&EPA
United States
Environmental Protection Agency
EPA DocumentW 740-R1-4003
August 2014
Office of Chemical Safety and
Pollution Prevention
TSCA Work Plan Chemical Risk Assessment
Methylene Chloride:
Paint Stripping Use
CASRN: 75-09-2
H
H
Cl
August 2014
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TABLE OF CONTENTS
LIST OF TABLES 6
LIST OF FIGURES 10
AUTHORS/CONTRIBUTORS/ACKNOWLEDGEMENTS/REVIEWERS 12
GLOSSARY OF TERMS AND ABBREVIATIONS 14
EXECUTIVE SUMMARY 19
1 BACKGROUND AND SCOPE 27
1.1 INTRODUCTION 27
1.2 BACKGROUND 28
1.2.1 Rationale for Selecting DCM for Risk Assessment 28
1.2.2 Overview of DCM Uses and Production Volume 28
1.2.3 Overview of Assessments ofDCM's Human Health Hazards 28
1.2.4 Overview EPA's Regulatory History of DCM 29
1.3 SCOPE OFTHE ASSESSMENT 30
1.3.1 Selection of DCM Uses 30
1.3.2 Selection of Exposure Pathway 30
1.3.3 Identification of Human Populations Exposed During the Use ofDCM-Based Paint Strippers 30
1.3.4 Why Environmental Risks Were Not Evaluated For DCM-Based Paint Strippers 32
2 SOURCES AND FATE 33
2.1 PHYSICAL AND CHEMICAL PROPERTIES 33
2.2 DCM PRODUCTION AND USES 34
2.2.1 Market Trends and Uses 34
2.2.1.1 Consumer Uses 37
2.2.1.2 Paint Stripping Applications 38
2.3 SUMMARY OF ENVIRONMENTAL FATE 38
3 HUMAN HEALTH RISK ASSESSMENT 39
3.1 OCCUPATIONAL EXPOSURE ASSESSMENT FORTHE USE OF DCM IN PAINT STRIPPING 39
3.1.1 Approach and Methodology for Estimating Occupational Exposures 39
3.1.1.1 Identification of Relevant Industries 39
3.1.1.2 Estimation of Potential Workplace Exposures for Paint Stripping Facilities 40
3.1.1.3 Summary of Occupational DCM Exposure Estimates 46
3.1.1.4 Worker Exposure Limits for DCM 49
3.2 CONSUMER EXPOSURE ASSESSMENT FORTHE USE OF DCM IN PAINT STRIPPING 50
3.2.1 Approach and Methodology for Estimating Consumer Exposures 50
3.2.2 Overview of the MCCEM 50
3.2.3 MCCEM Input Parameters and Assumptions 52
3.2.3.1 Estimation of Emission Profiles for Paint Removers/Strippers 52
3.2.3.2 Method of Application 53
3.2.3.3 Amount Applied to the Surface (Product Mass) 53
3.2.3.4 Stripping Sequence 54
3.2.3.5 Amount of Chemical Released 55
3.2.3.6 Airflow Rates and Volumes 55
3.2.3.7 Locations of Exposed Individuals 56
3.2.4 MCCEM Modeling Scenarios 56
3.2.4.1 Sensitivity Analysis 57
3.2.4.2 Exposure Scenarios for the DCM Inhalation Exposure Assessment 60
3.2.5 Consumer Model Results 65
3.3 HAZARD/DOSE-RESPONSE ASSESSMENT 67
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3.3.1 Approach and Methodology 67
3.3.1.1 Selection of Peer-Reviewed Hazard/Dose-Response Assessments as the Source Documents for the DCM TSCA
Assessment 67
3.3.1.2 Chronic Hazard and Dose-Response Assessment: EPA IRIS Toxicological Review of Methylene Chloride 68
3.3.1.2.1 Carcinogenic Effects Following Chronic Exposure to DCM 68
3.3.1.2.2 Non-Cancer Effects Following Chronic Exposure to DCM 69
3.3.1.3 Acute Hazard and Dose-Response Assessment 72
3.3.1.3.1 SMACs 73
3.3.1.3.2 California's Acute REL 74
3.3.1.3.3 AEGLs 75
3.3.2 Human Health Hazard Summary 78
3.3.2.1 Absorption, Distribution, Metabolism and Excretion 78
3.3.2.2 Human and Animal Toxicity Following Acute Exposure to DCM 79
3.3.2.3 Human and Animal Toxicity Following Repeated Exposures to DCM 80
3.3.2.3.1 Non-Cancer Effects 80
3.3.2.3.2 Carcinogenic Effects 81
3.3.2.4 Susceptible Subpopulations 82
3.3.3 Summary of Hazard Values Used to Evaluate Acute and Chronic Exposures 82
3.4 HUMAN HEALTH RISK CHARACTERIZATION 84
3.4.1 Risk Estimation Approach for Acute and Repeated Exposures 85
3.4.2 Acute Non-Cancer Risk Estimates for Inhalation Exposures to DCM 88
3.4.2.1 Acute Risks for Consumer Exposure Scenarios 88
3.4.2.2 Acute Risks for Occupational Exposure Scenarios 92
3.4.3 Non-Cancer and Cancer Risk Estimates for Chronic Inhalation Exposures to DCM 96
3.4.3.1 Cancer Risks for Occupational Exposure Scenarios 96
3.4.3.2 Non-Cancer Risks for Occupational Exposure Scenarios Following Chronic Exposure to DCM 102
3.4.4 Human Health Risk Characterization Summary 108
3.5 DISCUSSION OF KEY SOURCES OF UNCERTAINTY AND DATA LIMITATIONS 110
3.5.1 Uncertainties in the Occupational Exposure Estimates 110
3.5.2 Uncertainties in the Consumer Exposure Estimates Ill
3.5.3 Uncertainties in the Hazard and Dose-Response Assessments 113
3.5.3.1 Uncertainties in the Cancer Hazard/Dose-Response Assessments 113
3.5.3.2 Uncertainties in the Non-Cancer Hazard/Dose-Response Assessments 114
3.5.3.2.1 Uncertainties in the Acute Hazard/Dose-Response Assessments 114
3.5.3.2.2 Uncertainties in the Chronic Hazard/Dose-Response Assessments 115
3.5.4 Uncertainties in the Risk Assessment 116
3.6 CONCLUSIONS OFTHE HUMAN HEALTH RISKASSESSMENT 119
4 REFERENCES 121
APPENDICES 144
Appendix A REGULATORY HISTORY OF DCM IN THE U.S. AND ABROAD 144
A-l DCM Regulatory History in the U.S 144
A-2 DCM Regulatory History in Canada and Europe 145
Appendix B SUMMARY OF ENVIRONMENTAL EFFECTS: AQUATIC TOXICITY 146
B-l Acute Toxicity to Fish 146
B-2 Chronic Toxicity to Fish 147
B-3 Acute Toxicity to Aquatic Invertebrates 147
B-4 Toxicity to Aquatic Plants 147
Appendix C INVENTORY UPDATE REPORTING RULE DATA FOR DCM 148
Appendix D HOUSEHOLD PRODUCTS DATA FOR DCM 150
Appendix E ENVIRONMENTAL FATE OF DCM 152
E-l Fate in Air 153
E-2 Fate in Water 153
E-3 Fate in Soil/Sediment 154
E-4 Bioconcentration and Persistence 154
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Appendix F PAINT STRIPPING PROCESSES AND ASSOCIATED WORKERS ACTIVITIES, AND FACILITY AND POPULATION
INFORMATION 155
F-l Identification of Industrial Sectors 155
F-2 Descriptions of Paint Stripping Processes and Activities in Relevant Industries 156
F-2-1 Paint Stripping By Professional Contractors 156
F-2-2 Graffiti Removal 157
F-2-3 Paint Stripping at Automotive Body Repair and Maintenance Shops 158
F-2-4 Wood Furniture Stripping 158
F-2-5 Art Restoration and Conservation 161
F-2-6 Aircraft Paint Stripping 161
F-2-7 Ship Paint Stripping 161
F-2-8 Respiratory Protection 161
F-3 Facility and Worker Population Data 162
F-3-1 Potentially Exposed Population in the U.S 162
F-3-2 Numbers of Workers per Facility by Industry 163
F-3-2-1 Paint Stripping By Professional Contractors, Bathtub Refinishing, and Graffiti Removal 164
F-3-2-2 Paint Stripping at Automotive Body Repair and Maintenance Shops 164
F-3-2-3 Wood Furniture Stripping 165
F-3-2-4 Art Restoration and Conservation 167
F-3-2-5 Aircraft Paint Stripping 168
F-3-2-6 Ship Paint Stripping 169
Appendix G OCCUPATIONAL EXPOSURE LITERATURE DATA AND EXPOSURE CALCULATIONS 170
G-l Data Needs, Data Collection Strategy and Data Quality Criteria for the Occupational Exposure Analysis 170
G-l-1 Data Needs 170
G-l-2 Data Collection Strategy 171
G-l-3 Data Quality Criteria 172
G-2 Approach and Methodology for Estimating Occupational Exposure 174
G-2-1 Identification of Relevant Industries 174
G-2-2 Estimation of Potential Workplace Exposures for DCM-Based Paint Strippers 174
G-2-2-1 Workplace Exposures Based on Monitoring Data 174
G-2-2-2 Workplace Exposure Scenarios Evaluated in this Assessment 179
G-2-3 Worker Exposure Limits for DCM 186
G-3 Summary of Inhalation Monitoring Data 187
G-3-1 Bathtub Refinishing Exposures and Fatalities 187
G-3-2 Paint Stripping by Professional Contractors 188
G-3-3 Graffiti Removal 191
G-3-4 Paint Stripping at Automotive Body Repair and Maintenance Shops 192
G-3-5 Wood Furniture Stripping 193
G-3-6 Art Restoration and Conservation 202
G-3-7 Aircraft Paint Stripping 202
G-3-8 Ship Paint Stripping 203
G-3-9 Paint Stripping in Non-specific Workplace Settings 203
G-3-10 Summary of OSHAIMIS Data 205
Appendix H RESIDENTIAL/CONSUMER EXPOSURE ASSESSMENT 209
H-l Estimation of Emission Profiles for Paint Removers/Strippers 209
H-l-1 Conceptual Approach 210
H-l-1-1 MRI Chamber Study (EPA, 1994a) 212
H-l-1-2 LBL Chamber Study (LBL, 1986) 216
H-l-1-3 van Veen Chamber Study (van Veen et al., 2002) and EC Chamber Study (EC, 2004) 218
H-l-1-4 Discussion and Conclusions 220
H-2 Sensitivity Analysis for Inhalation Scenarios 223
H-3 Inhalation Exposure Scenario Inputs 223
H-4 Inhalation Model Outputs and Exposure Calculations 234
H-4-1 Exposure Calculations 234
H-4-2 TWA Concentrations 235
H-4-3 Modeling Results 235
H-5 Comparison of Modeling-based and Monitoring-based Exposure Estimates 241
H-5-1 Scenario Similarities and Differences 241
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H-5-2 Comparison of Exposure Estimates 242
H-6 MCCEM Inhalation Model ing Scenario Summaries 244
Appendix I RISK ASSESSMENT GUIDELINES, LITERATURE SEARCH STRATEGY AND DATA QUALITY CRITERIA USED IN
THE HAZARD/DOSE-RESPONSE ASSESSMENTS OF METHYLENE CHLORIDE 265
1-1 EPA/IRIS Toxicological Review 265
1-1-1 Risk Assessment Guidelines 265
1-1-2 Literature Search Strategy 266
1-1-3 Study Selection and Data Quality Criteria 266
1-2 Acute Exposure Guideline Levels (AEGLs) 269
1-3 Spacecraft Maximum Allowable Concentrations (SMACs) 269
1-4 California's Acute Reference Exposure Levels (RELs) 270
Appendix J SUMMARY OF THE DERIVATIONS OF THE EPA IRIS CANCER INHALATION UNIT RISK AND NON-CANCER
HUMAN EQUIVALENT CONCENTRATION FOR CHRONIC EXPOSURES 271
J-l Cancer Inhalation Unit Risk 271
J-2 Non-Cancer Hazard Value 273
Appendix K THE DERIVATIONS OF THE ACUTE HAZARD VALUES USED IN THE DCM RISK ASSESSMENT OF PAINT
STRIPPERS 275
K-l Spacecraft Maximum Allowable Concentrations (SMAC) 275
K-2 California's Acute Reference Exposure Level (REL) 276
K-3 Acute Exposure Level Guidelines (AEGL) 277
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LIST OF TABLES
Table ES-1. Ranges of DCM Occupational Exposure Estimates Used in the Risk Assessment Based on
Monitoring Data 21
Table 1-1. Primary Uses of DCM and Selection Criteria 31
Table 2-1. Physical-Chemical Properties of DCM a 33
Table 2-2. DCM Market Trends by Use 35
Table 2-3. Major and Minor Uses of DCM 36
Table 2-4. Major Uses of DCM in the U.S 37
Table 2-5. TSCA Consumer Uses of DCM 37
Table 3-1. Acute Occupational Exposure Scenarios for the Use of DCM-Based Paint Strippers 41
Table 3-2. Chronic Occupational Exposure Scenarios for the Use of DCM-Based Paint Strippers 42
Table 3-3. DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers - Scenario 1 -
Highest Exposed Scenario Group 47
Table 3-4. Occupational Exposure Limits for DCMa 49
Table 3-5. Consumer Exposure Scenarios for the DCM Inhalation Exposure Assessment 61
Table 3-6. Summary of DCM Consumer Paint Stripping Scenario Descriptions and Parameters 61
Table 3-7. Modeled DCM Air Concentrations to Which Consumer Users and Residential Bystanders are
Exposed 66
Table 3-8. Cancer and Non-Cancer Hazard Values Used in the Risk Evaluation of Chronic Exposures to
Workers Using DCM-Based Paint Strippers 71
Table 3-9. Non-Cancer Hazard Values Used in the Risk Evaluation of Acute Exposures to Workers and
Consumers Using DCM-Based Paint Strippers 76
Table 3-10. Summary of Inhalation Hazard Information Used in the Risk Evaluation of Acute and Chronic
Scenarios 83
Table 3-11. Use Scenarios, Populations of Interest and Toxicological Endpoints for Assessing Acute Risks to
DCM-containing Paint Strippers 85
Table 3-12. Use Scenarios, Populations of Interest and Toxicological Endpoints for Assessing Chronic Risks to
DCM-containing Paint Strippers 86
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Table 3-13. Margin of Exposure (MOE) Equation to Estimate Non-Cancer Risks Following Acute or Chronic
Exposures to DCM 87
Table 3-14. Equation to Calculate Cancer Risks 87
Table 3-15. Acute Risk Estimates for Residential Exposures to DCM-Based Paint Strippers: SMAC and
California's REL PODs. MOEs below benchmark MOE indicate potential health risks and are
denoted in bold text 89
Table 3-16. Acute Risk Estimates for Residential Exposures to DCM-Based Paint Strippers: AEGL-1 and AEGL-
2 PODs for Various Exposure Durations. MOEs below benchmark MOE indicate potential health
risks and are denoted in bold text 90
Table 3-17. Acute Risk Estimates for Occupational Exposures to DCM-Based Paint Strippers: AEGL-1 and
AEGL-2 PODs for Various Exposure Durations. MOEs below benchmark MOE indicate potential
health risks and are denoted in bold text 93
Table 3-18. Occupational Cancer Risks for Professional Contractors (Scenarios 1, 3, 15 and 16) 97
Table 3-19. Occupational Cancer Risks for Automotive Refinishing (Scenarios 1, 3, 15 and 16) 98
Table 3-20. Occupational Cancer Risks for Furniture Refinishing (Scenarios 1, 3, 15 and 16) 98
Table 3-21. Occupational Cancer Risks for Aircraft Stripping (Scenarios 1, 3, 15 and 16) 99
Table 3-22. Occupational Cancer Risks for Graffiti Removal (Scenarios I, 3, 15 and 16) 99
Table 3-23. Occupational Cancer Risks for Non-Specific Workplace Settings—Immersion Stripping of Wood
(Scenarios I, 3, 15 and 16) 100
Table 3-24. Occupational Cancer Risks for Non-Specific Workplace Settings—Immersion Stripping of Wood
and Metal (Scenarios I, 3, 15 and 16) 101
Table 3-25. Occupational Cancer Risks for Non-Specific Workplace Settings—Unknown (Scenarios 1, 3, 15
and 16) 101
Table 3-26. Occupational Cancer Risks for Art Restoration and Conservation (Scenarios 1, 3, 15 and 16).... 102
Table 3-27. Occupational Non-Cancer Risks for Professional Contractors Following Chronic Exposure to DCM
(Scenarios I, 3, 15 and 16) 103
Table 3-28. Occupational Non-Cancer Risks for Automotive Refinishing Following Chronic Exposure to DCM
(Scenarios I, 3, 15 and 16) 104
Table 3-29. Occupational Non-Cancer Risks for Furniture Refinishing Following Chronic Exposure to DCM
(Scenarios I, 3, 15 and 16) 104
Table 3-30. Occupational Non-Cancer Risks for Art Restoration and Conservation Following Chronic Exposure
to DCM (Scenarios I, 3, 15 and 16) 105
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Table 3-31. Occupational Non-Cancer Risks for Aircraft Stripping Following Chronic Exposure to DCM
(Scenarios 1, 3, 15 and 16) 105
Table 3-32. Occupational Non-Cancer Risks for Graffiti Removal Following Chronic Exposure to DCM
(Scenarios 1, 3, 15 and 16) 106
Table 3-33. Occupational Non-Cancer Risks for Non-Specific Workplace Settings (Immersion Stripping of
Wood) Following Chronic Exposure to DCM (Scenarios I, 3, 15 and 16) 106
Table 3-34. Occupational Non-Cancer Risks for Non-Specific Workplace Settings (Immersion Stripping of
Wood and Metal) Following Chronic Exposure to DCM (Scenarios I, 3, 15 and 16) 107
Table 3-35. Occupational Non-Cancer Risks for Non-Specific Workplace Settings (Unknown) Following
Chronic Exposure to DCM (Scenarios I, 3, 15 and 16) 107
Table 3-36. Summary of the Uncertainties in the Derivation of the Cancer Inhalation Unit Risk 113
Table C-l. National Chemical Information for DCM from 2012 CDR 148
Table C-2. Summary of Industrial DCM Uses from 2012 CDR 148
Table C-3. DCM Commercial/Consumer Use Category Summary 149
Table D-l. Household Products Containing DCM from NIH's Household Products Database 150
Table E-1. Environmental Fate Characteristics of DCM1 153
Table F-l. 2007 NAICS Codes Identified that Include Paint Stripping Activities 155
Table F-2. Calculation of Population of Workers that Potentially Perform Paint Stripping with DCM 162
Table F-3. 2007 U.S. Economic Census Data for Painting and Wall Covering and Flooring Contractors 164
Table F-4. 2007 U.S. Economic Census Data for Automotive Body, Paint, and Interior Repair and Maintenance
165
Table F-5. 2007 U.S. Economic Census Data for Reupholstery and Furniture Repair 166
Table F-6. Estimated Annual DCM Based Stripper Usage in California a 167
Table F-7. 2007 U.S. Economic Census Data for Industry Sectors that May Engage in Art Restoration and
Conservation Activities 167
Table F-8. 2007 U.S. Economic Census Data for Aircraft Manufacturing 168
Table F-9. 2007 U.S. Economic Census Data for Ship Building and Repairing 169
Table G-l. Data Quality Criteria and Acceptance Specifications for Occupational Data 173
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Table G-2. DCM 8-hr TWA Air Concentrations Used for Estimating Occupational Acute and Chronic Exposure
Concentrations for Non-Cancer and Cancer Risks and Non-8 hr Air Concentration Data from the
Literature 176
Table G-3. Acute Occupational Exposure Scenarios for the Use of DCM-Based Paint Strippers 179
Table G-4. Chronic Occupational Exposure Scenarios for the Use of DCM-Based Paint Strippers 180
Table G-5. DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers - Scenario 1-
Highest Exposed Scenario Group 184
Table G-6. Regulatory and Recommended Exposure Limits for DCM a 186
Table G-7. Summary of DCM Personal Concentrations during Graffiti Removal 192
Table G-8. Summary of Personal and Area Concentrations in a Furniture Refinishing Shop that Uses a Pump
and Brush Stripping Technique Measured Before Engineering Controls were Added 195
Table G-9. Summary of Personal and Area Concentrations in a Furniture Refinishing Shop that Uses a Pump
and Brush Stripping Technique Measured After Engineering Controls were Added to the
Stripping Booth 196
Table G-10. Summary of Personal and Area Concentrations in a Furniture Refinishing Shop that Uses a Pump
and Brush Stripping Technique Measured After Engineering Controls were Added to the
Stripping Booth and Wash Booth 197
Table G-ll. Summary of Worker Exposures to DCM During Furniture Paint Stripping using a Dip Tank after
Implementation of NIOSH-Recommended Slotted Hood Ventilation System3 200
Table G-12. Summary by Industry of OSHA IMIS Personal Monitoring Data for DCM from 1992 to 2012 207
Table H-l. DCM-containing Products Used in the MRI Chamber Studies 212
Table H-2. Fitted Parameters to MRI Study Results for Two DCM-Containing Paint Strippers 215
Table H-3. Comparison of Brush-on Product Ingredients forthe LBL and MRI Studies 216
Table H-4. Comparison of DCM Mass Released for LBL and MRI Studies of Brush-on Products 217
Table H-5. Estimated DCM Released for Four Experiments by van Veen et al. (2002) 219
Table H-6. Summary of DCM Chamber Studies 222
Table H-7. Schedule for Brush-on Application to Chest Surface: Four Segments with Repeat Application... 226
Table H-8. DCM Mass Released, by Application Target and Method 227
Table H-9. Estimated Exposures and Associated Conditions for Selected OPPT and LBL Cases 243
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LIST OF FIGURES
Figure 2-1. Chemical Structure of Methylene Chloride 33
Figure 3-1. Example of Time-Varying User Exposure Concentration and Maximum TWA Values for Selected
Averaging Times 58
Figure 3-2. Example of Time-Varying Residential Bystander Exposure Concentration and Maximum TWA
Values for Selected Averaging Times 58
Figure 3-3. Model Sensitivity Results: Percent Change from Base-Case Response for Maximum 1-hr TWA for
User and Residential Bystander 59
Figure 3-4. Model Sensitivity Results: Percent Change from Base-case Response for 24-hr TWA for User and
Residential Bystander 60
Figure F-l. Typical Flow Tray for Applying Stripper to Furniture 159
Figure F-2. Typical Water Wash Booth Used to Wash Stripper and Coating Residue from Furniture 159
Figure H-l. Model Fit to Data Extracted from MRI Chamber Study for BIX Spray-on Product 214
Figure H-2. Model Fit to Data Extracted from MRI Chamber Study Report for Strypeeze Brush-on Product. 214
Figure H-3. Theoretical Cumulative Mass of DCM Released for BIX Spray-on Stripper 215
Figure H-4. Theoretical Cumulative Mass of DCM Released for Strypeeze Brush-on Stripper 216
Figure H-5. DCM Concentrations from van Veen et al. (2002) Chamber Study 218
Figure H-6. TWA Concentrations for Ten Paint Removing Products (Reproduced from EC, 2004) 219
Figure H-7. Zone Volumes and Airflow Rates for Workshop Scenarios 229
Figure H-8. Zone Volumes and Airflow Rates for Bathroom Scenario 229
Figure H-9. Modeling Representation of the Bathtub and Virtual Compartment 231
Figure H-10. Air Velocity Distributions from Matthews et al. (1989) 232
Figure H-ll. Example of the Exposure Concentration Calculation as Defined in Equation H-ll 234
Figure H-12. Modeled DCM Concentrations for Scenarios 1 and 4, Stripper Application in Workshop using
Central Parameter Values 237
Figure H-13. Modeled DCM Concentrations for Scenarios 2 and 5, Stripper Application in Workshop using
Parameter Values selected for Upper-end User's Exposure 238
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Figure H-14. Modeled DCM Concentrations for Scenarios 3 and 6, Stripper Application in Workshop using
Parameter Values Selected for Upper-end-User's and Non-user (Bystander)'s Exposure 239
Figure H-15. Modeled DCM Concentrations for Scenario 7, Brush Application in Bathroom (Simulation).... 240
Figure 1-1. Study Quality Considerations for Epidemiological Studies 267
Figure 1-2. Study Quality Considerations for Animal Studies 268
Figure J-l. Process of deriving the DCM's cancer inhalation unit risk 272
Figure K-1. Illustration of the Different AEGL Threshold Levels 277
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AUTHORS/CONTRIBUTORS/ACKNOWLEDGEMENTS/REVIEWERS
This report was developed by the United States Environmental Protection Agency (EPA), Office
of Chemical Safety and Pollution Prevention (OCSPP), Office of Pollution Prevention and Toxics
(OPPT). The work plan risk assessment for methylene chloride (also called dichloromethane or
DCM) was prepared based on existing data and any additional information received during the
public comment period and peer review process. Mention of trade names does not constitute
endorsement by EPA.
EPA Assessment Team
Lead: Iris A. Camacho-Ramos, OPPT/Risk Assessment Division (RAD)
Team Members:
Christopher Brinkerhoff, OPPT/RAD
Judith Brown, OPPT/ Chemistry, Economics and Sustainable Strategies Division (CESSD)
Ernest Falke, OPPT/RAD
Cathy Fehrenbacher, OPPT/RAD
Conrad Flessner, OPPT/RAD (retired)
Amuel Kennedy, OPPT/RAD
Andy Mamantov, OPPT/RAD
Nhan Nguyen, OPPT/RAD
Scott Prothero, OPPT/RAD
Justin Roberts, OPPT/ CESSD
Yvette M. Selby-Mohamadu, OPPT/RAD
Management Lead:
Stanley Barone Jr., OPPT/RAD
Acknowledgements
We acknowledge the contributions of Mary Dominiak (OPPT/Chemical Control Division; retired)
in the development of the draft work plan risk assessment for DCM. In addition, we appreciate
the assistance from Chenise Farquharson (CCD) and members of OPPT's Environmental
Assistance Division (John Schoaff, Ana Coronado and Pamela Buster) for providing updates to
the regulatory history of DCM.
Also, portions of this document were prepared for EPA by Abt Associates, the Eastern Research
Group (ERG), Inc., the Syracuse Research Corporation (SRC) and Versar.
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EPA Internal Peer Reviewers
Office of Chemical Safety and Pollution Prevention
Anjali Lamba, OPPT/RAD
Brad Goodwin, AAAS, OPPT/CCD
Office of Children's Health Protection
Brenda Foos and Lindsay McCormick
Office of Research and Development
PaulSchlosserORD/NCEA
External Peer Review
EPA/OPPT released peer review plan in August of 2012 and draft risk assessment and charge
questions for peer review for public comment in January 2013. EPA/OPPT contracted with The
Scientific Consulting Group, Inc. (SCG) to convene a panel of ad hoc reviewers to conduct an
independent external peer review for the EPA's draft work plan risk assessment for DCM. As an
influential scientific product, the draft risk assessment was peer reviewed in accordance with
EPA's peer review guidance. The peer review panel performed its functions by web conference
and teleconference between September 26 and December 13, 2013. The panel consisted of the
following individuals:
Gary Ginsberg (Chair), Ph.D. Dale Hattis, Ph.D.
