressing garments, the worker is
exposed at the far-field concentration.
EPA assumed one occupational non-user is exposed at the far-field concentration for twelve
hours a day. The occupational non-user could be the cashier, tailor, or launderer, who works at
the facility but does not perform dry cleaning activities.
Table 2-28 presents the Monte Carlo results with the Latin hypercube sampling method and 10,000
iterations. Statistics of the 12-hr TWA exposures (95th and 50th percentiles) are calculated at the end of
the simulation after all iterations have completed. The AC, ADC, and LADC calculations are integrated
into the Monte Carlo simulation, such that the exposure frequency matches the model input values for
each iteration. As shown in the table, the worker who performs unloading and finishing activities have
the highest exposure; this exposure can be reduced if the facility switches from a third generation to
fourth generation machine. However, the machine type does not significantly impact exposure level for
other persons present at the facility, including the spot cleaner and the occupational non-user. The model
values cover a wider distribution of exposure levels when compared to the monitoring data. This is
likely due to the wide range of model input parameter values covering a higher number of possible
exposure scenarios. However, the modeled occupational non-user exposures are lower than actual
monitoring results. The model assumes the occupational non-user spends their time entirely in the far-
field. In reality, it is possible that these employees will occasionally perform activities in the near-field,
thereby having a higher level of exposure.
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Table 2-29 presents the exposure for children who may be present at the dry cleaning facility. Because
many dry cleaners are family owned and operated, EPA assumed children may be present for a four-
hour period (3 - 7pm) afterschool, during which they may be exposed at similar levels as occupational
non-users.
Table 2-28. Statistical Summary of 1-BP Dry Cleaning Exposures for Workers and Occupational
Non-users based on Modeling
12-hr TWA Exposures
Acute, Non-Cancer
Chronic, Non-Cancer
Chronic, Cancer
(PPm)
Exposures (ppm)
Exposures (ppm)
Exposures (ppm)
Cl-BP, 12-hr TWA
AC1-BP, 24-hrTWA
ADCl-BP, 24-hr TWA
LADCl-BP, 24-hr TWA
95th
50th
95th
50th
95th
50th
95th
50th
Machine Type
Percentile
Percentile
Percentile
Percentile
Percentile
Percentile
Percentile
Percentile
Workers: Machine Unloading and Finishing (Near-Field)
3rd Gen.
60.53
14.13
30.27
7.06
21.70
4.98
8.57
1.89
4th Gen.
6.36
2.38
3.18
1.19
2.30
0.84
0.94
0.31
Workers: Spot Cleaning (Near-Field)
3rd Gen.
7.93
2.93
3.97
1.47
2.83
1.03
1.14
0.39
4th Gen.
5.65
2.40
2.83
1.20
2.02
0.85
0.82
0.32
Occupational non-users (Far-Field)
3rd Gen.
6.65
1.82
3.33
0.91
2.37
0.64
0.95
0.24
4th Gen.
4.21
1.31
2.11
0.65
1.49
0.46
0.60
0.17
Table 2-29. Statistical Summary of 1-BP Dry Cleaning Exposures for Children based on Modeling
Machine Type
12-hr TWA
(PP
Cl-BP,
95th
Percentile
Exposures
m)
-hr TWA
50th
Percentile
Acute, No
Exposur
AC i-BP,
95th
Percentile
n-Cancer
es (ppm)
24-hr TWA
50th
Percentile
Chronic, P
Exposui
ADCi-bi
95th
Percentile
ion-Cancer
•es (ppm)
>, 24-hr TWA
50th
Percentile
Chronic
Exposur
LADCib
95th
Percentile
, Cancer
es (ppm)
', 24-hr TWA
50th
Percentile
Children (Far-Field)
3rd Gen.
4.03
0.54
0.67
0.09
N/A
N/A
N/A
N/A
4th Gen.
1.02
0.09
0.17
0.01
N/A
N/A
N/A
N/A
N/A - Not applicable
2.13 Spot Cleaner, Stain Remover
2.13.1 Process Description
On receiving a garment, dry cleaners inspect for stains or spots and remove them as much of as possible
before cleaning the garment in a machine. As Figure 2-19 shows, spot cleaning occurs on a spotting
board and can involve the use of a spotting agent containing various solvents, such as 1-BP. The
spotting agent can be applied from squeeze bottles, hand-held spray bottles, or even from spray guns
connected to pressurized tanks. Once applied, the dry cleaner may come into further contact with the 1-
BP if using a brush, spatula, pressurized air or steam, or their fingers to scrape or flush away the stain
(Young. 2012; NIOSH. 1997a).
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Figure 2-19. Overview of Use of Spot Cleaning at Dry Cleaners
EPA assessed a separate spot cleaning scenario at dry cleaners. This scenario represents dry cleaners or
other shops that use 1-BP-based spot cleaning formulations but do not otherwise use 1-BP in a dry
cleaning machine. The extent of such uses is likely limited, as Enviro Tech claimed that while DrySolv
spotting products were advertised to the dry cleaning industry, most were never commercialized (Enviro
Tech International, 2017b).
2.13.2 Number of Sites and Potentially Exposed Workers
See Section 2.12.2 for the estimated number of workers and occupational non-users at dry cleaning
shops.
2.13.3 Exposure Assessment
2.13.3.1 Worker Activities
As previously described, workers manually apply the spotting agent from squeeze bottles, hand-held
spray bottles, or spray guns, either before or after a cleaning cycle. After application, the worker may
manually scrape or flush away the stain using a brush, spatula, pressurized air or steam, or their fingers
(Young. 2012; NIOSH. 1997a).
2.13.3.2 Occupational Exposure Assessment Methodology
For spot cleaning, EPA assessed exposure using both available monitoring data and model results.
2.13.3.3 Occupational Exposure Results
Monitoring Data
Table 2-30 presents 8-hr TWA PBZ monitoring data from OSHA CEHD for three facilities where spot
cleaning is performed. At one facility, workers spray-applied solvent formulation to stained portions of
dresses and did not wear any personal protective equipment. It is unclear if there were any engineering
controls at the facility to mitigate worker exposure.
The 95th and 50th percentile exposure level for workers were 4.73 ppm and 0.9 ppm 8-hr TWA. No
exposure monitoring data are available for occupational non-users.
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Table 2-30. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Spot Cleaning
Based on Monitoring I
>ata
Category
Acute and Chrc
Exposures (8-Ho
AC 1-BP, 8-hr TWA dX
95th percentile
>nic, Non-Cancer
ur TWAs in ppm)
d ADC 1-BP, 8-hr TWA
50th percentile
Chronic, Cancer
LADCib
95th percentile
Exposures (ppm)
P, 8-hr TWA
50th percentile
Data
Points
Worker
Worker
4.73
0.90
2.42
0.4
6
Source: (OSHA. 2019) (OSHA. 2013b)
Model Data
Figure 2-20 illustrates the near-field/far-field modeling approach that EPA applied to spot cleaning
facilities. The model, including all input parameters, are described in more detail in 0. The model
framework has been peer reviewed as part of the 2016 draft 1-BP Risk Assessment. Since 2016, the
model has been updated to address public and peer review comments and to incorporate additional
information that became available.
As the figure shows, chemical vapors evaporate into the near-field (at evaporation rate G), resulting in
near-field exposures to workers at a concentration Cnf. The concentration is directly proportional to the
amount of spot cleaner 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 the chemical of interest dissipates into the far-field (i.e., the facility space
surrounding the near-field), resulting in occupational non-user exposures at a concentration Cff. Vff
denotes the volume of the far-field space into which the chemical of interest dissipates out of the near-
field. The ventilation rate for the surroundings, denoted by Qff, determines how quickly the chemical
dissipates out of the surrounding space and into the outdoor air.
Far-Field
Volatile Source
Figure 2-20. Schematic of the Near-Field/Far-Field Model for Spot Cleaning
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To determine the 1-BP use rate, EPA conducted a targeted literature search to identify information on
the typical amount of spotting agents used at dry cleaners. The Massachusetts Department of
Environmental Protection (MassDEP) provided a comparative analysis of several dry cleaner case
studies using various PERC alternatives. This document estimates a dry cleaner using 1-BP spends $60
per month on spotting agents. This particular facility dry cleans 100 pieces of garments per day.
MassDEP noted that the facility size can vary greatly among individual dry cleaners (MassDEP. 2013).
Blando et al. (2009) estimated that 1-BP solvent products cost $45 per gallon. Based on this information,
EPA calculated a spot cleaner use rate of 1.33 gallons per month, or 16 gallons per year. The Safety
Data Sheet for DrySolv, a common 1-BP formulation, indicates the product contains greater than 87
percent 1-BP by weight (Enviro Tech International. 2013).
EPA performed Monte Carlo simulations, applying 100,000 iterations and the Latin hypercube sampling
method. Table 2-31 presents a statistical summary of the exposure modeling results. The 95th and 50th
percentile exposure for workers (near-field) are 7.03 ppm and 3.24 ppm 8-hr TWA, respectively. These
results are generally comparable to the monitoring data. For occupational non-users (far-field), the 95th
and 50th percentile exposure levels are 4.68 ppm and 1.63 ppm 8-hr TWA, respectively. The table also
presents the AC, ADC, and LADC values, which are integrated into the Monte Carlo. EPA assumes no
engineering controls (e.g. exhaust hoods) are present at spot cleaning facilities, because controls may not
be financially feasible for small shops.
Table 2-31. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Use of
Spot Cleaning at Dry Cleaners Based on Modeling
Category
Acute, Non-Cancer Exposures
(8-Hour TWAs in ppm)
ACi -BP, 8-hr TWA
95th Percentile
50th Percentile
Chronic, Non-Cancer
Exposures (8-Hour TWAs in
ppm)
ADCl-BP, 8-hr TWA
Chronic, Cancer Exposures
(ppm)
LADCi -BP, 8-hr TWA
95th Percentile
50th Percentile
95th Percentile
50th Percentile
Worker
ONU
7.03
4.68
3.24
1.63
1.66
1.10
0.76
0.39
0.68
0.45
0.29
0.15
2.14 Adhesive Chemicals (Spray Adhesives)
2.14.1 Process Description
1-BP is used in spray adhesives for foam cushion manufacturing and fabrication (e.g., the furniture
industry). Figure 2-21 illustrates a typical process of using spray adhesives for foam cushion
manufacturing. During foam cushion manufacturing and fabrication, foam is cut into pieces and then
bonded together to achieve the appropriate shape. Spray guns are used to spray-apply an adhesive onto
flexible foam surfaces for bonding. Adhesive spraying typically occurs either on an open top workbench
with side panels that may have some local ventilation, or in an open workspace with general room
ventilation. After the adhesive is applied, workers assemble the cushions by hand-pressing together
pieces of cut flexible foam (NIOSH. 2003. 2002b).
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Align and compress foam
pieces to form bond
Spray adhesive
Finished furniture products
Fabricate furniture
Figure 2-21. Overview of Use of Spray Adhesive in the Furniture Industry
2.14.2 Number of Sites and Potentially Exposed Workers
EPA estimated the number of workers potentially exposed to 1-BP in spray adhesives using Bureau of
Labor Statistics' Occupational Employment Statistics (OES) data (2015) and U.S. Census' Statistics of
US Businesses (SUSB) (2012). The method for estimating number of workers is detailed in Appendix
A. The worker estimates were derived using industry- and occupation-specific employment data from
these sources. The industry sectors and occupations that EPA determined to be relevant to spray
adhesive use are presented in that Appendix.
The number of businesses in this use sector of 1-BP is estimated to be between 100 and 280 (CDC.
2016). Table 2-32 presents the estimated number of workers and occupational non-users using these
estimates. The total number of potentially exposed workers and occupational non-users ranges from
1,503 to 4,209. Recent discussion with industry suggests the 1-BP market has since declined due to
worker health issues associated with this use. In its 2017 public comment, Enviro Tech stated that it was
aware of only two end users who currently use 1-BP as a carrier for an adhesive (Enviro Tech
International 2017a). It is unclear whether the Enviro Tech estimate is comprehensive of the current
spray adhesive market.
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Table 2-32. Estimated Number of Workers Potentially Exposed to 1-BP in Spray Adhesive Use in
Foam Cushion Manufacturing
Exposed
Workers
Exposed
Occupational
Non-Users
Total Exposed
Estimated
Number of
Establishments
Workers per Site
Occupational
Non-Users per
Site
Low-end
551
952
1,503
100
6
10
High-end
1,543
2,666
4,209
280
6
10
Note: Number of workers and occupational non-users per site are calculated by dividing the exposed number of workers or
occupational non-users by the number of establishments. Values are rounded to the nearest integer.
2.14.3 Exposure Assessment
2.14.3.1 Worker Activities
Worker activities include manual spraying of 1-BP containing adhesives, typically in a spray station or
spray booth, and hand-pressing and assembling pieces of flexible foam after the adhesive is applied. See
Section 2.14.3.3 for additional discussion of worker activity, job function, and their potential for
exposure.
2.14.3.2 Occupational Exposure Assessment Methodology
For use of 1-BP in spray adhesives, EPA estimated exposure using available exposure monitoring data.
1-BP exposure monitoring data were identified in several literature studies, including journal articles,
NIOSH HHE, and OSHA CEHD database. NIOSH HHEs are conducted at the request of employees,
employers, or union officials and help inform on potential hazards present at the workplace. HHEs can
also be conducted in response to a technical assistance request from other government agencies. OSHA
CEHD are workplace monitoring data from OSHA inspections. These inspections can be random or
targeted, or can be the result of a worker complaint.
Among these sources, three NIOSH studies provide the most comprehensive information on worker
exposure to 1-BP from spray adhesives in foam cushion manufacturing. Two of the three HHEs also
compare exposure pre- and post-engineering controls. A summary of these HHEs follows:
• From March 1998 to April 2001, NIOSH investigated a facility in Mooresville, North Carolina to
assess 1-BP exposures during manufacturing of foam seat cushions (NIOSH 2002a). The
company had four departments: Saw, Assembly, Sew, and Covers. Workers in Assembly and
Covers departments worked directly with the adhesive; however, workers in all four departments
were exposed. The spray adhesive used at this facility contained between 60 and 80 percent 1-
BP. NIOSH conducted an initial exposure assessment in 1998 and observed that the ventilation
exhaust filters were clogged with adhesive. In 2001, NIOSH conducted a follow-up exposure
assessment after the facility made improvements to its ventilation system.
• From November 2000 to August 2001, NIOSH investigated workplace exposures to 1-BP during
manufacturing of foam seat cushions at another cushion company in North Carolina (NIOSH
2002b). This facility uses a spray adhesive containing 55 percent 1-BP. NIOSH conducted an
initial exposure assessment in 2000 and recommended that the facility reduce worker exposure
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by enclosing the spray stations to create "spray booths". Subsequently, in 2001, NIOSH
conducted a follow-up assessment after spray station enclosures were installed.
• From April 1999 to May 2001, NIOSH investigated another cushion company in North Carolina
(NIOSH. 2003). In this study, NIOSH conducted two separate exposure assessments. In the
initial assessment, NIOSH measured 1-BP inhalation exposures to workers in and near the
adhesive spray operation areas. In the second assessment, NIOSH measured additional 1-BP
inhalation exposures at the facility. There were no changes to the facility's ventilation system
(i.e. engineering controls) between the first and second assessment.
2.14.3.3 Occupational Exposure Results
Table 2-33 summarizes available 1-BP exposure data from the NIOSH and OSHA sources. The data set
includes pre-EC and post-EC scenarios for each worker job category. EPA defined three job categories
for 1-BP spray adhesive use:
• Sprayers: Workers who perform manual spraying of 1-BP adhesive as a regular part of his or her
job;
• Non-spravers: Workers who are not "sprayers", but either handle the 1-BP adhesive or spend the
majority of their shift working in an area where spraying occurs. For example, the NIOSH
(2002a) study indicated spraying occurs in the Assembly and Covers departments. EPA assumes
workers in these departments who do not perform spraying still work in the vicinity of spraying
operations and may be regularly exposed to 1-BP; and
• Occupational non-users: Workers who do not regularly perform work in an area of the facility
where spraying occurs. For example, EPA assumes workers in the Saw and Sew departments of
the 2002 NIOSH study (NIOSH. 2002a) are "occupational non-users".
For each worker job category (sprayer, non-sprayer or occupational non-user) and exposure scenario
(pre-EC or post-EC), EPA calculated the 95th and 50th percentile exposure levels from the observed data
set. Pre-EC exposure scenarios suggest that all workers at foam cushion manufacturing facilities that use
1-BP spray adhesives have substantial exposure to 1-BP. Sprayers have the highest levels of exposure
because they work directly with the 1-BP adhesive. However, non-sprayers and occupational non-users
may also be exposed at high levels. The difference in exposure between sprayers and non-sprayers may
not be meaningful, as the number of data points available for non-sprayers is less than half than the data
available for sprayers.
In general, exposure levels for occupational non-users vary widely depending on the worker's specific
work activity pattern, individual facility configuration, and proximity to the 1-BP adhesive. For
example, workers in the saw and sew departments in the NIOSH (2002a) study classified as
"occupational non-users" are exposed at levels above 100 ppm 8-hr TWA. The high exposure levels are
caused by their proximity to spraying operations in other departments, even though no adhesive is used
in the saw and sew departments (NIOSH. 2002a). Additionally, some workers may not have a single
assigned role; as such, their exposure level will vary depending on the specific tasks performed.
Post-EC exposure scenarios suggest that engineering controls, if well designed, maintained, and
operated, can reduce worker exposures by an order of magnitude. However, engineering controls alone
do not reduce exposures for sprayers and non-sprayers to levels below 0.1 ppm, the time-weighted
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average threshold limit value (TLV) recommended by the American Conference of Governmental
Industrial Hygienists (ACGIH).
Additional 1-BP worker exposure monitoring data have been identified in other literature studies such as
Hanley et al. (2009; 2006), Ichihara et al. (2002). Majersik et al. (2007). However, these studies are not
used in EPA's analysis because they either do not provide individual data points or lack specific
information on worker job descriptions to adequately categorize the exposure results.
Table 2-33. Statistical Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Spray
Adhesive on Monitoring Data
Categorya
Acute and Chrc
Exposures (8-Ho
AC l-BP, 8-hr twa ar
95th Percentile
>nic, Non-Cancer
ur TWAs in ppm)
d ADC 1-BP, 8-hr TWA
50th Percentile
Chronic, Cancer
LADCib
95th Percentile
Exposures (ppm)
P, 8-hr TWA
50th Percentile
Data
Points
Sprayer, Pre EC
253.6
132.8
130.04
52.8
83
Sprayer, Post EC
41.90
17.81
21.49
7.1
49
Non-Sprayerb. Pre EC
210.9
127.2
108.1
50.6
31
Non-Sprayerb, Post EC
28.8
18.0
14.79
7.2
9
ONU°, Pre EC
128.7
3.00
66.0
1.2
39
ONU°, Post EC
5.48
2.00
2.81
0.8
17
Sources: (OSHA. 2013b: NIOSH. 2003. 2002a. b) (Toraasonet al.. 2006)
a EC = Engineering Controls. Pre-EC = Initial NIOSH visit; Post EC = Follow-up NIOSH visit engineering controls
implemented: Enclosing spray tables to create "spray booths" and/or improve ventilation.
b Non-Sprayer refers to those employees who are not sprayers, but either handle the adhesive or spend the majority of their
shift working in an area where spraying occurs.
0 Occupational non-user refers to those employees who do not regularly work in a department/area where spraying occurs
(e.g., employees in saw and sew departments).
2.15 Other Uses
2.15.1 Process Description
Based on products identified in EPA's preliminary data gathering and information received in public
comments, a variety of other aerosol and non-aerosol uses may exist for 1-BP [see Preliminary
Information on Manufacturing, Processing, Distribution, Use, and Disposal: 1-Bromopropane, EPA-
HQ-OPPT-2016-0741 -0003 (U.S. EPA. 2017b)1. Examples of these uses include, but are not limited to
(AIA. 2017) (CRC Industries Inc.. 2017) (Enviro Tech International. 2017a) (HESIS. 2016):
• Aerosol mold cleaning and release: 1-BP is a carrier solvent in aerosol mold cleaning and release
products. These products are used to coat the molds for injection molding, compression molding,
blow molding and extrusion applications. The product use rate varies depending on mold size
and frequency of re-application. This use is likely limited because 1-BP is not compatible with
some mold release applications.
• Asphalt extraction: 1-BP is used for asphalt extraction in centrifuge extractors, vacuum
extractors, and reflux extractors. In this process, 1-BP is used to separate asphalt from the
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aggregate and filler material to allow for determination of asphalt content. This condition of use
is expected to make up one percent of the total domestic 1-BP use volume.
• Coin and scissor cleaner: 1-BP is used in product formulations designed to clean collectible coins
and scissors.
• General purpose degreaser: General purpose degreasing products containing 1-BP (both aerosol
and non-aerosol) are used in industrial settings, with usage varying widely by facility. Refineries
and utilities are known to be the largest volume users, with usage being cyclical as 1-BP is used
to clean and maintain equipment primarily during plant shutdowns. 1-BP is also used for heavy
duty transportation maintenance, e.g., maintaining buses, trains, trucks, etc.