Connecticut Department of Public Health George Perkins Marsh Institute,
Clark University
Thomas W. Armstrong, Ph.D.
TWA8HR Occupational Hygiene Consulting, LLC John C. Kissel, Ph.D.
University of Washington
Frank A. Barile, Ph.D.
St. John's University College of Pharmacy Stephen B. Pruett, Ph.D.
and Health Sciences College of Veterinary Medicine,
Mississippi State University
Anneclaire J. De Roos, PhD.
Drexel University School of Public Health
Ronald D. Hood, Ph.D.
Ronald D. Hood and Associates,
Toxicology Consultants
Please visit the EPA/OPPT's Work Plan Chemicals web page for additional information on the
DCM's peer review process
(http://www.epa.gov/oppt/existingchemicals/pubs/riskassess.html), the public docket (Docket:
EPA-HQ-OPPT-2012-0725) for the independent external peer review report and the response to
comments document.
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GLOSSARY OF TERMS AND ABBREVIATIONS
HE
ug/m3
AC
ACGIH
ACH
ADC
AEGL
AEGL-1
AEGL-2
AEGL-3
APF
AT
atm
ATSDR
BAF
BCF
BMD
BMDio
BMDL
BMDLio
BMDS
BMR
BOD
BW
C
°C
CROH
Cal EPA
CASRN
CBI
CDC
CCD
CCRIS
CDR
cm
cm2
cm3
CNS
CO
C02
COHb
Microgram(s)
Microgram(s) per cubic meter
Acute concentration
American Conference of Governmental Industrial Hygienists
Air changes per hour
Average daily concentration
Acute exposure guideline level
Discomfort/non-disabling threshold
Disability threshold
Death threshold
Assigned protection factor
Averaging time
Atmosphere(s)
Agency for Toxic Substances and Disease Registry
Bioaccumulation factor
Bioconcentration factor
Benchmark dose
Benchmark dose at 10% response
Benchmark dose, lower confidence limit(s)
Benchmark dose, lower confidence limit(s) at 10% response
Benchmark Dose Software
Benchmark response
Biochemical oxygen demand
Body weight
Contaminant concentration
Degree Celsius
Concentration in the rest of the house
California Environmental Protection Agency
Chemical abstracts service registry number
Confidential business information
Centers for Disease Control and Prevention
Chemical Control Division
Chemical Carcinogenesis Research Information System
Chemical data report
Centimeter(s)
Square centimeter(s)
Cubic centimeter(s)
Central nervous system
Carbon monoxide
Carbon dioxide
Carboxyhemoglobin
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CPSC
CYP
CYP2E1
DART/ETIC
DCM
DEM
DIY
DNA
DNASSB
DOE
DOSH
E
EO
EC
EC50
ECu+i
ECscenariol
tCscenario 2->4
ECscenario 2->16
ECG
ED
EETD
EF
EFH
EPA
EPCRA
ERG
EU
F
°F
FACE
FDA
ft
ft2
ft3
FTIR
g
g/cm2
g/cm3
GENE-TOX
g/ft2, g/sq ft
g/L
GLP
Consumer Product Safety Commission
Cytochrome P450
Cytochrome P450, family 2, subfamily E, polypeptide 1
Developmental and Reproductive Toxicology/Environmental Teratology
Information Center
Dichloromethane
Department of Environmental Management
Do-it-yourself
Deoxyribonucleic acid
Single stranded DNA-binding protein
U.S. Department of Energy
Division of Occupation Safety and Health
Emission rate
Initial emission rate
European Commission
Effective concentration necessary to produce a 50% response
Exposure concentration over the time interval / to i+1
Exposure concentration for scenario 1
Exposure concentration for scenario 2, 3 or 4
Exposure concentration for scenario 2 through 16
Electrocardiogram
Exposure duration
Economics, Exposure and Technology Division
Exposure frequency
Exposure Factors Handbook
U.S. Environmental Protection Agency
Emergency Planning and Community Right-to-Know Act
Eastern Research Group
European Union
Fraction of time spent in the use zone
Degrees Fahrenheit
Fatality Assessment and Control Evaluation
Food and Drug Administration
Foot/feet
Square foot/feet
Cubic foot/feet
Fourier transform infrared
Gram(s)
Gram(s) per square centimeter
Grams(s) per cubic centimeter
Genetic Toxicology Data Bank
Grams(s) per square foot
Gram(s) per liter
Good Laboratory Practices
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g/minute
g/mol
GC/ECD
GST
GST-T1
GWP
HEC
HEC99
HFC-32
HHE
HQ
HPLC
Ms)
HSDB
HSIA
HVAC
IDLH
IMIS
IPCC
IRIS
IRTA
IUR
IURR
K (upper-case)
k (lower-case)
Koc
Kow
kPa
L
lb(s)
LADC
LBL
LC50
LOAEL
LOEC
m
m2
m3
Macute
Mchronic
m3/hr
MATC
Grams(s) per minute
Gram(s) per mole
Gas chromatography and electron capture detector
Glutathione S-transferase
GST-thetal-1
Global warming potential
Human equivalent concentration
The HEC for which there is 99% likelihood that a randomly selected
individual would have an internal dose less than or equal to the internal
dose of the hazard value
Hydrofluorocarbon-32
Health hazard evaluation
Hazard quotient
High-performance liquid chromatography
Hour(s)
Hazardous Substances Data Bank
Halogenated Solvents Industry Alliance, Inc.
Heating, ventilation, and air conditioning
Immediately dangerous to life and health
Integrated Management Information Systems
Intergovernmental Panel on Climate Change
Integrated Risk Information System
Institute for Research and Technical Assistance
Inhalation unit risk
Inventory Update Reporting Rule
Kelvin
first-order rate constant
Soil organic carbon partition coefficient
Octanohwater partition coefficient
kilopascal(s)
Liter (s)
Pound(s)
Lifetime average daily concentration
Lawrence Berkeley Laboratory
Median lethal concentration
Lowest-observed-adverse-effect level
Lowest-observed-effect concentration
Meter(s)
Square meter(s)
Cubic meter(s)
Scenario-specific acute exposure modifier
Scenario-specific chronic exposure modifier
Cubic meter(s) per hour
Maximum acceptable toxicant concentration
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MCCEM
MCL
mg
mg/L
mg/m3
min
MITI
mM
mm Hg
ml
MMWR
MOE
MR
MRI
MSDS
MSU
NAICS
NAS
NESHAP
NHANES
NIH
NIOSH
NLS
NMP
NOAEL
NRC
NTP
OCSPP
OECD
OEHHA
OEM
OPPT
OSHA
PMN
PBPK
PEL
PFT
POD
ppb
ppm
psi
Q
RAD
RCRA
Multi-Chamber Concentration and Exposure Model
Maximum contaminant level
Milligram(s)
Milligram(s) per liter
Milligram(s) per cubic meter
Minute(s)
Ministry of International Trade and Industry
Millimolar
Millimeters of mercury
Milliliter(s)
Morbidity and Mortality Weekly Report
Margin of exposure
Mass released
Midwest Research Institute
Material safety data sheets
Michigan State University
North American Industry Classification System
National Academies
National Emission Standards for Hazardous Air Pollutants
National Health and Nutrition Examination Survey
National Institutes of Health
National Institute for Occupational Safety and Health
Non-linear least squares
N-Methylpyrrolidone
No-observed-adverse-effect level
National Research Council
National Toxicology Program
Office of Chemical Safety and Pollution Prevention
Organization for Economic Cooperation and Development
Office of Environmental Health Hazard Assessment
Original Equipment Manufacturing
Office of Pollution Prevention and Toxics
Occupational Safety and Health Administration
Premanufacture Notification Program
Physiologically-based pharmacokinetic
Permissible exposure limit
Perfluorocarbon tracer
Point of departure
parts per billion
Parts per million
Pound per square inch
Compartment ventilation rate or air flow rate in and out of the chamber
Risk Assessment Division
Resource Conservation and Recovery Act
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REL
RfC
RIA
ROM
RTECS
SCG
SDWA
SIC
SMAC
SNAP
SRC
STEL
sqft
t
TLV
TOXLINE
TRI
TSCA
TSCATS
TWA
UF
UFA
UFD
UFH
UFL
UFtotal
US or U.S.
UK
V
VOC
wt
WY
yr
Reference exposure level
Reference concentration
Regulatory impact analysis
Rest of the house
Registry of Toxic Effects of Chemical Substances
The Scientific Consulting Group, Inc.
Safe Drinking Water Act
Standard Industry Classification
Spacecraft maximum allowable concentration
Significant New Alternatives Policy
Syracuse Research Corporation
Short-term exposure limit
Square foot (feet)
Time
Threshold limit value
Toxicology Literature Online
Toxics Release Inventory
Toxic Substances Control Act
Toxic Substance Control Act Test Submission Database
Time-weighted average
Uncertainty factor
Interspecies uncertainty factor
Database uncertainty factor
Intraspecies uncertainty factor
LOAEL-to-NOAEL uncertainty factor
Total uncertainty factor
United States
United Kingdom
Volume
Volatile organic compound
Weight
Working years
Year(s)
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EXECUTIVE S U M M AR Y
As a part of the Environmental Protection Agency's (EPA) comprehensive approach to enhance
the Agency's existing chemicals management, in March 2012 EPA identified a work plan of
chemicals for further assessment under the Toxic Substances Control Act (TSCA)1. The Agency is
performing risk assessments on chemicals in the work plan. If an assessment identifies
unacceptable risks to humans or the environment, EPA will pursue risk management.
Methylene chloride (also called dichloromethane or DCM) was assessed as part of the work
plan.
DCM is a volatile organic compound (VOC) that is used as a solvent in a wide range of industrial,
commercial and consumer use applications, such as adhesives, paint stripping, Pharmaceuticals,
metal cleaning, chemical processing, and aerosols. It is the primary ingredient in many paint
stripping products. The 2012 Chemical Data Report (CDR) indicated 261.5 million pounds of
DCM were produced and imported into the U.S. with industry estimated domestic demand in
2010 of 181 million pounds.
EPA/OPPT identified DCM for further evaluation based on its likely carcinogenic properties in
humans, high potential for human exposure as it is widely used in consumer products, and
reported releases to the environment. For instance, DCM has been detected in drinking water,
indoor environments, ambient air, groundwater and soil.
Main Conclusions of this Risk Assessment
This risk assessment identifies cancer risk concerns and short-term and long-term non-cancer
risks for workers and "occupational bystanders" (other workers within the facility who are
indirectly exposed) from the use of DCM-containing paint strippers.
The assessment also identifies short-term non-cancer risks for consumers and residential
bystanders from the use of DCM-containing paint strippers.
The Focus of this Risk Assessment
This assessment characterizes human health risks from inhalation exposures to DCM for the
paint stripping uses. Other uses were considered during problem formulation, but not selected
for further risk analysis. Additional information is provided in the risk assessment regarding the
criteria for inclusion and exclusion of uses and the various assumptions in applying these
criteria.
The main route of exposure for DCM is believed to be inhalation for the paint stripping uses.
EPA/OPPT recognizes that highly volatile compounds such as DCM may also be absorbed
http://www.epa.gov/oppt/existingchemicals/pubs/workplans.html
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through the skin. However, EPA has neither the data nor the methodology to estimate DCM
dermal exposure. Based on the physical-chemical properties of DCM and the scenarios
described in this assessment, EPA/OPPT believes that inhalation is the main exposure pathway
for this risk assessment. The assessment may underestimate total exposures to DCM during
paint stripping due to this assumption.
An assessment of environmental effects is not included in this risk assessment. Based on DCM's
moderate persistence, low bioaccumulation, and low hazard for aquatic toxicity, potential
environmental impacts are judged to be low for the environmental releases associated to the
TSCA uses under the scope of this risk assessment. That judgment should not be misinterpreted
as a determination that DCM water and soil contamination is likely low. In fact, DCM has been
detected in drinking water, groundwater and soil, and EPA is committed to reducing the
presence of DCM in the environment through various regulatory programs (see section 1.1.2.2
for a summary of EPA's regulatory history on DCM).
Human Populations Targeted in This Assessment
EPA/OPPT assessed acute and chronic risks for workers using paint strippers containing DCM.
EPA/OPPT assumes that workers would be adults of both sexes (>16 and older, including
pregnant workers) based upon occupational work permits, although exposures to younger
workers in occupational settings cannot be ruled out. Data sources did not often indicate
whether exposure concentrations were for occupational users or bystanders. Therefore,
EPA/OPPT assumed that occupational exposures were for a combination of users and
bystanders.
EPA/OPPT also examined acute risks for consumer exposures in residential settings. EPA/OPPT
assumes that consumers would be adult individuals (>16 and older; both sexes including
pregnant women) that intermittently use DCM for paint stripping projects, although exposures
to younger users may be possible in residential settings. Bystanders would be individuals of any
age group (e.g., children, adults, the elderly) who are in a nearby area during product
application.
In either occupational or consumer setting, EPA/OPPT assumes that direct contact or close
proximity to the use would likely provide the highest exposures to DCM (i.e., for a consumer or
commercial application with substantial frequency or duration of exposure).
Workplace Exposures for Workers Using DCM-Based Paint Strippers
The estimation of occupational exposures to DCM relied upon published air monitoring data for
industries that use DCM-based paint strippers. These data and different combinations of days
per year of exposure (frequency), years of exposure (working lifetime), and respirator use and
effectiveness (assigned protection factors) were used to develop a variety of hypothetical
occupational scenarios.
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Acute risks were estimated from the 8-hour DCM air concentrations reported in the
occupational monitoring data. Chronic risks were based on non-cancer and cancer inhalation
exposure estimates calculated for various industries, as expressed as average daily
concentration (ADC) or lifetime average daily concentration (LADC), respectively. Table ES-1
summarizes the ranges of DCM exposures estimates for the various occupational scenarios
assessed in the risk assessment. These scenarios were developed to account for variations in
the use of respirators, exposure frequency, and working years for workers handling DCM-based
paint strippers.
Due to a lack of data, ADC and LADC estimates could not be made for the bathtub refinishing
sector. However, this sector is discussed in Appendix G since a number of deaths may be
attributed to use of DCM-based strippers for refinishing bathtubs.
Table ES 1. Ranges of DCM Occupational Exposure Estimates Used in the Risk Assessment
Based on Monitoring Data
Industry
Professional Contractors
Automotive Refinishing
Furniture Refinishing
Art Restoration and
Conservation
Aircraft Paint Stripping
Graffiti Removal
Non-Specific Workplace
Settings - Immersion
Stripping of Wood
Non-Specific Workplace
Settings - Immersion
Stripping of Wood and
Metal
Non-Specific Workplace
Settings - Unknown
Range for acute
8-hr concentration:
Scenario l->4
(mg/m3)
LOW-END
ESTIMATE
1.2
1.8
0.08
0.04
1.7
0.4
0.7
13
5.7
HIGH-END
ESTIMATE
2,980
416
2,245
2
3,802
1,188
7,000
1,017
428
ADC range:
Non-Cancer Effects
Following Chronic
Exposure
Scenarios 1->16
(mg/m3)
LOW-END
ESTIMATE
0.07
0.1
0.005
0.003
0.1
0.02
0.04
0.7
0.3
HIGH-END
ESTIMATE
680
95
513
0.5
868
271
1,598
232
98
LADC range:
Cancer Effects
Following Chronic
Exposure
Scenarios 1->16
(mg/m3)
LOW-END
ESTIMATE
0.04
0.06
0.003
0.002
0.06
0.01
0.02
0.4
0.2
HIGH-END
ESTIMATE
389
54
293
0.3
496
155
913
133
56
Note: Airborne concentration conversion factor for DCM is 3.47 img/m3 per ppm NIOSH (2011b).
Consumer Exposures from DCM-Based Paint Strippers
EPA/OPPT used the Multi-Chamber Concentration and Exposure Model (MCCEM) to estimate
consumer exposures to DCM-based paint strippers. This modeling approach was selected
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because published monitoring data for non-occupational inhalation exposures (i.e., consumer
do-it-yourself [DIY]) were limited to those from several chamber studies conducted in the U.S.
and Europe. The literature search for this assessment did not identify any published exposure
information for exposures to other household members (i.e., bystanders). Of the available
chamber studies, only one U.S. study provided sufficient information for the exposure modeling
(EPA. 1994a).
The model used a two-zone representation of a house to calculate the DCM exposure levels for
consumers and bystanders. The modeling approach integrated assumptions and input
parameters such as the chemical emission rate over time, the volumes of the house and the
room of use, the air exchange rate and interzonal airflow rate. The model also considered
product characteristics, use patterns, and user location during and after the product use.
MCCEM was used to evaluate seven indoor exposure scenarios. The primary distinctions among
the scenarios were type of application (i.e., brush vs. spray), location of product application
(i.e., workshop for six scenarios, bathroom for one scenario), the mass of DCM emitted, the
user's location during the wait period, and the air exchange rate of the rest of the house (ROM)
with outdoor air. A sensitivity analysis indicated that these latter three inputs were the most
sensitive variables in the modeling within application type.
Of the seven scenarios, two are considered central tendency for both the user and bystander,
four had combinations of inputs to estimate upper-end concentrations for the user, and two of
the latter also had input combinations to estimate upper-end concentrations for the bystander.
The seventh scenario simulated the conditions reported in an occupational exposure case
where the worker died due to DCM overexposure while stripping a bathtub (CDC, 2012). The
bathroom scenario was included in the consumer exposure assessment to estimate potential
exposures to bystanders.
Overall, the estimated inhalation exposure levels for the spray-on scenarios are about 2-fold
greater than those reported for the brush-on scenarios. Estimated exposure levels for users of
DCM-based paint strippers are higher than those reported for the bystander in the ROM. The
estimated exposure levels to bystanders in the bathroom scenario is in the same range as the
exposures to bystanders in the workshop scenarios.
Characterization of Hazards and Risks to Human Health
DCM's Carcinogenic Hazards and Risks:
DCM is likely to be carcinogenic in humans based on a mutagenic mode of action (EPA, 2011c).
EPA/OPPT used the inhalation unit risk (IUR) of 4 x 10"5 per ppm (1 x 10~5 per mg/m3) to
estimate excess cancer risks for the occupational scenarios. The IUR is reported in the EPA's
Integrated Risk Information System (IRIS) lexicological Review of Methylene Chloride (EPA,
2011c) and is the estimated upper bound excess lifetime cancer risk resulting from continuous
exposure to an airborne agent at 1 u.g/m3 (EPA, 2011c).
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The IUR for DCM was based on mouse liver and lung tumors reported in a cancer inhalation
bioassay (Mennear et al., 1988; NTP, 1986). There is high confidence in the IUR because it was
based on the best available dose-response data for liver and lung cancer in mice (EPA, 2011c).
Moreover, the mutagenic mode of action was supported by the weight of evidence from
multiple in vivo and in vitro studies (EPA, 2011c).
DCM's Non-Carcinogenic Hazards and Risks:
Acute and chronic exposure to DCM is primarily associated with neurological and hepatic
effects. The primary target organ of DCM toxicity is the brain. Neurological effects result from
either direct narcosis or the formation of carbon monoxide (CO). CO is produced as one of the
metabolic byproducts of DCM metabolism, which reversibly binds to hemoglobin as
carboxyhemoglobin (COHb). Part of the effect of DCM on the central nervous system (CNS)
comes from the accumulation of carboxyhemoglobin (COHb) in the blood, especially during
acute/short-term exposures to DCM.
Non-cancer risks associated with acute exposures to DCM (i.e., neurological effects) were
evaluated for workers, consumers and residential bystanders using the dose-response
information supporting the derivations of the Spacecraft Maximum Allowable Concentrations
(SMACsHNRC. 1996). the California acute reference exposure level (REL) (OEHHA. 2008). and the
Acute Exposure Guideline Levels (AEGLs)(NAC, 2008).
EPA/OPPT preferred the SMAC hazard value [or point of departure (POD)] over the California
acute REL POD as the health protective acute hazard value used to estimate acute risks for the
consumer scenarios. The SMAC POD was based on multiple human observations reporting
increased COHb levels after DCM exposure, coupled with the knowledge of what would be
considered a no-observable-adverse effect level (NOAEL) based on the extensive CO database
(NRC, 1996). However, the California acute REL POD was used to estimate risks for occupational
scenarios since an 8-hr SMAC POD was not available for the risk calculations. Although AEGLs
are intended for emergency response activities, the AEGL PODs were used in this assessment to
evaluate acute risks for discomfort/non-disabling (AEGL-1) and incapacitating (AEGL-2) effects
following DCM inhalation exposure.
Non-cancer risks for workers repeatedly exposed to DCM were evaluated using the hazard
value of 17.2 mg/m3 (4.8 ppm) for liver effects (EPA, 2011c). The value was derived in the DCM
IRIS assessment by PBPK modeling and expressed as the 1st percentile of the distribution of
human equivalent concentrations (HEC) i.e. the HECgg the concentration at which there is 99%
likelihood an individual would have an internal dose less than or equal to the internal dose of
hazard was used to protect toxicokinetically sensitive individuals. There is high confidence in
the non-cancer hazard value because it was derived from a well-conducted, peer-reviewed
animal inhalation study (Nitschke et al., 1988a). Further, the inhalation database contains
several studies consistently identifying the liver as the most sensitive non-cancer target organ
in rats (EPA. 2011c).
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Uncertainties of this Risk Assessment
The worker risk assessment has a number of uncertainties. While it is clear that the air
monitoring data represent real world exposure levels, EPA/OPPT cannot determine whether
these concentrations are representative of actual statistical distributions for exposed workers.
Further, EPA/OPPT cannot determine how accurately the hypothetical exposure scenarios
reflect occupational exposures based on variations in the use of respiratory protective
equipment, effectiveness of a used respirator in providing the protection indicated by its APF,
and actual exposure frequencies and working years. The estimates of numbers of workers
exposed to DCM-based strippers are uncertain due primarily to the assumed numbers of
workers per model plant in the estimation approach.
The consumer exposure assessment is composed of modeled exposure scenarios for which the
inputs are based on experimental data, survey information, and a number of assumptions with
varying degrees of uncertainty. The results are characterized as either plausible estimates of
individual exposure (e.g., central tendency), or possibly greater than the distribution of actual
exposures (e.g., bounding).
The extent of the identified uncertainties for estimating occupational or residential exposures is
not known. Consequently, under real world conditions, exposure could occur to either higher or
lower levels of DCM than those estimated, leading to a potential for under- or over-estimation
of actual risks.
There is general high confidence in the hazard database supporting the hazard values used to
estimate acute and chronic risks for various health effects associated with DCM inhalation
exposure (i.e., neurotoxicity, liver toxicity, and liver and lung cancer). However, there are
uncertainties about potential human health concerns for developmental neurotoxicity and
immunological effects following exposure to DCM.
The Results of this Risk Assessment
Size of the Exposed Population:
• Over 230,000 workers nationwide are directly exposed to DCM from DCM-based strippers.
This estimate only accounts for workers performing the paint stripping using DCM and does
not include other workers ("occupational bystanders") within the facility who are indirectly
exposed.
• No data were available to estimate the number of consumers and residential bystanders
exposed to DCM during the use of paint strippers.
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Cancer Risks Associated With Chronic Exposures to DCM:
• There are cancer risk concerns for workers and occupational bystanders exposed to DCM
that are employed at various industries handling DCM-contain ing paint strippers.
• Many of the occupational scenarios exceed at least one of the target cancer risks of 10~4,
10-5andlO-6.
• The greatest cancer risks occur for workers handling DCM-based paint strippers with no
respiratory protection for an extended period of time.
Non-Cancer Risks Associated With Chronic Exposures to DCM:
• There are non-cancer risks for liver effects for most workers (including bystanders) using
DCM-based paint strippers in relevant industries, with the exception of the art renovation
and conservation industry.
• Non-cancer risks occur for most workers (including bystanders) handling DCM-based paint
strippers with or without respiratory protection for various exposure scenarios that
predominantly reflect variations in exposure conditions (i.e., exposure frequency and
working years) in facilities reporting central tendency or high-end DCM air levels. Among all
of the occupational scenarios, the greatest risk concern is for workers engaging in long-term
use of the product (i.e., 250 days/year for 40 years) with no respiratory protection.
• Non-cancer risks are not reported when workers reduce their exposure to DCM-based
strippers by taking all three of the following actions; wearing respiratory protection (i.e.,
respirator with at least an assigned protection factor of 50), limiting exposure to central
tendency exposure conditions (i.e., 125 days/year for 20 years) and working in facilities with
low-end DCM air concentrations.
Non-Cancer Risks Associated With Acute Exposures to DCM:
• There are acute risks for neurological effects for most workers using DCM-based paint
strippers. These risks are present in the presence or absence of respiratory protection.
• There are concerns for incapacitating effects in workers handing DCM-containing paint
strippers on an acute/short-term basis with no respiratory protection. These concerns are
also present for workers wearing different types of respirators while performing paint
stripping in industries with high exposure to DCM.
• There are acute risks for neurological effects for consumers of DCM-based paint strippers at
residential settings. Also, bystanders are at risk while staying in the residence when paint
strippers are being applied.
• There are concerns for discomfort/non-disabling and incapacitating effects for consumers
exposed to DCM while applying the product or staying in the residence after completion of
the stripping task. These concerns are also present for residential bystanders in some
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scenarios when exposure conditions are at the highest in the rest of the house after
completing the paint stripping task.
• Application of DCM-based paint strippers in a bathroom generates unsafe exposure
conditions for the user of the product, but not residential bystanders. DCM concentrations
may reach levels associated with non-disabling and incapacitating effects for the user
applying the product. User relocation to the rest of the house after completing the paint
stripping task may also produce non-disabling and incapacitating effects as DCM's internal
dose builds up in the body over time.
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1 BACKGROUND AND SCOPE
1.1 INfTRODUCTION
As a part of EPA's comprehensive approach to enhance the Agency's existing chemicals
management, in March 2012 EPA identified a work plan of chemicals for further assessment
under the Toxic Substances Control Act (TSCA)2. The Agency is performing risk assessments on
chemicals in the work plan. If an assessment identifies unacceptable risks to humans or the
environment, EPA will pursue risk management. After gathering input from stakeholders, EPA
developed criteria used for identifying chemicals for further assessment3. The criteria focused
on chemicals that meet one or more of the following factors: (1) potentially of concern to
children's health (for example, because of reproductive or developmental effects); (2)
neurotoxic effects; (3) persistent, bioaccumulative, and toxic (PBT); (3) probable or known
carcinogens; (4) used in children's products; or (5) detected in biomonitoring programs. Using
this methodology, EPA identified a TSCA Work Plan of chemicals as candidates for risk
assessment in the next several years. In the prioritization process, DCM was identified for
assessment based on human health hazards and high exposure potential.
The target audience for this risk assessment is primarily EPA risk managers; however, it may
also be of interest to the broader risk assessment community as well as U.S. stakeholders that
are interested in issues related to DCM, especially when used as a paint stripper. The
information presented in the risk assessment may be of assistance to other Federal, State and
Local agencies as well as to members of the general public who are interested in the chemical
risks of DCM. The risk assessment may also help those interested in reducing risks associated
with the use of DCM-based paint strippers.
The initial step in EPA's risk assessment development process includes scoping and problem
formulation and is distinct from the initial prioritization exercise. During these steps EPA
reviews currently available data and information, including but not limited to, assessments
conducted by others (e.g., authorities in other countries), published or readily available reports,
and published scientific literature. During scoping and problem formulation the more robust
review of the factors influencing initial prioritization may result in refinement - either
addition/expansion or removal/contraction - of specific hazard or exposure concerns previously
identified in the prioritization methodology.
2 http://www.epa.gov/oppt/existingchemicals/pubs/workplans.html
3 http://www.epa.gov/oppt/existingchemicals/pubs/wpmethods.pdf
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1.2 BACKGROUND
1.2.1 Rationale for Selecting DCM for Risk Assessment
DCM was identified for assessment based on high human health hazards and exposure
potential. The high human health hazard ranking was assigned for potential cancer risks (i.e.,
likely human carcinogen) and acute4 and chronic5 non-cancer effects. DCM is a liquid VOC and
its high vapor pressure leads to rapid evaporation, which may pose an inhalation hazard for
humans. The high exposure potential ranking was assigned because DCM is widely used with
industrial, commercial and consumer user applications and at a relatively high percent content
particularly in paint stripping products. DCM is ubiquitously present in the environment with
levels detected in drinking water, indoor environments, ambient air, groundwater, and soil
(EPA. 2012d).
1.2.2 Overview of DCM Uses and Production Volume
DCM is mainly used as a solvent with a wide range of industrial, commercial, and consumer
uses, which include: solvent for vapor degreasing; paint/varnish removers; electronics; resin
cleaners; adhesives; tablet coatings; process solvent for cellulose acetate; butyl rubber;
cleaning solvent; plastics processing; blowing agent in polyurethane foams; propellant for paint
aerosols; refrigerant; heat-transfer fluid; extraction solvent for industrial applications and food;
color diluents for foods; and food packaging adhesives (Ash and Ash, 2009). DCM is the primary
ingredient in many paint stripping products (Mannsville, 1999).
U.S. demand for DCM in 2006 was estimated at 185 million pounds (Ibs) with a projected
demand of 181 million Ibs for 2010 (HSIA, 2008; ICIS, 2007). The 2012 non-confidential business
information (CBI) Chemical Data Reporting (CDR) indicated 261.5 million Ibs of DCM that were
produced and imported into the U.S. (EPA, 2013). More information on production volumes can
be found in Section 2.2.
1.2.3 Overview of Assessments of DCM's Human Health Hazards
Several organizations have developed high quality, peer-reviewed hazard/dose-response
assessments documenting the adverse health effects of DCM. These reports indicate that DCM
is likely to be carcinogenic to humans and is a liver and neurological toxicant. EPA/OPPT used
the human health toxicity information from these reports rather than developing a new
hazard/dose-response analysis for DCM.
4 Acute exposure is defined as exposure by the oral, dermal, or inhalation route for 24 hours or less (EPA, 2011b).
5 Chronic exposure is defined as repeated exposure by the oral, dermal, or inhalation route for more than
approximately 10% of the life span in humans and more than approximately 90 days to 2 years in typically used
laboratory animal species) (EPA, 2011b).
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For the evaluation of cancer and non-cancer risks following repeated exposure to DCM (i.e.,
occupational scenarios), EPA/OPPT relied on the cancer and non-cancer dose-response
information reported in the lexicological Review of Methylene Chloride recently published by
EPA's Integrated Risk Information System (IRIS) (EPA. 2011c).
Non-cancer risks associated with acute residential exposures to DCM were assessed using the
dose-response information supporting the derivations of the Spacecraft Maximum Allowable
Concentrations (SMACs) (NRC, 1996) and the Acute Exposure Guideline Levels (AEGLs)(NAC,
2008). The assessment also evaluated acute occupational risks with the California acute
reference exposure level (REL) and AEGL hazard values (OEHHA, 2008). The California acute
REL, but not the SMAC hazard value, was used to estimate acute occupational risks since an
8-hr SMAC hazard value was not available for the risk calculations.
Refer to Chapter 3 for more information about the hazard/dose-response approach for cancer
and non-cancer health endpoints, specifically sections 3.3.1.2 and 3.3.1.3.
1.2.4 Overview EPA's Regulatory History of DCM
DCM has been the subject of various EPA regulatory actions. EPA lists DCM as a toxic (i.e., non-
acute) hazardous waste under the Resource Conservation and Recovery Act (RCRA) (Code
U080) (EPA, 2012c). DCM is also listed on the Toxics Release Inventory (TRI) pursuant to section
313 of the Emergency Planning and Community Right-to-Know Act (EPCRA) (EPA, 2014).
Moreover, DCM is listed on the TSCA Inventory of Chemical Substances and is subject to
reporting under the TSCA CDR rule (EPA, 2011e).
EPA's Office of Air Quality Planning and Standards issued a final rule in January 2008, under the
National Emission Standards for Hazardous Air Pollutants (NESHAP) that established national
emission standards for using DCM to remove dried paint (i.e., including, but not limited to:
paint, enamel, varnish, shellac, and lacquer) from wood, metal, plastic, and other substrates
(EPA, 2008). The NESHAP also implemented management practices that minimize DCM
emissions.
Additionally, the Safe Drinking Water Act (SDWA) requires EPA to determine the level of
contaminants in drinking water at which no adverse health effects are likely to occur. EPA has
set an enforceable maximum contaminant level (MCL) for DCM at 0.005 mg/L or 5 ppb (EPA,
2010b).
Please refer to Appendix A for more information about the U.S. regulatory history of DCM,
including actions in other U.S. federal agencies and States. Appendix A also provides a brief
description of actions in Canada and Europe.
Page 29 of 279
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1.3 SCOPE OF THE ASSESSMENT
1.3.1 Selection of DCM Uses
EPA/OPPT focused the assessment on the use of DCM in paint stripping. Uses other than paint
stripping are not covered in the risk assessment because EPA/OPPT decided to focus on the use
of DCM with the highest potential exposures to both consumers and workers. Table 1-1 lists the
primary uses of DCM, indicates whether a use was considered for inclusion in this assessment,
and also presents the rationale for why a use was included or excluded from further
consideration.
Narrowing of the scope required exclusion of some uses based on comparative judgments
relative to paint stripping. These comparative judgments considered potential exposure among
the primary uses identified (e.g., percent content relative to potential exposure). In addition,
EPA/OPPT has a special interest in small shops and consumer use for this assessment due to the
possibility that these shops and consumers may have fewer resources or less expertise and
awareness of hazards, exposures, or controls as compared to large shops.
1.3.2 Selection of Exposure Pathway
This risk assessment assumed that DCM is primarily absorbed through the respiratory tract
because of DCM's high vapor pressure. EPA/OPPT recognizes that highly volatile compounds
such as DCM may also be absorbed through the skin. However, EPA has neither the data nor
the methodology to assess DCM dermal exposure. Based on the physical-chemical properties of
DCM and the scenarios described in this assessment, EPA/OPPT focuses on inhalation as the
main exposure pathway for this risk assessment. This assessment may underestimate total
exposures of DCM in paint stripping due to this assumption.
1.3.3 Identification of Human Populations Exposed During the Use of
DCM-Based Paint Strippers
EPA/OPPT's assessment evaluated the quantitative acute and chronic risk(s) for workers using
DCM-based paint strippers. EPA/OPPT has a special interest in exposures to workers employed
by "small commercial shops." The shop sizes can vary in most industries that do paint stripping,
and this issue is discussed in section 3.1.1.1.
Occupational exposures include possible direct exposures to workers who may use these
products at work, in training, or other situations. Data sources did not often indicate whether
exposure concentrations were for occupational users or bystanders. Therefore, EPA/OPPT
assumed that occupational exposures were for a combination of users and bystanders.
We also assumed that workers would be adults of both sexes [>16 years (yrs) and older],
although exposures to younger individuals may be possible in occupational settings.
Page 30 of 279
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Table 1 1. Primary Uses of DCM and Selection Criteria
Use Category
Adhesives
Paint stripping
Pharmaceuticals
Metal cleaning
Chemical
processing
Aerosols
(propellant use)
Polyurethane
foam
Percent
DCM
Content
60-100
25-100
N/Ab
15-40
N/Ab
<25
N/Ab
Population
Exposed a
Small commercial
shop workers,
consumers [including
do-it-yourself (DlYs)];
industrial workers
Small commercial
shop workers,
consumers (including
"DlYs"); industrial
workers
Industrial workers
Small commercial
shop workers,
consumers (including
"DlYs"); industrial
workers
Industrial workers
Small commercial
shop workers,
consumers (including
"DlYs"); industrial
workers
Industrial workers
Considered in this Assessment?
No - Relatively narrower range of removal
applications and likely lower exposure levels
compared to paint stripping. Information
indicates that many of the adhesive uses are
in adhesive removers.
Yes - Relatively high percent content range,
broad range of stripping and removal
applications (automotive, furniture, marine,
wall paint, similar coating removal).
No - Industrial use settings which are
generally believed to be better controlled and
monitored.
No - Small market percentage (7 percent) and
likely lower exposure levels compared to paint
stripping.
No - Industrial use settings which are
generally believed to be better controlled and
monitored.
No - Relatively low percent content range,
small market percentage (5 percent), and
likely lower exposure levels compared to paint
stripping.
No - Industrial use settings which are
generally believed to be better controlled and
monitored.
Notes:
a For the purposes of this assessment, consumers are defined as non-commercial/non-industrial users of
products containing DCM. Commercial workers are defined as persons employed in a commercial enterprise
providing salable goods or services. Examples of a commercial enterprise include, but are not limited to,
commercial and residential cleaning services, painting companies, carpet installers, commercial and
residential repair and refurbishing companies, and automotive painting and repair shops.
b For these industrial applications, the percent of DCM content is expected to be at or near 100 percent.
Page 31 of 279
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This assessment also examined consumer exposures to DCM-based paint strippers in residential
settings. Consumers were adult individuals of both sexes (i.e., >16 yrs and older, including
pregnant women) using DCM in their homes for paint stripping projects. It is possible that
younger users (i.e., <16 yrs) would be using the product in residential settings, but this
assessment did not look at this age group. EPA/OPPT also evaluated exposures to bystanders,
who are individuals of any age (e.g., children, adults, the elderly) that did not use the product,
but were indirectly exposed in the home while being nearby during product use.
EPA/OPPT used the DCM air concentrations from the occupational exposure assessment to
evaluate the acute and chronic human health risks associated with the use of DCM-based paint
strippers. For consumer exposures, EPA/OPPT only evaluated the human health risks to acute
exposures to DCM. The focus on acute exposures was based on the assumption that DCM is not
expected to significantly build up in the body between exposure events. DCM's plasma half-life
is estimated to be 40 minutes after inhalation exposure (DiVincenzo et al., 1972). Moreover,
EPA/OPPT assumed that consumers would not generally strip paint on a regular basis in their
residences allowing sufficient time between exposures to clear DCM and its metabolites from
the body.
1.3.4 Why Environmental Risks Were Not Evaluated For DCM-Based
PaintStrippers
EPA/OPPT did not assess the risks of environmental effects related to the use of DCM in paint
stripping products. This decision is supported by DCM's environmental fate and aquatic toxicity
data (Section 2.3).
Due to its volatility, DCM does not significantly partition to solid phases. Therefore, releases of
DCM to the environment are likely to evaporate to the atmosphere, or if released to soil,
migrate to groundwater. This substance has been shown to biodegrade over a range of rates
and environmental conditions and is considered to be moderately persistent in the
environment. Measured bioconcentration factors for DCM suggest its bioconcentration
potential is low.
The aquatic toxicity of DCM for fish, aquatic invertebrates, and aquatic plants is low based on
the OPPT criteria described in the TSCA Work Plan Chemicals Methods Document (EPA, 2012d)
and the Classification Criteria for Environmental Toxicity and Fate of Industrial Chemicals (EPA,
1992a). For these reasons, this assessment focused on human receptors rather than ecological
receptors.
Appendix B contains a summary of the aquatic toxicity studies considered in the evaluation of
environmental hazards of DCM.
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2 SOURCES AND FATE
Chapter 2 discusses the physical and chemical properties of DCM, sources related to its
production and uses, and its fate in the environment. The contents of this chapter supported
EPA/OPPT's decision to not evaluate environmental risks in this assessment.
2.1 PHYSICAL AND CHEMICAL PROPERTIES
The chemical structure for DCM is shown in Figure 2-1.
Figure 2 1. Chemical Structure of Methylene Chloride
H
...»CI
Cl
DCM is a volatile (vapor pressure = 351.8 mmHg at 25°C), colorless liquid with a chloroform-like,
sweet odor (OSHA, 2012b). DCM has a low boiling point (39.7°C ) and is moderately water
soluble (13.7 g/L at 20°C), but more dense than water (1.33 g/cm3 at 20°C). DCM is used as a
substitute for other solvents because it is non-flammable and non-explosive. DCM also is not
readily oxidizable (ECB, 2000; Lide, 2001; O'Neil, 2001). Table 2-1 shows the common physical-
chemical properties of DCM.
Table 2 1. Physical Chemical Properties of DCM a
Molecular formula
Molecular weight
Physical form
Melting point
Boiling point
Vapor pressure
Log Kow
Water solubility
Density
Flash point
CH2CI2
84.93
Colorless liquid; sweet, pleasant odor
resembling chloroform
-95°C
39.7°C
351.8 mmHg at 25°C
5.3 ("slow stirring" method); 5.9 at 25
°C (measured; OECD 117b)
13.7g/Lat20°C
1.33 g/cm3 at 20°C
none
Notes:
a Information obtained from (ECB, 2000)
b OECDTest Number 117: Partition Coefficient (n-octanol/water), High Performance Liquid Chromatography
(HPLC) Method
Page 33 of 279
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2.2 DCM PRODUCTION AND USES
DCM is mainly used as a solvent, at concentrations ranging from 20 to 100 percent, and is the
primary ingredient in many paint stripping products (Mannsville, 1999). It is a quick acting and
inexpensive solvent with a wide range of industrial, commercial, and consumer uses, which
include: solvent for vapor degreasing; paint/varnish removers; electronics; resin cleaners;
adhesives; tablet coatings; process solvent for cellulose acetate; butyl rubber; cleaning solvent;
plastics processing; blowing agent in polyurethane foams; propellant for paint aerosols;
refrigerant; heat-transfer fluid; extraction solvent for industrial applications and food; color
diluents for foods; and food packaging adhesives (Ash and Ash, 2009).
DCM also has several minor uses, especially as an extraction solvent for spice oleoresins and
hops, and for the removal of caffeine from coffee. It is approved as an extraction solvent for
these uses by the FDA, although most decaffeinators no longer use DCM due to concerns over
residuals.
2,^^
Use of DCM as a solvent in a number of sectors has been declining steadily since the mid-1980s
due to increasing government regulation (i.e., both federal and state), and environmental,
consumer, and worker exposure concerns (EPA, 1994d, 2006c, 2011c; ICIS, 2007). These
regulations include:
• a lower 8-hr time-weighted average (TWA) OSHA PEL of 25 ppm took effect in 1997;
• warning labeling requirements required by CPSC on all products containing more than
1 percent of DCM took effect in 1988 (CPSC. 1987):
• listing of DCM as a potential carcinogen by the National Institute of Occupational Safety and
Health (NIOSH);
• new OSHA standards requiring facilities using DCM to use vapor control equipment by 2000
(ICIS. 2007).
U.S. consumption of DCM declined from a high of approximately 540 million Ibs in the mid-
1980s to approximately 181 million Ibs currently (ICIS, 2007). In 1984, there were four domestic
producers of DCM selling around 501 million Ibs. In 2000, there were three domestic
manufacturers with five DCM plants in the U.S. (Cal EPA, 2000). Currently, there are only two
manufacturers in the U.S. with a total of three production plants in operation (EPA, 2013).
These companies are the Dow Chemical Company (one facility) and Occidental Chemical
Corporation (i.e., two facilities) (EPA, 2013).
U.S. demand for DCM in 2006 was estimated at 185 million Ibs by industry sources with a
projected demand of 181 million Ibs for 2010 (HSIA. 2008: ICIS. 2007). The 2012 non-
confidential business information (CBI) CDR indicated 261.5 million Ibs of DCM that were
produced and imported into the U.S. (EPA, 2013). DCM imports were estimated at 20 million Ibs
in 2006 (ICIS, 2007). Thus, the production volume of DCM makes up 80 to 96 percent of the
Page 34 of 279
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market share depending on the high or low estimates of total production and imports. In terms
of environmental releases, 292 facilities reported a total of 4.8 million Ibs of on- and off-site
disposal or other releases of DCM based on the EPA's 2010 TRI (EPA. 2011d).
Table 2-2 presents DCM market trends by use. Based on current estimations, use of DCM is
expected to increase in only one category, DCM as feedstock in the production of a refrigerant,
hydrofluorcarbon-32 (HFC-32) (Mannsville. 1999).
Table 2 2. DCM Market Trends by Use
DCM Use
Use Trend
Background
Paint stripper
Decreasing
OSHA's 1997 reduced PEL resulted in new equipment costs
(especially for small shops), which led to a reduction of DCM
use as a paint strippera
CPSC warning labels on consumer DIY products has also
resulted in less furniture refinishing use b
The aircraft industry has replaced DCM paint stripping on
commercial and military planes with non-chemical stripping
processes because new technology in chemical processing
has resulted in less of a need for DCM c
Use of substitutes like high-boiling ketones, glycol ethers, and
N-methylpyrrolidone (NMP) has been increasing d
Metal cleaner and
degreaser
Decreasing
Lower OSHA PEL resulted in reduced DCM use a
Aerosol products
Decreasing
• CPSC labeling requirements have led most aerosol
manufacturers to eliminate DCM use, but it is still somewhat
usedb
Foam adhesives
Decreasing
EPA's 2007 Flexible Polyurethane Foam Production and
Fabrication National Emission Standards for Hazardous Air
Pollutants (NESHAP) required a reduction in use of DCM e
Lower OSHA PEL has steered many foam manufacturers into
using non-DCM adhesives due to the cost of compliance with
the PEL3
Feedstock in
production of
refrigerant HFC-32
Increasing
Expected to grow because HFC-32 is an EPA Significant New
Alternatives Policy (SNAP) replacement chemical for HFC-226
Fluorocarbon production accounts for less than 10 percent of
DCM use f
Sources:
3 OSHA (2010)
b CPSC (1992)
c Paul! (1996)
d Mannsville (1999)
eHSIA(2010)
f ICIS (2007)
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Table 2-3 presents the major and minor uses of DCM, as well as the potential benefits of using
DCM in different industries.
Table 2 3. Major and Minor Uses of DCM
Major Uses3
• Paint removal
• Formulated products
• Adhesives
• Aerosol propellant
• Metal cleaner and degreaser
• Chemical processor for
polycarbonate resins and
cellulose triacetate
(photographic film)
• Flexible polyurethane foam
manufacturing
• Feedstock in the production of
the refrigerant,
hydrofluorocarbon-32 (HFC-32)
Minor Uses3
• Extraction solvent
for oils, waxes, fats,
spices, and hops
• Tablet coating for
Pharmaceuticals
Overall Benefits
• Low flammabilityb
• Non-corrosive to many
substrates'3
• Strong solvency properties'3
• No flash point under normal use
conditions and can be used to
reduce the flammability of other
substances0
• Lower costs
Sources: a Dow (1999); EPA (2013); HSIA (2008); IAQUK (2014)
b Mannsville (1999)
c HSIA (2010)
As recently as the 1980s, approximately 50 percent of the total DCM market was made up of
paint stripping products (Mannsville, 1999). Industry sources stated 40 percent of the domestic
DCM market was made up of paint strippers in 2006 (HSIA, 2008). However, the most recent
industry figures indicate paint stripping products now only make up 25 percent of the domestic
market for DCM (Table 2-4) (ICIS, 2007). These figures coupled with an overall decline in the
demand for DCM suggest manufacturers may be substituting other solvents for DCM in their
paint stripping products. Because the data are recent, EPA/OPPT cannot determine at this point
if this is a real trend.
The estimates for DCM by use are shown in Table 2-4. The percentages of DCM use by
application type are based on production volume for use in domestic products. While DCM use
in adhesives is a larger market share than paint stripping, the narrower range of removal
applications and likely lower exposure levels compared to paint stripping resulted in adhesive
use not being selected as a focal point for this assessment.
Page 36 of 279
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Table 2 4. Major Uses of DCM in the U.S.
Major Uses
Adhesives
Paint stripping
Pharmaceuticals
Metal cleaning
Chemical processing
Aerosols
Polyurethanefoam blowing
Miscellaneous
Percent of DCM Consumed in End Products
37
25
10
7
7
5
5
4
Sources: Ash and Ash (2009); EPA (2013); HSIA (2010); ICIS (2007)
2.2.1.1 Consumer Uses
DCM has a number of TSCA consumer uses. Table 2-5 presents the major consumer uses of
DCM.
Table 2 5. TSCA Consumer Uses of DCM
Consumer Uses
Paint strippers
Aerosol applications
Cleaners/protectors
Adhesives
Miscellaneous
Sources: a NIH (2005)
• Paint thinners3
• Paint removers and strippersb
• Aerosol paintsc
• Automotive products0
• Spray shoe polish3
• Water repellant/protectors3
• Spot removers3
• Wood floor and panel cleaners3
• Specialized electronic cleaners
(for TV, VCR, razor, etc.)3
• Contact cement3
• Super glues3
• Spray adhesives3
• Silicone lubricants
(excluding automotive)3
• Outdoor water repellants3
• Varnish removersb
• Graffiti removersb
• Rust removers3
• Primers3
• Wood stains3
• Transmission cleaners3
• Battery terminal protector3
• Brake quieter/cleaner3
• Gasket removers3
• Adhesive removers (general
purpose, tile and wallpaper)3
• Gasket removers3
b DHHS(2012)
c Mannsville(1999)
The 2012 CDR data indicated that DCM is used in the following commercial/consumer use
categories: paints and coatings, adhesives and sealants, and "other" (EPA, 2013)(Appendix C).
The National Institutes of Health (NIH) Household Products Database currently lists 50 products
containing DCM, in concentrations ranging from one to 100 percent. The products are divided
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almost evenly between aerosol and liquid formulations (with one in granular form)(DHHS,
2012).
DCM uses addressed by other agencies (i.e., non-TSCA uses) have changed over time. For
instance, the FDA banned DCM as an ingredient from all cosmetic products in 1989 (FDA, 1989)
after it was used as an ingredient in aerosol cosmetic products (e.g., hairsprays) in
concentrations ranging from 10 to 25 percent DCM.
2.2.1.2 Paint Stripping Applications
DCM is considered the best chemical stripper that is effective on the widest range of cured
coatings from the widest variety of substrates (Mannsville, 1999). It is characterized this way
because it can be used on almost any substrate, is very inexpensive, works quickly, and typically
only requires one application to remove all the necessary paint or coating. The major
applications for DCM-based paint strippers include use on Original Equipment Manufacturing
(OEM), field maintenance stripping, and home improvement and repair. Most of these users
purchase paint stripper from a formulator who mixes the DCM with other chemicals to achieve
the desired product (SRRP, 1992). For industrial use, paint strippers are typically 70 to 90
percent DCM by weight. Household paint strippers for consumer use are typically 60 to 80
percent DCM (EPA, 1993b; see Appendix D).
Several studies have been conducted to evaluate the extent of DCM use in paint stripping. In
2008, EPA estimated that a total of 39,000 establishments performed surface coating
operations, including paint stripping, motor vehicle, mobile equipment, and miscellaneous
activities. Specifically, EPA estimated that about 3,000 of these facilities were paint stripping
shops. Of these 3,000 facilities, 2,000 facilities used paint strippers containing < 2,000 Ibs of
DCM, while 1,000 facilities used products containing > 2,000 Ibs of the chemical (EPA, 2008).
^-S^SUMMARY^OF^
Knowledge of the environmental fate (transport and transformation) of a compound is
important to understanding its potential impact on specific environmental media (e.g., water,
sediment, soil) and exposures to target organisms of concern.
DCM is volatile and does not significantly partition to solid phases. Therefore, releases of DCM
to the environment are likely to evaporate to the atmosphere, or if released to soil, migrate to
groundwater. DCM has a global warming potential (GWP) of 8.7 relative to carbon dioxide and
thus can act as a greenhouse gas.
DCM has been shown to biodegrade over a range of rates and conditions and is considered to
be moderately persistent in the environment. Measured bioconcentration factors for DCM
suggest its bioconcentration potential is low. Appendix E has additional information about the
environmental fate of DCM.
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3 HUMAN HEALTH RISK ASSESSMENT
3.1 OCCUPATIONAL EXPOSURE ASSESSMENT FOR THE USE OF DCM
IN PAINT STRIPPING
Section 3.1.1 summarizes the approach and methodology used for estimating occupational
inhalation exposures to DCM for the use of DCM-based paint strippers. Section 3.1.1.3 lists the
occupational exposure estimates for the highest exposed worker population. Additional
information is found in Appendices F and G.
Appendix F describes the industries that may use DCM-based paint strippers, worker activities,
processes, numbers of sites, and numbers of exposed workers. Appendix G provides details
about the air concentrations and associated worker Average Daily Concentrations (ADCs) and
Lifetime Average Daily Concentrations (LADCs) presented in this section.
3.1.1 Approach and Methodology for Estimating Occupational Exposures
3.1.1.1 Identification of Relevant Industries
Because a variety of industries include paint stripping among their business activities,
EPA/OPPT made the effort to determine and characterize these industries, with a special
interest in small commercial shops. EPA/OPPT's interest in small shops for this assessment is
due to the possibility that these shops may have fewer resources or less expertise and
awareness of hazards, exposures, or controls as compared to large shops.
There is no standard or universal definition for the term "small shop". The various meanings of
this term can depend upon the industry sector (e.g., metal finishing, furniture repair, foam
production, chemical manufacturing) or governmental jurisdiction (e.g. OSHA, EPA, other
countries). For the purpose of risk assessment of work plan chemicals, EPA/OPPT generally
refers to entities, businesses, operators, plants, sites, facilities, or shops interchangeably and
considers a number of factors to categorize these as small. The factors that have been usually
considered include revenue, capacity, throughput, production, use rate of materials, or number
of employees. Further characterization to determine which factors best distinguish small shops
for all the various industries that perform paint stripping would require more research.
EPA/OPPT reviewed the published literature and evaluated the 2007 North American Industry
Classification System (NAICS) codes to determine industries that likely include paint stripping
activities (see Appendix F, Table F-l).
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The following industries were identified:
• Professional contractors;
• Bathtub refinishing;
• Automotive refinishing;
• Furniture refinishing;
• Art restoration and conservation;
• Aircraft paint stripping;
• Ship paint stripping; and
• Graffiti removal
By identifying these industries, EPA/OPPT identified corresponding worker subpopulations that
may be exposed to DCM due to the use of these paint strippers. Appendix F details the
industries identified, processes and worker activities that may contribute to workplace
exposures. Section 3.1.1.2 and Appendix F provide the estimated number of workers exposed
nationwide and average numbers of employees per facility for these industries.