• High voltage cable cleaner: 1-BP is contained in both aerosol and non-aerosol cleaning products,
which are used to clean the semi-conductive cores of high voltage cables when splicing and
terminating cables. A few ounces of product are used to clean each splice.
• Refrigerant flush: 1-BP is used to flush oxygen lines in hospitals and in the aerospace industry.
1-BP is also used to clean refrigeration lines in various industries. This condition of use is
expected to make up one percent of the total domestic 1-BP use volume.
• Temperature indicator: 1-BP is used in temperature indicating fluids and coatings. These
coatings can be applied to fabrics, rubber, plastics, glass, and/or polished metal. When the
substrate is heated, the coating will melt at the designated temperature, leaving a mark on the
surface. This condition of use is expected to make up less than 0.5 percent of the total domestic
1-BP use volume.
• Other uses: 1-BP has a number of other uses, such as adhesive accelerant, as coating component
for pipes and fixtures, and as laboratory chemical for research and development.
EPA expects the majority of these conditions of use to be niche uses.
2.15.2 Number of Sites and Potentially Exposed Workers
EPA has not identified information on the number of sites and potentially exposed workers associated
with these uses. The use of 1-BP for these conditions of use is expected to be minimal. It is possible that
some aerosol degreasing facilities presented in Section 2.11 also use 1-BP as a general-purpose cleaner /
degreaser.
2.15.3 Exposure Assessment
EPA has not identified exposure data associated with these conditions of use. The worker activity, use
pattern, and associated exposure will vary for each condition of use. For aerosol applications, EPA
anticipates the worker activity and exposure route may be similar to those described for aerosol
degreasing in Section 2.11. For uses as a temperature indicator, workers will likely be exposed via
inhalation of vapor as 1-BP volatilizes from the applied coating.
2.16 Disposal, Recycling
2.16.1 Process Description
Each of the conditions of use of 1-BP may generate waste streams that are collected and transported to
third-party sites for disposal, treatment, or recycling. Industrial sites that treat or dispose onsite wastes
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that they themselves generate are assessed in each condition of use assessment in Sections 2.1 through
2.15. Wastes containing 1-BP that are generated during a condition of use and sent to a third-party site
for treatment, disposal, or recycling may include wastewater, solid wastes, and other wastes.
Solid wastes are defined under RCRA as any material that is discarded by being: abandoned; inherently
waste-like; a discarded military munition; or recycled in certain ways (certain instances of the generation
and legitimate reclamation of secondary materials are exempted as solid wastes under RCRA). Solid
wastes may subsequently meet RCRA's definition of hazardous waste by either being listed as a waste at
40 CFR §§ 261.30 to 261.35 or by meeting waste-like characteristics as defined at 40 CFR §§ 261.20 to
261.24. Solid wastes that are hazardous wastes are regulated under the more stringent requirements of
Subtitle C of RCRA, whereas non-hazardous solid wastes are regulated under the less stringent
requirements of Subtitle D of RCRA. Solid wastes containing 1-BP may be regulated as a hazardous
waste under RCRA waste code D001 for ignitable liquids (40 CFR 261.21). 1-BP may also be co-
mingled with solvent mixtures that are RCRA regulated substances. These wastes would be either
incinerated in a hazardous waste incinerator or disposed to a hazardous waste landfill. Some amount of
1-BP may be improperly disposed as municipal wastes, although they are likely to be a small fraction of
the overall waste stream.
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
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 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
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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
(Environmental Technology Council. 2018).9
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.9
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.
Emissions Stack
Ash Handling
Scrubber Water or
Ash Handling
Combustion
Air Pollution Control
Waste Storage
Heat Recovery
Gas Temperature
Reduction
Feed Preparation
Disposal Disposal
Figure 2-22. 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 state 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.
9 Incineration Sendees: Heritage; https://www.heritage-enviro.com/services/incineration/
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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.
Solvent Recovery
Waste solvents are 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. The recovery process involves an initial vapor recovery
(e.g., condensation, adsorption and absorption) or mechanical separation (e.g., decanting, filtering,
draining, setline and centrifuging) step followed by distillation, purification and final packaging. Worker
activities are expected to be unloading of waste solvents and loading of reclaimed solvents. Figure 2-23
illustrates a typical solvent recovery process flow diagram (U.S. EPA. 1980). It is not known to what
extent 1-BP is collected for reclamation/recycling off-site.
Storage
Tank
Vent
Storage
Tank
Vent
Fugitive
Emissions
Fugitive
Emissions
Fugitive
Emissions
Fugitive
Emissions
Solvent
* Incinerator Stock
Fugitive Emissions
Storage
and
Handling
Storage
and
Handling
Initial
Treatment
Figure 2-23. General Process Flow Diagram for Solvent Recovery Processes
Source: (U.S. EPA. 1980)
2.16.2 Number of Sites and Potentially Exposed Workers
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Table 2-34 presents the industry sectors likely involved in waste treatment and disposal, and the average
number of workers and ONUs per site within these sectors based on EPA's analysis of BLS data. EPA
calculated the total number of workers and ONUs potentially exposed to 1-BP by multiplying these
estimates by the number of waste treatment and disposal facilities that reported releases to the TRI (i.e.
facilities that reported one of the NAICS codes in Table 2-34 as their primary NAICS code in TRI). For
reporting year 2016, three hazardous waste treatment and disposal facilities and one cement plant
reported releases of 1-BP to the TRI. It is possible that additional hazardous waste treatment facilities
treat and dispose 1-BP but do not meet the TRI reporting threshold for reporting year 2016. In addition,
it is possible that some consumer products containing 1-BP may be improperly disposed as municipal
solid wastes, and that some amount of 1-BP is present in non-hazardous waste streams.
Table 2-34. Estimated Number of Workers Potentially Exposed to 1-BP during Waste Handling
Exposed
Workers
Exposed
Occupational
Non-Users
Total Exposed
Estimated
Number of
Establishments
Workers per Site
Occupational
Non-Users per
Site
NAICS 562211 Hazardous H aste Treatment and Disposal
27
15
42
3
9
5
NAICS 562212 Solid Waste Landfill
unknown
3
2
NAICS 562213 Solid Waste Combustors and Incinerators
unknown
13
8
NAICS 562219 Other Nonhazardous Waste Treatment and Disposal
unknown
3
2
NAICS 327310 Cement Manufacturing
22
3
25
1
22
3
Note: Number of workers and occupational non-users per site are calculated by dividing the exposed number of workers or
occupational non-users by the number of establishments. Values are rounded to the nearest integer.
2.16.3 Exposure Assessment
2.16.3.1 Worker Activities
At waste disposal sites, workers are potentially exposed via dermal contact with waste containing 1-BP
or via inhalation of 1-BP vapor. Depending on the concentration of 1-BP in the waste stream, the route
and level of exposure may be similar to that associated with container unloading activities.
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
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operators, as well as truck drivers. The potential for dermal exposures is minimized by the use of trucks
and cranes to handle the wastes.
Hazardous Waste Incineration
More information is needed to determine the potential for worker exposures during hazardous waste
incineration and any requirements for personal protective equipment. There is likely a greater potential
for worker exposures for smaller scale incinerators that involve more direct handling of the wastes.
Municipal and Hazardous Waste Landfill
At landfills, typical worker activities may include operating refuse vehicles to weigh and unload the
waste materials, operating bulldozers to spread and compact wastes, and monitoring, inspecting, and
surveying and landfill site10. The potential for direct worker handling of the wastes is unknown.
2.16.3.2 Occupational Exposure Assessment Methodology
EPA did not identify exposure monitoring data related to waste treatment and disposal sites. To assess
worker exposure, EPA assumes wastes containing 1-BP are transported and handled as bulk liquid
shipments and models exposure using the Tank Truck and Railcar Loading and Unloading Release and
Inhalation Exposure Model (previously described in Section 2.2.3.2).
2.16.3.3 Occupational Exposure Results
Table 2-35 summarizes the model exposures from waste handling activities. The model assumes liquid
wastes contain 100 percent 1-BP, and estimates high-end and central tendency exposure concentrations
for waste unloading scenario at industrial facilities. The model exposure may not be representative of the
full distribution of possible exposure levels at waste disposal facilities.
Table 2-35. Summary of 1-BP 8-hr TWA Exposures (AC, ADC and LADC) for Disposal Based on
Modeling
Category
Acute and Chro
Exposures (8-Hoi
AC l-BP, 8-hr twa an
High-end
nic, Non-Cancer
ir TWAs in ppm)
1 ADC 1-BP, 8-hr TWA
Central tendency
Chronic, Cance
LADC]
High-end
r Exposures (ppm)
-BP, 8-hr TWA
Central tendency
Worker
6.01E-2
1.14E-2
3.08E-2
4.55E-3
111 http://www.calrecYcle.ca.gov/SWfacilities/landfills/needfor/Qperations.htm
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2.17 Dermal Exposure Assessment
Because 1-BP is a volatile liquid, the dermal absorption of 1-BP depends on the type and duration of
exposure. Where exposure is non-occluded, only a fraction of 1-BP that comes into contact with the skin
will be absorbed as the chemical readily evaporates from the skin. However, dermal exposure may be
significant in cases of occluded exposure, repeated contacts, or dermal immersion. For example, work
activities with a high degree of splash potential may result in 1-BP liquids trapped inside the gloves,
inhibiting the evaporation of 1-BP and increasing the exposure duration.
To assess exposure, EPA used the Dermal Exposure to Volatile Liquids Model (see following equation)
to calculate the dermal retained dose for both non-occluded and occluded scenarios. The equation
modifies the EPA/OPPT 2-HandDermal Exposure to Liquids Model (peer reviewed) by incorporating a
"fraction absorbed (fabs)" parameter to account for the evaporation of volatile chemicals and a
"protection factor (PF)" to account for glove use. Default PF values, which vary depending on the type
of glove used and the presence of employee training program, are shown in Table 2-36:
D — V ( Q" Xfabs) y y y C"TT
uexp pp ^ 1 derm ^ 11
Where:
Dexp is the dermal retained dose (mg/kg-day)
S is the surface area of contact (cm2)
Qu is the quantity remaining on the skin (mg/cm2-event)
Yderm is the weight fraction of the chemical of interest in the liquid (0 < Yderm < 1)
FT is the frequency of events (integer number per day)
fabs is the fraction of applied mass that is absorbed (Default for 1-BP: 0.0016)
PF is the glove protection factor (Default: see Table 2-36)
The fractional absorption (fabs) for 1-BP is estimated to be 0.16 percent in a non-occluded, finite dose
scenario based on an in vitro dermal penetration study conducted by Frasch et al. (2011). The author
noted a large standard deviation in the experimental measurement, which is indicative of the difficulty in
spreading a small, rapidly evaporating dose of 1-BP evenly over the skin surface. Appendix J provides
additional methods for estimating the fractional absorption, including the theoretical framework
provided by Kasting and Miller (Kasting and Miller. 2006).11
Table 2-36. Glove Protection Factors for Different Dermal Protection Strategies
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
11 Using the Kasting and Miller method, the steady-state fractional absorption for 1-BP is estimated to be 6 to 9 percent.
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Dermal Protection Characteristics
Setting
Protection Factor, PF
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
Source: (Marguart et al.. 2017)
Table 2-37 presents the estimated dermal retained dose for workers in various exposure scenarios,
including what-if scenarios for glove use. The exposure estimates assume one exposure event (applied
dose) per work day and that 0.16 percent of the applied dose is absorbed through the skin. Table 2-37
also includes estimated dermal retained dose for occluded scenarios for conditions of use where EPA
determined occlusion was reasonably expected to occur. Occluded scenarios are generally expected
where workers are expected to come into contact with bulk liquid 1-BP during use in open systems (e.g.,
during solvent changeout in vapor degreasing and dry cleaning) and not expected in closed-type systems
(e.g., during connection/disconnection of hoses used in loading of bulk containers in manufacturing).
See further discussion on occlusion in Appendix J. The exposure estimates are provided for each
condition of use, where the conditions of uses are "binned" based on the maximum possible exposure
concentration (Yderm), the likely level of exposure, and potential for occlusion. The exposure
concentration is determined based EPA's review of currently available products and formulations
containing 1-BP. For example, EPA found that 1-BP concentration in degreasing formulations such as
Solvon PB can be as high as 97 percent:
• Bin 1: Bin 1 covers industrial uses that generally occur in closed systems. For these uses, dermal
exposure is likely limited to chemical loading/unloading activities (e.g., connecting hoses) and
taking quality control samples. EPA assesses the following glove use scenarios for Bin 1
conditions of use:
o No gloves used: Operators in these industrial uses, while working around closed-system
equipment, may not wear gloves or may wear gloves for abrasion protection or gripping
that are not chemical resistant,
o Gloves used with a protection factor of 5, 10 and 20: Operators may wear gloves when
taking quality control samples or when connecting and disconnecting hoses during
loading/unloading activities. EPA assumes gloves may offer a range of protection,
depending on the type of glove and employee training provided,
o Scenarios not assessed: EPA does not assess occlusion as workers in these industries are
not likely to come into contact with bulk liquid 1-BP that could lead to chemical
permeation under the cuff of the glove or excessive liquid contact time with chemical
permeation through the glove.
• Bin 2: Bin 2 covers industrial degreasing uses, which are not closed systems. For these uses,
there is greater opportunity for dermal exposure during activities such as charging and draining
degreasing equipment, drumming waste solvent, and removing waste sludge. EPA assesses the
following glove use scenarios for Bin 2 conditions of use:
o No gloves used: Due to the variety of shop types in these uses, the actual use of gloves is
uncertain. EPA assumes workers may not wear gloves or may wear gloves for abrasion
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protection or gripping that are not chemical resistant during routine operations such as
adding and removing parts from degreasing equipment,
o Gloves used with a protection factor of 5, 10 and 20: Workers may wear gloves when
charging and draining degreasing equipment, drumming waste solvent, and removing
waste sludge. EPA assumes gloves may offer a range of protection, depending on the
type of glove and employee training provided,
o Occluded Exposure: Occlusion may occur when workers are handling bulk liquid 1-BP
when charging and draining degreasing equipment, performing work on the degreasing
tank, drumming waste solvent, and removing waste sludge. These activities could lead to
chemical permeation under the cuff of the glove or excessive liquid contact time where
chemical permeates through the glove.
• Bin 3: Bin 3 covers the use of 1-BP in spray adhesives in foam cushion product manufacturing,
which is a unique condition of use. Workers (sprayers) can be dermally exposed when mixing
adhesive, charging adhesive to spray equipment, and cleaning adhesive spray equipment. Other
workers (non-sprayers) may also have incidental contact with the applied adhesive during
subsequent fabrication steps. EPA assesses the following glove use scenarios for Bin 3
conditions of use:
o No gloves used: Actual use of gloves in this use is uncertain. EPA assumes workers may
not wear gloves or may wear gloves for abrasion protection or gripping that are not
chemical resistant during routine operations such as spray applications and fabrication
steps (non-sprayers).
o Gloves used with a protection factor of 5 and 10: Workers may wear gloves when mixing
adhesive, charging adhesive to spray equipment, and cleaning adhesive spray equipment.
EPA assumes the commercial facilities in Bin 3 do not offer activity-specific training on
donning and doffing gloves,
o Occluded Exposure: Occlusion may occur when workers are handling bulk liquid 1-BP
when mixing adhesive, charging adhesive to spray equipment, and cleaning adhesive
spray equipment that could lead to chemical permeation under the cuff of the glove or
excessive liquid contact time with to chemical permeation through the glove,
o Scenarios not assessed: EPA does not assess glove use with protection factors of 20 as
EPA assumes chemical-resistant gloves used in these industries would be accompanied
by basic employee training, but not activity-specific training.
• Bin 4: Bin 4 covers commercial activities of similar maximum concentration. Most of these uses
are uses at dry cleaners, and/or uses expected to have direct dermal contact with bulk liquids. At
dry cleaning shops, workers may be exposed to bulk liquids while charging and draining solvent
to/from machines, removing and disposing sludge, and maintaining equipment. Workers can also
be exposed to 1-BP used in spot cleaning products at the same shop. EPA assesses the following
glove use scenarios for Bin 4 conditions of use:
o No gloves used: Actual use of gloves in this use is uncertain. EPA assumes workers may
not wear gloves during routine operations (e.g., spot cleaning),
o Gloves used with a protection factor of 5 and 10: Workers may wear gloves when
charging and draining solvent to/from machines, removing and disposing sludge, and
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maintaining equipment. EPA assumes the commercial facilities in Bin 4 do not offer
activity-specific training on donning and doffing gloves,
o Occluded Exposure: Occlusion may occur when workers are handling bulk liquid 1-BP
when charging and draining solvent to/from machines, removing and disposing sludge,
and maintaining equipment that could lead to chemical permeation under the cuff of the
glove or excessive liquid contact time with chemical permeation through the glove,
o Scenarios not assessed: EPA does not assess glove use with protection factors of 20 as
EPA assumes chemical-resistant gloves used in these industries would be accompanied
by basic employee training, but not activity-specific training.
• Bin 5: Bin 5 covers aerosol uses, where workers are likely to have direct dermal contact with
film applied to substrate and incidental deposition of aerosol to skin. This bin also covers
miscellaneous non-aerosol applications that are typically niche uses of 1-BP. EPA assesses the
following glove use scenarios for Bin 5 conditions of use:
o No gloves used: Actual use of gloves in this use is uncertain. EPA assumes workers may
not wear gloves or may wear gloves for abrasion protection or gripping that are not
chemical resistant during routine aerosol applications,
o Gloves used with a protection factor of 5 and 10: Workers may wear gloves when
applying aerosol products. EPA assumes the commercial facilities in Bin 5 do not offer
activity-specific training on donning and doffing gloves,
o Scenarios not assessed: EPA does not assess glove use with protection factors of 20 as
EPA assumes chemical-resistant gloves used in these industries would be accompanied
by basic employee training, but not activity-specific training. EPA does not assess
occlusion for aerosol applications because 1-BP formulation is often supplied in an
aerosol spray can and contact with bulk liquid is unlikely. EPA also does not assess
occlusion for non-aerosol niche uses because the potential for occlusion is unknown.
As shown in the table, the calculated retained dose is low for all non-occluded scenarios as 1-BP
evaporates quickly after exposure. Dermal exposure to liquid is not expected for occupational non-users,
as they do not directly handle 1-BP.
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Table 2-37. Estimated Dermal Retained Dose (mg/day) for Workers in All Conditions of Use
Condition of Use
Bin
Non-Occluded Exposure
Max
Yd erm
No Gloves
(PF = 1)
Protective Gloves
(PF = 5)
Protective Gloves
(PF = 10)
Protective Gloves
(Industrial uses,
PF = 20)
Occluded
Exposure
Manufacture
Import, Repackaging
Processing - Incorporating into
formulation
Processing as a reactant
Bin 1
1.0
0.7
Processing - Incorporating into articles
Recycling
Disposal
0.4
0.2
N/A - occlusion
not expected
Use - Batch vapor degreaser
Use - In-line vapor degreaser
Bin 2
0.97
0.7
Use - Cold cleaner
0.3
0.2
2,180
Use - Adhesive chemicals (Spray
adhesives)
Bin 3
0.£
0.6
0.3
N/A
1,798
Use - Dry cleaning
Use - Spot cleaner. Stain remover
Bin 4
0.94
0.7
0.3
N/A
2,112
Use - Other non-aerosol uses
Use - Aerosol spray degreaser/cleaner,
other aerosol uses
Bin 5
1.0
0.7
0.4
N/A
N/A - occlusion
not expected
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3 Discussion of Uncertainties and Limitations
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. Where the statistical variation is
not known, assumptions are made to estimate the parameter distribution using available literature data.
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. 2001b). The following sections discuss
uncertainties associated with the 1-BP engineering assessment.
3.2.1 Number of Workers
There are a number of uncertainties surrounding the estimated number of workers potentially exposed to
1-BP, as outlined below. Most are unlikely to result in a systematic underestimate or overestimate, but
could result in an inaccurate estimate.
CDR are used to estimate the number of workers associated with the following conditions of use:
Manufacturing, Import, Processing as a Reactant, and Incorporation into Formulation, Mixture, or
Reaction Product. There are inherent limitations to the use of CDR data as they are reported by
manufacturers and importers of 1-BP. First, manufacturers and importers are only required to report if
they manufactured or imported 1-BP in excess of 25,000 pounds at a single site during any calendar
from 2012 to 2015; as such, CDR may not capture all site sand workers associated with any given
chemical. Second, the estimate is based on information that is known or reasonably ascertainable to the
submitter. CDR submitters (chemical manufacturers and importers) do not always have accurate
information on the number of potentially exposed workers at downstream processing sites.
There are also uncertainties associated with BLS data, which are used to estimate the number of workers
for the remaining conditions of use. First, BLS' OES employment data for each industry/occupation
combination are only available at the 3-, 4-, or 5-digit NAICS level, rather than the full 6-digit NAICS
level. This lack of granularity could result in an overestimate of the number of exposed workers if some
6-digit NAICS are included in the less granular BLS estimates but are not, in reality, likely to use 1-BP
for the assessed condition of use. EPA addressed this issue by refining the OES estimates using total
employment data from the U.S. Census' SUSB. However, this approach assumes that the distribution of
occupation types (SOC codes) in each 6-digit NAICS is equal to the distribution of occupation types at
the parent 5-digit NAICS level. If the distribution of workers in occupations with 1-BP exposure differs
from the overall distribution of workers in each NAICS, then this approach will result in inaccuracy.