3.1.1.2 Estimation of Potential Workplace Exposures for Paint Stripping Facilities
Workplace exposures based on monitoring data: EPA/OPPT used air concentration data and
estimates found in literature sources to serve as exposure concentrations for occupational
inhalation exposures to DCM. These air concentrations were used to estimate the exposure
levels for workers exposed to DCM as a result of the use of DCM-based paint strippers.
EPA/OPPT did not find enough monitoring data to determine complete statistical distributions
of actual exposure concentrations for the exposed population of workers in each of the
industries. Ideally, EPA/OPPT would like to know 50th and 95th percentiles for each population,
which are considered to be the most important parts of complete statistical exposure
distributions. The air concentration means and midpoints (means are preferred over midpoints)
served as substitutes for 50th percentiles, and high ends of ranges served as substitutes for 95th
percentiles.
Data sources often did not indicate whether monitored exposure concentrations were for
occupational users or bystanders. Therefore, EPA/OPPT assumed that these exposure
concentrations were for a combination of users and bystanders. Some bystanders may have
lower exposures than users, especially when they are further away from the source of
exposure.
Additionally, inhalation exposure data from OSHA and state health inspections were obtained
from the OSHA's Integrated Management Information System (IMIS) database. However, OSHA
IMIS data were not used to estimate workplace exposures, except where noted, because of the
high degree of uncertainty and questionable relevancy of these data to stripping with DCM-
containing products. Refer to Appendix G for a detailed discussion of the OSHA IMIS data.
Page 40 of 279
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Workplace exposure scenarios evaluated in this assessment: Workers performing DCM-based
paint stripping might or might not use a respirator and may be exposed to DCM at different
exposure frequencies (days per year) or working years. Thus, EPA/OPPT assessed acute risks for
4 occupational scenarios and chronic risks for 16 occupational scenarios based on 8-hr time-
weighted average (TWA) exposure concentrations and different variations in exposure
conditions. These scenarios were constructed within each industry evaluated in the
assessment.
To estimate acute exposure, EPA/OPPT defined 4 scenarios to reflect a combination of the
following (Table 3-1):
• No use of a respirator (APF = zero);
• Use of a respirator with an APF of 10, 25, or 50, which would reduce the personal breathing
concentration by 10-, 25- or 50-fold (i.e., 0.1, 0.04, 0.02), respectively.
Table 3 1. Acute Occupational Exposure Scenarios for the Use of DCM Based Paint
Strippers
Acute
Scenario
1
2
3
4
Respirator APF a
0
10
25
50
8-hr TWA Concentration
Multiplier11
1
0.1
0.04
0.02
Scenario Description
No respirator
Respirator APF 10
Respirator APF 25
Respirator APF 50
Notes:
3 APF= assigned protection factor. APFs of 10, 25 or 50 mean that the respirator reduced the personal
breathing concentration by 10-, 25- or 50-fold (i.e., 0.1, 0.04, 0.02).
b As indicated in equation 3-2, these multipliers are applied to the 8-hr time-weighted average (TWA) acute
exposure concentrations.
To estimate chronic exposure, EPA/OPPT defined 16 scenarios to reflect a combination of the
following (Table 3-2):
• No use of a respirator (APF = zero)6;
• Use of a respirator with an APF of 10, 25, or 50;
• An exposure frequency (EF) of the assumed Scenario 1 value of 250 days per year or half of
the assumed Scenario 1 value (the midpoint between the assumed Scenario 1 value and
zero: 125 days per year); and
• Exposed working years (WY) of the assumed Scenario 1 value of 40 years or half of the
assumed Scenario 1 value (the midpoint between the assumed Scenario 1 value and zero:
20 years).
The multipliers in Tables 3-1 and 3-2 were used to adjust the exposure estimates of acute and
chronic Scenario 1, respectively, to obtain the exposure estimates for the other exposure
scenarios. Additional information is presented below about the estimation approach to
calculate the acute and chronic exposure estimates.
' APF assumptions are the same for both acute and chronic scenarios.
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Table 3 2. Chronic Occupational Exposure Scenarios for the Use of DCM Based Paint
Strippers
Chronic
Scenario
1
2
3
4
5/9
6/10
7/11
8/12
13
14
15
16
Respirator
APFa
0
10
25
50
0
10
25
50
0
10
25
50
Exposure
Frequency
(EF) (days/yr)
250
250
250
250
250/ 125
250/ 125
250/ 125
250/ 125
125
125
125
125
Working
Years
(WY)
(years)
40
40
40
40
20/40
20/40
20/40
20/40
20
20
20
20
ADC/LADC
Multiplier11
1
0.1
0.04
0.02
0.5
0.05
0.02
0.01
0.25
0.025
0.01
0.005
Scenario Description
No respirator, high ends of
ranges for EF and WY
Respirator APF 10, high ends
of ranges for EF and WY
Respirator APF 25, high ends
of ranges for EF and WY
Respirator APF 50, high ends
of ranges for EF and WY
No respirator, one midpoint
and one high end of range for
EF and WY
Respirator APF 10, one
midpoint and one high end of
range for EF and WY
Respirator APF 25, one
midpoint and one high end of
range for EF and WY
Respirator APF 50, one
midpoint and one high end of
range for EF and WY
No respirator, midpoints of
ranges for EF and WY
Respirator APF 10, midpoints
of ranges for EF and WY
Respirator APF 25, midpoints
of ranges for EF and WY
Respirator APF 50, midpoints
of ranges for EF and WY
Notes:
a APF= assigned protection factor. APFs of 10, 25 or 50 mean that the respirator reduced the personal
breathing concentration by 10-, 25- or 50-fold, respectively.
b As indicated in equation 3-4, these multipliers are applied to the chronic average daily concentrations (ADCs)
and lifetime average daily concentrations (LADCs).
EPA/OPPT evaluated scenarios both with and without respirator use and a range of respirator
APFs because no data were found about the overall prevalence of the use of respirators to
reduce DCM exposures and it was not possible to estimate the numbers of workers who have
reduced exposures due to the use of respirators (as described by the data and information
sources presented in Appendices F and G).
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Likewise, EPA/OPPT made assumptions about the exposure frequencies and working years
because data were not found to characterize these parameters. Thus, EPA/OPPT evaluated
occupational risks by developing hypothetical scenarios under varying exposure conditions (i.e.,
use of respirators with different respiratory protection factors, and different exposure
frequencies and working years).
Approach for calculating acute and chronic workplace exposures: To facilitate the exposure
calculations for the occupational scenarios, EPA/OPPT first estimated the acute and chronic
exposure estimates for Scenario 1 (highest exposure group). Equations are described below.
The exposure estimates for Acute Scenarios 2 to 4 and Chronic Scenarios 2 to 16 were obtained
by adjusting scenario 1 (highest exposure group) with various multipliers (Tables 3-1 and 3-2 for
acute and chronic, respectively). The acute multipliers reflected the numerical reduction in
exposure levels when respirators were used. The chronic multipliers reflected the numerical
reduction in exposure levels when respirators were used and/or other EF and WY values were
used. Although 16 chronic scenarios were possible, scenarios 5 through 8 and 9 through 12
resulted in the same multiplier regardless of whether the scenario used an EF of 250 days/yr
and a WY of 20 yrs, or an EF of 125 days/yr and a WY of 40 years.
Acute occupational exposure estimates
For single (acute) workplace exposure estimates, the DCM single (acute) exposure
concentration was set to the 8-hour TWA air concentration in mg/m3 reported for the various
relevant industries. EPA/OPPT assumed that some workers could be rotating tasks and not
necessarily using DCM-based paint strippers on a daily basis. This type of exposure was
characterized as acute in this assessment as the worker would clear DCM and its metabolites
before the next encounter with the DCM-containing paint stripper.
Equation 3-1 was used to estimate the single (acute) exposure estimates for acute scenario 1
(EPA. 2009).
EC
scenario 1
= C
(Equation 3-1)
where:
EC scenario 1
= exposure concentration for a single 8-hr exposure to DCM (mg/m3) for
scenario 1
= contaminant concentration in air for relevant industry (central tendency,
low- or high-end 8-hr TWA in mg/m3 from Appendix G, Table G-2 or G-5);
Page 43 of 279
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Equation 3-2 was used to calculate the acute exposure estimates for scenarios 2 through 4.
t*L. scenario 2-» 4 — t*L. scenario 1 * M acute (Equation 3-2)
where:
EC scenario 2 -> 4 = exposure concentration for a single 8-hr exposure to DCM
(mg/m3) for acute scenarios 2, 3, or 4;
ECscenario i = single (acute) exposure concentration for relevant industry (8-hr
TWA in mg/m3 from Appendix G, Table G-2 or G-5);
M acute = Scenario-specific acute exposure multiplier (unit less) for relevant
industry (see Table 3-1)
Acute exposure estimates for scenario 1 are presented in Table 3-3. Acute exposure estimates
for scenarios 2 through 4 were integrated into the risk calculations by applying the scenario-
specific multipliers. Thus, separate tables listing the acute exposure estimates for scenarios 2
through 4 are not provided in this section, but are available in a supplemental Excel
spreadsheet documenting the risk calculations for this assessment (DCM Exposure and Risk
Estimates_081114.xlsx).
Chronic occupational exposure estimates
The worker exposure estimates for the non-cancer and cancer risk calculations were estimated
as ADCs and LADCs, respectively. Both ADC and LADC calculations for Scenario 1 were based on
the 8-hr TWA air concentration in mg/m3 reported for the various relevant industries (Appendix
G, Table G-5). EPA/OPPT assumed that the worker would be doing paint stripping activities
during the entire 8-hr work shift on a daily basis. Equation 3-3 was used to estimate the chronic
ADCs and LADCs for Scenario 1 (EPA, 2009).
_ C x ED x EF x WY
scenario 1 — ~(Equation 3-3)
f\ L
where:
EC scenario i = exposure concentration (mg/m3) for Scenario 1 = ADC for chronic non-
cancer risks or LADC for chronic cancer risks for Scenario 1;
C = contaminant concentration in air for relevant industry (central tendency,
low- or high-end 8-hr TWA in mg/m3 from Appendix G, Table G-2);
ED = exposure duration (hrs/day) = 8 hrs/day;
EF = exposure frequency (days/yr) = 250 days/yr for high-end of range
for both ADC and LADC calculations;
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WY = working years per lifetime (yrs) = 40 yrs for high end of range
for both ADC and LADC calculations; and
AT = averaging time (years x 365 days/years x 24 hrs/day) = 40 yrs for high
end of range for ADC calculations; 70 yrs for LADC calculations, which is
used to match the years used to calculate EPA's cancer inhalation unit
risk(IUR).
Equation 3-4 was used to estimate the chronic ADCs and LADCs for scenarios 2 through 16.
hC, scenario 2-> 16 = t-C- scenario 1 x M chronic (Equation 3-4)
where:
EC scenario 2 -> 16 = exposure concentration for chronic exposure concentration (ADC
or LADC) to DCM (mg/m3) for chronic scenarios 2 through 16
EC scenario i = chronic exposure concentration (ADC or LADC) for relevant
industry, chronic scenario 1 (in mg/m3 from Table 3-3);
M chronic = scenario-specific ADC/LADC chronic multiplier for relevant
industry (see Table 3-2)
Non-cancer and cancer exposure estimates (i.e., ADC and LADC, respectively) for scenario 1 are
presented in Table 3-3. The estimates for scenarios 2 through 16 were integrated into the risk
calculations by applying the scenario-specific ADC/LADC multipliers. Thus, separate tables
listing the chronic exposure estimates for scenarios 2 through 16 are not provided in this
section, but are available in a supplemental Excel spreadsheet documenting the risk
calculations for this assessment (DCM Exposure and Risk Estimates_081114.xlsx).
Numbers of exposed workers and shop sizes: Knowing the sizes of exposed populations
provides perspective on the prevalence of the health effects. Thus, EPA/OPPT estimated the
current total number of workers in the potentially exposed populations.
EPA/OPPT found limited data on numbers of workers exposed to DCM in shops that use DCM-
based paint strippers. EPA/OPPT relied on an estimation approach to estimate the total number
of exposed workers from the technical support document for the National Emission Standards
for Hazardous Air Pollutants (NESHAP) Paint Stripping Operations at Area Sources proposed rule
(EPA. 2007).
Based on the NESHAP data and analyses, EPA/OPPT estimates that over 230,000 workers
nationwide are directly exposed to DCM from DCM-based paint strippers. This estimate only
accounts for workers performing the paint stripping using DCM and does not include other
workers ("occupational bystanders") within the facility who are indirectly exposed. EPA/OPPT
cannot estimate the numbers of workers exposed in each of the individual industries that may
use DCM-based strippers. EPA/OPPT also cannot estimate the numbers of workers exposed in
Page 45 of 279
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small shops. Appendix E details the literature search, data found, and assumptions for worker
population exposed nationwide.
EPA/OPPT estimated the average number of employees per facility which can be a factor in
determining shop sizes. These estimates were derived by combining the facility and population
data obtained from the U.S. Census data, as described in Appendix F. The average number of
employees for the identified industries based on U.S. Census data were the following:
• Professional contractors (likely to include Bathtub refinishing): 5 workers/facility;
• Automotive refinishing: 6 workers/facility;
• Furniture refinishing: 3 workers/facility;
• Art restoration and conservation (not estimated);
• Aircraft paint stripping: 320 workers/facility (for aircraft manufacturing only);
• Ship paint stripping: 100 workers/facility; and
• Graffiti removal: 8 workers/facility.
These averages give some perspective on shop size but are simple generalizations.
3.1.1.3 Summary of Occupational DCM Exposure Estimates
Table 3-3 shows the DCM air concentrations used in this assessment for estimating acute and
chronic risks for the highest exposed worker scenario group (Scenario 1) within each industry.
The statistical issues of these estimates are briefly discussed in section 3.5.1.
Acute and chronic DCM exposure estimates for Acute Scenarios 2 through 4 and Chronic
Scenarios 2 through 16 were integrated into the risk calculations by applying multipliers to
Scenario 1. Separate tables listing the acute and chronic exposure estimates are not provided in
this section, but can be found in the supplemental Excel spreadsheet - DCM Exposure and Risk
Estimates_081114.xlsx. Also, Table ES-1 provides a summary of the ranges of acute, ADC and
LADC estimates for the various occupational scenarios.
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Table 3 3. DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers Scenario 1
Highest Exposed Scenario Group
Industry/
Activity
Professional
Contractors
Bathtub
Refinishing
Automotive
Refinishing
Furniture
Refinishing
Art
Restoration
and
Conservation
Aircraft
Paint
Stripping
Ship Paint
Stripping
Graffiti
Removal
Non-Specific
Workplace
Settings -
Immersion
Stripping of
Wood
Time
Range of
Studies
1981-
2004
2003
1989-
2007
2005
1977-
2006
1980
1993
1980-
1994
ACUTE EXPOSURE ESTIMATES
Single 8-hr Concentration
(mg/m3)3
Mean
-
-
253
499
High
2,980
-
416
2,245
(1,266)
C
Midpoint
1,520
-
253
1,125
Low
60
-
90
4.0
2.0
-
-
260
-
3,802
-
1,188
7,000
1,944
-
603
3,518
86
-
18
35
CHRONIC EXPOSURE ESTIMATES
USED IN THE NON-CANCER RISK
ESTIMATES
ADC (mg/m3)b
Mean
-
-
58
114
High
680
-
95
513
(289)
C
Midpoint
347
-
58
257
Low
14
-
21
0.9
0.5
-
-
59
-
868
-
271
1,598
444
-
138
803
20
-
4.1
8.0
CHRONIC EXPOSURE
ESTIMATES USED IN THE
CANCER RISK ESTIMATES
LADC (mg/m3)b
Mean
-
-
33
65
High
389
-
54
293
(165)
C
Midpoint
198
-
33
147
Low
7.8
-
12
0.5
0.3
-
-
34
-
496
-
155
913
254
-
79
459
11
-
2.3
4.6
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Table 3 3. DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers Scenario 1
Highest Exposed Scenario Group
Industry/
Activity
Non-Specific
Workplace
Settings -
Immersion
Stripping of
Wood and
Metal
Non-Specific
Workplace
Settings -
Immersion
Stripping of
Metal
Non-Specific
Workplace
Settings -
Unknown
Time
Range of
Studies
1980
1997-
2004
ACUTE EXPOSURE ESTIMATES
Single 8-hr Concentration
(mg/m3)3
Mean
-
-
357
High
1,017
-
428
Midpoint
825
-
357
Low
633
-
285
CHRONIC EXPOSURE ESTIMATES
USED IN THE NON-CANCER RISK
ESTIMATES
ADC (mg/m3)b
Mean
-
-
81
High
232
-
98
Midpoint
188
-
81
Low
145
-
65
CHRONIC EXPOSURE ESTIMATES
USED IN THE CANCER RISK
ESTIMATES
LADC (mg/m3)b
Mean
-
-
47
High
133
-
56
Midpoint
108
-
47
Low
83
-
37
Notes:
Sources are reported in Table G-2 and discussed in section G-3.
a Calculated acute single 8-hr concentrations are only estimated from 8-hr TWA exposures; see Equation 3-1. Airborne concentration conversion
factor for DCM is 3.47 mg/m3 per ppm (NIOSH, 2011b).
b Calculated ADCs and LADCs are only calculated from 8-hr TWA exposures; see Equation 3-3.
c The values in parentheses are the 95th percentiles of the calculated acute single 8-hr concentrations and the calculated ADCs and LADCs.
- Indicates no data found.
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3.1.1.4 Worker Exposure Limits for DCM
Both regulatory and non-regulatory worker exposure limits have been established for DCM by
OSHA, NIOSH, and the American Conference of Government Industrial Hygienists (ACGIH).
EPA/OPPT analysis showed that the OSHA permissible exposure limit (PEL) and Action Level
values were exceeded for some industries using DCM-based strippers when the OSHA values
were compared to the air concentrations.
Table 3-4 provides a summary of the current occupational exposure values established by
OSHA, NIOSH, and ACGIH. Appendix F presents additional background on processes, respiratory
protection, facilities and worker populations.
OSHA's amended regulatory occupational exposure limits for DCM were effective April 10,
1997. The amendments included reducing the PEL, reducing and changing the averaging time of
the short-term exposure limit (STEL), adding an Action Level, and removing the ceiling limit
(OSHA, 1997a). See Appendix G, section G-2-3, for more details.
Table 3 4. Occupational Exposure Limits for DCMa
Source
OSHA PEL
NIOSH exposure limits
ACGIH TLV f
Limit Type
PEL (8-hr TWA) b
STEL (15-minute TWA)
Action Level (8-hr TWA)
IDLHd
RELe
8-hr TWA
Exposure Limit
25 ppm c
125 ppm
12.5 ppm
2,300 ppm
Ca
50 ppm
Notes:
a Source: OSHA (1997a)
b PEL= Permissible exposure limit ; TWA= Time-weighted average
c Airborne concentration conversion factor for DCM is 3.47 mg/m3 per ppm (NIOSH, 2011b).
d IDLH = Immediately dangerous to life and health. IDLH values are based on effects that might occur from a
30-minute exposure.
e REL = Recommended Exposure Limit. The REL notation "Ca" is for a potential occupational carcinogen. The
NIOSH Pocket Guide website has detailed policy recommendations for chemicals with "Ca" notations
(NIOSH, 2011a).
f TLV = Threshold limit value
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3.2 CONSUMER EXPOSURE ASSESSMENT FOR THE USE OF DCM IN
PAINT STRIPPING
Section 3.2 summarizes the modeling approach used for estimating consumer inhalation
exposures to DCM for the use of DCM-based paint strippers. The consumer modeling is
discussed in greater detail in Appendix H.
3.2.1 Approach and Methodology for Estimating Consumer Exposures
EPA/OPPT used the Multi-Chamber Concentration and Exposure Model (MCCEM) to estimate
consumer exposures to DCM-based paint strippers. This modeling approach was selected
because published monitoring data for non-occupational inhalation exposures (i.e., consumer
do-it-yourself [DIY]) were limited to those from several chamber studies conducted in the U.S.
and Europe. The literature search for this assessment did not identify any published exposure
information for exposures to other household members (i.e., bystanders). Of the available
chamber studies, only one U.S. study provided sufficient information for the exposure modeling
(EPA. 1994a).
3.2.2 Overview of the MCCEM
The MCCEM is an exposure model that estimates airborne concentrations of chemicals released
from products in residential settings or other indoor environments (EPA, 2010a). EPA/OPPT
relied on a model-based consumer exposure assessment in the absence of sufficient measured
data for consumer exposures to DCM-based paint strippers.
The MCCEM incorporates the following features (EPA, 2010a):
• Represents a multiple zone model that uses a deterministic, mass-balance equation to
predict time varying indoor air concentrations;
• Uses chemical volatilization rates from chamber test emission data as an input, making it a
higher tier model;
• Considers the amount of time individuals spend each day within each zone based on human
activity patterns;
• Has been peer reviewed in 1998.
The MCCEM generally uses a two-zone representation of a house to calculate acute air
concentrations of DCM for consumers and bystanders for various exposure scenarios. Zone 1
represents the area where the consumer was using the product, whereas Zone 2 represents the
rest of the house (ROM). Zone 2 was used for modeling passive exposure to house residents
(bystanders), such as children, adults, pregnant women and the elderly (EPA, 2010a). The
model assumes complete mixing in each zone.
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The MCCEM uses 3 zones to model the bathtub "source cloud" scenario. In this scenario, Zone 1
represents the arbitrary volume close to the tub. Zone 2 represents the bathroom volume, and
Zone 3 was the rest of house.
For this assessment, the general steps of the calculation engine within the MCCEM include:
1. Introduction of DCM into the room of use by applying the paint stripper on a surface and
estimation of the declining emission rate in that room: Consumer products that are
applied to surfaces are best represented by the incremental source model. This model
assumes a constant application rate over time, coupled with an emission rate for each
instantaneously applied segment that declines exponentially over time. Depending on the
type of applied product, either one or two exponential expressions may be needed to
characterize the declining emission rate (EPA, 2010a). From an analysis of chamber test
data, EPA/OPPT determined that a single-exponential expression was appropriate for paint
strippers with DCM as a primary ingredient.
2. Transfer of DCM to the rest of the house as a function of the rate of chemical loss and gain
for that zone: MCCEM requires the conservation of pollutant mass as well as the
conservation of air mass when predicting indoor air concentrations in different house
zones. The modeled concentration in each zone is a function of the time-varying emission
rate in the room of use, the zone volumes, the air exchange rate and the interzonal airflow
rates among zones and between each zone and outdoor air (EPA, 2010a).
3. Estimation of the zone-specific airborne concentrations of DCM as the modeled occupant
moves around the house: MCCEM estimated detailed time series of zone-specific (e.g.,
house, workshop, and bathroom) concentrations to account for an individual's location at
specific times. The model output was in the form of instantaneous values at the end of
consecutive one-minute time intervals for the entire duration of the model run (i.e., 24 hrs
in this case) for both the user and residential bystander. The one-minute intervals were
used to calculate acute maximum TWA concentrations for certain averaging periods for the
user and residential bystanders (i.e., one, 10, and 30 minutes; 1-, 4-, 8- and 24-hrs). The
maximum TWA concentration for any averaging period was defined as the highest value of
the consecutive running averages for that averaging period. These general steps are
explained in greater detail in Appendix H.
EPA/OPPT used the DCM air concentrations for the different averaging periods to evaluate the
human health risks of acute, but not chronic, exposures to DCM-based paint strippers in
residential settings. The focus on acute exposures is based on the assumption that DCM is not
expected to significantly buildup in the body between exposure events. DCM's plasma half-life
is estimated to be 40 minutes after inhalation exposure (DiVincenzo et al., 1972). Moreover,
EPA/OPPT assumed that consumers would not generally do paint stripping jobs on a regular
basis in their residences, allowing sufficient time between exposures to clear DCM and its
metabolites from the body.
Page 51 of 279
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-Z^SJ^
EPA/OPPT identified and used published data for current product characteristics, use patterns,
exposure factors, and air monitoring data to set the model input parameters and develop
appropriate consumer exposure scenarios.
Brown (2012) reported a list of DCM -containing products currently available for consumer
purchase. EPA/OPPT used the list of consumer products to determine reasonable percentage of
DCM in products and product densities. Other resources providing information on product
characteristics included the NIH Household Products Database, Material Safety Data Sheets
(MSDS), and Product Labels and Technical Data Sheets. Additional data sources were identified
and used to support model assumptions and input parameters and they are discussed below.
EPA/OPPT assessed the data quality of the identified sources before using the information for
the modeling approach. Data quality criteria were similar to those used for evaluating
occupational data (Appendix H, section H-l-3 and Table H-l).
The model assumptions and input parameters are summarized in section 3.2.2 and explained
more fully in Appendix H.
3.2.3.1 Estimation of Emission Profiles for Paint Removers/Strippers
EPA/OPPT identified air monitoring studies for consumer paint strippers using DCM -containing
products, including the Midwest Research Institute (MRI) chamber study (EPA, 1994a), the
European Commission (EC) study (EC, 2004), and a study conducted in the Netherlands by (van
Veen et al., 2002). Data from the MRI chamber study were used as the basis for developing
emission profiles for both brush-on and spray-on applications for this assessment (EPA, 1994a).
The MRI chamber data were considered adequate to support the exposure estimation effort
and the products studied were considered to be the most representative of paint strippers
available in the U.S. consumer product market.
The EC (2004) study is the most current experimental study conducted for paint strippers.
However, one of its main limitations was the failure to provide the raw data in the report. Thus,
the overall findings of the EC study could not be verified. Additionally, the study may not be
representative of use patterns and DCM-containing products in the U.S.
Although the van Veen et al. (2002) study provided useful information, the study was
conducted on a small scale and the exposure scenario assessed did not represent well the use
patterns in the U.S.
Further discussion and comparison of the air monitoring/chamber test studies above is
provided in Appendix H, section H-5.
Page 52 of 279
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^5^2.^,2^^
Product labels and technical data sheets indicate that DCM-based paint strippers are sold as
brush-on or spray-on products. Thus, EPA/OPPT assessed consumer exposures to products
applied by these two application methods. Each application method is characterized by specific
chemical release characteristics, DCM weight fractions, application rates, and time required for
application. The modeling approach was designed to consider these differences between brush-
on and spray-on products.
3.2.3.3 Amount Applied to the Surface (Product Mass)
The product application mass (grams of product) was determined for each of the cases
examined using application rates (in g/ft2) calculated from the EPA (1994a) chamber tests and
the surface areas of objects (in ft2) to be stripped.
EPA (1994a) reported the most complete air monitoring data for the consumer use of paint
strippers containing DCM7. The study documented chamber experiments for five paint stripping
products used in the U.S., including two paint-stripping products containing DCM. The two DCM
products were: 1) a spray-on product containing 80 to 85 percent DCM; and, 2) a brush-on
product containing >10 percent DCM. EPA/OPPT used descriptions of the study design and the
results to determine product application rates (i.e., in g/ft2 and g/min) and estimated the
fraction of applied chemical mass that ultimately was released to the indoor air. Unfortunately,
the experimental data could not be used directly to assess indoor residential inhalation
exposures in this assessment because the values for the required exposure factors, (e.g.,
room/house volume, airflow rates, and surface area of object) did not reflect the range of
possible residential values. Furthermore, the experiments did not provide concentrations for
areas in the rest of the house where the product was not being used.
The calculated application rates were ~90 g/ft2 and ~68 g/ft2 for a brush-on and spray-on
application, respectively. These application rates are similar to those recommended by
Savogran (i.e., 42 to 83 g/ft2 based on a nominal density of 1.1 g/cm3)8.
Surface areas for the consumer exposure modeling were selected so that the resulting mass (g)
of the applied product corresponded approximately to the CPSC (1992) survey results for
amount of paint stripper used, as reported in the latest Exposure Factors Handbook (EFH) (EPA,
2011a). The CPSC (1992) survey reported the following central (near the median) and upper-
end estimates for the amount of paint stripper product used per event:
7 Appendix H discusses other studies that were reviewed, but were not used to estimate the emission profiles of
DCM-based paint strippers.
8 Savogran sells retail and industrial cleaning and paint preparation products, including paint removers
http://www.savogran.com/
Page 53 of 279
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• 50th percentile value of 32 ounces or 1,000 g for the central-tendency surface area of 10 ft2.
The median value is also supported by Riley et al. (2001)9;
• ~80th percentile value of 80 ounces or 2,500 g for the upper-end surface area of 25 ft2.
To assist the reader to visualize the exposure scenarios, a coffee table of 4 x 2.5 ft could
represent the central-tendency surface area of 10 ft2, while a chest of drawers 4 ft high x 2.5 ft
wide x 1.5 ft deep could represent the upper-end surface area of 25 ft2. The model used median
product masses of 900 and 680 g for the brush-on and spray-on scenarios, respectively. Upper-
end product masses for the brush-on and spray-on scenarios were 2,250 and 1700 g,
respectively.
The bathroom scenario occurred in a confined space and was assumed to be performed by a
home contractor, as opposed to a consumer. A lower mass of 477 g was used for the brush-on
bathroom scenario. The lower mass value was derived from the largest application amount
identified in the NIOSH report (CDC, 2012). A surface area of 36 ft2 was calculated for a bathtub,
resulting in an application rate of 13.25 g/ft2.
3^,2^^
The stripping sequence was based in part on product label instructions, which for some DCM-
containing products (i.e., Klean Strip® products) indicate that no more than 9 ft2 should be
stripped at a time. Product label information also indicated that the stripping should be
repeated to remove multiple coats of paint. As a result, the surface areas of the coffee table,
chest and bathtub were divided as follows:
• 10-ft2 coffee table: Surface area was divided into 2 application segments of 5 ft2 each with
repeat application for a total of 4 segments;
• 25-ft2 chest: Surface area was divided into 4 application segments of 6.25 ft2 each with
repeat application for a total of 8 segments;
• 36-ft2 bathtub: Surface area was divided into 4 application segments of 9 ft2 each with
repeat application for a total of 8 segments.
The stripping sequence for brush-on and spray-on applications was divided into 3 steps: (1)
product application, (2) wait period, and (3) scraping. EPA/OPPT used product label information
to establish the time durations (in minutes) that the user would require to complete each step.
Table H-7 in Appendix H describes the detailed stripping sequence for the brush-on application
to the chest surface.
It was further assumed that the paint scrapings were removed from the house as soon as
scraping was completed for the last segment. In addition, back-to-back stripping sequences
9 Rileyet al. (2001) represents the most current use-pattern survey available for paint strippers. Refer to Appendix
H for more information on this study.
Page 54 of 279
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with no overlapping activities were modeled because it is likely that the user would take breaks
during the wait period.
3.2.3.5 Amount of Chemical Released
The amount of chemical released during and after the stripping event is the product of three
parameters: amount applied to the surface (discussed above), weight fraction of chemical in
the applied product, and fraction of the chemical that is released to indoor air.
From the product list developed by (Brown, 2012), the median DCM weight fraction was
determined to be 0.53 for the brush-on application and 0.8 for the spray-on application. The
corresponding 90th percentile weight fractions were 0.88 for brush-on and 0.87 for spray-on. A
weight fraction of 1.0 (maximum exposure estimate derived from product label) was assumed
for the bathtub application.
Release fractions of 0.33 and 0.66 were used for brush-on and spray-on applications,
respectively, based on the analysis of the MRI chamber data (EPA, 1994a). Appendix H lists the
resultant mass released for the different application targets and methods.
3.2.3.6 Airflow Rates and Volumes
Information about the zone volumes, air exchange rates and interzonal air flows was obtained
from published sources including the 2011 EFH (EPA. 2011a). Rileyet al. (2001). EPA (1995a).
Matthews etal. (1989) and CDC (2012).
The house volume chosen for the model runs (492 m3) was the central value listed in the 2011
EFH (EPA, 2011a). The volume assigned to the in-house workshop area was 54 m3, which is
similar to the value reported in Riley et al. (2001) for the mean volume of the room used for
paint stripping (51 m3). The volume for the ROM (438 m3) is determined by subtraction (492 m3 -
54 m3). For the bathtub scenario, the bathroom volume was set at 9 m3 for consistency with
that reported in CDC (2012).
The air exchange rate (ACH) values for the ROM were the central and low-end values of 0.45/hr
and 0.18/hr, respectively. The ACH values corresponded to the mean and 10th percentile values
reported by the 2011 EFH (EPA, 2011a) and represented the indoor-outdoor airflow rate for the
ROH.
For the workshop scenarios, it was assumed that multiple windows were opened. This
assumption was supported by both product's labeling instructions and survey data that found
the majority of paint stripper users kept a window or door open during use (CPSC, 1992; EPA,
1987; Pollack-Nelson, 1995; Rileyetal., 2001). The indoor-outdoor airflow rate assigned to the
workshop (68 m3/hr) was obtained by multiplying the room volume of 54 m3 by the 90th
percentile of the air-exchange-rate distribution from the EFH (1.26 hr; EPA, 2011a), as it was
thought to be a reasonable representation of the open-window case.
Page 55 of 279
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ACH values and house volumes described above were used to derive the interzonal airflow
rates for the workshop scenarios. Appendix H describes how the interzonal airflow rates were
estimated using an algorithm developed by (EPA, 1995a).
The modeling of the tub stripping for the bathroom scenario considered a source-cloud effect
to better represent the user's exposure to DCM emitted from the paint stripper. The concept of
a "source cloud" in the bathroom scenario assumes that the user is typically exposed to
elevated concentrations in the immediate vicinity of the application area while stripping the
bathtub for an extended period. To account for the source-cloud effect, the model was
designed to create a third zone ("source cloud") within the bathroom to represent the DCM
concentrations in the vicinity of the tub. The airflow rate between the cloud and the rest of the
bathroom was based on work by Matthews et al. (1989). The indoor-outdoor airflows were
based on the air exchange rate of 0.18 ACH assuming windows closed and no exhaust fan.
Please refer to Appendix H, section H-3 (Inhalation Exposure Scenario Inputs: Airflow Rates and
Volumes) for more information.
3.2.3.7 Locations of Exposed Individuals
The model places the user in the work area for stripper application and scraping, which is either
in the workshop or a bathroom. During the waiting phase of the stripping process, the user may
be placed in the ROM as a central-tendency assumption or in the room of use as an upper-end
assumption. However, residential bystanders are located in the ROM.
Riley et al. (2001) supports the reasonableness of placing the user in the ROM during the wait
period. The survey reported that 65 percent of users take breaks outside the work area.
EPA/OPPT also assumed that users leaving the room of use would be aware of inhalation health
hazards from the product's labeling warnings.
However, EPA assumes that some users would stay in the workshop because they do not read
the product's labels and may therefore not be aware of health concerns or precautionary
techniques. Pollack-Nelson (1995) reported that ~28 percent of consumers did not read the
product labels while using paint strippers. Moreover, many labels do not specifically
recommend users to leave the room during the wait period. Rileyet al. (2001) indicated that 20
percent of participants reported taking breaks inside the work area. EPA/OPPT assumed that
the user left the workshop during the wait period for most scenarios, but also included two
scenarios with the users staying in the workshop during the wait time.
Changing the values for various combinations of input parameters generates a wide range of
plausible exposure scenarios and can increase the level of confidence in the model results.
Thus, EPA/OPPT conducted a sensitivity analysis as a first step to guide the development of
Page 56 of 279
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exposure scenarios for the inhalation exposure assessment of DCM-based paint strippers. The
sensitivity analysis helped us to determine which parameters used in the model have the most
influence over the results of the assessment.
The types of factors that can be varied in MCCEM include the following:
• The configuration of the structure (residence in this case) being modeled, including the
number of zones, volume of each zone, airflow rates between each zone and outdoor air,
and airflow rates between zones (i.e., interzonal airflow rates);
• The quantity of DCM emitted from the applied product and the time-varying emission rate,
which are related to: (1) the type and area of surface being stripped; (2) the type of
application (e.g., brush-on vs. spray-on); and (3) the rate at which the product is applied to
the surface; and
• Locations during and after stripping of users and residential bystanders.
The methods for and results of this sensitivity analysis are described immediately below
followed by discussion of the consumer exposure scenarios supporting the risk assessment.
^2^4-l^SensitivityAnalysis
The sensitivity analysis was conducted using an approach that has been termed a "nominal
range sensitivity analysis" (Freyand Patil, 2002). With this approach, a "base case" is defined
first, typically consisting of central values for each model input. The base case for the sensitivity
analysis was formed as follows:
• House volume of 492 m3 (corresponds to a 36 ft x 30 ft, two-story house with 8-ft ceiling);
• Workshop (area of product use) volume of 54 m3 (corresponds to a 20 ft x 12 ft room with
8-ft ceiling) and an indoor-outdoor airflow rate of 68 m3/hr (expected value for a room with
multiple open windows);
• Airflow rate of 197 m3/hr for the ROM, assuming windows closed, corresponding to an air
exchange rate of 0.45 ACH;
• Brush-on application with a target surface area of 10 ft2;
• Applied product mass of 900 g (90 g/ft2) and emitted (released to indoor air) DCM mass of
148.5 g, assuming a DCM weight fraction of 0.5 in the product and a release fraction of 0.33;
• User located in workshop during application and scraping periods but in ROM during wait
periods between applying/scraping and after completion of all applying/scraping.
The time required to apply and scrape the paint stripper, including the wait time between
applying and scraping, is about an hour, according to CPSC (1992). Consequently, the model
was run for a 24-hr period to capture all or most of the declining indoor-air concentrations
following the episode of product use.
For this assessment, the relevant exposure measures included the maximum TWA
concentrations for certain averaging periods (i.e., one, 10, and 30 minutes and 1, 4, and 8 hrs)
Page 57 of 279
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in addition to the 24-hr TWA value. All the exposure durations were reported in the model runs;
but only the maximum 1-hr and the 24-hr TWA were used for the sensitivity analysis.
Figures 3-1 and 3-2 show a generic example of the user and bystander exposure to DCM for
selected averaging times.
Figure 3-1. Example of Time-Varying User Exposure Concentration and Maximum TWA
Values for Selected Averaging Times
I
o
I
01
o
User Exposure Concentration
•10-min max
30-min max
•1-hr max
4-hr max
Time, hours
Figure 3-2. Example of Time-Varying Residential Bystander Exposure Concentration and
Maximum TWA Values for Selected Averaging Times
"SB
_g
4-»
as
01
o
200 -i
150 -
100 -
Non-user Exposure Concentration
10-min max
30-min max
1-hr max
4-hr max
50 -
345
Time, hours
Page 58 of 279
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The next step after running the base case consists of varying the input parameters—one at a
time—and recording the model response (i.e., average or peak concentrations to which
individuals are exposed). The "index of sensitivity" is the magnitude of change in model
response, typically expressed as a percent change from that of the base case. Details about the
computation approach for the sensitivity analysis are described in Appendix H, Section H-2
(Sensitivity Analysis for Inhalation Scenarios).
Figures 3-3 and 3-4 display the sensitivity results for two exposure measures, maximum 1-hr
TWA and 24-hr TWA, respectively. The results can be summarized as follows:
• The model is highly sensitive to changes in chemical mass as shown by a 75 percent change
from the base case response in both the user and residential bystander exposed to DCM for
1- and 24-hrs. This is indicative of a linear and proportional response.
• The model is even more sensitive to changes in the user location during the wait period
between applying and scraping (i.e., user stays in workshop vs. moves to ROM) irrespective
of whether the user is exposed to DCM for 1- and 24-hrs.
• The model response is somewhat sensitive to the ROM air exchange rate with outdoor air
(ROM ACH) for the bystander, but not for the user.
As a result of the sensitivity analysis, EPA/OPPT determined that the chosen modeling scenarios
should include some variations in each of these three factors (i.e., DCM chemical mass emitted,
user location during the wait period, and the ROM ACH with outdoor air) to address greater
model sensitivity.
Figure 3-3. Model Sensitivity Results: Percent Change from Base-Case Response for
Maximum 1-hr TWA for User and Residential Bystander
o
Q.
t/l
QJ
200% -
180W -
160%
-------
Figure 3-4. Model Sensitivity Results: Percent Change from Base-case Response for 24-hr
TWA for User and Residential Bystander
o
Q.
01
in
re
u
re
.a
re
u
100% -
90% -
80% -
70% -
60% -
50% -
40% -
30% -
20% -
10% -
0%
124-hour Average User
124-hour Average Non-User
Cheir Mass ROHACH
Workshop Interzonal Workshop UserStaysin
ACH Flow Volurre Workshop
Notes:
Chem Mass= Chemical mass
ROM ACH= Rest of the house air exchange rate
Non-user= Residential bystander
3.2.4.2 Exposure Scenarios for the DCM Inhalation Exposure Assessment
Table 3-5 lists the seven indoor exposure scenarios evaluated for this risk assessment. Also,
Table 3-6 summarizes the input parameters and assumptions that were used to build the
scenarios.
The following factors were considered in developing the scenarios:
• The type of application (i.e., brush-on or spray-on), weight fraction of applied product,
application rate, surface area of object to be stripped, and emission rate of the chemical
concern, which can affect the amount of DCM that ultimately is released to the indoor
environment;
• The location where the product is applied, which relates to exposure factors such as the
room volume and its air exchange rate with outdoor air;
• The house volume and air exchange rate, for reasons similar to those for the product use
location;
• Precautionary behaviors such as opening windows in the application room and the user
leaving the application room during the effect period, and related changes to the air
exchange rates and the proximity of the user to the source of DCM emissions.
Page 60 of 279
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Table 3 5. Consumer Exposure Scenarios for the DCM Inhalation Exposure Assessment
Scenario ID
1
2
3
4
5
6
7
Scenario Description
Type of Application
Brush-on
Brush-on
Brush-on
Spray-on
Spray-on
Spray-on
Brush-on
Location of Product Use
Workshop
Workshop
Workshop
Workshop
Workshop
Workshop
Bathroom
Concentration
Characterization3
Central tendency
User Upper-end
User and Bystander upper-end
Central tendency
User Upper-end
User and Bystander Upper-end
Bystander Upper-end
Note:
a Conditions obtained by varying the most sensitive parameters within application type: DCM mass emitted;
user location during the wait period; and the rest of the house (ROM) air exchange rate with outdoor air.
Table 3 6. Summary of DCM Consumer Paint Stripping Scenario Descriptions and Parameters
Scenario
ID
Cone.
Characte-
rization
DCM Released
Weight
Fraction
Surface
Area
Treated a,
ft2
Application
Rate, g/ft2
Release
Fraction
Stripping Method
Room of Use
Volume,
m3
Ventilation/ACH,
1/hr
House
Volume,
m3
ROM
ACH, hr -1
User
Location
During
Wait
Period b
By-
stander
Location
Brush-on Exposure Scenarios in Workshop
1
2
3
Central
Upper-end
for user c
Upper-end
for user
and
bystander c
0.53
(central)
0.88
(upper-
end)
10
coffee
table
(central)
25
chest of
drawers
(upper-
end)
90
0.33
• Four segments for coffee
table (i.e., two 5-ft2
segments with repeat
application) and eight
segments for chest of
drawers (i.e., four 6.25-ft2
segments with repeat
application)
• 2-minute application,
15-minute wait, and 4-
minute scrape per
segment
• No overlapping activities
• Scrapings removed from
house after last scraping
54
(central)
Open windows/
1.26
(professional
judgment, 90th
percentile)
492
(central)
0.45
(central)
0.18
(low-
end)
ROM
Workshop
ROM
ROM
(entire
time)
Page 61 of 279
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Table 3 6. Summary of DCM Consumer Paint Stripping Scenario Descriptions and Parameters
Scenario
ID
Cone.
Characte-
rization
DCM Released
Weight
Fraction
Surface
Area
Treated a,
ft2
Application
Rate, g/ft2
Release
Fraction
Stripping Method
Room of Use
Volume,
m3
Ventilation/ACH,
1/hr
House
Volume,
m3
ROM
ACH, hr -1
User
Location
During
Wait
Period »
By-
stander
Location
Spray-on Exposure Scenarios in Workshop
4
5
6
Central
Upper-end
for userc
Upper-end
for user
and
l_ • _l C
bystander
0.80
(central)
0.87
(upper-
end)
10
coffee
table
(central)
25
chest of
drawers
(upper-
end)
68
0.66
• Four segments for coffee
table (i.e., two 5-ft2
segments with repeat
application) and eight
segments for chest of
drawers (i.e., four 6.25-ft2
segments with repeat
application)
• 1-minute application,
15-minute wait, and 4-
minute scrape per
segment
• No overlapping activities
• Scrapings removed from
house after last scraping
54
(central)
Open windows/
I'JC
.ZD
(professional
judgment, 90th
percentile)
492
(central)
0.45
(central)
0.18
(low-
end)
ROM
Workshop
ROM
ROM
(entire
time)
Page 62 of 279
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Table 3 6. Summary of DCM Consumer Paint Stripping Scenario Descriptions and Parameters
Scenario
ID
Cone.
Characte-
rization
DCM Released
Weight
Fraction
Surface
Area
Treated a,
ft2
Application
Rate, g/ft2
Release
Fraction
Stripping Method
Room of Use
Volume,
m3
Ventilation/ACH,
1/hr
House
Volume,
m3
ROM
ACH, hr -1
User
Location
During
Wait
Period »
By-
stander
Location
Brush-on Exposure Scenario in Bathroom
7
Simulation
for
bystander
exposure
0.88
(upper-
end)
36
bathtub
(upper-
end)
13.25
0.33
• Eight segments (i.e., four
9 ft2 segments with
repeat application)
• 3-minute application,
15-minute wait, and 6-
minute scrape per
segment
• No overlapping activities
• Scrapings removed from
house after last scraping
9
(low-
end)"
Window closed,
no exhaust fan/
0.18 e
(low-end)
492
(central)
0.18
(low-
end)
ROM
ROM
(entire
time)
Notes:
a The surface area values were selected so that the calculated amount of product applied (in grams) corresponds approximately to the CPSC (1992) survey results for amount
of paint stripper used (50th percentile value of 32 ounces or 1,000 g for the central surface area of 10 ft2 and ~80th percentile value of 80 ounces or 2,500 g for the upper-
end surface area of 25 ft2).
b For all scenarios, the user is in the treatment room during the application and scraping times and in ROM after the last scraping.
c Changes in both chemical mass and ACH parameters are more influential than changes in only user location from workshop to the rest of the house. Consequently, the user
concentrations for Scenarios 3 and 6 are higher than those for Scenarios 2 and 5, respectively.
d 1 m3 for the vicinity of the tub (source cloud) and 8 m3 for the rest of the bathroom.
e Because the user is working in the semi-enclosed work area (bathtub) for an extended period, a third zone ("source cloud") was created within the bathroom to represent
the DCM concentrations in the vicinity of the tub; this is a virtual zone, with no physical boundaries. The airflow rate between the cloud and the rest of the bathroom was
based on work by Matthews et al. (1989)(for more information, see discussion in Appendix H, H.3. Inhalation Exposure Scenario Inputs (Airflow Rates and Volumes).
Abbreviations: ROH= room of use; ACH= air exchange rate
Page 63 of 279
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The primary distinctions among the seven scenarios were as follows: type of application (i.e.,
brush vs. spray); location of product application (i.e., workshop for most scenarios, bathroom
for one scenario); and values used for other inputs including the DCM mass emitted, the user's
location during the effect or wait period, and the air exchange rate of the rest of the house
(ROM) with outdoor air. The sensitivity analysis indicated that these latter three inputs were the
most sensitive variables in the modeling within application type.
Central-tendency or upper-end input parameters were used when building the exposure
scenarios. Central-tendency values10 are exposure values expected to be near the average or
median for the range of exposure values. On the other hand, upper-end values11 are plausible
exposure values from the upper half of the range of expected exposure amounts. Of the
scenarios listed in Tables 3-5 and 3-6, two are considered central tendency for both the user
and the bystander, four had combinations of inputs to estimate upper-end concentrations for
the user, and two of the latter also had input combinations to estimate upper-end
concentrations for the bystander.
EPA/OPPT developed the seventh scenario to simulate the actual reported conditions from a
Centers for Disease Control and Prevention (CDC)/NIOSH occupational exposure case for a DCM
paint stripper used on a bathtub (CDC, 2012; Chester et al., 2012). In this case, the user died
after using a DCM-based paint strippers in a confined (i.e., closed, poorly ventilated) bathroom.
Thus, the purpose of including this latter scenario was to estimate the DCM air concentrations
to residential occupants outside the use zone (i.e., bystanders) under conditions of high
product use in the room of use. The selected parameter values for scenario 7 (e.g., large surface
area, small room size, minimal ventilation, upper-end weight fraction, and low ROM ventilation)
would increase concentrations and exposures so that the combinations of parameter values
would be expected to result in upper-end to bounding concentrations for the user and
residential bystander.
Further details of the exposure scenario inputs are discussed in Appendix H, section H-3
(Inhalation Exposure Scenario Inputs).
10 As noted in Section 2.3.1 (Individual Risk) of the EPA (1992b) exposure assessment guidelines, "Individual risk
descriptors will generally require the assessor to make estimates of high-end exposure, and sometimes additional
estimates (e.g., estimates of central tendency such as average or median exposure)." For this assessment,
scenarios with central parameter values refer to a set of inputs that are expected to result in a central (i.e., near
the median) estimate of individual exposure.
11 As also noted in Section 2.3.1 of the EPA (1992b) exposure assessment guidelines, "a high end exposure estimate
is a plausible estimate of the individual exposure for those persons at the upper end of an exposure distribution.
The intent of this designation is to convey an estimate of exposures in the upper range of the distribution, but to
avoid estimates that are beyond the true distribution; these latter estimates are called "bounding."
Conceptually, the high end of the distribution means above the 90th percentile of the population distribution, but
not higher than the individual in the population who has the highest exposure." For this assessment, scenarios
labeled "upper-end" were modeled by selecting low- and high-end values for sensitive parameters. An "upper-
end" exposure estimate is above central tendency and may include the high end of the exposure distribution.
Page 64 of 279
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3.2.5 Consumer Model Results
Table 3-7 provides the scenario-specific DCM air concentrations for the consumer user of DCM-
containing paint strippers and residential bystanders. These concentrations were calculated by
computing running averages and selecting the maximum of these averages. For example, for
the 1-hr averaging period, the 1-hr average concentration was calculated for each one-minute
start time during the 24-hr period (e.g., zero to 60, one to 61, and etc.), for which the maximum
of these averages is reported in Table 3-7. As the averaging time increases, the user to
bystander exposure ratio decreases. For example, the ratio of user to bystander maximum one-
minute concentration is ~5:1 for scenario 1, whereas the ratio is ~1.5:1 for the 24-hr user and
bystander TWA values.
Appendix H provides additional information on various aspects of the model output, such as the
following:
• Mathematical description of the calculations (section H-4, Inhalation Model Outputs and
Exposure Calculations)
• Comparison of results resulting from the MCCEM modeling and the Lawrence Berkley
Laboratory (LBL) study monitoring data (section H-5, Comparison of Modeling-based and
Monitoring-based Exposure Estimates)
• Scenario summaries for each of the modeled scenarios, including both model inputs and
results (section H-6, MCCEM Inhalation Modeling Scenario Summaries)
Page 65 of 279
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Table 3 7. Modeled DCM Air Concentrations to Which Consumer Users and Residential Bystanders are Exposed
Scenario
1. Brush application in workshop,
central parameter estimates
2. Brush application in workshop,
upper-end user estimates b
3. Brush application in workshop,
upper-end user and bystander
estimates b
4. Spray application in workshop,
central parameter estimates
5. Spray application in workshop,
upper-end user estimates b
6. Spray application in workshop,
upper-end user and bystander
estimates b
7. Brush application in bathroom,
simulation
Individual3
User
Bystander
User
Bystander
User
Bystander
User
Bystander
User
Bystander
User
Bystander
User
Bystander
Maximum Values for Averaging Period, mg/m3 (ppm)
1 Minute
630 (180)
130 (38)
1,300
(370)
220 (63)
1,800
(520)
470 (140)
1,500
(430)
300 (87)
2,000
(570)
330 (95)
2,800
(810)
710 (210)
2,428
(699)
224 (64)
10
Minutes
380 (110)
130 (38)
1,300
(360)
220 (63)
1,200
(340)
470 (140)
780 (220)
300 (87)
1,900
(550)
330 (95)
1,600
(470)
710 (210)
1,455
(419)
224 (64)
30
Minutes
270 (78)
130 (37)
1,100
(330)
220 (62)
900 (260)
470 (140)
600 (170)
300 (86)
1,800
(510)
320 (93)
1,300
(360)
710 (200)
887 (255)
222 (64)
IHour
220 (64)
120 (36)
1,100
(300)
210 (59)
760 (220)
460 (130)
490 (140)
280 (82)
1,600
(460)
310 (89)
1,100
(320)
700 (200)
799 (230)
218(63)
4 Hours
120 (35)
82 (24)
420 (120)
140 (39)
560 (160)
380 (110)
270 (77)
190 (54)
620 (180)
200 (59)
810 (230)
580 (170)
536 (154)
187 (54)
8 Hours
69(20)
49 (14)
220 (64)
82 (24)
400 (120)
290 (83)
150 (44)
110(32)
330 (96)
120 (35)
580 (170)
430 (120)
340 (98)
150 (43)
24 Hours
23 (6.7)
17 (4.8)
75 (22)
28 (8.0)
160 (45)
120 (34)
52(15)
38(11)
110(32)
42(12)
230 (66)
180 (51)
135 (39)
70(20)
Notes:
a The bystander was assumed to be in Rest-of-House (ROM).
b Changes in both chemical mass and air changes per hour (ACH) parameters are more influential than changes in only user location from workshop to the rest
of the house. Consequently, the user concentrations for Scenarios 3 and 6 are higher than those for Scenarios 2 and 5, respectively.
Page 66 of 279
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3.3 HAZARD/DOM-RESPOP^ ASSESSMENT
3.3.1 Approach and Methodology
3.3.1.1 Selection of Peer-Reviewed Hazard/Dose-Response Assessments as the
Source Documents for the DCM TSCA Assessment
EPA/OPPT's work plan risk assessment for DCM is primarily based on the peer-reviewed hazard
and dose-response information12 published in the following reports:
• Toxicological Review of Methylene Chloride published in 2011 by EPA's Integrated Risk
Information System (IRIS) (EPA. 2011c):
• Spacecraft Maximum Allowable Concentrations (SMAC)for Selected Airborne Contaminants:
Methylene chloride (Volume 2) published by the U.S. National Academies (NRC, 1996);
• Acute Reference Exposure Level (REL) and Toxicity Summary for Methylene Chloride
published by the Office of Environmental Health Hazard Assessment (OEHHA, 2008);
• Interim Acute Exposure Guideline Levels (AEGL)for Methylene Chloride developed by the
U.S. National Advisory Committee on AEGLs (NAC, 2008).