Second, EPA's judgments about which industries (represented by NAICS codes) and occupations
(represented by SOC codes) are associated with the uses assessed in this report are based on EPA's
understanding of how 1-BP is used in each industry. Designations of which industries and occupations
have potential exposures is nevertheless subjective, and some industries/occupations with few exposures
might erroneously be included, or some industries/occupations with exposures might erroneously be
excluded. This would result in inaccuracy but would be unlikely to systematically either overestimate or
underestimate the count of exposed workers.
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3.2.2 Analysis of Exposure Monitoring Data
To analyze exposure monitoring data, EPA categorized individual PBZ data point as either "worker" or
"occupational non-user". Exposures for occupational non-users can vary substantially. Most data
sources do not sufficiently describe the proximity of these employees to the 1-BP exposure source. As
such, exposure levels for the "occupational non-user" category will have high variability depending on
the specific work activity performed. It is possible that some employees categorized as "occupational
non-user" have exposures similar to those in the "worker" category depending on their specific work
activity pattern.
Some data sources may provide exposure estimates that are higher than typical across the distribution of
facilities for that condition of use. For example, NIOSH HHEs for the spray adhesive use were
conducted to address concerns regarding adverse human health effects reported following 1-BP
exposure with spray adhesive use in furniture manufacturing. Two HHEs were requested by the North
Carolina Department of Labor; one was conducted in response to a confidential request submitted by the
facility's employees.
There are limited exposure monitoring data in literature for certain conditions of use or job categories.
For the spray adhesive use example, the number of data points available for non-sprayers is less than
half of the data points available for sprayers. Additionally, very few exposure monitoring data are
available for cold cleaning and for spot-cleaning. Where few data points are available, assessed exposure
levels are unlikely to be representative of worker exposure across the entire job category or industry.
For vapor degreasing and cold cleaning, several sources do not contain detailed information describing
the type of degreaser or cleaner present at the facility. The lack of such information results in uncertainty
in the assessed exposure levels associated with specific subcategories of such equipment. For example,
the data presented for batch open-top vapor degreasers may actually include data associated with other
types of degreaser.
Where sufficient data were available, the 95th and 50th percentile exposure concentrations were
calculated using available data. The 95th percentile exposure concentration is intended to represent a
high-end exposure level, while the 50th percentile exposure concentration represents typical (central
tendency) exposure level. The underlying distribution of the data, and the representativeness of the
available data, are not known.
3.2.3 Near-Field / Far-Field Model Framework
The near-field / far-field approach is used as a framework to model inhalation exposure for many
conditions of use. The following describe uncertainties and simplifying assumptions generally
associated with this modeling approach:
• There is some degree of uncertainty associated with each model input parameter. In general, the
model inputs were determined based on review of available literature. Where the distribution of
the input parameter is known, a distribution is assigned to capture uncertainty in the Monte Carlo
analysis. Where the distribution is unknown, a uniform distribution is often used. The use of a
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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). Since vapor degreasing and cold
cleaning involve automated processes, a worker may actually walk away from the near-field
during part of the process and return when it is time to unload the degreaser. As such, assuming
the worker is exposed at the near-field concentration for the entire activity duration may
overestimate exposure.
• For certain 1-BP applications (e.g. vapor degreasing and cold cleaning), 1-BP vapor is assumed
to emit continuously while the equipment operates (i.e. constant vapor generation rate). Actual
vapor generation rate may vary with time. However, small time variability in vapor generation is
unlikely to have a large impact in the exposure estimates as exposures are calculated as a time-
weighted average.
• The exposure models represent model workplace settings for each 1-BP condition of use. The
models have not been regressed or fitted with monitoring data.
• The models represent a baseline scenario that do not have LEV. EPA does not have adequate
data to construct LEV systems into the exposure models. Additionally, there is no data on the
fraction of U.S. facilities that use LEV. Where available, "what-if' values on engineering control
effectiveness are applied to the model baseline to provide post-EC scenarios. These values were
obtained by reviewing statements made in published literature regarding potential emission or
exposure reductions after implementation of engineering control or equipment substitution.
Each subsequent section below discusses uncertainties associated with the individual model.
3.2.3.1 Vapor Degreasing and Cold Cleaning Model
The vapor degreasing and cold cleaning assessments use a near-field / far-field approach to model
worker exposure. In addition to the uncertainties described above, the vapor degreasing and cold
cleaning models have the following uncertainties:
• To estimate vapor generation rate for vapor degreasing, EPA references a 1-BP emission factor
developed by CARB for the California Solvent Cleaning Emissions Inventories (CARB. 2011).
The emission factor is an average emission for the "vapor degreasing" category for the California
facilities surveyed by CARB. The category includes batch-loaded vapor degreaser, aerosol
surface preparation process, and aerosol cleaning process. For the purpose of modeling, EPA
assumes the 1-BP emission factor is entirely attributed to vapor degreasing applications. The
representativeness of the emission factor for vapor degreasing emissions in other geographic
locations within the U.S. is uncertain.
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• The CARB emission factor covers batch degreasing units. However, CARB does not further
specify whether these are open-top vapor degreasers, enclosed, or other types of batch
degreasers. EPA assumes the emission factor is representative of open-top vapor degreaser, as it
is the most common design for batch units using 1-BP. In addition, EPA assumes that the
surveyed facilities likely switched to using 1-BP, an alternative, non-HAP solvent, as a way of
complying with Federal and State regulations for HAP halogenated solvents (i.e., chemical
substitution, rather than equipment changes).
• The CARB emission factor, in the unit of pound per employee-year, was developed for the
purpose of estimating annual emissions. These types of emission factor typically reflect the
amount of solvent lost / emitted, some of which may not be relevant to worker exposure. For
example, 1-BP emitted and captured through a stack may not result in worker exposure.
Therefore, assuming all of the 1-BP is emitted into the workplace air may result in
overestimating of exposure. In addition, the use of an annual emission factor does not capture
time variability of emissions. The approach assumes a constant emission rate over a set number
of operating hours, while actual emissions and worker exposures will vary as a function of time
and worker activity.
• EPA combines the CARB emission factor with nationwide Economic Census employment data
across 78 NAICS industry sector codes. It should be noted that vapor degreasing is not an
industry-specific operation. Only a subset of facilities within the 78 selected industry sectors are
expected to operate vapor degreasers. Therefore, the industry-average employment data may not
be representative of the actual number of employees at vapor degreasing facilities.
• To estimate worker exposure during cold cleaning, EPA applied an emission reduction factor to
the vapor degreasing model by comparing the AP-42 emission factors for the two applications.
The AP-42 emission factors are dated. Furthermore, the cold cleaning model results have not
been validated with actual monitoring data.
• EPA assumes workers and occupational non-users remove themselves from the contaminated
near- and far-field zones at the conclusion of the task, such that they are no longer exposed to
any residual 1-BP in air.
• The model assumes an exposure reduction of 90 percent with engineering control. In reality,
engineering controls and their effectiveness are site-specific. Additionally, the 90 percent
reduction is a value based on TCE, and may not be applicable to a more volatile chemical such
as 1-BP.
3.2.3.2 Aerosol Degreasing Model
The aerosol degreasing assessment also uses a near-field/far-field approach to model worker exposure.
Specific uncertainties associated with the aerosol degreasing scenario are presented below:
• The model references a CARB study 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 1-BP.
• The Use Dossier identifies 25 different aerosol degreasing formulations containing 1-BP (EPA-
HO-OPPI-:-«I • < * 4 i< M03.0: ^ 201 b)). For each Monte Carlo iteration, the model
determines the 1-BP concentration in product by selecting one of 25 possible formulations,
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assuming equal probability of each formulation being used. In reality, some formulations are
likely more prevalent than others.
3.2.3.3 Dry Cleaning Model
The multi-zone dry cleaning model also uses a near-field/far-field approach. Specific uncertainties
associated with the dry cleaning scenario are presented below:
• The model assumes each facility only has one dry cleaning machine, cleaning one to fourteen
loads of garments per day. While the dry cleaning facilities in Blando et al. Q ) and NIOSH
Q ) appear to only have one machine, the representativeness of these two studies is not
known. Larger facilities are likely to have more machines, which could result in additional 1-BP
exposures.
• The model conservatively uses a hemispherical volume based on the dry cleaning machine door
diameter as the near-field for machine unloading. The small near-field volume results in a large
spike in concentration when the machine door is opened, where any residual 1-BP solvent is
assumed to be instantaneously released into the near-field. In reality, the residual solvent will
likely be released continuously over a period of time. In addition, the worker may move around
while unloading the garments, such that the worker's breathing zone will not always be next to
the machine door throughout the duration of this activity. Therefore, these assumptions may
result in an overestimate of worker exposure during machine unloading.
• Many of the model input parameters were obtained from (Von Grote. 20031 which is a German
study. Aspects of the U.S. dry cleaning facilities may differ from German facilities. However, it
is not known whether the use of German data will under- or over-estimate exposure.
• The model does not cover all potential worker activities at dry cleaners. For example, workers
could be exposed to 1-BP emitted due to equipment leaks, when re-filling 1-BP solvent into dry
cleaning machines, when interrupting a dry cleaning cycle, or when performing maintenance
activities (e.g., cleaning lint and button traps, raking out the still, changing solvent filter, and
handling solvent waste) (OSHA. 2005). However, there is a lack of information on these
activities in the literature, and the frequency of these activities is not well understood. The
likelihood of equipment leaks is dependent on whether the machines are properly converted and
maintained. The frequency of solvent re-filling depends on a specific dry cleaner's workload and
solvent consumption rate, which is also affected by the presence of leaks. Based on observations
reported by (NIOSH. 2010) and (Blando et al.. 2010). solvent charging is not performed every
day. EPA was unable to develop a modeling approach for these exposure activities due to the
lack of available information.
3.2.3.4 Spot Cleaning Model
The spot cleaning assessment also uses a near-field/far-field approach to model worker exposure. The
model estimates a use rate of 16 gallons per year spot cleaner. This value was derived using a MassDEP
case study for one specific dry cleaner in Massachusetts, handling 100 pieces of garments per day.
MassDEP noted that the size of each dry cleaner can vary substantially. As such, the spot cleaner use
rate will also vary by the individual facility work load.
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3.2.4 Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure
Model
For Import/repackaging, Processing as a reactant, and Processing - Incorporation into articles, the Tank
Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model is used to estimate
the airborne concentration associated with generic chemical loading scenarios at industrial facilities.
Specific uncertainties associated with this model are described below:
• After each loading event, the model assumes saturated air containing 1-BP 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 representativeness of the whole
range of loading equipment used at industrial facilities handling 1-BP.
• 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 1-BP, and the
accuracy of EPA's assumption on equipment type are not known.
• The model assumes the use a vapor balance system to minimize fugitive emissions. Although
most industrial facilities are likely o use a vapor balance system when loading/unloading volatile
chemicals, EPA does not know whether these systems are used by all facilities that potentially
handle 1-BP.
3.2.5 Modeling Dermal Exposures
The Dermal Exposure to Volatile Liquids Model assumes a single exposure event per day based on
existing framework of the EPA/OPPT 2-Hand Dermal Exposure model. The model does not address
how contact duration and frequency affects dermal exposure.
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4 REFERENCES
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Appendix A Approach for Estimating Number of Workers
This appendix summarizes the methods that EPA used to estimate the number of workers where CDR
data are not available. This approach is used to estimate number of workers associated with the
following 1-BP conditions of use:
• Processing - Incorporation into Articles;
• Batch Vapor Degreaser (Open-Top);
• Batch Vapor Degreaser (Closed-Loop);
• In-line Vapor Degreaser (Conveyorized);
• Aerosol Spray Degreaser/Cleaner;
• Dry Cleaning;
• Adhesive Chemicals (Spray Adhesives); and
• Disposal.
The method consists of the following steps:12
1. Identify the North American Industry Classification System (NAICS) codes for the industry
sectors associated with each condition of use.
2. Estimate total employment by industry/occupation combination using the Bureau of Labor
Statistics' Occupational Employment Statistics (OES) data (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 1-BP instead of other chemicals (i.e., the
market penetration of 1-BP in the condition of use).
5. Estimate the number of sites and number of potentially exposed employees per site.
6. Estimate the number of potentially exposed employees within the condition of use.
For the following conditions of use, the approach for estimating number of workers has been previously
documented in Appendix F of EPA's 2016 draft Risk Assessment:
• Vapor Degreaser (Batch Open-Top, Batch Closed-Loop, and Conveyorized);
• Aerosol Spray Degreaser/Cleaner;
• Dry Cleaning and Spot Cleaning; and
• Adhesive Chemicals (Spray Adhesives).
Step 1: Identifying Affected NAICS Codes
As a first step, EPA identified NAICS industry codes associated with each condition of use. EPA
generally identified NAICS industry codes for a condition of use by:
12 For conditions of use previously assessed in EPA's 2016 draft Risk Assessment, 2015 BLS data (U.S. BLS. 2015) and
2012 SUSB data (U.S. Census Bureau. 2012) are used.
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• Querying the U.S. Census Bureau's NAICSSearch tool using keywords associated with each
condition of use to identify NAICS codes with descriptions that match the condition of use.
• Referencing EPA/OPPT Generic Scenarios (GS's) and Organisation for Economic Co-operation
and Development (OECD) Emission Scenario Documents (ESDs) for a condition of use to
identify NAICS codes cited by the GS or ESD.
• Reviewing Chemical Data Reporting (CDR) data for the chemical, identifying the industrial
sector codes reported for downstream industrial uses, and matching those industrial sector codes
to NAICS codes using Table D-2 provided in the CDR reporting instructions.
TableApx A-l provides the applicable NAICS codes for these 1-BP conditions of use.
Table Apx A-l. Affected NAICS Codes for Select 1-BP Conditions of Use
Condition of Use
NAICS
Industry
Processing - Incorporation into
Articles
326150
Urethane and Other Foam Product (except Polystyrene)
Manufacturing
Batch Vapor Degreaser (Open-
Top)
Multiple
See Aroendix F ofEPA's2016 1-BP draft Risk Assessment
Batch Vapor Degreaser (Closed-
Loop)
In-line Vapor Degreaser
(Conveyorized)
Aerosol Spray
Degreaser/Cleaner
Multiple
See Aroendix F ofEPA's2016 1-BP draft Risk Assessment
Dry Cleaning
812320
Drycleaning and Laundry Services (except Coin-Operated)
Adhesive Chemicals (Spray
Adhesives)
337121
Upholstered Household Furniture Manufacturing
337125
Household Furniture (except Wood and Metal) Manufacturing
337127
Institutional Furniture Manufacturing
337214
Office Furniture (except Wood) Manufacturing
Disposal
562211
Hazardous Waste Treatment and Disposal
562212
Solid Waste Landfill
562213
Solid Waste Combustors and Incinerators
562219
Other Nonhazardous Waste Treatment and Disposal
327310
Cement Manufacturing
Step 2: Estimating Total Employment by Industry and Occupation
BLS's (2016) OES data provide employment data for workers in specific industries and occupations.
The industries are classified by NAICS codes (identified previously), and occupations are classified by
Standard Occupational Classification (SOC) codes.
Among the relevant NAICS codes (identified previously), EPA reviewed the occupation description and
identified those occupations (SOC codes) where workers are potentially exposed to 1-BP. Table Apx
A-2 shows the SOC codes EPA classified as occupations potentially exposed to 1-BP. 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.
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TableApx A-2. SOCs with Worker and ONU Designations for All Conditions of Use Except Dry
Cleaning
SOC
Occupation
Designation
11-9020
Construction Managers
O
17-2000
Engineers
O
17-3000
Drafters, Engineering Technicians, and Mapping Technicians
0
19-2031
Chemists
0
19-4000
Life, Physical, and Social Science Technicians
0
47-1000
Supervisors of Construction and Extraction Workers
0
47-2000
Construction Trades Workers
w
49-1000
Supervisors of Installation, Maintenance, and Repair Workers
0
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
0
51-2000
Assemblers and Fabricators
w
51-4020
Forming Machine Setters, Operators, and Tenders, Metal and Plastic
w
51-6010
Laundry and Dry-Cleaning Workers
w
51-6020
Pressers, Textile, Garment, and Related Materials
w
51-6030
Sewing Machine Operators
0
51-6040
Shoe and Leather Workers
0
51-6050
Tailors, Dressmakers, and Sewers
0
51-6090
Miscellaneous Textile, Apparel, and Furnishings Workers
0
51-8020
Stationary Engineers and Boiler Operators
w
51-8090
Miscellaneous Plant and System Operators
w
51-9000
Other Production Occupations
w
W = Worker designation
O = ONU designation
For dry cleaning facilities, due to the unique nature of work expected at these facilities and that different
workers may be expected to share among activities with higher exposure potential (e.g., unloading the
dry cleaning machine, pressing/finishing a dry cleaned load), EPA made different SOC code worker and
ONU assignments for this condition of use. Table Apx A-3 summarizes the SOC codes with worker and
ONU designations used for dry cleaning facilities.
Table Apx A-3. 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
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SOC
Occupation
Designation
51-6010
Laundry and Dry-Cleaning Workers
W
51-6020
Pressers, Textile, Garment and Related Materials
W
51-6030
Sewing Machine Operators
0
51-6040
Shoe and Leather Workers
0
51-6050
Tailors, Dressmakers, and Sewers
0
51-6090
Miscellaneous Textile, Apparel, and Furnishings Workers
0
W = worker designation
O = ONU designation
After identifying relevant NAICS and SOC codes, EPA used BLS data to determine total employment
by industry and by occupation based on the NAICS and SOC combinations. For example, there are
110,640 employees associated with 4-digit NAICS 8123 {Drycleaning and Laundry Services) and SOC
51-6010 (Laundry and Dry-Cleaning Workers).
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 1-BP exposure are included. As an example, OES data are
available for the 4-digit NAICS 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 A-4 illustrates this granularity adjustment for NAICS 812320.
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TableApx A-4. 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
8123
49-9070
Maintenance and Repair
Workers, General
w
3,260
46.0%
1,499
8123
49-9090
Miscellaneous Installation
Maintenance, and Repair
Workers
w
1,080
46.0%
497
8123
51-6010
Laundry and Dry-Cleaning
Workers
w
110,640
46.0%
50,867
8123
51-6020
Pressers, Textile, Garment,
and Related Materials
w
40,250
46.0%
18,505
8123
51-6030
Sewing Machine Operators
0
1,660
46.0%
763
8123
51-6040
Shoe and Leather Workers
0
Not Reported for this NAICS Code
8123
51-6050
Tailors, Dressmakers, and
Sewers
0
2,890
46.0%
1,329
8123
51-6090
Miscellaneous Textile,
Apparel, and Furnishings
Workers
0
0
46.0%
0
Total Potentially Exposed Employees
206,070
94,740
Total Workers
72,190
Total Occupational Non-Users
22,551
Note: numbers may not sum exactly due to rounding.
W = worker
O = occupational non-user
Source: (U.S. Census Bureau. 2015) (U.S. BLS. 2016)
Step 4: Estimating the Percentage of Workers Using 1-BP 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, where available. This accounts for the fact that 1-BP may be only one of multiple
chemicals used for the applications of interest. EPA only identified market penetration data for a limited
number of conditions of use. In the absence of market penetration data for a given condition of use, EPA
assumed 1-BP may be used at up to all sites and by up to all workers calculated in this method as a
bounding estimate. This assumes a market penetration of 100%. Market penetration is discussed for each
condition of use in the main body of this report.
Step 5: Estimating the Number of Workers per Site
EPA calculated the number of workers and occupational non-users in each industry/occupation
combination using the formula below (granularity adjustment is only applicable where SOC data are not
available at the 6-digit NAICS level):
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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 (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 a Condition of Use
EPA estimated the number of workers and occupational non-users potentially exposed to 1-BP and the
number of sites that use 1-BP in a given condition of use through the following steps:
6. A. Estimating the number of establishments that use 1-BP by:
i. Obtaining the number of establishments from SUSB (2015) at the 6-digit NAICS level
(Step 5) for each NAICS code in the condition of use and summing these values, and
multiplying by the market penetration factor from Step 4; or
ii. Obtaining the number of establishments from the TRI, literature, or public comments for
the condition of use.
6.B. Estimating the number of workers and occupational non-users potentially exposed to 1-BP by
taking the number of establishments calculated in Step 6. A and multiplying it by the average
number of workers and occupational non-users per site from Step 5.
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Appendix B Equations for Calculating Acute and Chronic Exposures
for Non-Cancer and Cancer
This report assesses 1-BP exposures to workers and occupational non-users in occupational settings,
presented as 8-hr time weighted average (TWA) exposure. The 8-hr TWA exposures are then used to
calculate acute exposure concentration (AC), average daily concentration (ADC) for chronic, non-cancer
risks, and lifetime average daily concentration (LADC) for chronic, cancer risks.
Acute workplace exposures are assumed to be equal to the contaminant concentration in air (8-hr TWA,
unless otherwise noted).
EquationApx B-l
AC = CXED
AT^cute
Where:
AC = Acute exposure concentration
C = Contaminant concentration in air (8-hr TWA)
ED = Exposure duration (hr/day)
ATAcute = Averaging time for acute exposure (hr)
ADC and LADC are used to estimate workplace exposures for non-cancer and cancer risks, respectively.