To a lesser extent, the Toxicological Profile for Methylene Chloride published by the Agency for
Toxic Substances and Disease Registry (ATSDR) was consulted for hazard information (ATSDR,
2000. 2010).
EPA/OPPT used the DCM IRIS assessment as the principal data source for chronic toxicity hazard
and dose-response information. The DCM IRIS assessment used a weight-of-evidence approach,
the latest scientific information and physiologically-based pharmacokinetic (PBPK) modeling to
develop hazard and dose-response assessments for carcinogenic and non-carcinogenic health
effects resulting from lifetime exposure to DCM.
The DCM IRIS assessment followed the principles set forth by the various risk assessment
guidelines issued by the National Research Council (NRC) and EPA. Primary, peer-reviewed
literature identified through September 2011 was systematically reviewed and included where
that literature was determined to be critical to the assessment (EPA, 2011c).
In addition, EPA/OPPT used the SMAC, the California acute REL and AEGL technical support
documents as the data source for acute toxicity hazard and dose-response information. SMACs
and the California acute REL for DCM are derived following the Guidelines for Developing
12 EPA/OPPT uses the hazard values (i.e., points of departure) and, in most cases, the same uncertainty factors that
were used to derive the SMAC, acute REL and AEGLs and EPA's IRIS cancer/non-cancer values for chronic
exposures to DCM. Since EPA/OPPT is using margin of exposures (MOEs) to estimate risk, our approach does not
use the derived human health guidelines (e.g., RfC, SMAC, acute ERL and AEGLs) for risk estimation. See sections
3.3.1.2 and 3.3.1.3 for more details.
Page 67 of 279
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Spacecraft Maximum Allowable Concentrations for Space Station Contaminants (NRC, 1992)
and California's Air Toxics Hot Spots Program risk assessment guidelines for acute RELs (OEHHA,
1999), respectively. AEGLs are developed based on the criteria discussed in the Standing
Operating Procedures (SOP) for Developing Acute Exposure Guideline Levels for Hazardous
Chemicals (NRC. 2001).
Appendix I provides additional information about the information considered in the
development of the DCM IRIS (section 1-1), AEGL (section 1-2), SMAC (section 1-3) and the
California acute REL (section 1-4) toxicology assessments.
3.3.1.2 Chronic Hazard and Dose-Response Assessment: EPA IRIS Toxicological
Review of Methylene Chloride
EPA/OPPT used the DCM cancer and non-cancer hazard/dose-response assessments published
by the EPA's IRIS program to estimate chronic risks for the occupational scenarios. A summary
of the approach and methodology is provided in sections 3.3.1.2.1 (Carcinogenic Effects) and
3.3.1.2.2 (Non-Cancer Effects).
3.3.1.2.1 Carcinogenic Effects Following Chronic Exposure to DCM
DCM is likely to be carcinogenic in humans by a mutagenic mode of action (EPA, 2011c). The
EPA IRIS cancer dose-response analysis used linear low-dose extrapolation to derive an
inhalation unit risk (IUR) of 4 x 10~5 per ppm (1 x 10~5 per mg/m3; assuming a 70-year human
lifetime)13. The IUR was used in the EPA/OPPT risk assessment to estimate excess cancer risks
for the inhalation occupational exposures scenarios.
The IUR for DCM was derived from mouse liver and lung tumor incidence data (Mennear et al.,
1988; NTP, 1986). The IUR is defined as the upper-bound excess lifetime cancer risk estimated
to result from continuous exposure to an agent at a concentration of 1 u.g/m3 in air (EPA,
2011c). There is high confidence in the IUR because it was based on the best available dose-
response data for liver and lung cancer in mice (EPA, 2011c). Moreover, the weight of evidence
from multiple in vivo and in vitro studies supported the mutagenicity of DCM and the key role
of glutathione S-transferase (GST) metabolism and the formation of DNA-reactive GST-pathway
metabolites (EPA, 2011c). Appendix J contains more information on how the cancer IUR was
developed for DCM. Table 3-8 lists the cancer dose-response information that EPA/OPPT used
in the work plan risk assessment for DCM.
EPA/OPPT decided not to use the IUR to calculate the theoretical cancer risk associated with a
single (acute) exposure to paint strippers containing DCM. NRC (2001) published methodology
for extrapolating cancer risks from chronic to short-term exposures to mutagenic carcinogens.
13 The inhalation unit risk for dichloromethane should not be used with exposures exceeding the point of
departure (BMDLio = 7,700 mg/m3 or 2,200 ppm), because above this level the fitted dose-response model does
not characterize what is known about the carcinogenicity of DCM.
Page 68 of 279
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These methods were published with the caveat that extrapolation of lifetime theoretical excess
cancer risks to single exposures has great uncertainties.
As NRC (2001) explains, "There are no adopted state or federal regulatory methodologies for
deriving short-term exposure standards for workplace or ambient air based on carcinogenic risk,
because nearly all carcinogenicity studies in animals and retrospective epidemiologic studies
have entailed high-dose, long-term exposures. As a result, there is uncertainty regarding the
extrapolation from continuous lifetime studies in animals to the case ofonce-in-a-lifetime
human exposures. This is particularly problematical, because the specific biologic mechanisms
at the molecular, cellular, and tissue levels leading to cancer are often exceedingly diverse,
complex, or not known. It is also possible that the mechanisms of injury of brief, high-dose
exposures will often differ from those following long-term exposures. To date, U.S. federal
regulatory agencies have not established regulatory standards based on, or applicable to, less
than lifetime exposures to carcinogenic substances (NRC, 2001)." Thus, the final EPA/OPPT work
plan risk assessment for DCM does not estimate excess cancer risks for acute exposures
because the relationship between a single short-term exposure to DCM and the induction of
cancer has not been established in the current scientific literature.
3-3-l-2-^
The EPA IRIS non-cancer dose-response assessment calculated a hazard value of 17.2 mg/m3
(4.8 ppm) for chronic DCM inhalation exposures (EPA, 2011c). The hazard value was estimated
by PBPK modeling and expressed as the 1st percentile of the distribution of human equivalent
concentrations (HEC) i.e. the HECgg the concentration at which there is 99% likelihood an
individual would have an internal dose less than or equal to the internal dose of hazard was
used to protect toxicokinetically sensitive individuals. EPA/OPPT used the PBPK-derived HEC as
the non-cancer hazard value for the occupational risk calculations.
The derivation of the non-cancer hazard value was based on the hepatic effects reported in a
2-year rat study. Specifically, female rats reported liver lesions (i.e., hepatic vacuolation)
following exposure to 500 ppm DCM for 6 hrs/day, 5 days/week for 2 years (Nitschke et al.,
1988a). The rat data were suitable for non-cancer dose-response analysis in the DCM IRIS
assessment. The animal-to-human extrapolation was conducted by PBPK modeling, coupled
with benchmark dose14 estimation. The DCM IRIS assessment chose the 1st percentile HEC i.e.
the HECgg the concentration at which there is 99% likelihood an individual would have an
internal dose less than or equal to the internal dose of hazard of 17.2 mg/m3 as the point of
departure (POD)15 for the non-cancer dose-response assessment because it would protect
toxicokinetically sensitive individuals. Appendix J contains more information on how the non-
cancer PBPK-derived HEC was developed.
14 The benchmark dose (BMD) is a dose or concentration that produces a predetermined change in response rate
of an adverse effect (called the benchmark response or BMR) compared to background (EPA, 2011c).
15 A point of departure (POD) is a dose or concentration that can be considered to be in the range of observed
responses, without significant extrapolation. A POD is used to mark the beginning of extrapolation to determine
risk associated with lower environmentally relevant human exposures (EPA, 2011b).
Page 69 of 279
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There is high confidence in the key study supporting the non-cancer hazard value. Nitschke et
al. (1988a) is a well-conducted, peer-reviewed study that used three dose groups plus a control.
In addition, the inhalation database contains several studies consistently identifying the liver as
the most sensitive non-cancer target organ in rats (EPA, 2011c).
EPA/OPPT used the same endpoint and study-specific uncertainty factors (UFs) that the EPA
IRIS program applied to the PBPK-derived HEC to interpret the non-cancer risk estimates (i.e.,
margin of exposure, MOE16) for workers. EPA/OPPT did not use a database uncertainty factor
for the benchmark MOE for specific endpoints. This uncertainty in the database is discussed
qualitatively in the risk characterization.
A total UF of 10 was used as the benchmark MOE and was allocated as follows:
• interspecies UF (UFA) of 3 to account for toxicodynamic differences between animals and
humans,
• intraspecies UF (UFn) of 3 to account for toxicodynamic differences within humans
Table 3-8 lists the cancer and non-cancer dose-response information that EPA/OPPT used in
this assessment to evaluate risks associated with chronic exposures to DCM.
16 Margin of Exposure (MOE) = (Non-cancer hazard value, POD) 4- (Human Exposure). The benchmark MOE is used
to interpret the MOEs and consists of the UFs for interspecies and intraspecies uncertainty set by the IRIS
program. Refer to section 3.4 for more information about the MOE calculations.
Page 70 of 279
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Table 3 8. Cancer and Non Cancer Hazard Values Used in the Risk Evaluation of Chronic Exposures to Workers Using DCM
Based Paint Strippers
Effects
Category
CANCER
NON-CANCER
Target
Organ/
System
Liver
and
lung
Liver
Species
Mouse
(male)
Rat
(female)
Route of
Exposure and
Exposure
Concentrations1
Inhalation
Oppm,
2,000 ppm,
4,000 ppm
Inhalation
0 ppm,
50 ppm,
200 ppm,
500 ppm
Duration
6 hrs/day,
5 days/week
for 2 years,
beginning at
7-8 weeks of
age
6 hrs/day,
5 days/week
for 2 years
Notes:
1 Airborne concentration conversion factor for DCM is 3.47 mg/m3
POD Type
Male liver tumors:
Mouse internal BMDio and
BMDLio = 913.9and
544.4 mg DCM metabolized
via GST pathway/liter
tissue/day, respectively
Male lung tumors:
Mouse internal BMDio and
BMDLio = 61.7 and 48.6 mg
DCM metabolized via GST
pathway/liter tissue/day,
respectively
Rat internal BMDLi0 =
531.82 mg DCM
metabolized via
cytochrome P450 (CYP)
pathway/liter liver
tissue/day
perppmNIOSH (2011b)
Effect
Liver
and
lung
tumors
Hepatic
effects
(vacuol
ation)
Uncertainty
Factors (UFs)
for
Benchmark
MOE2
Not
applicable
UFA= 3;
UFH=3;
Total UF=10
Hazard Value
Used in
Chronic Risk
Assessment
Inhalation
Unit Risk
(IUR):
4 x 10'5 per
ppm
(lxlO-5per
mg/m3)
1st percentile
human
equivalent
concentratio
n(HEC)i.e.
theHEC99:
17.2 mg/m3
(4.8 ppm)
Additional
Information3
Internal dose
BMDLio values
for each type of
tumor were
converted into
an IUR that
combined both
types of
tumors.
Allometric
scaling and
probabilistic
modeling were
used to
calculate the
hazard value
(i.e., HEC99)
from the rat
internal
BMDLio.
Reference
Mennear
etal.
(1988)
NTP
(1986)
Nitschke
etal.
(1988a)
2 Margin of Exposure (MOE) = (Non-cancer hazard value) 4- (Human Exposure). The benchmark MOE is used to interpret the MOEs and consists of the interspecies (UFA) and
intraspecies (UFn uncertainty factors. UF values were those used in the DCM IRIS assessment (EPA. 2011c).
3 for further information see Appendix J
Page 71 of 279
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3.3.1.3 Acute Hazard and Dose-Response Assessment
Workers and consumers can be exposed to a single (acute) exposure to DCM when handling
DCM-containing paint strippers. In this assessment, non-cancer risks following acute exposures
to DCM were assessed using the dose-response information (i.e., PODs) supporting the
derivations of the Spacecraft Maximum Allowable Concentrations (SMACsKNRC, 1996) and the
Acute Exposure Guideline Levels (AEGLs)(NAC, 2008). The assessment also evaluated acute risks
with the POD from the California acute reference exposure level (REL)(OEHHA, 2008), but the
SMAC POD was preferred over the REL POD for reasons explained in Sections 3.3.1.3.1 (SMACs)
and 3.3.1.3.2 (California's Acute REL). Although AEGLs are intended for emergency response
activities, the AEGL PODs were used in this assessment to evaluate acute risks associated with
discomfort/non-disabling (AEGL-1) and incapacitating (AEGL-2) effects following DCM exposure
from the use of paint strippers.
EPA/OPPT assumed that consumers would not generally perform paint stripping jobs on a
regular basis in their residences allowing sufficient time between exposures to clear DCM and
its metabolites from the body. This assumption was supported by DCM's short plasma half-life
(~40 min) (DiVincenzo et al., 1972). Evaluation of acute risks in occupational scenarios is
appropriate based on the assumption that some workers could be rotating tasks and not
necessarily using DCM-based paint strippers on a daily basis. This type of exposure would allow
the worker to clear DCM and its metabolites before the next encounter with the DCM-
containing paint stripper.
The consumer exposure modeling indicated that virtually all of the DCM release occurs within
2 hrs after product application for both spray and brush paint strippers. This is very shortly after
the last scraping is finished due to DCM's relatively high volatility (Appendix H, section H-l-1-4).
After the peak concentration is reached, the modeling showed that the concentration decline is
due almost exclusively to ventilation rather than to declining emissions. EPA/OPPT used these
observations as the basis to select acute hazard values (i.e., SMAC and AEGL PODs) applicable
to 1-hr exposures for consumer scenarios.
In contrast, for occupational scenarios, the California REL POD was time scaled to 8 hrs to
compare the hazard value to the 8-hr air concentration estimated from the monitoring data.
This assumed that the worker would be performing paint stripping activities during the entire
8-hr work shift. The 8-hr AEGL-2 was used to evaluate whether the 8-hr occupational exposures
estimates exceeded the threshold for disability. However, comparisons of consumer exposure
estimates with AEGLs incorporated AEGL PODs for shorter or longer time durations (i.e.,
10-min, 30-min, 4-hr and 8-hr) in addition to the 1-hr POD to evaluate a wider concentration-
time response.
Sections 3.3.1.3.1 (SMACs), 3.3.1.3.2 (AEGLs), and 3.3.1.3.3 (California's Acute REL) summarize
the approach and methodology used in the acute inhalation risk assessment. Appendix K
provides additional information about the definitions of the SMAC, AEGL and the California
acute REL values and how their respective PODs were derived.
Page 72 of 279
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3.3.1.3.1 SMACs
SMACs are developed by the U.S. National Academies (NAS) to provide guidance on chemical
exposures that may occur during normal operations of spacecraft as well as emergency
situations (NRC, 1996). EPA/OPPT used the SMACs dose-response assessment as the starting
point for deriving acute air concentrations for residential users of DCM-based paint strippers, as
well as other residential occupants that may be indirectly exposed (e.g., children, adults, the
elderly).
The DCM acute risk assessment used the acute POD of 350 mg/m3 (100 ppm) supporting the
derivation of the 1-hr SMAC. The POD was considered the NOAEL17 for central nervous system
(CNS) effects associated with the formation of 3% carboxyhemoglobin (COHb) in human blood
based on various human studies (Andersen et al., 1991; Astrand et al., 1975; DiVincenzo and
Kaplan. 1981: Peterson. 1978: Putzetal.. 1979: Ratneyetal.. 1974: Stewart et al.. 1972).
The 1-hr SMAC POD derivation relied on COHb levels in human blood as an indicator of CNS
depression since the metabolism of DCM produces carbon monoxide (CO) and carbon dioxide
(C02). Furthermore, there are extensive studies about the relationship between COHb blood
levels and human health adverse effects, primarily CNS effects. Thus, EPA/OPPT preferred the
1-hr SMAC POD over the 1-hr California acute REL (section 3.3.1.3.2) as the health protective
hazard value used to estimate acute risks for the consumer scenarios. The SMAC POD was
based on multiple human observations reporting increased COHb levels after DCM exposure,
coupled with the knowledge of what would be considered a NOAEL COHB level based on the
extensive CO database (NRC, 1996). However, the California acute REL POD was used to
estimate risks for occupational scenarios since an 8-hr SMAC POD was not available for the risk
calculations.
The SMAC assessment did not adjust the 1-hr POD with UFs as the intended audience for the
values is healthy astronauts. However, EPA/OPPT used a total UF of 10 as the benchmark MOE
when interpreting the MOE risk estimates. The total UF took into account a 10-fold factor for
variability within the human population based on the following reasons:
• an evaluation of the COHb data for different human subpopulations supports the approach
of retaining the default intraspecies UF of 10 under the premise that a level of 3% COHb is
considered protective of neurotoxic effects in most individuals (e.g., healthy individuals,
children), but may not be protective enough for patients with coronary artery disease and
the fetus (NRC, 2010). At COHb levels of 2 or 4%, patients with coronary artery disease may
experience a reduced time until onset of angina (chest pain) during physical exertion (Allred
et al., 1989a; Allred etal., 1989b, 1991). Other studies have also confirmed a reduced time
to onset of exercise-induced chest pain at a COHb between 2.5 and 4.5 percent (Anderson
etal., 1973; Aronowetal., 1972; Kleinman etal., 1989; Kleinman etal., 1998; Shepsetal.,
1987). Fetuses are at higher risk for CO toxicity because of higher CO affinity and slower CO
17
NOAEL= No-observed-adverse-effect level
Page 73 of 279
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elimination (NRC, 2010). There are no studies reporting effects on the unborn after a single
acute exposure resulting in lower COHb levels (EPA, 2000a; NRC, 2010);
• adult workers and consumers of both sexes are expected to be the users of DCM-based
paint strippers, whereas residential bystanders (i.e., individuals of any age) are expected to
be indirectly exposed to DCM; and
• no need to apply an interspecies UF for animal-to-human extrapolation because human
data were used to support the 1-hr SMAC POD.
Appendix K contains more information on the derivation of the 1-hr SMAC POD. Table 3-9 lists
the derivation information for the SMAC POD used in this assessment
3.3.1.3.2 California's Acute REL
Acute RELs are developed by the Office of Environmental Health Hazard Assessment (OEHHA)
from the State of California. The acute REL is defined as the concentration level at or below
which no adverse health effects are anticipated (i.e., one or eight hrs) in a human population,
including sensitive subgroups, exposed on an intermittent basis (OEHHA, 1999).
As an alternative approach to estimate acute inhalation risks, this assessment also considered
the POD of 840 mg/m3 (240 ppm) supporting the derivation of the 1-hr acute REL. The POD was
considered the LOAEL18 for subtle impairment of the nervous system function in humans based
on human volunteers exposed to 195 ppm DCM (696 mg/m3) for 1.5 hrs (Putzetal., 1979). The
1.5-hr exposure concentration was then time-scaled to obtain the 1- or 8-hrs PODs of
840 mg/m3 (240 ppm) and 290 mg/m3 (80 ppm), respectively. As discussed in Section 3.3.1.3.1,
EPA/OPPT preferred the 1-hr SMAC POD to estimate acute risks because the hazard value was
based on multiple human observations reporting increased COHb levels after DCM exposure,
coupled with the knowledge of what would be considered a NOAEL COHB level based on the
extensive CO database (NRC, 1996).
EPA/OPPT used a total UF of 60 as the benchmark MOE when interpreting the MOE risk
estimates based on the acute REL POD. The total UF consisted of an intraspecies UF of 10 to
account for human variability and a LOAEL-to-NOAEL UF19 of 6 (OEHHA. 2008).
Appendix K contains more information on the derivation of the 1-hr REL POD. Table 3-9 lists the
derivation information for the REL POD used in this assessment.
18 LOAEL= Lowest-observed-adverse-effect level
19 The acute REL documentation does not provide the basis for the selection of a LOAEL-to-NOAEL UF of 6.
Page 74 of 279
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3.3.1.3.3 AEGLs
AEGLs are emergency response values designed for once-in-a-lifetime exposures to airborne
chemicals. AEGL values are threshold levels developed for three different health effect end
point tiers (discomfort/non-disabling effects = AEGL-1 threshold; disability = AEGL-2 threshold;
and death = AEGL-3 threshold) and different durations of exposure (10 min; 30 min; 1 hr; 4 hrs;
and 8 hrs) within the constraints of available data.
An AEGL threshold represents an estimated point of transition between one defined set of
symptoms or adverse effects in one tier and another defined set of symptoms or adverse
effects in the next tier (NRC, 2001). This concept is reflected in the definition of AEGLs which
describe AEGLs as maximum airborne concentrations above which there is an increasing
likelihood of the adverse effects associated with the respective AEGL tiers. In other words,
AEGL-2 and -3 values are not safe and are in the range where some human response may be
anticipated. The AEGL values are intended to protect the general public, including susceptible
individuals such as infants, children, the elderly, persons with asthma, and those with other
illnesses in the context of emergency-related chemical releases, and not consumer exposures
(NRC. 2001).
Recent reports have documented human fatalities among bathtub refinishers using DCM-based
paint stripping products (CDC, 2012; Chester et al., 2012). Such real-life situations support our
current risk approach of evaluating how far the acute consumer and occupational exposure are
from the thresholds for discomfort/non-disabling effects (AEGL-1) and disability (AEGL-2).
EPA/OPPT used these comparisons to provide an indicator of whether the exposure estimates
would be expected to produce human adverse effects following DCM exposure. Please note
that the comparisons to the AEGL-3 PODs were not included in this assessment as none of the
DCM air concentrations for the occupational and consumer scenarios exceeded the AEGL-3 POD
threshold for lethal effects. However, a summary of the AEGL-3 POD derivations is included in
Appendix K for reference.
The scientific literature supports two relevant toxicity endpoints for acute exposures to DCM:
(1) CNS depression related to the brain concentration of DCM itself; and (2) COHb formation in
the blood (NRC, 2008). Taking this into consideration, PBPK modeling was used to calculate
AEGL PODs based on DCM concentrations in brain and peak COHb in blood. CNS effects drove
the setting of AEGL values for the shorter exposure durations, whereas formation of COHb
determined the AEGL values for longer exposure durations. This is consistent with the
observations that CNS effects occur soon after the onset of exposure, while peak levels of COHb
in blood can be reached hours later after cessation of exposure. Also the metabolic pathway
leading to the formation of carbon monoxide is saturable around 500 ppm (NAC, 2008).
Table 3-9 describes the AEGL-1 and -2 PODs that EPA/OPPT used in the acute risk assessment. It
also summarizes derivation information for the AEGL PODs with more detailed information
found in Appendix K.
Page 75 of 279
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Table 3 9. Non Cancer Hazard Values Used in the Risk Evaluation of Acute Exposures to Workers and Consumers Using DCM Based
Paint Strippers
Reference
Value
SMAC
California
Acute PEL
AEGL-1
(threshold
for
discomfort/
non-
disabling
effects)
Target
Organ/
System
Central
Nervous
System
Central
Nervous
System
Central
Nervous
System
(Direct
effect in
brain)
Species
Human
Human
Human
Route of
Exposure
and
Exposure
Concen-
trations1
Inhalation
COHb data
from
several
sources
Inhalation
195 ppm
(696
mg/m3)
Inhalation
213 to
986 ppm
Duration
Ihr
90 min
(1.5 hrs)
60-
120 min
(1-2 hrs)
POD Type
NOAEL = 100 ppm
(350 mg/m3)
supported by
various human
studies
LOAEL = 195 ppm
(696 mg/m3) at 90
minutes (Putzet a/.,
1979) or 240 ppm
(840 mg/m3) when
time adjusted to a
60-min exposure
No observed effect
forslightCNS
effects at 1-hr
exposure to 514
ppm (1,840 mg/m3)
equivalent to a
brain concentration
of 0.063 mM.
Effect
CNS depression
related to
formation of 3%
COHb in blood
Impaired
performance on
dual-task and
auditory
vigilance tests in
humans
No effect level
for light-
headedness,
difficulties in
enunciation
Hazard Value
Used in Acute
Risk
Assessment
100 ppm
(350 mg/m3)
l-hrRELPOD=
240 ppm
(840 mg/m3)
8-hrRELPOD=
80 ppm
(290 mg/m3)
10-min =
870 ppm
(3,000 mg/m3)
4
30-min =
690 ppm
(2,400 mg/m3)
4
l-hr =
600 ppm
(2,130 mg/m3)
4
Uncertainty
Factors (UFs)
for
Benchmark
MOE 2'3
UFs were not
applied to the
1-hr SMAC.
However,
EPA/OPPT
applied a
UFH=10inthe
acute risk
assessment
to account
for human
variability.
UFH=10;
UFL=6;
Total UF=60
UFH = 3
Total UF = 3
Additional
Information
NOAELsforCNS
depression have not
been reported for
DCM exposures. A
linear regression
analysis estimated
the DCM
concentration
(350 mg/m3) that
produces ~3 percent
COHb concentration
in blood (NOAEL)
ten Berge equation
(Cnxt = k, n = 2) was
used for time
adjustment from 90
to 60 min or 480 min
(8 hrs).
PBPK model was
used. Time scaling
was based on
maximum DCM
concentration in
human brain. AEGL
PODsfor4-and 8-hr
were not calculated
since they would be
above the
corresponding AEGL-
2 values.
Reference
NRC
(1996,
2008)
OEHHA
(2008)
NAC
(2008)
Page 76 of 279
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Table 3 9. Non Cancer Hazard Values Used in the Risk Evaluation of Acute Exposures to Workers and Consumers Using DCM Based
Paint Strippers
Reference
Value
AEGL-2
(threshold
for
disability) 5
Target
Organ/
System
Central
Nervous
System
(Direct
effect in
brain or
COHb
formation
in blood)
Species
Human
Route of
Exposure
and
Exposure
Concen-
trations1
Inhalation
CNS
effects:
195 to
751 ppm
COHb
formation:
0, 117 or
253 ppm
(0, 420, or
900
mg/m3)
Duration
CNS
effects:
Up to
230 min
(3.8 hr)
COHb
formation
50-70
min
POD Type
CNS effects:
DCM concentration
in human brain of
0.137 mM
equivalent to a 230-
min exposure to
751 ppm
COHb formation:
No observed effect
level (NOEL) of 4%
COHb
Effect
CNS effects:
Absence of CNS
effects in
humans
COHb formation:
COHb formation
in patients with
coronary artery
disease
Hazard Value
Used in Acute
Risk
Assessment
10-min= 1,700
ppm (6,000
mg/m3)6
30-min= 1,200
ppm (4,200
mg/m3)6
l-hr= 560
ppm (2,000
mg/m3)7
4-hr= 100
ppm
(350 mg/m3)7
8-hr= 60 ppm
(210 mg/m3)7
Uncertainty
Factors (UFs)
for
Benchmark
MOE 2'3
UFH=1
Total UF = 1
Additional
Information
PBPK model was
used. Time scaling
was based on
maximum DCM
concentration in
human brain (10 and
30 minutes) or on
COHb formation (1-,
4-, and 8-hr
exposure)
Reference
NAC
(2008)
NRC
(2010)
Notes:
1 Airborne concentration conversion factor for DCM is 3.47 mg/m3 per ppm NIOSH (2011b)
2 Margin of Exposure (MOE) = (Non-cancer hazard value, POD) -f (Human Exposure). The benchmark MOE is used to interpret the MOEs and consists of UFs.
3 UFH=intraspecies UF; UFL=LOAEL-to-NOAEL UF
4 These are the AEGL PODs without the 3X intraspecies UF adjustment.
5 PBPK modeling was used to predict both the DCM concentration in brain and COHb levels. The toxic endpoint (CNS effects or COHb formation) changed over
the exposure range of 10 min to 8 hrs. CNS effects determined the AEGL values for the shorter exposure durations, whereas formation of COHb determined the
AEGL values for longer exposure durations. This is consistent with the observations that CNS effects occur soon after the onset of exposure, while peak levels of
COHb in blood can be reached hours later after cessation of exposure. Also the metabolic pathway of carbon monoxide is saturable around 500 ppm (NAC,
2008).
6 AEGL derivations were driven by CNS effects.
7 AEGL derivations were driven by COHb formation.
Page 77 of 279
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3.3.2 Human Health Hazard Summary
The information presented in this section is not intended to be an exhaustive discussion of
DCM's toxicity, but rather a summary of its toxicity via the inhalation route of exposure. The
section also summarizes the absorption, distribution, metabolism and excretion of DCM. Thus,
the reader is referred to the original documents for detailed toxicity data supporting the
summary presented in this document.
J3^3L2^^
DCM is rapidly absorbed through inhalation exposure. The pulmonary uptake of DCM ranges
roughly from 40 to 60 percent (Andersen et al., 1991; Gamberale et al., 1975; Stewart et a I.,
1976), but may be up to 70 percent during the first minutes of exposure (Riley et al., 1966). The
uptake decreases with exposure duration and concentration (Peterson, 1978; Stewart et al.,
1976), and a steady-state absorption rate is generally achieved within 2 hrs for exposures up to
200 ppm (DiVincenzo and Kaplan, 1981; DiVincenzo et al., 1972).
Animal studies show that following absorption, DCM is rapidly distributed throughout the body,
including the liver, brain, and subcutaneous adipose tissue (ATSDR, 2000; Carlsson and
Hultengren, 1975; EPA, 2011c). DCM's plasma half-life is estimated to be 40 minutes after
inhalation exposure (ATSDR, 2000; DiVincenzo et al., 1972). Metabolism occurs predominantly
in the liver, although additional transformation occurs in the lungs and kidneys (ATSDR, 2000).
In the liver, metabolism of DCM involves two primary pathways. The first pathway produces CO
and C02, and saturation occurs at very low concentrations of a few hundred ppm. The second
pathway yields formaldehyde and formic acid, and saturation occurs at very high
concentrations (>10,000 ppm).
Acute toxic effects (i.e., CNS depression) may persist for hours after cessation of exposure
because of continued metabolism of DCM released from tissue storage (ATSDR, 1990). COHb
levels can continue to increase reaching peak levels as much as 5 to 6 hours after exposure
(ATSDR. 2000).
Elimination of DCM is predominantly through the lungs. Unchanged DCM also is found in small
amounts in the urine and feces (ATSDR, 2000). At low doses, a large percentage of DCM is
transformed into COHb and eliminated as CO, while at higher doses, more of the unchanged
parent compound is exhaled (ATSDR, 1990).
DCM has been detected in human breast milk (EPA, 1980; Pellizzari et al., 1982); thus, it is
possible that infants could be exposed to DCM through maternal exposures. However, PBPK
modeling suggests that lactating females who breast feed their infants will not deliver DCM in
quantities significant enough to be harmful (Fisher et al., 1997).
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Blood concentrations of DCM were below the level of detection in 1,165 individuals who
participated in the recent National Health and Nutrition Examination Survey (NHANES) 2003 to
2004 subsample of the U.S. population (CDC, 2009). DCM was present in the urine of workers
employed at a pharmaceutical factory. Urine levels appear to be nearly eliminated during the
overnight period after exposure has occurred (HSDB, 2012). Human health effects associated
with exposure to low environmental levels of DCM or low levels detected in biomonitoring
studies are unknown (CDC, 2009).
3.3.2.2 Human and Animal Toxicity Following Acute Exposure to DCM
Acute inhalation exposure of humans to DCM decreases the oxygen availability in the blood by
COHb formation. Acute exposure to DCM also results in neurological impairment from the
interaction of DCM with membranes in the nervous system (ACGIH, 2001; ATSDR, 2000; Bos et
al.. 2006: Cherry et al.. 1983: Gamberale et al.. 1975: Putz et al.. 1979: Winneke. 1974).
The organ most often affected in exposures to high levels of DCM is the brain. Effects on lung,
liver, or kidney have also been reported in humans as primary signs of DCM toxicity (NAC,
2008). In some cases, high COHb levels (i.e., up to 40 percent) are measured without serious
complaints. The reported COHb levels could not be linked to effects in a dose-related way in
any of the human observations (NAC, 2008).
Acute lethality in humans following inhalation exposure is related to CNS depressant effects.
These effects include loss of consciousness and respiratory depression, resulting in irreversible
coma, hypoxia, and eventual death (NAC, 2008). Especially at exposure to high concentrations
in which death occurs within a relatively short time, it is unlikely that the formation of CO will
have resulted in life-threatening levels of COHb (NAC, 2008). Only one fatal case was reported
to be related to a myocardial infarction (i.e., heart attack) without any signs of reported CNS
depression (NAC, 2008).
Acute non-lethal effects in humans are most frequently described as CNS-related only (NAC,
2008). Acute exposure to humans results in acute neurobehavioral deficits measured in
psychomotor tasks including: tests of hand-eye coordination, visual evoked response changes,
and auditory vigilance, which may occur at concentrations >200 ppm with 4-8 hrs of exposure
(ACGIH. 2001: ATSDR. 2000: Bos et al.. 2006: Cherry et al.. 1983: Gamberale et al.. 1975: Putz et
al., 1979; Winneke, 1974). In few cases, cardiotoxic effects (i.e., evidenced by
electrocardiogram [ECG] changes) were reported in humans (EPA, 2011c).
Neurological evaluations in animals during and after acute inhalation exposure to DCM (i.e.,
>200 to 1000 ppm for 1 to 8 hrs) have resulted in CNS depressant effects with decreased motor
activity, impaired memory, and changes in responses to sensory stimuli (EPA, 2011c). Several
neurological mediated parameters, including decreased activity (Heppel and Neal, 1944; Heppel
et al., 1944; Kjellstrand et al., 1985; Weinstein et al., 1972), impairment of learning and memory
(Alexeeff and Kilgore, 1983), and changes in responses to sensory stimuli (Rebert et al., 1989),
were reported from acute and short-term DCM exposure. Evidence of a localized
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immunosuppressive effect in the lung resulting from inhalation DCM exposure was seen in CD-I
mice acutely exposed to 100 ppm for 3 hrs (Aranyi et al., 1986).
3.3.2.3 Human and Animal Toxicity Following Repeated Exposures to DCM
3.3.2.3.1 Non-Cancer Effects
Relatively little is known about the long-term neurological effects of chronic low level DCM
exposures in humans, although there are studies that provide some evidence of an increased
prevalence of neurological symptoms among workers with average exposures of 75 to 100 ppm
(Cherry et al., 1981). Long-term effects on some neurological measures (i.e., possible
detriments in attention and reaction time in complex tasks) have been observed in retired
workers whose past chronic exposures were in the 100 to 200 ppm range (Lash et al., 1991).
These studies are limited by the relatively small sample sizes and their low power for detection
of statistically significant results (EPA, 2011c).
Following repeated inhalation exposure to DCM, the liver is the most sensitive target for non-
cancer toxicity in rats and mice. Lifetime exposure was associated with hepatocyte vacuolation
and necrosis in F344 rats exposed to 1,000 ppm for 6 hrs/day (Mennear et al., 1988; NTP,
1986), hepatocyte vacuolation in Sprague-Dawley rats exposed to 500 ppm for 6 hrs/day (Burek
et al., 1984; Nitschke et al., 1988a), and hepatocyte degeneration in B6C3Fi mice exposed to
2,000 ppm for 6 hrs/day (i.e., lower concentrations were not tested in mice) (Mennear et al.,
1988; NTP, 1986). Other effects were renal tubular degeneration in F344 rats and B6C3Fi mice
at 2,000 ppm, testicular atrophy in B6C3Fi mice at 4,000 ppm, and ovarian atrophy in B6C3Fi
mice at 2,000 ppm (EPA, 2011c).
Lung toxicity has also been reported in rodents exposed to DCM. In a 13-week exposure study
conducted by NTP (1986), rats exposed to 8,400 ppm DCM reported an increased incidence of
foreign body pneumonia (EPA, 2011c).
A two-generation inhalation exposure to DCM revealed no significant effects on reproductive
performance in rats (up to 1,500 ppm) (Nitschke et al., 1988b). Some evidence of a decrease in
fertility index was seen in male mice exposed to 150 and 200 ppm (Raje et al., 1988), and no
adverse effects on fetal development of mice or rats exposed to up to 1,250 ppm were seen by
(Schwetz et al., 1975). Decreases in fetal body weight and changes in behavioral habituation
were observed in offspring of Long-Evans rats exposed to 4,500 ppm during the gestational
period (Bornschein et al., 1980; Hardin and Manson, 1980).
Though few developmental effects were observed at high exposures to DCM (Bornschein et al.,
1980; Schwetz et al., 1975), there are no studies that have adequately evaluated
neurobehavioral and neurochemical changes resulting from gestational DCM exposure. The
available data identified changes in behavior habituation (Bornschein et al., 1980) and increases
in COHb (Schwetz et al., 1975) following DCM exposure (EPA, 2011c). (Bornschein et al., 1980)
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study observed developmental neurotoxicity effects at 4,500 ppm, this was the only dose group
used in the study. No other neurological endpoints have been evaluated in the available
developmental studies of DCM. The potential for developmental neurotoxicity occurring at low
exposures to DCM represents a data gap (EPA, 2011c).
The significance of this data gap also is supported by evidence from adult neurotoxicity testing
indicating that acute/short term exposures can affect neurotransmission and neurotransmitters
levels. These effects on neurotransmitters levels, while transient, may have qualitatively
different outcomes if they occur during development of the nervous system when
neurotransmitters serve a critical role in patterning the nervous system (Barone et al., 2000;
Rice and Barone, 2000).
3.3.2.3.2 Carcinogenic Effects
EPA concluded that DCM is likely carcinogenic in humans by a mutagenic mode of action (EPA,
2011c). The conclusion was based on evidence from both animal studies and epidemiological
data reporting DCM-induced carcinogenicity.
Studies in humans provide evidence for an association between occupational exposure to DCM
and increased risk for some specific cancers, including brain cancer (Hearne and Pifer, 1999;
Heinemanetal., 1994; Tomenson, 2011), liver cancer (Lanes etal., 1990; Lanes etal., 1993),
non-Hodgkin lymphoma (Barry etal., 2011; Miligiet al., 2006; Seidler et al., 2007; Wang etal.,
2009), and multiple myeloma (Gold etal., 2011).
In addition, several cancer bioassays in animals have identified the liver and lung as the most
sensitive target organs for DCM-induced tumor development (EPA, 2011c). For example,
B6C3F1 mice reported statistically significant increases in hepatocellular adenomas and
carcinomas when exposed to DCM for 2 years via drinking water (NCA, 1983; Serota et al.,
1986). Lung and liver tumors were reported in B6C3F1 mice exposed to 2,000 or 4,000 ppm
DCM for 6 hrs/day, 5 days/week for 2 years by inhalation (Mennear et al., 1988; NTP, 1986).
Inhalation animal studies have also reported benign mammary tumors in F344 rats exposed to
2,000 or 4,000 ppm DCM for 6 hrs/day, 5 days/week for 2 years (Mennear et al., 1988; NTP,
1986). Brain tumors were observed in a 2-year inhalation study that exposed Sprague-Dawley
rats to relatively low concentrations of DCM (0-500 ppm) (Nitschke et al., 1988a). These tumors
are exceedingly rare in rats, and there are few examples of statistically significant trends in
animal bioassays (Sills et al., 1999). Please refer to Chapter 4 and 5 of the DCM IRIS assessment
for detailed information about the epidemiological and animal studies evaluated in the cancer-
assessment, as well as their strengths and limitations (EPA, 2011c).
The hypothesized mode of action for DCM-induced lung and liver tumors is through a
mutagenic mode of carcinogenic action. A weight-of-evidence analysis of in vivo and in vitro
data provide support to the proposed mutagenicity of DCM and the key role of GST metabolism
and the formation of DNA-reactive GST-pathway metabolites (EPA, 2011c).
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3.3.2.4 Susceptible Subpopulations
Certain human subpopulations may be more susceptible to exposure to DCM than others. One
basis for this concern is the potential effect of COHb, a metabolic byproduct of DCM exposure.
The COHb generated from DCM is expected to be additive to COHb from other sources. Of
particular concern are smokers who maintain significant constant levels of COHb and persons
with existing cardiovascular disease (ATSDR, 2000).
Varying susceptibility to DCM may be correlated with polymorphism in its metabolizing
enzymes. Genetic polymorphisms have been identified for both GSTtheta-1 and CYP2E1 (Garte
and Crosti. 1999).
Hemoglobin in the fetus has a higher affinity for CO than does adult hemoglobin. Thus, the
neurotoxic and cardiovascular effects may be exacerbated in fetuses and in infants with higher
residual levels of fetal hemoglobin when exposed to high concentrations of DCM (OEHHA,
2001).
3.3.3 Summary of Hazard Values Used to Evaluate Acute and Chronic
Exposures
Table 3-10 summarizes the hazard values (i.e., PODs), adverse effects and UFs that are relevant
for the risk evaluation of acute and chronic exposure scenarios.
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Table 3 10. Summary of Inhalation Hazard Information Used in the Risk Evaluation of Acute
and Chronic Scenarios
Exposure
Duration
for Risk
Analysis
CHRONIC
EXPOSURE
ACUTE
EXPOSURE
Hazard Value Used in Risk Assessment
Inhalation Unit Risk (IUR):
4x 10'5 per ppm
(1 x 10'5 per mg/m3)
1st percentile human equivalent concentration (HEC) i.e. the HEC99:
17.2 mg/m3
(4.8 ppm)
1-hr SMACPOD= 100 ppm
(350 mg/m3)
1-hr California REL POD= 240 ppm
(840 mg/m3)
8-hr California REL POD=80 ppm
(290 mg/m3) (for occupational scenarios)
AEGL-1 POD (threshold for discomfort/non-disabling effects)
10-min= 870 ppm (3,000 mg/m3)
30-min= 690 ppm (2,400 mg/m3)
l-hr= 600 ppm (2,130 mg/m3)
AEGL-2 POD (threshold for disability)
10-min= 1,700 ppm (6,000 mg/m3)6
30-min= 1,200 ppm (4,200 mg/m3)6
l-hr= 560 ppm (2,000 mg/m3)7
4-hr= 100 ppm (350 mg/m3)7
8-hr= 60 ppm (210 mg/m3) 7
Effect
Liver and lung
tumors
Liver effects
Central nervous
system (CNS)
depression related
to the formation of
3% COHb in blood
Impairment of the
CNS
CNS effects
(light headedness,
difficulty in
enunciation)
CNS effects for 10-
and 30-min AEGL-2
PODs
COHb formation for
1-, 4- and 8-hr
AEGL-2 PODs
Total
Uncertainty
Factor (UF) for
Benchmark
MOE
Not applicable
Total UF=10
Total UF=10
Total UF=60
Total UF=3
Total UF=1
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3.4 HUMAN HEALTH RISK CHARACTERIZATION
Exposure to DCM is associated with adverse effects on the nervous system, liver and lung.
These non-cancer adverse effects are deemed important for acute and chronic risk estimation
for the scenarios and populations addressed in this risk assessment.
DCM is likely to be carcinogenic to humans. The cancer risk assessment uses the IUR derived in
the 2011 DCM IRIS assessment based on liver and lung tumors in rodents. The weight-of-
evidence analysis for the cancer endpoint was sufficient to conclude that DCM-induced tumor
development operates through a mutagenic mode of action (EPA, 2011c).
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3.4.1 Risk Estimation Approach for Acute and Repeated Exposures
Tables 3-11 and 3-12 show the use scenarios, populations of interest and toxicological
endpoints that were used for estimating acute or chronic risks, respectively.
Table 3 11. Use Scenarios, Populations of Interest and Toxicological Endpoints for Assessing Acute
Risks to DCM containing Paint Strippers
Use
Scenarios
Populations
And Toxicological
Approach
OCCUPATIONAL USE
RESIDENTIAL USE
Population of Interest and
Exposure Scenario:
Users
Adults of both sexes (>16 years old) exposed
to DCM during
an 8-hr workday 1>2
Adults of both sexes (>16 years old) typically
exposed to DCM for 1 hr. Other shorter
(10-min, 30-min) or longer exposure times
(4-hr, 8-hr) were also assumed when
comparing DCM air concentrations with
AEGLs.
Population of Interest and
Exposure Scenario:
Bystander
Adults of both sexes (>16 years old)
indirectly exposed to DCM while being in
the same building during product use.
Individuals of any age indirectly exposed to
DCM while being in the rest of the house
during product use.
Non-Cancer Health Effects: CNS effects and COHb formation in the blood (see Table 3-10).
Hazard Values (PODs)for Occupational
Scenarios:3
8-hr California REL POD= 290 mg/m3
8-hr AEGL-2 POD = 210 mg/m3
Health Effects of Concern,
Concentration and Time
Duration
Hazard Values (PODs)for Residential
Scenarios:
1-hr SMAC POD= 350 mg/m3
1-hr California REL POD= 840 mg/m3
10-min AEGL-1 POD= 3,000 mg/m3
30-min AEGL-1 POD = 2,400 mg/m3
1-hr AEGL-1 POD = 2,130 mg/m3
10-min AEGL-2 POD = 6,000 mg/m3
30-min AEGL-2 POD = 4,200 mg/m3
1-hr AEGL-2 POD = 2,000 mg/m3
4-hr AEGL-2 POD = 350 mg/m3
8-hr AEGL-2 POD = 210 mg/m3
Cancer Health Effects: Acute cancer risks were not estimated. Relationship is not known
between a single short-term exposure to DCM and the induction of cancer in humans.
Uncertainty Factors (UF)
used in Non-Cancer
Margin of Exposure (MOE)
calculations
UFforSMACPODs=10
UF for California REL POD= 60
UF for AEGL-1 PODs= 3
UF for AEGL-2 PODs= 1
Notes:
1 It is assumed no substantial buildup of DCM in the body between exposure events due to DCM's short biological half-life
(~40 min).
2 EPA/OPPT believes that the users of these products are generally adults, but younger individuals may be users of DCM-
based paint strippers.
3 AEGL-1 POD for 8-hr is not available since the DCM AEGL technical support document did not derive AEGL-1 values for
8-hrs.
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Table 3 12. Use Scenarios, Populations of Interest and Toxicological Endpoints for Assessing
Chronic Risks to DCM containing Paint Strippers
Use
Scenarios
Populations
And Toxicological
Approach
OCCUPATIONAL USE
Population of Interest and
Exposure Scenario:
Users
Adults of both sexes (>16 years old) exposed to DCM during
an 8-hr workday for up to 250 days per year for 40 working years depending on the
occupational scenario 1>2
Population of Interest and
Exposure Scenario:
Bystander
Adults of both sexes (>16 years old) indirectly exposed to DCM while being in the same
building during product use.3
Health Effects of Concern,
Concentration and Time
Duration
Hazard Value (PODs)
for Non-Cancer Effects
(liver effects):
1st percentile human equivalent
concentration (HEC) i.e. the HEC99:
17.2 mg/m3
(4.8 ppm)
Hazard Value (PODs)
for Cancer Effects
(liver and lung tumors):
Inhalation Unit Risk (IUR):
4 x 10"5 per ppm
(Ix 10'5 per mg/m3)
Uncertainty Factors (UF)
used in Non-Cancer
Margin of Exposure (MOE)
calculations
UFfortheHEC99 = 10
UF is not applied for the cancer risk calculations.
Notes:
1 It is assumed no substantial buildup of DCM in the body between exposure events due to DCM's short biological half-life
(~40 min).
2 EPA/OPPT believes that the users of these products are generally adults, but younger individuals may be users of DCM-
based paint strippers.
3 Data sources did not often indicate whether exposure concentrations were for occupational users or bystanders.
Therefore, EPA/OPPT assumed that exposures were for a combination of users and bystanders. Some bystanders may
have lower exposures than users, especially when they are further away from the source of exposure.
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Acute or chronic MOEs (MOEaCute or MOEchronic) were used in this assessment to estimate non-
cancer risks (Table 3-13).
Table 3 13. Margin of Exposure (MOE) Equation to Estimate Non Cancer Risks Following
Acute or Chronic Exposures to DCM
MOE acute or chronic = Non-cancer Hazard value (POD)
Human Exposure
MOE =
Hazard value (POD) =
Human Exposure =
Margin of exposure (unitless)
derived from various toxicological documents (see Tables 3-10, 3-11, 3-12)
Exposure estimate (in ppm) from occupational or consumer exposure
assessment. ADCs were used for non-cancer risks associated with chronic
exposures to DCM. Acute concentrations as expressed as 8-hr TWA DCM air
concentrations were used for acute risks.
Study-specific UFs were identified for each hazard value (i.e., POD). These UFs accounted for (1)
the variation in susceptibility among the members of the human population (i.e., inter-
individual or intraspecies variability); (2) the uncertainty in extrapolating animal data to humans
(i.e., interspecies uncertainty); and (3) the uncertainty in extrapolating from a LOAEL rather
than from a NOAEL.
The total UF for each non-cancer hazard value was the benchmark MOE used to interpret the
MOE risk estimates for each use scenario. The MOE estimate was interpreted as human health
risk if the MOE estimate was less than the benchmark MOE (i.e. the total UF). On the other
hand, the MOE estimate indicated negligible concerns for adverse human health effects if the
MOE estimate exceeded the benchmark MOE. Typically, the larger the MOE, the more unlikely
it is that a non-cancer adverse effect would occur.
Cancer risks for repeated exposures to DCM were estimated using the equation in Table 3-14.
Estimates of cancer risks should be interpreted as the incremental probability of an individual
developing cancer over a lifetime as a result of exposure to the potential carcinogen (i.e.,
incremental or excess individual lifetime cancer risk).
Table 3 14. Equation to Calculate Cancer Risks
Risk= Human Exposure x IUR
Risk =
Human exposure =
IUR =
Cancer risk (unitless)
Exposure estimate (LADC in ppm) from occupational exposure assessment
Inhalation unit risk 4 x 10"5 per ppm (1 x 10"5 per mg/m3) (EPA, 2011c)
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3.4.2 Acute Non-Cancer Risk Estimates for Inhalation Exposures to DCM
The acute inhalation risk assessment used CNS effects to evaluate the acute risks for consumer
and occupational use of DCM-containing paint strippers. Health hazard values were derived
from the SMAC and the California acute REL hazard/dose-response assessments. This
assessment gives preferences to those acute risk estimates derived from the SMAC
hazard/dose-response assessment because the SMAC POD was based on multiple human
observations reporting increased COHb levels after DCM exposure, coupled with the knowledge
of what would be considered a NOAEL COHb level based on the extensive CO database (NRC,
1996).
Hazard values based on the AEGL hazard/dose-response assessment were also included in the
acute risk assessment. As discussed in section 3.3.1.3.3, AEGL PODs for the respective tiers
(discomfort/non-disabling effects = AEGL-1 threshold; disability = AEGL-2 threshold; and death
= AEGL-3 threshold) are selected to represent an estimated point of transition between one
defined set of symptoms or adverse effects in one tier and another defined set of symptoms or
adverse effects in the next tier (NRC, 2001). Although the AEGL PODs and total UFs do not have
the degree of conservatism that other values have, EPA/OPPT used them in this assessment to
gauge how far the acute consumer and occupational exposure are from the thresholds for
discomfort/non-disabling effects (AEGL-1) and disability (AEGL-2). These comparisons provide
an indicator of whether the exposure estimates would be expected to produce human adverse
effects following DCM exposure.
3.4.2.1 Acute Risks for Consumer Exposure Scenarios
Acute inhalation risks for CNS effects were reported for all of the consumer exposure scenarios
when risks were evaluated with the SMAC and the California acute REL PODs and respective
benchmark MOEs. There risks were reported for both the product user and the residential
bystanders exposed to DCM, irrespective of the type of product used (i.e., brush-on vs. spray-
on paint stripper) (Table 3-15).
Consumers using DCM-based paint strippers reported risk concerns for non-disabling effects
(AEGL-1) during the first hour of product use (i.e., 10-min, 30-min or 1-hr exposure). For
instance, MOEs based on the AEGL-1 PODs were lower than the benchmark MOE for users
using brush-on and spray-on products in those scenarios constructed with upper-end estimates
for either the user or the user and bystanders (Scenarios 2, 3, 5 and 6) (Table 3-16).
Likewise, risk concerns for incapacitating effects (AEGL-2) in product users were observed in
Scenarios 2, 3, 5 and 6 at longer exposure times (i.e., 4-hr or 8-hrs). Interestingly, these risks
were also reported for residential bystanders in Scenarios 3 and 6, where upper end user and
bystander parameters were used to construct the scenarios (Table 3-16).
The bathroom scenario (#7) was constructed to simulate a human fatality case during a bathtub
refinishing project. It was included in the assessment to estimate the DCM air concentrations to
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residential occupants outside the use zone (i.e., bystanders) under conditions of high product
use in the room of use. As expected, risk concerns for incapacitating effects (AEGL-2) were seen
in users exposed to DCM for 4- and 8-hrs. Similarly, the users showed risks for non-disabling
effects (AEGL-1) during the first hour of product use (i.e., 10-min, 30-min or 1-hr). Bystanders
did not show risk concerns for non-disabling (AEGL-1) and incapacitating (AEGL-2) effects at any
of the exposure durations (i.e., 10-min, 30-min, 1-hr, 4-hr or 8-hr) (Table 3-16).