These exposures are estimated as follows:
Equation Apx B-2
Equation Apx B-3
Equation Apx B-4
Equation Apx B-5
An/- TAP./- CxEDxEFxWY
ADC or LADC =
AT or ATr
EF = AWD X f
day hr
AT = LTX 260— X 8-
yr day
day hr
ATC = LTC X 260— X 8-
yr day
Where:
ADC = Average daily concentration (8-hr TWA) used for chronic non-cancer risk calculations
LADC = Lifetime average daily concentration (8-hr TWA) used for chronic cancer risk
calculations
EF = Exposure frequency (day/yr)
WY = Working years per lifetime (yr)
AT = Averaging time (hr) for chronic, non-cancer risk
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ATc = Averaging time (hr) for cancer risk
AWD = Annual working days (day/yr)
f = Fractional working days with exposure (unitless)
LT = Lifetime years (yr) for non-cancer risk
LTc = Lifetime years (yr) for cancer risk
The parameter values in TableApx B-l and TableApx B-2 are used to calculate each of the above
acute or chronic exposure estimates. Where exposure is calculated using probabilistic modeling, the AC,
ADC, and LADC calculations are integrated into the Monte Carlo simulation. In this case, the lifetime
working years (LT) is defined as a triangular distribution with a minimum of 10.4 years, a mode of 36
years, and a maximum of 44 years (U.S. BLS. 2014) (U.S. Census Bureau. 2019a) (U.S. Census Bureau.
2019b). The corresponding 95th and 50th percentile values for this distribution is 40 years and 31 years,
respectively.
Table Apx B-l. Parameter Values for Calculating Acute Concentration
Parameter Name
Symbol
Value
Unit
Exposure Duration
ED
8
lir/day
Averaging Time (acute)
AT\ci no
8
lir/day
Table Apx B-2. Parameter Values for Calculating ADC and LADC
Parameter Name
Symbol
95th Percentile Value
50th Percentile
Value
Unit
Exposure Duration
ED
8
8
lir/day
Annual Working Days
AWD
260
260
day/yr
Fractional Working Days with
Exposure
f
1
1
unitless
Working Years per Lifetime
WY
40
31
yr
Lifetime (chronic, non-cancer)
LT
40
31
yr
Lifetime (chronic, cancer)
LTC
78
78
yr
Averaging Time (chronic, non-
cancer)
AT
83,200
64,480
hr
Averaging Time (chronic,
cancer)
ATC
162,240
162,240
hr
Table Apx B-3 presents parameters specific to the dry cleaning condition of use. The 95th and 50th
percentile exposure frequencies are determined through a 100,000-iteration Monte Carlo simulation,
where the fractional working days with exposure is defined as a uniform distribution with values ranging
from 0.8 to 1, and the annual working day is defined as a triangular distribution with minimum of 250
days, maximum of 312 days, and mode of 300 days per year.
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TableApx B-3. Parameter Values for Calculating ADC and LADC for Dry Cleaning
Parameter Name
Symbol
95th Percentile Value
50th Percentile Value
Unit
Exposure Duration
ED
8
8
lir/day
Exposure Frequency
EF
293
258
day/yr
Averaging Time (chronic, non-
cancer)
AT
93,760
63,984
hr
Averaging Time (chronic,
cancer)
ATC
182,832
160,992
hr
TableApx B-4 presents the parameters for calculating AC, ADC, and LADC where the exposure
concentration, C, is presented as 12-hr TWA (instead of 8-hr TWA). In this case, the averaging time in
the denominator of the ADC and LADC equation is calculated using EquationApx B-6.
EquationApx B-6
day hr
AT or ATC = LT or LTC x 365 x 24——
yr day
Table Apx B-4. Parameter Values for Calculating AC, ADC and LADC using 12-hr TWA
Exposure Concentration
Parameter Name
Symbol
95th Percentile Value
50th Percentile Value
Unit
Exposure Duration
ED
12
12
lir/day
Averaging Time (acute)
ATAcute
12
12
lir/day
Averaging Time (chronic, non-
cancer)
AT
350,400
271,560
hr
Averaging Time (chronic,
cancer)
ATC
683,280
683,280
hr
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Appendix C Summary of Department of Defense Data
Table Apx C-l summarizes available 1-BP exposure monitoring data at six DOD facilities from 2014 to
2017. The monitoring data comprise of short-term samples where the sampling time ranges from six to
180 minutes (0.1 to 3 hours). Short-term exposure level ranges from 0.3 to 22.5 ppm.
Based on available process descriptions, all work activities monitored involved some type of degreasing,
including vapor degreasing, aerosol degreasing, cold cleaning, spray or wipe cleaning. The process
equipment may be automatic or manually operated. Some degreasing processes occur on an as-needed
basis, while others are conducted throughout the entire work shift. In each case, it is not clear whether
the worker performs additional activities with potential for 1-BP exposure outside of the sampling
duration, as such, it is not possible to calculate the full-shift TWA exposure from the short-term
measurements.
Table Apx C-l. Summary of DOD Exposure Monitoring Data
Workplace
Process Name
Process
Frequency
Process
Duration
Sample
Date
Work
Shift
Duration
Sampling
Time
(min)
Measured
Result
(ppm)
Advanced
Composites
198E Phosphoric Acid Line
Daily
6-8 hours
12 Dec 17
8 Hours
24
2.7
Generators
Workplace
3 56A Parts Cleaning
Daily
0-15 mins
04 Sep 14
9 Hours
66
4.8
Daily
0-15 mins
19 Nov 14
9 Hours
82
0.6
Electrical/
Enviromnental /
Battery Shop
Electrical Components
Maintenance/Repair/Replace
Daily
0.5-1 hour
07 Jul 17
10 Hours
180
22.5
Daily
0.5-1 hour
07 Jul 17
10 Hours
140
0.3
56-N10
56: BLDG: Validate pre-
cleaning with contact cleaner
(spray/wipe cleaning) in Pre-
Cleaning Area
Special
Occasions
-
21 Jul 16
8 Hours
96
5.2
Special
Occasions
-
21 Jul 16
8 Hours
101
8.0
Code 32
3221-1018 Vapor
Degreasing Code 3221
Daily
-
02 Jun 14
8 Hours
151
1.4
Daily
-
02 Jun 14
8 Hours
151
1.4
Daily
-
02 Jun 14
8 Hours
142
2.9
Daily
-
02 Jun 14
8 Hours
101
1.4
FRCNW-500-
530-NDI
IND00208-Aerosol Can
Degreasing
Special
Occasions
0-15 mins
31 Aug 17
8 Hours
6
5.2
Data not available/provided
Source: (Defense Occupational Environmental Health Readiness System - Industrial Hygiene. 2018)
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Appendix D Tank Truck and Railcar Loading and Unloading Release
and Inhalation Exposure Model Approach and Parameter
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/OPPT 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;
• Import (repackaging); and
• Other similar conditions of use at industrial facilities (e.g., industrial processing aid).
As an example, imported 1-BP material may be packaged and loaded into a container before distributing
to another industrial processing or use site (e.g., formulation sites). At the industrial processing or use
site, 1-BP is then unloaded from the container into a process vessel before being incorporated into a
mixture, used as a chemical intermediate, or otherwise processed/used. For the model, EPA assumes 1-
BP 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 1-BP is volatile (vapor pressure above 0.01 torr at room temperature), fugitive emissions may
occur when 1-BP is loaded into or unloaded from a tank truck or railcar. Sources of these emissions
include:
• Displacement of saturated air containing 1-BP as the container/truck is filled with liquid;
• Emissions of saturated air containing 1-BP 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.
D.l Displacement of Saturated Air Inside Tank Trucks and Railcars
For screening-level assessments, EPA typically uses the EPA/OAQPS AP-42 Loading Model to
conservatively assess exposure during container unloading activities ( 2013a). The model
estimates release to air from the displacement of air containing chemical vapor as a container/vessel is
filled with liquid. 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. 2013aY
EPA expects the majority of industrial facilities to use a vapor balance system to minimize fugitive
emissions when loading and unloading tank trucks and railcars. 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.
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D.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 1-BP released will depend on
concentration in the vapor and the volume of vapor in the loading arm/hose/piping.
TableApx D-l presents the dimensions for several types of loading systems according to an OPW
Engineered Systems catalog. 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 1-BP 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 D-l
_fxMWx3,786AxVhxXxVP
1 ~ tdisconnect XTXRX 3, 600 X 760
Default values for Equation Apx D-l can be found in Table Apx D-2.
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Table Apx D-l. 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 Ann Fixed Reach
201.75
207.75
212.5
NA
2.7
6.4
11.6
NA
Top Loading Scissor Type Ann
197.875
206.5
213.25
NA
2.7
6.3
11.6
NA
Supported Boom Ann B-32-F
327.375
335
341.5
NA
4.5
10.3
18.6
NA
Unsupported Boom Ann GT-32-F
215.875
224.5
231.25
NA
2.9
6.9
12.6
NA
Slide Sleeve Ann 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: (OPW Engineered 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 D-2. Default Values for Calculating Emission Rate of 1-BP 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 factora
1
dimensionless
MW
Molecular weight of the chemical
122.99
g/mol
vh
Volume of transfer hose
See Table Apx D-l
gallons
r
Fill rate a
2 (tank truck)
1 (railcar)
containers/hr
tdiscomiect
Time to disconnect hose/couplers (escape of saturated vapor from
disconnected hose or transfer ann into air)
0.25
hr
X
Vapor pressure conection factor
1
dimensionless
VP
Vapor pressure of the pure chemical
146.26
ton
T
Temperature
298
K
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. 2013a).
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D.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. 2015) and EPA's
Protocol for Equipment Leak Emission Estimates (1995), the following equation can be used to estimate
emission rate El, calculated as the sum of average emissions from each process unit:
EquationApx D-2
V. ^ i'000
El = 2J>F** WFtoc XN)X
Parameters for calculating equipment leaks using Equation Apx D-3 can be found in TableApx D-3.
Table Apx D-3. Parameters for Calculating Emission Rate of 1-BP 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 D-4
kg/lir-
source
WFtoc
Average weight fraction of chemical in the stream
1
dimensionl
ess
N
Number of pieces of equipment of the applicable equipment
type in the stream
See Table Apx D-4
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 D.2. 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 D-4 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. 1995). 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 1-BP. 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.
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Table Apx D-4. Default Values for Fa and N
Equipment Type
Service
SOCMI Emission
Factor, Fa (kg/hr-
source)a
Number of
Equipment, N
(central tendency)
Number of
Equipment, N
(high-end)
Valves
Gas
Light liquid
Heavy liquid
0.00597
0.00403
0.00023
3 (gas)
5 (light liquid)
3 (gas)
10 (light 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 1-BP has a vapor pressure of 146 mmHg (19.5 kPa) at 25 °C. EPA
modeled 1-BP liquid as a light liquid.
b - The light liquid pump seal factor can be used to estimate the leak rate from agitator seals.
EPA assumed the following equipment are used in loading racks for the loading/unloading of tank
trucks and railcars. Figure Apx D-l illustrates an example tank truck and unloading rack equipment.
• Tank Truck Loading/Unloading:
o Liquid Service:
¦ Four valves (modeled as valves in light liquid service)
¦ One safety relief valve (modeled as valve in light liquid service)
¦ One bleed valve or sampling connection
¦ 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)
¦ 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. Therefore, a total of:
¦ Eight valves (modeled as valves in light liquid service)
¦ Two safety relief valves (modeled as valve in light liquid service)
¦ Two bleed valves or sampling connections
¦ 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)
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¦ One pressure relief valve
¦ One bleed valve (modeled as a sampling connection)
¦ One transfer arm connector
Vapor service line
Liquid service line
FigureApx D-l. Illustration of Transfer Lines Used During Tank Truck Unloading and
Associated Equipment Assumed by EPA
D.4 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. 2013a). The EPA OPPT Mass
Balance Inhalation Model estimates the exposure concentration using Equation Apx D-3 and the default
parameters found in TableApx D-5 (U.S. EPA. 2013a). TableApx D-6 presents exposure estimates for
1-BP using this approach. These estimates assume one unloading/loading event per day and 1-BP 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).
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EquationApx D-3
r
_ «->V
m~v~
vm
TableApx D-5. 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 l.OOO.OOOXXXW
or
MWXQXk 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
122.99
g/mol
Q
Outdoor ventilation rate
237,600 (central tendency)
26,400 x (60 x (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
146.26
torr
vm
Molar volume
24.45 25°C, 1 atm
L/mol
EPA also calculated acute and 8-hr TWA exposures as shown in Equation Apx D-4 and Equation Apx
D-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-hr TWA
exposure is the weighted average exposure during an entire 8-hr 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.
Equation Apx D-4
Cm(leak only) ^ (.h-event ~ tdisconnect) (Qn(ieafc and hose) ^ ^ disconnect)^ ^ ^cont
Acute TWA =
h-shift
Equation Apx D-5
Cm(leak only) ^ (.h-event ~ tdisconnect) (pm(leak and hose) ^ ^disconnect)) ^ ^cont
8 - hr TWA =
Where:
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Cm(ieak only) = Airborne concentration (mass-based) due to leaks during unloading while
hose connected (mg/m3)
Cm(ieak and hose) = Airborne concentration (mass-based) due to leaks and displaced air during
hose disconnection (mg/m3)
hevent = Exposure duration of each loading/unloading event (hr/event); calculated
as the inverse of the fill rate, r : 0.5 hr/event for tank trucks and 1 hr/event
for railcars
hshift = Exposure duration during the shift (hr/shift); calculated as h event X Ncont'. 0.5
hr/shift for tank trucks and 1 hr/shift for railcars
tdisconnect = Time duration to disconnect hoses/couplers (during which saturated vapor
escapes from hose into air) (hr/event)
Ncont = 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 D-6. Calculated 1-BP Emission Rates and Resulting Exposures 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
TWAa
(mg/m3)
8-hr
TWA
(mg/m3)
8-hr
TWA
(ppm)
Central Tendency
0.049
0.008
0.057
0.85
0.99
0.92
0.058
0.011
High-End
0.059
0.072
0.131
1.85
4.12
2.42
0.30
0.060
a - Acute TWA exposure is a 0.5-hr TWA exposure for the central tendency scenario and a 1-hr TWA exposure for the high-
end scenario.
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Appendix E Open-Top Vapor Degreasing Near-Field/Far-Field
Inhalation Exposure Model Approach and Parameter
This appendix presents the modeling approach and model equations used in the following models:
• Open-Top Vapor Degreasing Near-Field/Far-Field Inhalation Exposure Model; and
• Cold Cleaning Near-Field/Far-Field Inhalation Exposure Model.
The model was developed through review of relevant literature and consideration of existing EPA/OPPT
exposure models. The model uses a near-field/far-field approach (Keil. 2009). where a vapor generation
source located inside the near-field leads to the evaporation of vapors into the near-field, and indoor air
movements lead to the convection of vapors between the near-field and far-field. Workers are assumed
to be exposed to 1-BP vapor 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;
• Emission factor;
• Number of employees per site; and
• Operating hours per day.
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 50th and 95th percentile values. The
statistics were calculated directly in @Risk. The 50th percentile value was selected to represent a central
tendency exposure level, whereas the 95th percentile value was selected to represent a high-end
exposure. The following subsections detail the model design equations and parameters for the vapor
degreasing model.
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E.l Model Design Equations
FigureApx E-l illustrates the near-field/far-field modeling approach as it was applied by EPA to
degreasing facilities. As the figure shows, 1-BP vapors evaporate into the near-field (at evaporation rate
G), resulting in near-field exposures to workers at a concentration Cnf. The concentration is directly
proportional to the emission from the degreasing 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 1-BP dissipates into the far-field (i.e., the facility space surrounding the near-field), resulting in
occupational non-user exposures to 1-BP at a concentration Cff. Vff denotes the volume of the far-field
space into which the 1-BP dissipates out of the near-field. The ventilation rate for the surroundings,
denoted by Qff, determines how quickly 1-BP dissipates out of the surrounding space and into the
outdoor air.
Near-Fie Id
vo ati e Source
Figure Apx E-l. The Near-Field/Far-Field Model as Applied to the Open-Top Vapor Degreasing
Near-Field/Far-Field Inhalation Exposure Model and the Cold Cleaning Near-Field/Far-Field
Inhalation Exposure Model
The model design equations are presented below in EquationApx E-l through EquationApx E-l6.
Near-Field Mass Balance
dC\
Equation Apx E-l
Far-Field Mass Balance
Equation Apx E-2
V,
JNF
NF
dt
— CffQnf CnfQnf + ^
V,
dC,
FF
FF '
dt
CnfQnf CffQnf CffQff
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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;
G
average vapor generation rate; and
t
elapsed time.
Both of the previous equations can be solved for the time-varying concentrations in the near-field and
far-field as follows (Keil. 2009):
EquationApx E-3
CNF = G{k1 + k2eXlt - k3eX2t)
Equation Apx E-4
Cpp = G ^— 1- k4eXlt - kse^2t^
Where:
Equation Apx E-5
1
kl (_QnF__\q
\Qnf + Qff)
Equation Apx E-6
^ _ QnfQff + ^2^nf(.Qnf + Qff)
QnfQffVnf(.^i ~ ^2)
Equation Apx E-7
^ _ QnfQff + ^i^vf(Qwf + Qff)
QnfQffVnf(.^i ~ ^2)
Equation Apx E-8
+ (?/vf\ ,
M QKF )k2
Equation Apx E-9
_ /^2^/VF + Q/Vf\ ^
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EquationA
= 0.5
EquationA
X2 = 0.5
px E-10
^Qnf^ff + Vnf(Qnf + Qff)
Vnf^ff
+
(QnfVff + Vnf(Qnf + Qff)\ a (QnfQff\
1 ^ j ~4tewV
VNFVFF
px E-ll
Qnf^ff + Vnf(Qnf + QffT
V ^/VF^FF ,
/Qnf^ff + Vnf(Qnf + Qff)\ _ . /QnfQff\
\ ^/VF^FF / V ^/VF^FF '
EPA calculated the hourly TWA concentrations in the near-field and far-field using the following
equations. Note that the numerator and denominator of Equation Apx E-12 and EquationApx E-13,
use two different sets of time parameters. The numerator is based on the operating hours for the scenario
while the denominator is fixed to an averaging time span, t avg, of 8 hours (since EPA is interested in
calculating 8-hr TWA exposures). Mathematically, the numerator and denominator must reflect the
same amount of time. This is indeed the case since the numerator assumes exposures are zero for any
hours not within the operating time. Therefore, mathematically speaking, both the numerator and the
denominator reflect eight hours regardless of the values selected for ti and t2.
Equation Apx E-12
j^2 CNFdt J^2 G{kx + k2eXlt — k3eX2t)dt
C
NF.TWA ~ rtnvn - t
f a"g dt vavg
r(i * , MAlt2 k3ex^\ ( k2ex^ k3ex^\
C (fclt2 + -2^ ij—j - C [kltl +^J[
^avg
Equation Apx E-13
C,
CFFdt Stl G + k4e^ - kse^) dt
ff.twa ft dt ^
1^11? Is / -h
(j2_ k4eA^ _ kseA^\ _ (J±_ k^_
b\QFF+ A2 ) U{qff+ Ai
A,
tavg
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. Note that the FSA is not equal to the surface
area of the entire near-field. EPA defined the near-field zone to be a rectangular box resting on the floor;
therefore, no mass transfer can occur through the near-field box's floor. FSA is calculated in
Equation Apx E-14, below:
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EquationApx E-14
FSA = 2{LnfHnf) + 2(WnfHnf) + (LnfWnf)
Where: Lnf, Wnf, and Hnf are the length, width, and height of the near-field, respectively. The near-
field ventilation rate, Qnf, is calculated in Equation Apx E-15 from the near-field indoor wind speed,
vnf, and FSA, assuming half of FSA is available for mass transfer into the near-field and half of FSA is
available for mass transfer out of the near-field:
Equation Apx E-15
1
Qnf — 2 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 E-16:
Equation Apx E-16
Qff = Vff^ER
Using the model inputs in TableApx E-l, EPA estimated 1-BP 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.
E.2 Model Parameters
Table Apx 1-1 summarizes the model parameters and their values for the Open-Top Vapor Degreasing
Near-Field/Far-Field Exposure Model.
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TableApx E-l. Summary of Parameter Values and Distributions Used in the Open-Top Vapor Degreasing Near-Field/Far-Field
Inhalation Exposure Model
Input
Parameter
Symbol
Unit
Model Parameter
Values
Uncertainty Analysis
Assumptions
Distribution
Type
Comments
Value
Basis
Lower
Bound
Upper
Bound
Mode
Near-field
indoor wind
speed
Vnf
cm/s
(ft/s)
0
202.2
Lognonnal,
H= 22.41 cm/s
o= 19.96 cm/s
See Section E.2.3
Near-field
volume
Vnf
ft3
600
—
—
—
—
—
See Section E.2.4
Far-field
volume
Vff
ft3
10,594
Minimum
10,594
70,629
17,657
Triangular
See Section E.2.1
Air exchange
rate
AER
hr1
2
Minimum
2
20
3.5
Triangular
See Section E.2.2
Operating
days per year
OD
day/yr
260
—
—
—
—
—
The 2001 EPA Generic Scenario on the Use of
Vapor Degreasers estimates that degreasers of
all sizes operate 260 davs per vear (ERG. 2001).
Starting time
ti
hr
0
—
—
—
—
—
Constant value.
Exposure
Duration
t2
hr
—
—
—
—
—
—
Equal to operating hours per day.
See Section E.2.5
Averaging
time
tavg
hr
8
—
—
—
—
—
See Section E.2.6
Emission
factor
EF
lb/employe
e-yr
0
77.7
Lognonnal,
H= 10.4
c= 17.2
See Section E.2.7
Number of
employees per
site
EMP
employee/
site
1
1,800
LogLogistic
T =1
(3 = 51.1
a= 2.13
See Section E.2.8
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Input
Parameter
Symbol
Unit
Model Parameter
Values
Uncertainty Analysis
Assumptions
Distribution
Type
Comments
Value
Basis
Lower
Bound
Upper
Bound
Mode
Units per site
U
unit/site
1
1.2
Discrete
The EPA TCE RA (2014b) estimated 1 unit/site
for small vapor degreasing facilities, and 1.2
unit/site for large facilities based on analysis of
the National Emissions Inventory (NEI).
Because NEI data are not available for 1-BP,
EPA assumed equal probability of small versus
large facilities.
Vapor
generation
rate
G
kg/unit-hr
N/A
Calculated as the following:
G = EF x EMP / (2.2 x OH x OD x U)
Operating
hours per day
OH
lir/day
2
—
2
24
—
Discrete
See Section E.2.9
Engineering
controls
effectiveness
EC
%
90
Value suroorted bv Waddenet al. (1989). The
study indicates local exhaust ventilation can
reduce workplace emissions by 90 percent. The
estimate is based on an LEV system for an
open-top vapor degreaser (lateral exhaust hoods
installed on two sides of the tank).
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E.2.1 Far-Field Volume
EPA used the same far-field volume distribution for each of the models discussed. The far-field volume
is based on information obtained from von Grote et al. (2003) that indicated volumes at German metal
degreasing facilities can vary from 300 to several thousand cubic meters. They noted that smaller
volumes are more typical and assumed 400 and 600 m3 (14,126 and 21,189 ft3) in their exposure models
(Von Grote. 2003). These are the highest and lowest values EPA identified in the literature; therefore,
EPA assumes a triangular distribution bound from 300 m3 (10,594 ft3) to 2,000 m3 (70,629 ft3) with a
mode of 500 m3 (the midpoint of 400 and 600 m3) (17,657 ft3).
E.2.2 Air Exchange Rate
EPA used the same air exchange rate distribution for each of the models discussed. The air exchange
rate is based on data from Hellweg et al. (2009) and information received from a peer reviewer during
the development of the 2014 TSCA Work Plan Chemical Risk Assessment Trichloroethylene:
Degreasing, Spot Cleaning and Arts & Crafts Uses (SCG.' ) Hellweg et al. (2.009) reported that
average air exchange rates for occupational settings using mechanical ventilation systems vary from 3 to
20 hr"1. The risk assessment peer reviewer comments indicated that values around 2 to 5 hr"1 are likely
(SCG. 2013). in agreement with the low end reported by 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 2 hr"1, per the
risk assessment peer reviewer (SCG. 2013) and a maximum of 20 hr"1 per Hellweg et al. (2009).
E.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 industrial
distribution for facilities performing vapor degreasing and/or cold cleaning.
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 industrial facilities to a lognormal distribution with the
following parameter values: mean of 22.41 cm/s and standard deviation of 19.96 cm/s. In the model, the
lognormal distribution is truncated at a maximum allowed value of 202.2 cm/s (largest surveyed 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
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workplace setting. However, a mean air speed (averaged over a work area) is the required input for the
model.
E.2.4 Near-Field Volume
EPA assumed a near-field would have constant dimensions of 10 ft x 10 ft x 6 ft resulting in a total
volume of 600 ft3.
E.2.5 Exposure Duration
EPA assumed the maximum exposure duration for each model is equal to the entire work-shift (eight
hours). Therefore, if the degreaser/cold cleaning machine operating time was greater than eight hours,
then exposure duration was set equal to eight hours. If the operating time was less than eight hours, then
exposure duration was set equal to the degreaser/cold cleaning machine operating time (see Section
E.2.9 for discussion of operating hours).
E.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 for each of the models.
E.2.7 Emission Factor
EPA referenced 1-BP emission factor from a CARB study to estimate vapor generation rate.
To develop the California Solvent Cleaning Emissions Inventories, CARB surveyed solvent cleaning
facilities and gathered site-specific information for 213 facilities. CARB estimated a 1-BP emission
factor of 10.43 lb/employee-yr with a standard deviation of 17.24 lb/employee-yr (CARB. 2011). CARB
estimated that more than 98 percent of 1-BP emissions were attributed to vapor degreasing for the
solvent cleaning facilities surveyed. EPA applied a lognormal distribution to account for uncertainty in
the CARB emission factor. The distribution is truncated at the 99th percentile value of the dataset to
prevent the model from sampling values that approach infinity or are otherwise unrealistically large.
E.2.8 Number of Employees
To estimate the number of employees, EPA used data from the 2007 Economic Census for the vapor
degreasing NAICS codes identified in the TCE RA (U.S. EPA. 2014b). EPA fitted a LogLogisties
distribution to the Census data set. The distribution is truncated at the highest observed NAICS-specific
average employee per site from Census (1,800 employees), and has a lower bound of 1 employee per
site.
E.2.9 Operating Hours
For the operating hours, EPA used a discrete distribution based on the daily operating hours reported in
the 2014 NEI for TCE (1 r \ V \ ^ < ** i). It should be noted that not all units had an accompanying
reported daily operating hours; therefore, the distribution for the operating hours per day is based on a
subset of the reported units. The lowest observed value is 2 hr/day, and the highest value is 24 hr/day.
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Appendix F Cold Cleaning Near-Field/Far-Field Inhalation Exposure
Model Approach and Parameter
The Cold Cleaning Near-Field/Far-Field Inhalation Exposure Model uses the same model design
equations as described in E.l, but incorporates the several parameters specific to cold cleaning
operation. Table Apx F-l presents the parameters for the cold cleaning model.
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TableApx F-l. Summary of Parameter Values and Distributions Used in the Open-Top Vapor Degreasing Near-Field/Far-Field
Inhalation Exposure Model
Model Parameter
Values
Uncertainty Analysis
Assumptions
Input
Parameter
Symbol
Unit
Value
Basis
Lower
Bound
Upper
Bound
Mode
Distributio
n Type
Comments
Near-field
indoor wind
speed
Vnf
cm/s
(ft/s)
0
202.2
Lognonnal,
H= 22.41
cm/s
a= 19.96
cm/s
Baldwin and Mavnard (1998) surveyed the wind
speeds in 55 work areas covering a wide range of
workplaces. The study states that the pooled
distribution of all surveys and the distributions of
each survey, in general, could be approximated by
a lognonnal distribution. For industrial facilities,
the parameter is a lognonnal distribution with a
mean of 22.41 cm/s, and standard deviation of
19.96 cm/s. The maximum value is detennined to
be 202.2 cm/s, the largest observed value in the
study.
Near-field
volume
Vnf
ft3
600
EPA applied the same dimensions used in the
final TCE risk assessment (i.e., 10 ft for L\|. and
W- i. and 6 ft for H- , ) (U.S. EPA. 2014b). Value
supported by Demou et al. (2009).
Far-field
volume
Vff
ft3
10,594
Minimum
10,594
70,629
17,657
Triangular
Per von Grote et al. (2003). volumes at European
metal degreasing facilities can vary from 300 to
several thousand cubic meters. They noted smaller
volumes are more typical, and assumed 400 and
600 m3 in their models. EPA assumed a triangular
distribution bound from 300 m3 (10,594 ft3) to
2,000 m3 (70,629 ft3) with a mode of 500 m3 (the
midpoint of 400 and 600 m3, or 17,657 ft3)
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Input
Parameter
Symbol
Unit
Model Parameter
Values
Uncertainty Analysis
Assumptions
Distributio
n Type
Comments
Value
Basis
Lower
Bound
Upper
Bound
Mode
Air exchange
rate
AER
hr1
2
Minimum
2
20
3.5
Triangular
Hellwes et al. (2009) identifies averase AER for
occupational settings utilizing mechanical
ventilation systems to be between 3 and 20 hr1.
The EPA TCE RA peer review comments indicate
values around 2 to 5 hr1 may be more likely
(SCG. 2013). A trianeular distribution is used
with the mode equal to the midpoint of the range
provided by the RA peer reviewers (3.5 is the
midpoint of the range 2 to 5 hr1).
Operating
days per year
OD
day/yr
260
—
—
—
—
—
The 2001 EPA Generic Scenario on the Use of
Vapor Degreasers estimates that degreasers of all
sizes operate 260 davs per vear (ERG. 2001).
Starting time
ti
hr
0
—
—
—
—
—
Constant value.
Exposure
Duration
t2
hr
—
—
—
—
—
—
Equal to operating hours per day.
Averaging
time
tavg
hr
8
—
—
—
—
—
Constant value.
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Model Parameter
Values
Uncertainty Analysis
Assumptions
Input
Parameter
Symbol
Unit
Value
Basis
Lower
Bound
Upper
Bound
Mode
Distributio
n Type
Comments
Emission
factor
EF
lb/employe
e-yr
0
77.7
Lognormal,
p= 10.4
a= 17.2
To develop the California Solvent Cleaning
Emissions Inventories, CARB surveyed solvent
cleaning facilities and gathered site-specific
information for 213 facilities. CARB estimated a
1-BP emission factor of 10.43 lb/employee-yr
with a standard deviation of 17.24 lb/employee-yr
(CARB. 2011). CARB estimated that more than
98 percent of 1-BP emissions were attributed to
vapor degreasing for the solvent cleaning facilities
surveyed.
EPA applied a lognormal distribution to account
for uncertainty in the CARB emission factor. The
distribution is truncated at the 99th percentile
value of the dataset.
Number of
employees per
site
EMP
employee/
site
1
1,800
LogLogistic
Y=1
(3 = 51.1
a= 2.13
Data based on 2007 Economic Census for the
vapor degreasing NAICS codes identified in the
TCE RA (U.S. EPA. 2014b). EPA fitted a
LogLogistics distribution to the Census data set.
The distribution is truncated at the highest
observed NAICS-specific average employee per
site from Census (1,800 employees) and has a
lower bound of 1 employee per site.
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Input
Parameter
Symbol
Unit
Model Parameter
Values
Uncertainty Analysis
Assumptions
Distributio
n Type
Comments
Value
Basis
Lower
Bound
Upper
Bound
Mode
Units per site
U
unit/site
1
1.2
Discrete
The EPA TCE RA (2014b) estimated 1 unit/site
for small vapor degreasing facilities, and 1.2
unit/site for large facilities based on analysis of
the National Emissions Inventory (NEI). Because
NEI data are not available for 1-BP, EPA assumed
equal probability of small versus large facilities.
Vapor
generation
rate
G
kg/unit-hr
N/A
Calculated as the following:
G = EF x EMP / (2.2 x OH x OD x U)
Reduction
Factor
RF
0.032
0.57
Uniform
EPA AP-42 suggests that cold cleaning emissions
range from 3.2 to 57.1 percent of emissions from
a traditional ODcn-toD vaoor desreaser (U.S. EPA.
1981).
Operating
hours per day
OH
lir/day
3
24
Discrete
Distribution is based on NEI data for cold cleaner
operating hours per day for TCE. The lowest
observed value is 3 hr/day, and the highest value
is 24 hr/day.
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Appendix G Brake Servicing Near-Field/Far-Field Inhalation
Exposure Model Approach and Parameter
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/OPPT exposure models. This model uses a near-field/far-field
approach (Keil. 2.009). 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 1-BP 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 1-BP in the aerosol formulation;
• Amount of degreaser used per brake j ob;
• Number of degreaser applications per brake j ob;
• Time duration of brake j ob;
• Operating hours per week; and
• Number of j obs 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.
G.l 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
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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
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 1-1 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 a 1-BP 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 1-BP dissipates into the far-field
(i.e., the facility space surrounding the near-field), resulting in occupational bystander exposures to 1-BP
at a concentration Cff. Vff denotes the volume of the far-field space into which the 1-BP dissipates out
of the near-field. The ventilation rate for the surroundings, denoted by Qff, determines how quickly 1-
BP dissipates out of the surrounding space and into the outside air.
nf c
Non-
volatile Source
Figure Apx G-l. 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 G.2.5 and G.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
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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
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,n (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 brakejob (e.g., 9:05 am, 9:10 am,. ..9:55 am). In the first scenario, the brakejobs are performed
back-to-back, if performing more than one brakejob on the given day. Therefore, the second brakejob
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 brakejobs are performed every other hour, if performing more than one
brakejob on the given day. Therefore, the second brakejob 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 brakejob, 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 brakejob,
the workers and ONUs continue to be exposed as the airborne concentrations decay during the time in
which no brakejobs are occurring and then again when the next brakejob is initiated. In both scenarios,
the workers and ONUs are no longer exposed once they leave work.
Based on data from CARB (GARB. 2000). EPA assumes each brakejob requires one 14.4-oz can of
aerosol brake cleaner as described in further detail below. The model determines the application rate of
1-BP using the weight fraction of 1-BP in the aerosol product. EPA uses a discrete distribution of weight
fractions for 1-BP based on aerosol products identified in EPA's Use Dossier ( ).
The model design equations are presented below in EquationApx G-l through EquationApx G-21.
Near-Field Mass Balance
Equation Apx G-l
Far-Field Mass Balance
Equation Apx G-2
dCFF
Vff~= CnfQnf ~ CffQnf — CFFQFF
Where:
Vnf
Vff
near-field volume;
far-field volume;
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Qnf =
near-field ventilation rate;
Qff =
far-field ventilation rate;
Cnf =
average near-field concentration;
Cff =
average far-field concentration; and
t
elapsed time.
Solving EquationApx G-l and EquationApx G-2 in terms of the time-varying concentrations in the
near-field and far-field yields Equation Apx G-3 and Equation Apx G-4, 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 1-BP 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 1-BP 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 G-13 and Equation Apx G-14. The k coefficients
(Equation Apx G-5 through Equation Apx G-8) 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 G-3
Equation Apx G-4
Where:
Equation Apx G-5
Ki
CNFt = C^i t eXlt+ k2t eX2°
1 V -^£771,71 >
CpFt =(k3t eXlt — k4t eX2t)
V 3,Lm,n J
QnF (CFF,o(tm,n) CWF0(tmn)^ A2VNFCNF,o(tm,n)
m'n Vnf&i ~ ^2)
Equation Apx G-6
QnF ^NF,o(Sm,n) ~ ^FF,0 (*771,71)) + ^-l^VF^JVF.Oi^m.n)
2,tm'n Vnf(Ai-A2)
Equation Apx G-7
(.QnF + AjVnf)(,QnF (CFF,o(tm,n) ~ ^NF.oiSm.vS) ~ ^¦2^NF^NF,o(j;m,n)')
3,tm'n Qnf^nf(^i — ^2)
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EquationApx G-8
(.QnF + ^2^Nf)(.QnF (j-'NF.O (j'm.n) ~ ^FF.O^m.n)) + ^l^NF^NF.oiSm.n})
4,tm'n Qnf^nfC^i — ^2)
EquationA
Xx = 0.5
EquationA
X2 = 0.5
oxG-9
1 2
(Qnf^ff + Vnf(Qnf + Qff)\ \( Qnf^ff + Vnf(Qnf + Qff)\ „ /QnfQffn
V KvfKfF / J V KvF^FF
I _ 4 ZvwfvffX
/ \ ^/VF^FF '
ox G-10
f Qnf^ff + Vnf(Qnf + Qff)\ /QnfQff + Vnf(Qnf + Qff)\ _ . /Q/vfQff\
\ ^/VF^FF / J\ ^/VF^FF / V ^/VF^FF '
Equation Apx G-ll
0, m = 0
r (7 ^ = Mmt ( m9\ f \
nf,o\ m,nj ) 1 10OO J + CNF(tmn_1) , n > 0 for allmwhere brake job occurs
yVNF \ g / '
Equation Apx G-12
Equation Apx G-13
C,
r 0, m = 0
FF,o{tm,n) (.CFF(t7Tljn_1) , /or all n where m > 0
Xx X2 I \ Ai A2
NF, 5-min TWA, tmn y. +
l2 ll
Equation Apx G-14
I ^ C- " I ^ C- I I ^ C " " "I- -T"
V Ai A2 J \ A\ A2
C;
FF, 5-min TWA, t
m,n f- *¦
l2 ll
After calculating all near-field/far-field 5-minute TWA exposures (i.e., CWF 5-minTWA,tmn ar|d
Cpp 5-min twa, tmn) f°r 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:
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EquationApx G-15
_ 2m=0 2n=0 [^NF,5-min TWA,tm n X 0.0833 hr\
CNF, 8-hr TWA ~ g ^
Equation Apx G-16
n 2m=0 2n=0[^FF,5-minTWA,tm/n X 0.0833 hr\
CNF, 8-hr TWA = :
Equation Apx G-17
r _ Hri=o[C/VF,5-min TWA,tm,n X 0.0833 hr\
Cnf, 1-hr TWA - Thr^
Equation Apx G-18
r _ 1rn=o[^FF,5-mmTWA,tmin X 0.0833 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 G-l). 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 G-19, below:
Equation Apx G-19
FSA = x x TcR^p^j
Where: Rnf is the radius of the near-field
The near-field ventilation rate, Qnf, is calculated in Equation Apx G-20 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 G-20
1
Qnf ~ 2 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 G-21:
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EquationApx G-21
Qff = Vff^ER
Using the model inputs described in Appendix G.2, EPA estimated 1-BP 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.
G.2 Model Parameters
FigureApx G-l 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 G-l. 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.
2000).
Air exchange
rate
AER
hr1
—
—
1
20
3.5
Triangular
Demou et al. (2009) identifies
typical AERs of 1 hr1 and 3 to 20
hr1 for occupational settings with
and without mechanical
ventilation systems, respectively.
Hellwee et al. (2009) identifies
average AERs for occupational
settings utilizing mechanical
ventilation systems to be between
3 and 20 hr1. Golsteijn, et al.
(2014) indicates a characteristic
AER of 4 hr1. Peer reviewers of
EPA's 2013 TCE draft risk
assessment commented that
values around 2 to 5 hr1 may be
more likelv (SCG. 2013). in
agreement with Golsteijn et al.
(2014). A triansular 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 hr1).
Near-field indoor
wind speed
Vkf
Mir
—
—
0
23,882
—
Lognonnal
Lognonnal distribution fit to
commercial-type workplace data
from Baldwin and Maynard
(1998).
cin/s
—
—
0
202.2
—
Lognonnal
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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 radius
Rnp
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.
1-BP weight
fraction
wtfrac
wt frac
—
—
0.01
1
—
Discrete
Discrete distribution of 1-BP-
based aerosol product
formulations based on products
identified in EPA's Use Dossier
(2017b).
Degreaser Used
per Brake Job
wd
oz/job
14.4
—
—
—
—
Constant
Value
Based on data from 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 1-BP/
application
—
—
0.4
37.1
—
Calculated
Calculated from wtfrac, Wd, and
Na.
Operating hours
per week
OHpW
hr/week
—
—
40
122.5
—
Lognonnal
Lognonnal distribution fit to the
operating hours per week
observed in CARB (2000) site
visits.
Number of
Brake Jobs per
Work Shift
Nj
jobs/site-shift
—
—
1
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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G.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 ( )0). 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.
G.2.2 Air Exchange Rate
The air exchange rate (AER) is based on data from Demou et al. (2.009). Hellweg et al. (2009).
Golsteijn, et al. (2014). and information received from a peer reviewer during the development of the
2014 TSCA Work Plan Chemical Risk Assessment Trichloroethylene: Degreasing, Spot Cleaning and
Arts & Crafts Uses (SCG. 2013). Demou et al. (2009) identifies typical AERs of 1 hr"1 and 3 to 20 hr"1
for occupational settings with and without 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. Golsteijn, 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 (SCG. 2013).
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. (2.009) and a maximum of 20 hr"1 per Demou et al. (2.009)
and Hellweg et al. (2009).
G.2.3 Near-Field Indoor Air Speed
Baldwin and Mavnaal i 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 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
mean air speed observed in Baldwin and Maynard (1998) to prevent the model from sampling values
that approach infinity or are otherwise unrealistically large.
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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.
G.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 G-l). The near-field volume is
calculated per EquationApx G-22. 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 G-22
1 4
VNF = 2 X g
G.2.5 Application Time
EPA assumed an average of 11 brake cleaner applications per brake job (see Section G.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.
G.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.
G.2.7 1-BP Weight Fraction
EPA reviewed the Preliminary Information on Manufacturing, Processing, Distribution, Use, and
Disposal: 1-Bromopropane report ( 017b) for aerosol degreasers and cleaners that contain 1-
BP. EPA (2017b) identifies 25 aerosol degreasers and cleaners that overall range in 1-BP content from
one to 100 weight percent. The identified aerosol degreasers and cleaners include a brake and engine
cleaner and also electronic/electrical parts cleaners, a resin remover, machine cleaners, and general
purpose degreasers. EPA includes all of these aerosol cleaners in the estimation of 1-BP content as: 1)
automotive maintenance and repair facilities may use different degreaser products interchangeably as
observed by CARB (2000); and 2) 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 1-BP weight fraction based on the number of occurrences
of each product type. For all but two products, the concentration of 1-BP was reported as a range. EPA
used a uniform distribution to model the 1-BP weight fraction within the product type. Table_Apx G-2
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provides a summary of the reported 1-BP content reported in the safety data sheets identified in EPA
(2017b). the number of occurrences of each product type, and the fractional probability of each product
type.
Table Apx G-2. Summary of 1-Bromopropane-Based Aerosol Degreaser Formulations
Name of Aerosol Degreaser Product
Identified in EPA (2017b)
1-Bromopropane
Weight Percent
Number of
Occurrences
Fractional Probability
Aerosol buffing solution (PERC-
based)
1-3%
1
0.040
Aerosol cleaner (NMP-based)
25-30%
1
0.040
Super degreaser
40-50%
1
0.040
LPS Instant Super Degreaser (SDS
indicates aerosol form)
90-100%
1
0.040
5020 Quick Solv Solvent Degreaser
(SDS indicates aerosol form)
60-100%
1
0.040
United C174 Contact Cleaner - aerosol
contact cleaner
10-30%
1
0.040
PENSOLVPB 2000 - aerosol solvent
degreaser (>95% 1-BP)
95-100%
1
0.040
NU TRI CLEAN Aerosol (>90% 1-
BP)
90-100%
1
0.040
POWER SOLV 5000
90-100%
1
0.040
Solv 2427
60-100%
1
0.040
Type TRTM Cleaner/ Degreaser -
Aerosol
95-100%
1
0.040
CRC Cable Clean Degreaser 02064
90-100%
1
0.040
CRC Cable Clean RD
1-3%
1
0.040
CBC II contact Cleaner
44%
1
0.040
Electro-Wash NR
65-75%
1
0.040
Kontact Restorer
65-75%
1
0.040
Pow-R-WashNR Contact Cleaner
65-75%
1
0.040
LPS NoFlash Nu
60-70%
1
0.040
525 Contact Cleaner
47-84%
1
0.040
Enviro Tac
60-100%
1
0.040
Mega Safe
60-100%
1
0.040
76334 High Tech Electronic Cleaner
40-50%
1
0.040
PC AII
60-100%
1
0.040
Sprayon® ELTM 2846 Non-
chlorinated Flash Free Electronic
Solvent Aerosol
or
EL2846 Non-chlorinated Electrical
Degreaser - Aerosol
92.64%
1
0.040
N-Propyl Bromide Safety Solvent
90-100%
1
0.040
Total
25
1.000
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G.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).
G.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 ( 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.
G.2.10 Amount of 1-BP Used per Application
EPA calculated the amount of 1-BP used per application using EquationApx G-23. The calculated
mass of 1-BP used per application ranges from 0.4 to 37.1 grams.
Equation Apx G-23
Where:
Amt
Wd
Wtfrac
Na
Amt =
Wd x wtfrac x 28.3495^-
oz
Na
Amount of 1-BP used per application (g/application);
Weight of degreaser used per brake job (oz/job);
Weight fraction of 1-BP in aerosol degreaser (unitless); and
Number of degreaser applications per brake job (applications/job).
G.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).
G.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
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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 EquationApx G-24 and rounding to the nearest
integer. The calculated number of brake jobs per work shift ranges from one to four.
Equation Apx G-24
Where:
Nj
OHpW
936
jobs
x 8
hours
Nj =
site-year shift
r„wee/cs „.. ...
52 x OHpW
yr r
Number of brake jobs per work shift (j ob s/ site-shift); and
Operating hours per week (hr/week).
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Appendix H Dry Cleaning Multi-Zone Inhalation Exposure Model
Approach and Parameter
This appendix presents the modeling approach and model equations used in the Dry Cleaning Multi-
Zone Inhalation Exposure Model. The model was developed through review of relevant literature and
consideration of existing EPA exposure models. This model uses a near-field/far-field approach (Keil.
2009). where a vapor generation source located inside the near-field diffuses into the surrounding
environment. Workers are assumed to be exposed to 1-BP vapor concentrations in the near-field, while
occupational non-users are exposed at concentrations in the far-field. Because there are multiple
activities with potential 1-BP exposure at a dry cleaner, a multi-zone modeling approach is used to
account for 1-BP vapor generation from multiple sources.
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;
• Exposure duration;
• Concentration of solvent in the drum after the dry cleaning cycle;
• Residual solvent adhered to garments after dry cleaning;
• Spot cleaning use rate; and
• Operating hours per day.
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 Professional 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 10,000 iterations to capture the range of
possible input values (i.e., including values with low probability of occurrence). Note: this is fewer
iterations than used for the near-field/far-field models described in other appendices as the multi-zone
model takes significantly longer to run and 10,000 iterations allowed the simulation to be complete in a
reasonable amount of time while still capturing the variability of each parameter.
Model results from the Monte Carlo simulation are presented as 95th and 50th percentile values. The
statistics were calculated directly in @Risk13. 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 dry
cleaning model.
13 @Risk\ Palisade; https://www.palisade.com/risk/
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H.l Model Design Equations
FigureApx H-l illustrates the near-field/far-field modeling approach as it was applied by EPA to the
Dry Cleaning Multi-Zone Inhalation Exposure Model. As the figure shows, 1-BP vapor is generated in
each of the three near-fields, resulting in worker exposures at concentrations Cs, Cd, and Cf. The
volume of each zone is denoted by Vs, Vd, and Vf. The ventilation rate for the near-field zone (Qs, Qd,
Qf) determines how quickly 1-BP dissipates into the far-field (i.e., the facility space surrounding the
near-fields), resulting in occupational non-user exposures to 1-BP at a concentration Cff. Vff denotes
the volume of the far-field space into which the 1-BP dissipates out of the near-field. The ventilation rate
for the surroundings, denoted by Qff, determines how quickly 1-BP dissipates out of the surrounding
space and into the outside air.
Dry Cleaning
Machine
x VD /
S /
Cn
Far-field (background)
Cc
-FF
Q,
FF
Figure Apx H-l. Illustration of the Dry Cleaning Multi-Zone Inhalation Exposure Model
The model design equations are presented below in EquationApx H-l through EquationApx H-l5.
Near-Field Mass Balance for Spot Cleaning (Multi-Zone)
Equation Apx H-l
dCs
^s~dt = ^FF®S ~ ^sQs + Gs
Near-Field Mass Balance for Finishing (Multi-Zone)
Equation Apx H-2
dCF
Vf = CppQp — CpQp + Gf
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Near-Field Mass Balance for Dry Cleaning Machine (Multi-Zone)
EquationApx H-3
dCD
Vd = cffQd — cdQd
Far-Field Mass Balance
Equation Apx H-4
d C
Vff ^ = CsQs + CfQf + CdQd — CFFQS — CFFQF — CFFQD — CFFQFF
Where:
Vs
= near-field volume for spot cleaning;
Vf
= near-field volume for finishing;
Vd
= near-field volume for unloading dry cleaning machine;
Vff
= far-field volume;
Qs
= near-field ventilation rate for spot cleaning;
Qf
= near-field ventilation rate for finishing;
Qd
= near-field ventilation rate for dry cleaning machine;
Qff
= far-field ventilation rate;
Cs
= average near-field concentration for spot cleaning;
Cf
= average near-field concentration for finishing;
Cd
= average near-field concentration for dry cleaning machine;
Cff
= average far-field concentration;
Gs
= average vapor generation rate for spot cleaning;
Gf
= average vapor generation rate for finishing; and
t
= elapsed time.
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. Note that the FSA may not be equal to the surface
area of the entire near-field.
For spot-cleaning, EPA defined the near-field zone to be a rectangular box resting on the floor;
therefore, no mass transfer can occur through the near-field box's floor. FSA is calculated using
EquationApx H-5:
Equation Apx H-5
FSAs = 2 (LSHS) + 2{WSHS) + (LSWS)
For finishing, EPA defined the near-field zone to be a rectangular box resting on the floor; therefore, no
mass transfer can occur through the near-field box's floor. FSA is calculated using Equation Apx H-6:
Equation Apx H-6
FSAf = 2 (LnfHnf) + 2 (WnfHnf) + (LnfWnf)
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For dry cleaning, EPA defined the near-field zone to be a hemispheric area projecting from the door of
the dry cleaning machine, calculated as EquationApx H-7:
EquationApx H-7
FSAd = 2nr^
Where:
FSAs = free surface area for spot cleaning;
FSAf = free surface area for finishing;
FSAd = free surface area for dry cleaning machine;
Ls = near-field length for spot cleaning;
Hs = near-field height for spot cleaning;
Ws = near-field width for spot cleaning;
Lf = near-field length for finishing;
Hf = near-field height for finishing;
Wf = near-field width for finishing; and
td = radius of the dry cleaning machine door opening.
The near-field ventilation rates, Qs, Qd, and Qf are calculated from the near-field indoor wind speed,
vnf, and FSA, using Equation Apx H-8 through Equation Apx H-10, assuming half of FSA is available
for mass transfer into the near-field and half of FSA is available for mass transfer out of the near-field.
The near-field indoor wind speed is assumed to be the same across all three near fields:
Equation Apx H-8
Qs = 2 vnfFSAs
Equation Apx H-9
1
Qf — 2 vnfF$Af
Equation Apx H-10
Qd = 2 VnfFSAd
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 H-l 1:
Equation Apx H-ll
Qff = Vff^ER
The model results in the following four, coupled ordinary differential equations (ODEs) given in
Equation Apx H-l2 through Equation Apx H-l5:
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EquationApx H-12
EquationApx H-13
Equation Apx H-14
dCs _ Qs Qs r Gs
~7T — TT Ls + TT + TT
dt Vs Vs Vs
dCF Qp Qp Gp
—- = - — CF + — CFF + —
dt Vp F Vp FF Vp
dCD _ Qd Qd
~7T ~ ~ ~w~ + 77" lff
dt VD VD
Equation Apx H-15
dCpp _ Qs n , Qf n , Qd n Qs + Qf + Qd + Qff n
~ T/ s + T/ lf + T/ ld t/ lff
Clt V FF VpF VpF VpF
When solving coupled ODEs, it is common to transform the equations into a standard mathematical
format. This standard mathematical format allows one to more easily identify appropriate solution
methodologies from standard mathematical references. EPA transformed these four ODEs into the
following format in Equation Apx H-16 through Equation Apx H-19:
Equation Apx H-16
Equation Apx H-17
Equation Apx H-18
Equation Apx H-19
Where:
y'i = «iiyi + a14y4 + #1
y'2 = a22j2 + a24y4 + 92
y'i = a33y3 + a34y4
3/4 = a41y1 + a42y2 + a43y3 + a44y4
dCs
dt
dCF
dt
dCr
Yi
= y2
= ys
dt
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And:
dCFF
~dT = y*
Cs = Vi CF = y2 CD = y3 CFF = y4
Qs Qf Qd
— ^11 — ^22 — ^"3 "3
Vs Vf Vd
Qs Qf Qd
— = a14 — = a24 a34
vs 14 Vf Z4 Vd 34
Qs _ „ Qf _ „ Qd _ „ Qs+Qf+Qd+Qff _ „
T7 — a41 T7 — a42 T7 — a43 ^ — a44
K pp V pp V pp V pp
Gs Gp
7S ~ &1 VF~
These ordinary differential equations can be solved using a numerical integration method. EPA used the
fourth-order Runge-Kutta method (RK4). RK4 numerically integrates a system of coupled ordinary
differential equations from time step n to n+1 with a constant time step size of h using the following
equations (shown for generic variables yi, y2, y3, and y4 as a function of t).
EquationApx H-20
EquationApx H-21
Equation Apx H-22
Equation Apx H-23
dyx
-fa=f&.y\.y2.yz.y*)
dy2
-££¦ = f2(t,y\,y2,y*,y4)
dy3
-fa = h(t,y\,y2,y-z,y±)
dy4
~^~ = f4(t,yvy2, y 3, y4)
Where, for each ODE j = 1, 2, 3, 4 (where 1 = spot cleaning, 2 = finishing, 3 = dry cleaning machine,
and 4 = far field):
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EquationApx H-24
k{ = fj(t,yvy2,yz,yA)
Equation Apx H-25
111 11
kl2 = fj(.t + 2h'yi + 2kih'y2 + 2kih'y3 + 2k*h,y4 + 2k*h^
Equation Apx H-26
111 11
ki = f}(t + 2h,yi + 2kzh,y2 + 2kzh,y3 + 2k*k'y4 + 2k^
Equation Apx H-27
k{ = fj(t + h,y1+ k\h,y2 + k\h,yz + k\h,yA + /cf/i)
Equation Apx H-28
yji+i _ y-n + ^h(k[ + 2kJ2 + 2kJ3 + k{)
RK4 is an explicit integration method, meaning it solves for the dependent variables at step n I
explicitly using the dependent variables at step n. RK4 is a fourth-order method, which means the local
truncation error at a single integration step is on the order of h5, while the total global error is on the
order of h4.
The choice of step size h is such to allow a successful integration of the system of differential equations.
If parameter values are chosen such that the differential equation coefficients (the a terms in
Equation Apx H-16 through Equation Apx H-19) are sufficiently large, the differential equations may
become stiff. Stiff differential equations would require sufficiently small time step sizes to allow their
integration. Stiffness can be difficult to predict. If stiffness is encountered, meaning if the solution
diverges to unrealistic values, such as infinity, the step size should be reduced to see if that allows for
successful integration.
Exposure Estimate Equations
The dry cleaning industry is characterized by a large number of small businesses, many are family-
owned and operated. EPA assumed small dry cleaners operate up to 12 hours a day and up to six days a
week. In addition, EPA assumed each facility has a single machine. The assumption of a single machine
per facility is supported by a recent dry cleaning industry study conducted in King County, Washington,
where 96 percent of 151 respondents reported having only one machine at their facility. Four reported
having two machines, and two reported having three machines (Whittaker and Joh an son. 2011). Based
on the survey results, this assumption is presumably representative of the majority of small dry cleaning
shops.
EPA modeled the baseline scenario assuming the facility operates a converted third generation machine,
the machine type observed at all three New Jersey dry cleaners evaluated in the Blando et al. (2010)
study. For the engineering control scenario, EPA modeled a facility with a fourth-generation machine.
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EPA believes facilities using 1-BP are unlikely to own fifth generation machines (ERG. 2005).
EPA assessed three types of workers within the modeled dry cleaning facility: 1) a worker who performs
spot cleaning; 2) a worker who unloads the dry cleaning machine and finishes and presses the garments;
and 3) an occupational non-user. Each worker type is described in further detail below. EPA assumed
each worker activity is performed over the full 12-hour operating day.
• EPA assumed spot cleaning occurs for a duration varying from two to five hours in the middle of
the 12-hour day. The worker is exposed at the spot cleaning near-field concentration during this
time, and at the far-field concentration for the remainder of the day. Spot cleaning can be
performed for both dry cleaned loads and for laundered loads.
• EPA assumed a separate worker unloads the dry cleaning machine and finishes and presses the
garments. After each load, EPA assumed this worker spends five minutes unloading the machine,
during which he or she is exposed at the machine near-field concentration. After unloading, the
worker spends five minutes in the finishing near-field to prepare the garments. Then, the worker
spends another 20 minutes finishing and pressing the cleaned garments. During this 20-minute
period of finishing and pressing, the residual 1-BP solvent is off-gassed into the finishing near-
field. The amount of residual 1-BP solvent is estimated using measured data presented in von
Grote et al. (2003). These unloading and finishing activities are assumed to occur at regular
intervals throughout the twelve-hour day. The frequency of unloading and finishing depends on
the number of loads dry cleaned each day, which varies from 1 to 14, where 14 was the
maximum number of loads observed in the NIOSH (2010) and Blando et al. (2010) studies.
When this worker is not unloading the dry cleaning machine or finishing and pressing garments,
the worker is exposed at the far-field concentration.
• EPA assumed one occupational non-user is exposed at the far-field concentration for 12 hours a
day. The occupational non-user could be the cashier, tailor, or launderer, who works at the
facility but does not perform dry cleaning activities.
Using the model inputs described in Appendix H.2, EPA estimated 1-BP inhalation exposures for
workers performing spot cleaning, workers unloading the dry cleaning machine and performing
finishing and pressing activities, 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 10,000 iterations and the
Latin Hypercube sampling method for each model.
H.2 Model Parameters
Table Apx H-l summarizes the model parameters and their values for the Dry Cleaning Multi-Zone
Inhalation Exposure Model. Each parameter is discussed in detail in the following subsections.
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TableApx H-l. Summary of Parameter Values and Distributions Used in the Open-Top Vapor Degreasing Near-Field/Far-Field
Inhalation Exposure Model
Input Parameter
Symbol
Unit
Constant Model
Parameter Values
Variable Model Parameter Values
N otes/Comments
Value
Basis
Lower
Bound
Upper
Bound
Mode
Distribution
Type
Facility Parameters
Facility Height
Fh
ft
12
Median
—
—
—
—
See Section H.2.1.1
Facility Floor Area
F area
ft2
—
—
500
20,000
—
Beta
See Section H.2.1.1
Far-field volume
Vff
ft3
—
—
6,000
240,000
—
—
See Section H.2.1.1
Air exchange rate
AER
lir1
—
—
1
19
3.5
Triangular
See Section H.2.1.2
Near-field indoor wind
speed
Vnf
ft/to
—
—
—
202.2
—
Lognonnal
See Section H.2.1.3
cm/s
—
—
—
23,882
—
Lognonnal
Dry Cleaning Machine Parameters
Machine Door Diameter
D
ft
2.083
—
—
—
—
—
See Section H.2.2.1
Number of Loads per Day
LD
loads/day
—
—
1
14
—
Uniform
See Section H.2.2.2
Load Time
LT
hr/load
0.5
—
—
—
—
—
See Section H.2.2.3
3rd Generation Machine
Cylinder 1-BP
Concentration
Cc_3RD
ppm
—
—
2,000
8,600
—
Uniform
See Section H.2.2.4
4th Generation Machine
Cylinder 1-BP
Concentration
Cc_4TH
ppm
—
—
240
360
—
Uniform
See Section H.2.2.4
Cylinder Volume
VC
m3
—
—
0.24
0.64
—
Uniform
See Section H.2.2.5
Starting time
tl
to
0
—
—
—
—
—
Constant value.
Exposure Duration
t2
to-
0.083
—
—
—
—
—
See Section H.2.2.6
Finishing and Pressing Parameters
Near-field length
Lnf
ft
10
—
—
—
—
—
See SectionH.2.3.1
Near-field width
Wnf
ft
10
—
—
—
—
—
Near-field height
Hnp
ft
6
—
—
—
—
—
3rd Generation Machine
Residual Solvent
Rsolvent 3RD
g/kg
—
—
0.26
3.75
—
Discrete
See SectionH.2.3.2
4th Generation Machine
Residual Solvent
Rsolvent 4TH
g/kg
—
—
0.12
1.26
—
Discrete
See SectionH.2.3.2
Load Size
LS
lb/load
30
—
—
—
—
—
See SectionH.2.3.3
Exposure Duration
t3
hr
0.33
—
—
—
—
—
See SectionH.2.3.4
Spot Cleaning Parameters
Near-field length
Lnf
ft
10
—
—
—
—
—
See Section H.2.4.1
Near-field width
Wnf
ft
10
—
—
—
—
—
Near-field height
Hnf
ft
6
—
—
—
—
—
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Input Parameter
Symbol
Unit
Constant Model
Parameter Values
Variable Model Parameter Values
N otes/Comments
Value
Basis
Lower
Bound
Upper
Bound
Mode
Distribution
Type
Use Rate
UR
gal/yr
—
—
13.92
16
—
Uniform
See Section H.2.4.2
Exposure Duration
U
to
—
—
2
5
—
Uniform
See Section H.2.4.3
Other Parameters
Operating hours per day
OH
to-
12
—
—
—
—
—
See Section H.2.5.1
Operating days
OD
day s/yr
—
—
249
313
300
Triangular
See Section H.2.5.2
Fractional days of exposure
f
unitless
—
—
0.8
1.0
—
Uniform
See SectionH.2.5.3
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H.2.1 Facility Parameters
H.2.1.1 Far-Field Volume
EPA calculated the far-field volume by setting a distribution for the facility floor area and multiplying
the floor area by a facility height of 12 ft (median value per CARB study) as discussed in more detail
below.
The 2006 CARB California Dry Cleaning Industry Technical Assessment Report (CARB. 2006) and the
Local Hazardous Waste Management Program in King County A Profile of the Dry Cleaning Industry in
King County, Washington (Whittaker and Johanson. 2011) provide survey data on dry cleaning facility
floor area. The CARB (2006) study also provides survey data on facility height. Using survey results
from both studies, EPA composed the following distribution of floor area. To calculate facility volume,
EPA used the median facility height from the CARB (2006) study. The facility height distribution in the
CARB (2006) study has a low level of variability, so the median height value of 12 ft presents a simple
but reasonable approach to calculate facility volume combined with the floor area distribution.
Table Apx H-2. Com
posite Distribu
ion of Dry Cleaning Facility Floor Areas
Floor Area
Value (ft2)
Percentile (as
fraction)
Source
20,000
1
(Whittaker and Johanson. 2011)
3,000
0.96
(Whittaker and Johanson. 2011)
2,000
0.84
(Whittaker and Johanson. 2011)
1,600
0.5
(CARB. 2006)
1,100
0.1
(CARB. 2006)
500
0
(CARB. 2006)
EPA fit a beta function to this distribution with parameters: ai = 6.655, <12 = 108.22, min = 500 ft2, max
= 20,000 ft2.
H.2.1.2 Air Exchange Rate
von Grote et al. (2006) indicated typical air exchange rates (AERs) of 5 to 19 hr"1 for dry cleaning
facilities in Germany. Klein and Kurz (1994) indicated AERs of 1 to 19 hr"1, with a mean of 8 hr"1 for
dry cleaning facilities in Germany. During the 2013 peer review of EPA's 2013 draft risk assessment of
TCE, a peer reviewer indicated that air exchange rate values around 2 to 5 hr"1 are likely (SCG. 2013). in
agreement with the low end of the ranges reported by von Grote et al. and Klein and Kurz. 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"1). The minimum and maximum of the distribution are 1 and 19 hr"
1, respectively.
H.2.1.3 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 categorizing the air speed
surveys into settings representative of industrial facilities and representative of commercial facilities.
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EPA fit separate distributions for these industrial and commercial settings and used the commercial
distribution for dry cleaners.
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).
The air speed surveys representative of commercial facilities were fit 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 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.
H.2.2 Dry Cleaning Machine Parameters
H.2.2.1 Machine Door Diameter
EPA determined an approximate door diameter of 25 inches by reviewing images of several 4th
generation PCE machine models manufactured by Bowe and Firbimatic.
H.2.2.2 Number of Loads per Day
EPA used a uniform distribution for the number of loads per day ranging from 1 to 14 based on
observations from NIOSH (2010) and Blando et al. (2010).
H.2.2.3 Load Time
EPA estimates that dry cleaning loads using PERC have an average cycle duration of 30 minutes (0.5
hours). This estimate is consistent with von Grote (2003). which estimated total cleaning and finishing
batch times of between 45 to 65 minutes for machines equivalent to U.S. 3rd generation machines and
between 50 to 70 minutes for machines equivalent to U.S. 4th generation machines, von Grote (2003)
further estimated that between one-fourth and one-third of the total cleaning and finishing batch time is
spent finishing/pressing (see Section H.2.3.4). EPA assumed a total cleaning and finishing batch time of
60 minutes with the following breakdown:
• The finish/pressing duration is 20 minutes (see Section H.2.3.4);
• The time to unload the garments from the machine is 5 minutes based on engineering judgment;
• The time to prepare the garments for finishing/pressing is 5 minutes based on engineering
judgment; and
The machine cycle duration is 30 minutes based on the total cleaning and finishing batch time of 60
minutes minus the above task durations.
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H.2.2.4 Machine Cylinder Concentration
EPA used two different distributions for machine cylinder concentration depending on the machine type
being modeled (third or fourth generation). For third generation machines, EPA used a uniform
distribution from 2,000 to 8,600 ppm to estimate the machine cylinder concentration after a dry cleaning
cycle. ERG (2005) indicated that the use of refrigerated condensers (the vapor control system used in
third generation machines) can reduce PCE concentrations in the drum to between 2,000 and 8,600 ppm.
EPA assumed the concentration in the drum after a cycle is not affected by the type of dry cleaning
solvent used, and that these values are representative of residual concentrations of 1-BP.
For fourth generation machines, EPA used a uniform distribution from 240 to 360 ppm to estimate the
machine cylinder concentration after a dry cleaning cycle. CDC (1997b) indicated that the use of
refrigerated condensers and carbon adsorbers in fourth generation machines can reduce the PCE
concentration in the drum below 300 ppm after the cycle is complete. EPA used a uniform distribution
of 300 ppm +/- 20% to account for variability and uncertainty in the residual concentration. EPA
assumed the concentration in the drum after a cycle is not affected by the type of dry cleaning solvent
used.
H.2.2.5 Cylinder Volume
EPA assessed the cylinder volume using a uniform distribution of 0.24 to 0.64 m3 based on data from
von Grote (2003). von Grote (2003) presented the five most common machine sizes used in Germany
based on a 2002 survey with sizes ranging from 0.24 to 0.64 m3. EPA did not have data on the machine
sizes or distributions used in the U.S. Therefore, EPA modeled the cylinder volume using the range
provided by von Grote (2003) and assuming a uniform distribution of machine sizes.
H.2.2.6 Exposure Duration
EPA assumes it takes the worker five minutes to unload the dry cleaning machine.
H.2.3 Finishing and Pressing Parameters
H.2.3.1 Near-Field Volume
EPA assumed a near-field of constant dimensions of 10 ft x 10 ft x 6 ft resulting in a total volume of 600
ft3.
H.2.3.2 Residual Solvent
EPA used two different distributions for the amount of residual solvent that adheres to garments after the
dry cleaning cycle depending on the machine type being modeled (third or fourth generation). The
distributions for both machine types are based on data from von Grote (2003) who estimated residual
solvent for both normal loads and "off-the-peg" loads, von Grote (2003) defines "off-the-peg" loads as
loads with suits and jackets with shoulder pads and estimates that approximately 20% of all loads
cleaned are off-the-peg with the remaining 80% being normal loads. For third generation machines, von
Grote (2003) presents data estimating 0.26 g residual solvent/kg clothes for normal loads and 3.75 g
residual solvent/kg clothes for off-the peg loads. It should be noted that von Grote (2003) uses different
definitions of machines generations than used in the U.S. The fourth-generation machines in von Grote
(2003) are defined as non-vented dry-to-dry machines with refrigerated condensers which corresponds
to third-generation machines in the U.S. Therefore, EPA used data for fourth-generation machines in
von Grote (2003) to model U.S. third-generation machines.
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von Grote (2003) does not have a machine generation corresponding to fourth-generation machines in
the U.S. von Grote (2003) fourth-generation machines correspond to U.S. third-generation machines and
von Grote (2003) fifth-generation machines correspond to U.S. fifth-generation machines (machines
with refrigerated condensers, carbon adsorbers, and interlocks on the door). However, the only
difference between U.S. fourth- and fifth-generation machines is the presences of interlocks on the door
to prevent workers from opening prior to the solvent concentration dropping below 300 ppm. As
discussed in Appendix H.2.2.4, fourth-generation machines are also expected to reduce cylinder
concentrations after a cycle to 300 ppm. Therefore, EPA expects residual solvent for fourth-generation
machines to be similar to fifth-generation machines and uses residual solvent data from von Grote
(2003) for fifth-generation machines in the estimates for fourth-generation machines, von Grote (2003)
presents data estimating 0.12 g residual solvent/kg clothes for normal loads and 1.26 g residual
solvent/kg clothes for off-the peg loads for fifth-generation machines. EPA assumes a discrete
distribution for both third- and fourth-generation estimates assuming 80% of loads are normal loads and
20% are off-the-peg (Von Grote. 2003).
H.2.3.3 Load Size
The CARB (2006) and King County (Whittaker and Johanson. 2011) studies provide machine
capacities, and the King County study also provides data on actual size of loads used by dry cleaners.
EPA used the King County study data on actual load sizes to build a distribution.
TableApx H-3 summarizes the survey results for respondents' primary (if facility has more than one
machine) or only machine. The study reports a maximum reported load of 150 lb, a minimum reported
load of 7 lb, and a median reported load of 30 lb for the primary machine (Whittaker and Johanson.
2011).
Table Apx H-3. Survey Responses of Actual Pounds Washed per Load for Primary Machine (if
Actual Pounds of
Clothes Washed
Results for Primary Machine
Number of
Percent of
Respondents
Respondents
1-10
4
3
11-20
36
25
21-30
76
53
31-40
16
11
41-50
6
4
51+
6
4
Total
144
100
Source: (Whittaker and Johanson. 2011)
EPA used these survey results to build a distribution to describe the actual wash loads per machine, as
summarized in Table Apx H-4. To build this distribution, EPA set the following:
• The maximum, median, and minimum were set as 150 lb, 30 lb, and 7 lb, respectively, as stated
in the King County survey report (Whittaker and Johanson. 2011).
• The 96th percentile was set at 50 lb as the high-end of the bin "41 to 50 lb". Per Table Apx H-3,
4% of respondents reported greater than 50 lb; therefore, 96% of facilities reported 50 lb or less.
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• The 28th percentile was set at 20 lb as the high-end of the bin "11 to 20 lb". Per TableApx H-3,
28% of respondents reported 20 lb or less.
EPA then determined the best-fit distribution using the software @Risk.
Table Apx H-4. Distribution of Actual Load Sizes from 201
Actual Load Washed (lb)
Percentile
(as fraction)
150
1
50
0.96
30
0.5
20
0.28
7
0
) King County Survey
Source: (Whittaker and Johanson. 2011)
EPA fit a beta distribution to this distribution with parameters: ai = 2.3927, <12 = 12.201, min = 7 lb, max
= 150 lb. The root-mean squared (RMS) error is 0.0365, Figure Apx H-2 illustrates this fit.
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0.8
0.6
0.4
FigureApx H-2. Fit Comparison of Beta Cumulative Distribution Function to Load Size Survey
Results
H.2.3.4 Exposure Duration
Fit Comparison for Load Size
RiskBetaGeneral(2.3927,12.201,7,150)
.6
@RISK for Excel
Palisade Corporation
| Statistics^
¦
Input 1
BetaGeneral
Minimum
7.00
7.00
Maximum
150.00
150.00
Mean
31.68
30.45
Mode
N/A
22.81
Median
30.00
28.23
Std Dev
19.37
13.41
Skewness
2.5076
0.8640
Kurtosis
13.5139
3.7151
LeftX
9.3
9.3
LeftP
5.0%
0.7%
Right X
49.6
49.6
Right P
95.0%
90.6%
Dif. X
40.24
40.24
Dif. P
90.0%
89.9%
1%
7.46
9.71
5%
9.32
12.70
10%
11.64
15.03
15%
13.96
16.94
20%
16.29
18.66
25%
18.61
20.28
30%
20.91
21.86
35%
23.18
23.42
40%
25.45
24.98
45%
27.73
26.58
50%
30.00
28.23
55%
32.17
29.96
60%
34.35
31.78
65%
36.52
33.75
70%
38.70
35.90
75%
40.87
38.32
30%
43.04
41.11
85%
45.22
44.50
90%
47.39
48.94
95%
49.57
55.81
99%
125.00
69.31
EPA assumed workers take 20 minutes to press and finish each load. This estimate is consistent with
von Grote (2003), which estimated that residual solvent will evaporate continuously over a period of
approximately between one-fourth and one-third of the total time to clean and finish a single load of
garments, von Grote (2003) estimated total cleaning and finishing batch times of between 45 to 65
minutes for machines equivalent to U.S. 3rd generation machines and between 50 to 70 minutes for
machines equivalent to U.S. 4th generation machines. This yields an overall range of finishing/pressing
times of approximately 11 to 23 minutes.
H.2.4 Spot Cleaning Parameters
H.2.4.1 Near-Field Volume
EPA assumed a near-field of constant dimensions of 10 ft x 10 ft x 6 ft resulting in a total volume of 600
ft3.
H.2.4.2 Spot Cleaning Use Rate
A MassDEP comparative analysis worksheet provides an example case study for a facility, which
spends $60 per month on spot cleaner (MassDEP. 2013). The cost of 1-BP-based spot cleaner is
estimated at $45 per gallon (Blando et al.. 2009). These estimates result in a 1-BP-based spot cleaner use
rate of 16 gallons per year. EPA assumes the 1-BP concentration could vary uniformly from 87 to 100
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percent (Enviro Tech International. 2013). Applying this concentration to the 16 gallon per year use rate
results in a range of 13.92 to 16 gal/yr of 1-BP. EPA modeled this range using a uniform distribution.
H.2.4.3 Exposure Duration
Morris and Wolf (2005) used data collected from dry cleaners to develop two model PERC-based dry
cleaners: a small and large dry cleaner. The authors estimated the small dry cleaner spends 2.46 hr/day
spotting and the large dry cleaner spends 5 hr/day spotting. EPA models the spot cleaning duration as a
uniform distribution varying from 2 to 5 hr/day.
H.2.5 Other Parameters
H.2.5.1 Operating Hours
EPA assumed a typical dry cleaner operates 12 hours per day based on engineering judgment.
II.2.5.2 Operating Days per Year
EPA modeled the operating days per year using a triangular distribution from 250 to 312 days per year
with a mode of 300 days per year14. The low-end operating days per year is based on the assumption that
at a minimum the dry cleaner operates five days per week and 50 weeks per year. The mode of 300 days
per year is based on an assumption that most dry cleaners will operate six days per week and 50 weeks
per year. The high-end value is based on the assumption that the dry cleaner would operate at most six
days per week and 52 weeks per year, assuming the dry cleaner is open year-round.
H.2.5.3 Fractional Number of Operating Days that a Worker Works
To account for lower exposure frequencies and part-time workers, EPA defines a fractional days of
exposure as a uniform distribution ranging from 0.8 to 1.0. EPA expects a worker's annual working days
may be less than the operating days based on BLS/Census data that showed the weighted average
worked hours per year and per worker in the dry cleaning sector is approximately 1,600 (i.e., 200 day/yr
at 8 hr/day) which falls outside the range of operating days per year used in the model (250 to 312
day/yr with mode of 300 day/yr).
The low end of the range, 0.8, was derived from the observation that the weighted average of 200 day/yr
worked (from BLS/Census) is 80% of the standard assumption that a full-time worker works 250 day/yr.
The maximum of 1.0 is appropriate as dry cleaners may be family owned and operated and some
workers may work as much as every operating day. EPA defines the exposure frequency as the number
of operating days (250 to 312 day/yr) multiplied by the fractional days of exposure (0.8 to 1.0).
14 For modeling purposes, the minimum value was set to 249 days per year and the maximum to 313 days per year; however,
these values have a probability of zero; therefore, the true range is from 250 to 312 days per year.
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Appendix I Spot Cleaning Near-Field/Far-Field Inhalation Exposure
Model Approach and Parameter
This appendix presents the modeling approach and model equations used in the Spot Cleaning Near-
Field/Far-Field Inhalation Exposure Model. The model was developed through review of relevant
literature and consideration of existing EPA/OPPT exposure models. The model uses a near-field/far-
field approach (Keil. 2.009). where a vapor generation source located inside the near-field leads to the
evaporation of vapors into the near-field, and indoor air movements lead to the convection of vapors
between the near-field and far-field. Workers are assumed to be exposed to 1-BP vapor 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;
• Spot cleaner use rate;
• Vapor generation rate; and
• Operating hours per day.
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 a high-
end exposure, whereas the 50th percentile value was selected to represent a central tendency exposure
level. The following subsections detail the model design equations and parameters for the spot cleaning
model.
1.1 Model Design Equations
Figure Apx 1-1 illustrates the near-field/far-field modeling approach as it was applied by EPA to spot
cleaning facilities. As the figure shows, 1-BP vapors evaporate into the near-field (at evaporation rate
G), resulting in near-field exposures to workers at a concentration Cnf. The concentration is directly
proportional to the amount of spot cleaner 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-
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field zone (Qnf) determines how quickly 1-BP dissipates into the far-field (i.e., the facility space
surrounding the near-field), resulting in occupational non-user exposures to 1-BP at a concentration Cff.
Vff denotes the volume of the far-field space into which the 1-BP dissipates out of the near-field. The
ventilation rate for the surroundings, denoted by Qff, determines how quickly 1-BP dissipates out of the
surrounding space and into the outdoor air.
Near-Field
Volatile Source
Figure Apx 1-1. The Near-Field/Far-Field Model as Applied to the Spot Cleaning Near-Field/Far-
Field Inhalation Exposure Model
The model design equations are presented below in EquationApx 1-1 through EquationApx 1-16.
Near-Field Mass Balance
dCflp
EquationApx 1-1
V,
NF '
dt
CffQnf CnfQnf + ^
Far-Field Mass Balance
EquationApx 1-2
Where:
V,
dC,
FF
FF
dt
— CnfQnf CffQnf CffQff
Vnf =
near-field volume;
Vff =
far-field volume;
Qnf =
near-field ventilation rate;
Qff =
far-field ventilation rate;
Cnf =
average near-field concentration;
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Cff = average far-field concentration;
G = average vapor generation rate; and
t = elapsed time.
Both of the previous equations can be solved for the time-varying concentrations in the near-field and
far-field as follows (Keit. 2009):
EquationApx 1-3
EquationApx 1-4
Where:
EquationApx 1-5
EquationApx 1-6
EquationApx 1-7
EquationApx 1-8
EquationApx 1-9
EquationA
= 0.5
CNF = G(/cx + k2eXlt - k3e^2t)
CFF = G (— 1- k4eXlt - k$eX2t
\Qff
)
k± =
(qJ+qJ Qff
kn =
ko =
•Qnf + Qff'
QnfQff + ^2^nf(.Qnf + Qff)
QnfQff^nf(^i ~ ^2)
QnfQff + ^i^nf(.Qnf + Qff)
QnfQffVnf(.^i ~ ^2)
(A1VNF + Qnf\
4 = i q7f > 2
_ M2Vnf + Qnf\ j.
5 v qnf ) 3
px 1-10
/ QnfQff + ^nf(Qnf + Qff)
V KvfKff ,
+
/QnfQff + ^nf(Qnf + Qff)\ _ . /QnfQff\
\ ^nf^ff ) \ ^nf^ff '
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EquationA
X2 = 0.5
3x1-11
Qnf^ff + Vnf(Qnf + QffT
V ^NF^FF /
(<-
/ Qnf^ff + Vnf(Qnf + Qff)\
\ VnfVff J
^ (QnfQff\
V Vjyp Vpp )
EPA calculated the hourly TWA concentrations in the near-field and far-field using the following
equations. Note that the numerator and denominator of Equation Apx 1-12 and EquationApx 1-13 use
two different sets of time parameters. The numerator is based on the operating hours for the scenario
while the denominator is fixed to an averaging time span, t_avg, of 8 hours (since EPA is interested in
calculating 8-hr TWA exposures). Mathematically, the numerator and denominator must reflect the
same amount of time. This is indeed the case: although the spot cleaning operating hours ranges from
two to five hours (as discussed in Section 1.2.8), EPA assumes exposures are equal to zero outside of the
operating hours, such that the integral over the balance of the eight hours (three to six hours) is equal to
zero in the numerator. Therefore, the numerator inherently includes an integral over the balance of the
eight hours equal to zero that is summed to the integral from ti to t2.
EquationApx 1-12
CNFdt JG{kx + k2eXlt — k3eX2t)dt
C,
NF.TWA ~ ~7t
tr
JQ avg dt "ctvg
r(i * I k2eXlt2 k2ex^\ ( k2ex^ k3ex^\
G [k^ + —) ~ G [k^+^T1 —)
tavg
EquationApx 1-13
C,
CFFdt _ Jt'2 c(^+ kAe^ - kse^c) dt
FF.TWA ~ Tf
f avg dt *avg
t„
n(t2 , k4eA^ kseA^\ n(tx , k4eA>
U{Qpp+ A2 ) b{Qpp+ Ax
tavg
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. Note that the FSA is not equal to the surface
area of the entire near-field. EPA defined the near-field zone to be a rectangular box resting on the floor;
therefore, no mass transfer can occur through the near-field box's floor. FSA is calculated in
Equation Apx 1-14, below:
EquationApx 1-14
FSA = 2{LnfHnf) + 2 (WnfHnf) + (LNFWNF)
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Where: Lnf, Wnf, and Hnf are the length, width, and height of the near-field, respectively. The near-
field ventilation rate, Qnf, is calculated in EquationApx 1-15 from the near-field indoor wind speed,
vnf, and FSA, assuming half of FSA is available for mass transfer into the near-field and half of FSA is
available for mass transfer out of the near-field:
EquationApx 1-15
1
Qnf ~ 2 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 1-16:
EquationApx 1-16
Qff = VffAER
Using the model inputs in TableApx 1-1, EPA estimated 1-BP inhalation exposures for workers in the
near-field and for occupational bystanders 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.
1.2 Model Parameters
Table Apx 1-1 summarizes the model parameters and their values for the Spot Cleaning Near-Field/Far-
Field Exposure Model. Each parameter is discussed in detail in the following subsections.
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TableApx 1-1. Summary of Parameter Values and Distributions Used in the Spot Cleaning 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
Floor Area
A
ft2
—
—
500
20,000
—
Beta
Facility floor area is based on data from the
CARB (2006) and Kins Countv (Whittaker
and Johanson. 2011) studv. EPA fit a beta
function to this distribution with parameters:
ai = 6.655, a? = 108.22, min = 500 ft2, max =
20,000 ft2.
Far-field volume
Vff
ft3
—
—
6,000
240,000
—
—
Floor area multiplied by height. Facility
height is 12 ft (median value per CARB
study).
Near-field length
Lnp
ft
10
—
—
—
—
—
EPA assumed a constant near-field volume.
Near-field width
Wnf
ft
10
—
—
—
—
—
Near-field height
Hnp
ft
6
—
—
—
—
—
Air exchange rate
AER
hr1
—
—
1
19
3.5
Triangular
Values based on von Grote et al. (2006).
Klein and Kur/ (1994), and EPA TCE RA
oeer review comments (SCG. 2013). The
mode represents the midpoint of the range
reported in (SCG. 2013).
Near-field indoor wind
speed
Vnf
cm/s
—
—
0
202.2
—
Lognonnal
Lognonnal distribution fit to the data
Dresented in Baldwin and Mavnard (1998).
For commercial facilities, distribution has a
mean wind speed of 10.85 cm/s and standard
deviation of 7.88 cm/s.
Mir
—
—
0
23,882
—
Lognonnal
Starting time
ti
hr
0
—
—
—
—
—
Constant value.
Exposure Duration
t2
hr
—
—
2
5
—
Uniform
Equal to operating hours per day.
Averaging time
tavg
hr
8
—
—
—
—
—
Constant value.
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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
Use rate
UR
gal/yr
—
—
13.92
16
—
Uniform
MassDEP case study estimates a 1-BP dry
cleaner spends $60/month on spot cleaning
agent. At an estimated cost of $45/gal
(Blando et al.. 2009). this translates to 1.3
gal/month or 16 gal/yr. EPA assumed the
formulation contains 87 to 100% 1-BP.
Vapor generation rate
G
mg/hr
—
—
2.97E+0
3
9.32E+04
—
Calculated
G is calculated based on UR and assumes
100% volatilization.
g/min
—
—
0.05
1.55
—
Calculated
Operating hours per
day
OH
lir/day
—
—
2
5
—
Uniform
Determined from a California survey
Dcrformcd bv Wolf and Morris (2005) and an
analysis of two model plants constructed by
the researchers.
Operating days per
year
OD
days/yr
—
—
249
313
300
Triangular
Operating days/yr distribution assumed as
triangular distribution with min of 250, max
of 312, and mode of 300.
Fractional days with
exposure
f
unitless
—
—
0.8
1
—
Uniform
EPA assumed 0.8 to 1 to account for part-
time employees at dry cleaners. The low-end
of range corresponds to approximately 200
days/yr (i.e. the weighted average hours for
dry cleaning employees based on
BLS/Census data).
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1.2.1 Far-Field Volume
EPA calculated the far-field volume by setting a distribution for the facility floor area and multiplying
the floor area by a facility height of 12 ft (median value per CARB study) as discussed in more detail
below.
The 2006 CARB California Dry Cleaning Industry Technical Assessment Report (CARB. 2006) and the
Local Hazardous Waste Management Program in King County A Profile of the Dry Cleaning Industry in
King County, Washington (Whittaker and Johanson. 2011) provide survey data on dry cleaning facility
floor area. The CARB (2006) study also provides survey data on facility height. Using survey results
from both studies, EPA composed the following distribution of floor area. To calculate facility volume,
EPA used the median facility height from the CARB (2006) study. The facility height distribution in the
CARB (2006) study has a low level of variability, so the median height value of 12 ft presents a simple
but reasonable approach to calculate facility volume combined with the floor area distribution.
TableApx I-2.Composite Distribution of Dry Cleaning Facility Floor Areas
Floor Area
Value (ft2)
Percentile (as
fraction)
Source
20,000
1
King County
3,000
0.96
King County
2,000
0.84
King County
1,600
0.5
CARB 2006
1,100
0.1
CARB 2006
500
0
CARB 2006
EPA fit a beta function to this distribution with parameters: ai = 6.655, <12 = 108.22, min = 500 ft2, max
= 20,000 ft2.
1.2.2 Near-Field Volume
EPA assumed a near-field of constant dimensions of 10 ft wide by 10 ft long by 6 ft high resulting in a
total volume of 600 ft3.
1.2.3 Air Exchange Rate
von Grote (2006) indicated typical air exchange rates (AERs) of 5 to 19 hr"1 for dry cleaning facilities in
Germany. Klein and Kurz (1994) indicated AERs of 1 to 19 hr"1, with a mean of 8 hr"1 for dry cleaning
facilities in Germany. During the 2013 peer review of EPA's 2013 draft risk assessment of TCE, a peer
reviewer indicated that air exchange rate values around 2 to 5 hr"1 are likely (SCG 2013). in agreement
with the low end of the ranges reported by von Grote et al. and Klein and Kurz. 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"1).
1.2.4 Near-Field Indoor Wind 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 categorizing 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
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distribution for dry cleaners (including other textile cleaning facilities that conduct spot cleaning).
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).
The air speed surveys representative of commercial facilities were fit 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 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.
1.2.5 Averaging Time
EPA is interested in estimating 8-hr TWAs for use in risk calculations; therefore, a constant averaging
time of eight hours was used.
1.2.6 Use Rate
The Massachusetts Department of Environmental Protection (MassDEP) provided a comparative
analysis of several dry cleaner case studies using various PERC alternatives. The document estimates a
1-BP dry cleaner spends $60 per month on spot cleaning agent (MassDEP. 2013). At an estimated cost
of $45 per gallon (Blando et at.. 2009). this use rate translates to 1.3 gallon per month or 16 gallons per
year.
According to the Safety Data Sheet, Dry Sol v contains more than 87 percent 1-BP by weight (Enviro
Tech International. ). EPA assumed the spot cleaning formulation contains 87 to 100 percent 1-BP.
1.2.7 Vapor Generation Rate
EPA set the vapor generation rate for spot cleaning (G) equal to the use rate of 1-BP with appropriate
unit conversions. EPA assumed all 1-BP applied to the garment evaporates. EPA used a density of 1.33
g/cm3. To calculate an hourly vapor generation rate, EPA divided the annual use rate by the number of
operating days and the number of operating hours selected from their respective distributions for each
iteration.
1.2.8 Operating Hours
Wolf and Morris (2005) surveyed dry cleaners in California, including their spotting labor. The authors
developed two model plants: a small PERC dry cleaner that cleans 40,000 lb of clothes annually; and a
large PERC dry cleaner that cleans 100,000 lb of clothes annually. The authors modeled the small dry
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cleaner with a spotting labor of 2.46 hr/day and the large dry cleaner with a spotting labor of 5 hr/day.
EPA models a uniform distribution of spotting labor varying from 2 to 5 hr/day.
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Appendix J Dermal Exposure Assessment Method
This method was developed through review of relevant literature and consideration of existing exposure
models, such as EPA models and the European Centre for Ecotoxicology and Toxicology of Chemicals
Targeted Risk Assessment (ECETOC TRA).
J.l Incorporating the Effects of Evaporation
J.l.l Modification of EPA/OPPT Models
Current EPA/OPPT dermal models do not incorporate the evaporation of material from the dermis. The
dermal retained dose, Dexp (mg/day), is calculated as ( 013a):
EquationApx J-l
Dexp = S x Qu x Yderm x FT
Where:
S is the surface area of contact (cm2)
Qu is the quantity remaining on the skin after an exposure event (mg/cm2-event)
Yderm is the weight fraction of the chemical of interest in the liquid (0 < Yderm < 1)
FT is the frequency of events (integer number per day).
Here Qu does not represent the quantity remaining after evaporation, but represents the quantity
remaining after the bulk liquid has fallen from the hand that cannot be removed by wiping the skin (e.g.,
the film that remains on the skin).
One way to account for evaporation of a volatile solvent would be to add a multiplicative factor to the
EPA/OPPT model to represent the proportion of chemical that remains on the skin after evaporation,/abs
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EquationApx J-3
P MW3A
X = 3.4 X 10~3u° 78 „
|/0.76c
Oct
Where:
u is the air velocity (m/s)
Koctis the octanol:water partition coefficient
MW is the molecular weight
Sw is the water solubility (|ag/cm3)
Pvp is the vapor pressure (torr)
Chemicals for which % » 1 will largely evaporate from the skin surface, while chemicals for which x
« 1 will be largely absorbed; x = 1 represents a balance between evaporation and absorption.
Equation Apx J-3 is applicable to chemicals having a log octanol/water partition coefficient less than or
equal to three (log Kow < 3)15. The equations that describe the fraction of the initial mass that is
absorbed (or evaporated) are rather complex (Equations 20 and 21 of (Kasting and Miller, 2006)) but
can be solved.
J.2.1 Small Doses (Case 1: Mo < Msat)
In the small dose scenario, the initial dose (Mo) is less than that required to saturate the upper layers of
the stratum corneum (Mo < Msat), and the chemical is assumed to evaporate from the skin surface at a
rate proportional to its local concentration.
For this scenario, Frasch (2012) calculated the fraction of applied mass that is absorbed, based on the
infinite limit of time (i.e. infinite amount of time available for absorption after exposure):
Equation Apx J-4
, mgbsi™) 2 + fx
Jabs M0 2 + 2/
Where:
mabs is the mass absorbed
Mo is the initial mass applied
/is the relative depth of penetration in the stratum corneum (f= 0.1 can be assumed)
X is as previously defined
Note the simple algebraic solution in Equation Apx J-4 provides a theoretical framework for the total
mass that is systemically absorbed after exposure to a small finite dose (mass/area) of chemical, which
depends on the relative rates of evaporation, permeation, and the initial load. At "infinite time", the
15 For simplification, Kasting and Miller (2006) does not consider the resistance of viable tissue layers underlying the stratum
corneum, and the analysis is applicable to hydrophilic-to-moderately lipophilic chemicals. For small molecules, this
limitation is equivalent to restricting the analysis to compounds where Log Kow < 3.
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applied dose is either absorbed or evaporated (Frasch. 2012). The finite dose is a good model for splash-
type exposure in the workplace (Frasch and Bunge. 2015).
The fraction of the applied mass that evaporates is simply the complement of that absorbed:
EquationApx J-5
mevap(co) 2 x~fX
Mq ~ 'abs ~ 2 + 2/
Where:
mevap is the mass evaporated
The fraction absorbed can also be represented as a function of dimensionless time x (Dt/h2), as shown in
Equation Apx J-6:
Equation Apx J-6
00 _ ry
* ™ _ mabs _ . V 1 „ ( X2+^ 1 ~ f) Xn ~ COSXn\
\X2+X*+X)\ TT„ J
where the eigenvalues Xn are the positive roots of the equation:
Equation Apx J-7
Xn ¦ cot(2n) + x = 0
Equation Apx J-6 and Equation Apx J-7 must be solved analytically. It should be noted that the
dimensionless time x is not a representation of exposure duration for a work activity; rather, it represents
the amount of time available for absorption after the initial exposure dose is applied. Since most dermal
risk assessments are typically more concerned with the quantity absorbed, rather than the time course of
absorption, the simple algebraic solution is recommended over the analytical solution.
3.2.2 Large Doses (Case 2: Mo > Msat)
For large doses (Mo > Msat), the chemical saturates the upper layers of the stratum corneum, and any
remaining amount forms a residual layer (or pool) on top of the skin. The pool acts as a reservoir to
replenish the top layers of the membrane as the chemical permeates into the lower layer. In this case,
absorption and evaporation approach steady-state values as the dose is increased, similar to an infinite
dose scenario.
The steady-state fraction absorbed can be approximated by Equation Apx J-8:
Equation Apx J-8
1
/afcsC00) — . 1
Z + 1
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TableApx J-l presents the estimated absorbed fraction calculated using the steady-state approximation
for large doses (EquationApx J-8) for 1-BP.
Table Apx J-l. Estimated Fraction Evaporated and Absorbed (fabs) using Steady-State
Chemical Name
l-Bromopropane
CASRN
106-94-5
Molecular Formula
CiHyBr
Molecular Weight (g/mol)
122.99
Pw (torr)
146.26
Universal gas constant, R (L*atm/K*mol)
0.0821
Temperature, T (K)
303
Log Iv
2.1
Koct
125.9
Sw (g/L)
2.45
Sw (ng/cm3)
2450
Industrial Setting
u (m/s)a
0.1674
Ratio of Evaporative Flux to Dermal Flux, x
16.28
Fraction Evaporated
0.94
Fraction Absorbed
0.06
Commercial Setting
u (m/s)a
0.0878
Evaporative Flux, x
9.84
Fraction Evaporated
0.91
Fraction Absorbed
0.09
a EPA used air speeds from Baldwin and Maynard (1998): the 50th percentile of industrial occupational environments of
16.74 cm/s is used for industrial settings and the 50th percentile of commercial occupational enviromnents of 8.78 cm/s is
used for commercial settings.
J.3 Comparison of fabS to Experimental Values for 1-BP
Sections J.2 presents a theoretical framework for estimating the fraction of volatile chemical absorbed in
finite dose and infinite dose scenarios. Where available, experimental studies and actual measurements
of absorbed dose are preferred over theoretical calculations.
In a 2011 study, Frasch et al. tested dermal absorption characteristics of 1-BP. For the finite dose
scenario, Frasch et al. (2011) determined that unoccluded exposure resulted in less than 0.2 percent of
applied 1-BP dose penetrated the skin - a value substantially lower than the theoretical ~6 percent
absorbed estimated using Equation Apx J-8. The 2011 Frasch et al. study recognized the large standard
deviation of certain experimental results, and the difficulty of spreading a small, rapidly evaporating
dose of 1-BP evenly over the skin surface. Frasch et al. (2011) also raised the possibility that 1-BP may
dehydrate the stratum corneum, thereby decreasing the skin permeability after initial exposure.
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J.4 Potential for Occlusion
Gloves can prevent the evaporation of volatile chemicals from the skin, resulting in occlusion.
Chemicals trapped in the glove may be broadly distributed over the skin (increasing S in EquationApx
J-2), or if not distributed within the glove, the chemical mass concentration on the skin at the site of
contamination may be maintained for prolonged periods of time (increasing Qu in Equation Apx J-2).
Conceptually, occlusion is similar to the "infinite dose" study design used in in vitro and ex vivo dermal
penetration studies, in which the dermis is exposed to a large, continuous reservoir of chemical.
The impact of occlusion on dermal uptake is complex: continuous contact with the chemical may
degrade skin tissues, increasing the rate of uptake, but continuous contact may also saturate the skin,
slowing uptake (Dancik et at.. 2015). These phenomena are dependent upon the chemical, the vehicle
and environmental conditions. It is probably not feasible to incorporate these sources of variability in a
screening-level population model of dermal exposure without chemical-specific studies.
Existing EPA/OPPT dermal models (Equation Apx J-l) could theoretically be modified to account for
the increased surface area and/or increased chemical mass in the glove. This could be achieved through
a multiplicative variable (such as used in Equation Apx J-2 to account for evaporative loss) or a change
in the default values of S and/or Qu. It may be reasonable to assume that the surface area of hand in
contact with the chemical, S, is the area of the whole hand owing to the distribution of chemical within
the glove. Since Qu reflects the film that remains on the skin (and cannot be wiped off), a larger value
should be used to reflect that the liquid volume is trapped in the glove, rather than falling from the hand.
Alternatively, the product SxQu (cm2 x mg/cm2-event) could be replaced by a single variable
representing the mass of chemical that deposits inside the glove per event, M (mg/event):
Equation Apx J-9
Dexp = M x Yderm x FT
Garrod et al. (2001) surveyed contamination by in volatile components of non-agricultural pesticide
products inside gloves across different job tasks and found that protective gloves were nearly always
contaminated inside. While the study does not describe the exact mechanism in which the contamination
occurs (e.g. via the cuff, permeation, or penetration through imperfections in glove materials), it
quantified inner glove exposure as "amount of product per unit time", with a median value of 1.36 mg
product per minute, a 75th percentile value of 4.21 mg/min, and a 95th percentile value of 71.9 mg/min. It
is possible to use these values to calculate the value of M, i.e. mass of chemical that deposits inside the
glove, if the work activity duration is known.
Assuming an activity duration of one hour, the 50th and 95th percentile values translate to 81.6 mg and
4,314 mg of inner glove exposure. While these values may be used for M in Equation Apx J-9, EPA
notes the significant difference between the 50th and 95th percentile deposition, with the 95th percentile
value being two times more conservative than the defaults for the EPA/OPPT 2-Hand Dermal Exposure
Model (where the product S x Quis 2,247 mg/event). Given the significant variability in inner glove
exposure and lack of information on the specific mechanism in which the inner glove contamination
occurs, EPA presents occluded exposure estimates using 2,247 mg/event for parameter M in
Equation Apx J-9.
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EPA does not expect occlusion scenarios to be a reasonable occurrence for all conditions of use.
Specifically, occlusion is not expected at sites using chemicals in closed systems where the only
potential of dermal exposure is during the connecting/disconnecting of hoses used for unloading/loading
of bulk containers (e.g., tank trucks or rail cars) or while collecting quality control samples including
manufacturing sites, repackaging sites, sites processing the chemical as a reactant, formulation sites, and
other similar industrial sites. Occlusion is also not expected to occur at highly controlled sites where,
due to purity requirements, the use of engineering controls is expected to limit potential dermal
exposures. EPA also does not expect occlusion at sites where contact with bulk liquid chemical is not
expected such as aerosol degreasing sites.
EPA expects occlusion to be a reasonable occurrence at sites where workers may come in contact with
bulk liquid chemical and handle the chemical in open systems. This includes conditions of use such as
vapor degreasing, cold cleaning, and dry cleaning where workers are expected to handle bulk chemical
during cleanout of spent solvent and addition of fresh solvent to equipment. Similarly, occlusion may
occur at coating or adhesive application sites when workers replenish application equipment with liquid
coatings or adhesives.
J.5 Incorporating Glove Protection
Data about the frequency of effective glove use - that is, the proper use of effective gloves - is very
limited in industrial settings. Initial literature review suggests that there is unlikely to be sufficient data
to justify a specific probability distribution for effective glove use for a chemical or industry. Instead,
the impact of effective glove use should be explored by considering different percentages of
effectiveness (e.g., 25% vs. 50% effectiveness).
Gloves only offer barrier protection until the chemical breaks through the glove material. Using a
conceptual model, Cherrie et al. (2004) proposed a glove workplace protection factor - the ratio of
estimated uptake through the hands without gloves to the estimated uptake though the hands while
wearing gloves: this protection factor is driven by flux, and thus varies with time. The ECETOC TRA
model represents the protection factor of gloves as a fixed, assigned protection factor equal to 5, 10, or
20 (Marquart et ). Where, similar to the APR for respiratory protection, the inverse of the
protection factor is the fraction of the chemical that penetrates the glove.
The protection afforded by gloves can be incorporated into the EPA/OPPT model (EquationApx J-l)
by modification of Qu with a protection factor, PF (unitless, PF > 1):
Equation Apx J-10
Dexp = S x x Yderm x FT
Given the limited state of knowledge about the protection afforded by gloves in the workplace, it is
reasonable to utilize the PF values of the ECETOC TRA model (Marquart et al.. ), rather than
attempt to derive new values. Table Apx J-2 presents the PF values from ECETOC TRA model (version
3). In the exposure data used to evaluate the ECETOC TRA model, Marquart et al. (2017) reported that
the observed glove protection factor was 34, compared to PF values of 5 or 10 used in the model.
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TableApx J-2. Exposure Control Efficiencies and Protection Factors for Different Dermal
Protection Strategies from ECETOC TRA v3
Dermal Protection Characteristics
Affected User Group
Indicated
Efficiency (%)
Protection
Factor, PF
a. Any glove / gauntlet without permeation data and without
employee training
Both industrial and
professional users
0
1
b. Gloves with available permeation data indicating that the
material of construction offers good protection for the
substance
80
5
c. Chemically resistant gloves (i.e., as b above) with "basic"
employee training
90
10
d. Chemically resistant gloves in combination with specific
activity training (e.g., procedure for glove removal and
disposal) for tasks where dermal exposure can be expected to
occur
Industrial users only
95
20
Source: (Marquart et al.. 2017)
J.6 Proposed Dermal Dose Equation
Accounting for all parameters above, the proposed, overall equation for estimating dermal exposure is:
EquationApx J-ll
( Qu Xfabs)
D — V U.OSJ y pj,
uexp pp * 1 derm ^ 11
EPA presents exposure estimates for the following deterministic dermal exposure scenarios:
• Dermal exposure without the use of protective gloves (Equation Apx J-l 1, PF = 1)
• Dermal exposure with the use of protective gloves (Equation Apx J-l 1, PF = 5)
• Dermal exposure with the use of protective gloves and employee training (EquationApx J-ll,
PF = 20 for industrial users and PF = 10 for professional users)
• Dermal exposure with occlusion (Equation Apx J-9)
EPA assumes the following parameter values for EquationApx J-ll in addition to the parameter values
presented in Table Apx J-l:
• S, the surface area of contact: 1,070 cm2, representing the total surface area of both hands.
• Qu, the quantity remaining on the skin: 2.1 mg/cm2-event. This is the high-end default value used
in the EPA/OPPT dermal models (U.S. EPA. 2013a).
• Yderm, the weight fraction of the chemical of interest in the liquid: EPA will assess a unique value
of this parameter for each occupational scenario or group of similar occupational scenarios.
• FT, the frequency of events: 1 event per day
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For Equation Apx J-9, EPA assumes the quantity of liquid occluded underneath the glove (M) is equal
to the product of the entire surface area of contact (S = 1,070 cm2) and the assumed quantity of liquid
remaining on the skin (Qu = 2.1 mg/cm2-event), which is equal to 2,247 mg/event. See discussion in
Section J.4.
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