Table 3 15. Acute Risk Estimates for Residential Exposures to DCM Based Paint Strippers:
SMAC and California's REL PODs. MOEs below benchmark MOE indicate
potential health risks and are denoted in bold text
Exposure
Scenario
Scenario #1
Brush application in
workshop,
central parameter values
Scenario #2
Brush application in
workshop,
upper-end values for user
Scenario #3
Brush application in
workshop, upper-end
values for user and
bystander estimates
Scenario #4
Spray application in
workshop, central
parameter values
Scenario #5
Spray application in
workshop, upper-end
values for user
Scenario #6
Spray application in
workshop, upper-end
values for user and
bystander estimates
Scenario #7
Brush application in
bathroom, simulation
Individual
User
Bystander
User
Bystander
User
Bystander
User
Bystander
User
Bystander
User
Bystander
User
Bystander
Maximum
Value for
1-hr
Averaging
Period
(mg/m3)
220
120
1,100
210
760
460
490
280
1,600
310
1,100
700
799
218
Margin of Exposure (MOE)
1-hr SMAC POD
Total UF or
Benchmark
MOE=10*Preferred
Approach
1.6
2.9
0.3
1.7
0.5
0.8
0.7
1.3
0.2
1.1
0.3
0.5
0.4
1.6
1-hr California REL POD
Total UF or
Benchmark MOE=60
3.8
7.0
0.8
4.0
1.1
1.8
1.7
3.0
0.5
2.7
0.8
1.2
1.1
3.9
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Table 3 16. Acute Risk Estimates for Residential Exposures to DCM Based Paint Strippers: AEGL 1 and AEGL 2 PODs for Various
Exposure Durations. MOEs below benchmark MOE indicate potential health risks and are denoted in bold text
Consumer
Scenario
Scenario #1:
Brush
application in
workshop,
central
parameter
estimates
Scenario #2:
Brush
application in
workshop,
upper-end user
estimates
Scenario #3:
Brush
application in
workshop,
upper-end user
and bystander
estimates
Scenario #4:
Spray
application in
Individual
User
Bystander
User
Bystander
User
Bystander
User
Maximum Values for Averaging
Period, mg/m3
10-
min
380
130
1,300
220
1,200
470
780
30-
min
270
130
1,100
220
900
470
600
1-hr
220
120
1,100
210
760
460
490
4-hr
120
82
420
140
560
380
270
8-hr
69
49
220
82
400
290
150
Margin of Exposure (MOE)
AEGL-l PODs
Total UF or Benchmark
MOE =3
10-min
(3,000
mg/m3)
7.9
23.1
2.3
13.6
2.5
6.4
3.8
30-min
(2,400
mg/m3)
8.9
18.5
2.2
10.9
2.7
5.1
4.0
1-hr
(2,130
mg/m3)
9.7
17.8
1.9
10.1
2.8
4.6
4.3
AEGL-2 PODs
Total UF or Benchmark MOE =1
10-min
(6,000
mg/m3)
15.8
46.2
4.6
27.3
5.0
12.8
7.7
30-min
(4,200
mg/m3)
15.6
32.3
3.8
19.1
4.7
8.9
7.0
1-hr
(2,000
mg/m3)
9.1
16.7
1.8
9.5
2.6
4.3
4.1
4-hr
(350
mg/m3)
2.9
4.3
0.8
2.5
0.6
0.9
1.3
8-hr
(210
mg/m3)
3.0
4.3
1.0
2.6
0.5
0.7
1.4
Page 90 of 279
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Table 3 16. Acute Risk Estimates for Residential Exposures to DCM Based Paint Strippers: AEGL 1 and AEGL 2 PODs for Various
Exposure Durations. MOEs below benchmark MOE indicate potential health risks and are denoted in bold text
Consumer
Scenario
workshop,
central
parameter
estimates
Scenario #5:
Spray
application in
workshop,
upper-end user
estimates
Scenario #6:
Spray
application in
workshop,
upper-end user
and bystander
estimates
Scenario #7:
Brush
application in
bathroom,
simulation
Individual
Bystander
User
Bystander
User
Bystander
User
Bystander
Maximum Values for Averaging
Period, mg/m3
10-
min
300
1,900
330
1,600
710
1,455
224
30-
min
300
1,800
320
1,300
710
887
222
1-hr
280
1,600
310
1,100
700
799
218
4-hr
190
620
200
810
580
536
187
8-hr
110
330
120
580
430
340
150
Margin of Exposure (MOE)
AEGL-l PODs
Total UF or Benchmark
MOE =3
10-min
(3,000
mg/m3)
10.0
1.6
9.1
1.9
4.2
2.1
13.4
30-min
(2,400
mg/m3)
8.0
1.3
7.5
1.8
3.4
2.7
10.8
1-hr
(2,130
mg/m3)
7.6
1.3
6.9
1.9
3.0
2.7
9.8
AEGL-2 PODs
Total UF or Benchmark MOE =1
10-min
(6,000
mg/m3)
20.0
3.2
18.2
3.8
8.5
4.1
26.8
30-min
(4,200
mg/m3)
14.0
2.3
13.1
3.2
5.9
4.7
18.9
1-hr
(2,000
mg/m3)
7.1
1.3
6.5
1.8
2.9
2.5
9.2
4-hr
(350
mg/m3)
1.8
0.6
1.8
0.4
0.6
0.7
1.9
8-hr
(210
mg/m3)
1.9
0.6
1.8
0.4
0.5
0.6
1.4
Page 91 of 279
-------
3.4.2.2 Acute Risks for Occupational Exposure Scenarios
Acute inhalation risks for CNS effects were reported for most of the relevant industries when
occupational risks were evaluated with the California acute REL POD and respective benchmark
MOE. These risks were irrespective of the absence or presence of respirators and were
observed with central tendency or high-end DCM air concentrations. No risks were found for
workers handling DCM-based strippers in the art restoration and conservation industry
(Table 3-17).
Workers handling DCM-contain ing paint strippers with no respirator showed risks for
incapacitating effects (AEGL-2) when employed in all of the relevant industries, except the art
restoration and conservation industry (Table 3-17). These risks were present with either central
tendency or high-end DCM air concentrations of DCM.
Workers employed in industries with high exposure to DCM [i.e., professional contractors,
furniture refinishing, aircraft paint stripping, and immersion stripping of wood (non-specific
workplace settings)] typically showed risks for incapacitating (AEGL-2) effects when using APF
10 respirators (Scenario 2) during high exposure conditions. The use of APF 25 respirators
(Scenario 3) was not protective for workers employed in the immersion stripping of wood (non-
specific workplace settings when DCM air concentrations were as high as 7,000 mg/m3.
Page 92 of 279
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Table 3 17. Acute Risk Estimates for Occupational Exposures to DCM Based Paint Strippers: AEGL 1 and AEGL 2 PODs for Various
Exposure Durations. MOEs below benchmark MOE indicate potential health risks and are denoted in bold text
Professional
Contractors
Scenario 1 (No
respirator, APF=0)
Scenario 2
(Respirator, APF 10)
Scenario 3
(Respirator, APF 25)
Scenario 4
(Respirator, APF 50)
Automotive
Refinishing
Scenario 1 (No
respirator, APF=0)
Scenario 2
(Respirator, APF 10)
Scenario 3
(Respirator, APF 25)
Scenario 4
(Respirator, APF 50)
Furniture
Refinishing
Scenario 1 (No
respirator, APF=0)
Scenario 2
(Respirator, APF 10)
Scenario 3
(Respirator, APF 25)
Scenario 4
(Respirator, APF 50)
Acute 8-hr concentration (mg/m3)
Mean
High
2,98
0
298
119
60
Midpoint
1,520
152
61
30
Low
60
6
2
1
Acute 8-hr concentration (mg/m3)
Mean
253
25
10
5
High
416
42
17
8
Midpoint
253
25.3
10
5
Low
90
9
4
2
Acute 8-hr concentration (mg/m3)
Mean
499
49.9
20
10
High
2,24
5
225
90
45
Midpoint
1,125
113
45
23
Low
4
0.4
0.2
0.1
Acute MOE (8hr-REL POD=290 mg/m3)
Total UF or Benchmark MOE=60
Mean
High
0.1
1
2
5
Midpoint
0.2
2
5
10
Low
5
48
121
242
Acute MOE (8hr-REL POD=290 mg/m3)
Total UF or Benchmark MOE=60
Mean
1
12
29
57
High
0.7
7
17
35
Midpoint
1
12
29
57
Low
3
32
81
161
Acute MOE (8hr-REL POD=290 mg/m3)
Total UF or Benchmark MOE=60
Mean
0.6
6
15
29
High
0.1
1.3
3
6
Midpoint
0.3
2.6
6
13
Low
73
725
1813
3625
Acute MOE (8hr-AEGL-2 POD=210 mg/m3)
Total UF or Benchmark MOE=1
Mean
High
0.07
0.7
1.8
4
Midpoint
0.1
1.4
4
7
Low
4
35
88
175
Acute MOE (8hr-AEGL-2 POD=210 mg/m3)
Total UF or Benchmark MOE=1
Mean
0.8
8
21
42
High
0.5
5
13
25
Midpoint
0.8
8
21
42
Low
2
23
58
117
Acute MOE (8hr-AEGL-2 POD=210 mg/m3)
Total UF or Benchmark MOE=1
Mean
0.4
4
11
21
High
0.1
0.9
2
5
Midpoint
0.2
2
5
9
Low
53
525
1312
2625
Page 93 of 279
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Table 3 17. Acute Risk Estimates for Occupational Exposures to DCM Based Paint Strippers: AEGL 1 and AEGL 2 PODs for Various
Exposure Durations. MOEs below benchmark MOE indicate potential health risks and are denoted in bold text
Art Restoration
and
Conservation
Scenario 1 (No
respirator, APF=0)
Scenario 2
(Respirator, APF 10)
Scenario 3
(Respirator, APF 25)
Scenario 4
(Respirator, APF 50)
Aircraft Paint
Stripping
Scenario 1 (No
respirator, APF=0)
Scenario 2
(Respirator, APF 10)
Scenario 3
(Respirator, APF 25)
Scenario 4
(Respirator, APF 50)
Graffitti
Removal
Scenario 1 (No
respirator, APF=0)
Scenario 2
(Respirator, APF 10)
Scenario 3
(Respirator, APF 25)
Scenario 4
(Respirator, APF 50)
Acute 8-hr concentration (mg/m3)
Mean
High
Midpoint
Low
2
0.2
0.1
0.04
Acute 8-hr concentration (mg/m3)
Mean
High
3,80
2
380
152
76
Midpoint
1,944
194
78
39
Low
86
9
3
2
Acute 8-hr concentration (mg/m3)
Mean
260
26
10
5
High
1,18
8
118.
8
48
24
Midpoint
603
60.3
24
12
Low
18
1.8
0.7
0.4
Acute MOE (8hr-REL POD=290 mg/m3)
Total UF or Benchmark MOE=60
Mean
High
Midpoint
Low
145
1450
3625
7250
Acute MOE (8hr-REL POD=290 mg/m3)
Total UF or Benchmark MOE=60
Mean
High
0.1
1
2
4
Midpoint
0.2
1.5
4
7
Low
3
34
84
167
Acute MOE (8hr-REL POD=290 mg/m3)
Total UF or Benchmark MOE=60
Mean
1
11
28
56
High
0.2
2
6
12
Midpoint
0.5
5
12
24
Low
16
161
403
806
Acute MOE (8hr-AEGL-2 POD=210 mg/m3)
Total UF or Benchmark MOE=1
Mean
High
Midpoint
Low
105
1050
2625
5250
Acute MOE (8hr-AEGL-2 POD=210 mg/m3)
Total UF or Benchmark MOE=1
Mean
High
0.1
0.6
1
3
Midpoint
0.1
1
3
5
Low
2
24
61
122
Acute MOE (8hr-AEGL-2 POD=210 mg/m3)
Total UF or Benchmark MOE=1
Mean
0.8
8
20
40
High
0.2
2
4
9
Midpoint
0.4
3
9
17
Low
12
117
292
583
Page 94 of 279
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Table 3 17. Acute Risk Estimates for Occupational Exposures to DCM Based Paint Strippers: AEGL 1 and AEGL 2 PODs for Various
Exposure Durations. MOEs below benchmark MOE indicate potential health risks and are denoted in bold text
Non-Specific
Workplace Settings
- Immersion
Stripping of Wood
Scenario 1 (No
respirator, APF=0)
Scenario 2
(Respirator, APF 10)
Scenario 3
(Respirator, APF 25)
Scenario 4
(Respirator, APF 50)
Non-Specific
Workplace Settings
- Immersion
Stripping of Wood
and Metal
Scenario 1 (No
respirator, APF=0)
Scenario 2
(Respirator, APF 10)
Scenario 3
(Respirator, APF 25)
Scenario 4
(Respirator, APF 50)
Non-Specific
Workplace Settings
- Unknown
Scenario 1 (No
respirator, APF=0)
Scenario 2
(Respirator, APF 10)
Scenario 3
(Respirator, APF 25)
Scenario 4
(Respirator, APF 50)
Acute 8-hr concentration (mg/m3)
Mean
High
7,00
0
700
280
140
Midpoint
3,518
352
141
70
Low
35
4
1
0.7
Acute 8-hr concentration (mg/m3)
Mean
High
1,01
7
101.
7
41
20
Midpoint
825
83
33
17
Low
633
63
25
13
Acute 8-hr concentration (mg/m3)
Mean
357
36
14
7
High
428
43
17
9
Midpoint
357
36
14
7
Low
285
29
11
6
Acute MOE (8hr-REL POD=290 mg/m3)
Total UF or Benchmark MOE=60
Mean
High
0.04
0.4
1
2
Midpoint
0.1
0.8
2
4
Low
8
83
207
414
Acute MOE (8hr-REL POD=290 mg/m3)
Total UF or Benchmark MOE=60
Mean
High
0.3
3
7
14
Midpoint
0.4
4
9
18
Low
0.5
5
11
23
Acute MOE (8hr-REL POD=290 mg/m3)
Total UF or Benchmark MOE=60
Mean
0.8
8
20
41
High
0.7
7
17
34
Midpoint
0.8
8
20
41
Low
1
10
25
51
Acute MOE (8hr-AEGL-2 POD=210 mg/m3)
Total UF or Benchmark MOE=1
Mean
High
0.03
0.3
0.8
2
Midpoint
0.1
0.6
1.5
3
Low
6
60
150
300
Acute MOE (8hr-AEGL-2 POD=210 mg/m3)
Total UF or Benchmark MOE=1
Mean
High
0.2
2
5
10
Midpoint
0.3
3
6
13
Low
0.3
3
8
17
Acute MOE (8hr-AEGL-2 POD=210 mg/m3)
Total UF or Benchmark MOE=1
Mean
0.6
6
15
29
High
0.5
5
12
25
Midpoint
0.6
6
15
29
Low
0.7
7
18
37
Page 95 of 279
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3.4.3 Non-Cancer and Cancer Risk Estimates for Chronic Inhalation
Exposures to DCM
Non-cancer and cancer risk estimates for inhalation exposures to DCM were only derived for
occupational scenarios since the exposures for consumer uses were not considered chronic in
nature. Hazard values were obtained from the EPA IRIS lexicological Review of Methylene
Chloride (EPA. 2011c).
3.4.3.1 Cancer Risks for Occupational Exposure Scenarios
The cancer risk assessment evaluated the incremental individual lifetime cancer risks for
continuous exposures to DCM occurring during the use of paint stripping products. Excess
cancer risks were calculated by multiplying the EPA inhalation unit risk for DCM (EPA, 2011c) by
the exposure estimate (i.e., LADC). Cancer risks were expressed as number of cancer cases per
million.
Occupational scenarios assumed that the exposure frequency (i.e., the number of days per year
workers or bystanders are exposed to DCM) was either 125 or 250 days per year for an
occupational exposure duration of 20 or 40 years over a 70-yr lifespan. It is recognized that the
combination of these assumptions may yield conservative cancer risk estimates for some of the
occupational scenarios evaluated in this assessment. Nevertheless, EPA/OPPT does not have
additional information for further refinement of the exposure assumptions.
EPA typically uses a benchmark cancer risk level between IxlO"4 and IxlO"6 for determining the
acceptability of the cancer risk in a population. Since the benchmark cancer risk level will be
determined during risk management, the occupational cancer risk estimates were compared to
three benchmark levels within EPA's acceptability range. The benchmark levels were:
1. IxlO"6: the probability of 1 chance in 1 million of an individual developing cancer;
2. IxlO"5: the probability of 1 chance in 100,000 of an individual developing cancer, which
is equivalent to 10 cancer cases in 1 million;
3. IxlO"4: the probability of 1 chance in 10,000 of an individual developing cancer, which is
equivalent to 100 cancer cases in 1 million.
Tables 3-18 to 3-26 show the excess cancer risks calculated for workers of different industries
handling DCM-based paint strippers. Selected scenarios ranging from the highest exposure
scenario (i.e., no respiratory protection and high end values for EF and WY-i.e., Scenario 1) to
the lowest exposure scenario (e.g., respiratory protection APF 50 and midpoints for EF and
WY-Scenario 16) were included in the tables. Calculations of cancer risks for the full set of
industries and scenarios are provided in the supplemental Excel spreadsheet, DCM Exposure
and Risk Estimates_081114.xlsx.
Workers showed excess cancer risks for all of the industries evaluated when working with DCM-
based paint strippers for 250 days/year for 40 years with no respiratory protection (Scenario 1).
Generally, Scenario 1 exceeded the three target cancer levels with the exception of art
restoration and conservation that only exceeded the IxlO"6 target level.
Page 96 of 279
-------
On the other hand, workers showed a reduction in cancer risks when working for 125 days/year
for 20 years with adequate respiratory protection (Scenario 16). That reduction in excess cancer
risk was one or two orders of magnitude depending on the industry involved in paint stripping
activities when compared with Scenario 1.
For Scenarios 3 and 15, occupational cancer risks for the different industries fell between the
risks calculated for Scenario 1 and 16, and generally exceeded one or more benchmark cancer
levels when workers were exposed to high or midpoint DCM air concentrations.
Table 3 18. Occupational Cancer Risks for Professional Contractors (Scenarios 1, 3, 15 and 16)
s*
V
Lowest Exposure Highest Exposure
Professional
Contractors
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
LADC(mg/m3)
** LADCs for scenarios 2 to 16 have
been adjusted with the multiplier
High
389
16
4
2
Midpoint
198
8
2
1
Low
8
0.31
0.08
0.04
Excess Cancer Risk
(Inhalation Unit Risk =
IxlO'5 per mg/m3)
High
3.9E-03
1.6E-04
3.9E-05
1.9E-05
Midpoint
2.0E-03
7.9E-05
2.0E-05
9.9E-06
Low
7.8E-05
3.1E-06
7.8E-07
3.9E-07
Page 97 of 279
-------
Table 3 19. Occupational Cancer Risks for Automotive Refinishing (Scenarios 1, 3, 15 and 16)
s*
t =
V)
O
Q.
X
LLJ
tt
01
DO
X
s
3
V)
o
Q.
X
LLJ
tt
01
—I
Automotive
Refinishing
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
LADC(mg/m3)
** LADCs for scenarios 2 to 16 have
been adjusted with the multiplier
Mean
33
1
0.3
0.2
High
54
2
1
0.3
Midpoint
33
1
0.33
0.2
Low
12
0.48
0.12
0.1
Excess Cancer Risk
(Inhalation Unit Risk =
IxlO"5 per mg/m3)
Mean
3.3E-04
1.3E-05
3.3E-06
1.7E-06
High
5.4E-04
2.2E-05
5.4E-06
2.7E-06
Midpoint
3.3E-04
1.3E-05
3.3E-06
1.7E-06
Low
1.2E-04
4.8E-06
1.2E-06
6.0E-07
Table 3 20. Occupational Cancer Risks for Furniture Refinishing (Scenarios 1, 3, 15 and 16)
A
*
Lowest Exposure Highest Exposure
Furniture
Refinishing
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
LADC(mg/m3)
** LADCs for scenarios 2 to 16 have
been adjusted with the multiplier
Mean
65
3
1
0.3
High
293
12
3
1.5
Midpoint
147
6
1
0.7
Low
0.5
0.02
0.01
0.003
Excess Cancer Risk
(Inhalation Unit Risk =
IxlO'5 per mg/m3)
Mean
6.5E-04
2.6E-05
6.5E-06
3.3E-06
High
2.9E-03
1.2E-04
2.9E-05
1.5E-05
Midpoint
1.5E-03
5.9E-05
1.5E-05
7.4E-06
Low
5.0E-06
2.0E-07
5.0E-08
2.5E-08
Page 98 of 279
-------
Table 3 21. Occupational Cancer Risks for Aircraft Stripping (Scenarios 1, 3, 15 and 16)
^
A
Lowest Exposure Highest Exposure
Aircraft Paint
Stripping
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
LADC(mg/m3)
** LADCs for scenarios 2 to 16 have
been adjusted with the multiplier
High
496
20
5
2
Midpoint
254
10
3
1
Low
11
0.44
0.11
0.06
Excess Cancer Risk
(Inhalation Unit Risk =
IxlO"5 per mg/m3)
High
5.0E-03
2.0E-04
5.0E-05
2.5E-05
Midpoint
2.5E-03
l.OE-04
2.5E-05
1.3E-05
Low
1.1E-04
4.4E-06
1.1E-06
5.5E-07
Table 3 22. Occupational Cancer Risks for Graffiti Removal (Scenarios 1, 3, 15 and 16)
*
A
Lowest Exposure Highest Exposure
Graffiti Removal
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
LADC (mg/m3)
** LADCs for scenarios 2 to 16 have
been adjusted with the multiplier
Mean
34
1
0.340
0.2
High
155
6
2
0.8
Midpoint
79
3
1
0.4
Low
2.3
0.092
0.023
0.012
Excess Cancer Risk
(Inhalation Unit Risk =
IxlO'5 per mg/m3)
Mean
3.4E-04
1.4E-05
3.4E-06
1.7E-06
High
1.6E-03
6.2E-05
1.6E-05
7.8E-06
Midpoint
7.9E-04
3.2E-05
7.9E-06
4.0E-06
Low
2.3E-05
9.2E-07
2.3E-07
1.2E-07
Page 99 of 279
-------
Table 3 23. Occupational Cancer Risks for Non Specific Workplace Settings Immersion
Stripping of Wood (Scenarios 1, 3, 15 and 16)
^
A
V
Lowest Exposure Highest Exposure
Non-Specific
Workplace
Settings -
Immersion
Stripping of Wood
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
LADC(mg/m3)
** LADCs for scenarios 2 to 16 have
been adjusted with the multiplier
High
913
37
9
5
Midpoint
459
18
5
2
Low
4.6
0.184
0.046
0.023
Excess Cancer Risk
(Inhalation Unit Risk =
IxlO'5 per mg/m3)
High
9.1E-03
3.7E-04
9.1E-05
4.6E-05
Midpoint
4.6E-03
1.8E-04
4.6E-05
2.3E-05
Low
4.6E-05
1.8E-06
4.6E-07
2.3E-07
Page 100 of 279
-------
Table 3 24. Occupational Cancer Risks for Non Specific Workplace Settings Immersion
Stripping of Wood and Metal (Scenarios 1, 3, 15 and 16)
A
*
.
V
Highest Exposure
Exposure
Lowest
Non-Specific
Workplace
Settings -
Immersion
Stripping of Wood
and Metal
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
LADC (mg/m3)
** LADCs for scenarios 2 to 16 have
been adjusted with the multiplier
High
133
5
1
1
Midpoint
108
4
1
1
Low
83
3
1
0.415
Excess Cancer Risk
(Inhalation Unit Risk =
IxlO'5 per mg/m3)
High
1.3E-03
5.3E-05
1.3E-05
6.7E-06
Midpoint
1.1E-03
4.3E-05
1.1E-05
5.4E-06
Low
8.3E-04
3.3E-05
8.3E-06
4.2E-06
Table 3 25. Occupational Cancer Risks for Non Specific Workplace Settings Unknown
(Scenarios 1, 3, 15 and 16)
/V S!
-
3
U)
O
Q.
i2
4-*
VI
Ol
^
.5?
IE
Ol
^
=
U)
0
O
2
tt
Ol
|
5
Non-Specific
Workplace
Settings -
Unknown
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
LADC (mg/m3)
** LADCs for scenarios 2 to 16 have
been adjusted with the multiplier
Mean
47
2
0.5
0.2
High
56
2
1
0.3
Midpoint
47
2
0.5
0.2
Low
37
1
0.4
0.2
Excess Cancer Risk
(Inhalation Unit Risk =
IxlO"5 per mg/m3)
Mean
4.7E-04
1.9E-05
4.7E-06
2.4E-06
High
5.6E-04
2.2E-05
5.6E-06
2.8E-06
Midpoint
4.7E-04
1.9E-05
4.7E-06
2.4E-06
Low
3.7E-04
1.5E-05
3.7E-06
1.9E-06
Page 101 of 279
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Table 3 26. Occupational Cancer Risks for Art Restoration and Conservation (Scenarios 1, 3, 15
and 16)
^
A
Lowest Exposure Highest Exposure
Art Restoration
and Conservation
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years
(WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
LADC (mg/m3)
** LADCs for scenarios 2 to 16 have
been adjusted with the multiplier
Mean High Midpoint Low
0.3
0.012
0.003
0.0015
Excess Cancer Risk
(Inhalation Unit Risk =
IxlO'5 per mg/m3)
Mean High Midpoint Low
3.0E-06
1.2E-07
3.0E-08
1.5E-08
3.4.3.2 Non-Cancer Risks for Occupational Exposure Scenarios Following Chronic
Exposure to DCM
EPA/OPPT estimated non-cancer risks for the occupational use of DCM-containing paint
strippers. Chronic exposure to DCM has been associated with liver effects. As previously
discussed, the DCM IRIS assessment developed a non-cancer hazard value (i.e., POD) based on
hepatic effects. EPA/OPPT used the PBPK-derived 1st percentile HEC i.e. the HEC99 the
concentration at which there is 99% likelihood an individual would have an internal dose less
than or equal to the internal dose of hazard reported in the DCM IRIS assessment (EPA, 2011c)
to calculate non-cancer risks associated with the repeated use of DCM-based strippers at
different workplace settings.
Tables 3-27 to 3-35 show the non-cancer MOE estimates calculated for workers of different
industries handling DCM-based paint strippers on a repeated basis. Selected scenarios ranging
from the highest exposure scenario (i.e., no respiratory protection and high end values for EF
and WY-i.e., Scenario 1) to the lowest exposure scenario (e.g., respiratory protection APF 50
and midpoints for EF and WY-Scenario 16) were included in the tables. Calculations of non-
cancer risks for the full set of industries and scenarios are provided in the supplemental Excel
spreadsheet, DCM Exposure and Risk Estimates_081114.xlsx.
Most workers using DCM-based paint strippers showed non-cancer risks for liver effects, with
the exception of workers employed in the art renovation and conservation industry (Table 3-
30). For instance, risk concerns for liver effects were reported for most workers handling DCM-
Pagel02of279
-------
based paint strippers. These risk findings were reported with or without respiratory protection
and using the product in a repeated nature at facilities usually reporting central tendency or
high-end DCM air levels. Among all of the occupational scenarios, the greatest risk concern is
for workers engaging in long-term use of the product (i.e., 250 days/year for 40 years) with no
respiratory protection.
Non-cancer risks were not observed for workers that reduce their exposure to DCM-based
strippers by doing all of the following: (1) wearing adequate respiratory protection (i.e., APF 50
respirator), (2) limiting exposure to central tendency exposure conditions (i.e., 125 days/year
for 20 years) and (3) working in facilities with low-end DCM air concentrations. This observation
was reported in all of the relevant industries.
Table 3 27. Occupational Non Cancer Risks for Professional Contractors Following Chronic
Exposure to DCM (Scenarios 1, 3, 15 and 16)
.,
/\
Lowest Exposure Highest Exposure
Professional
Contractors
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
ADC (mg/m3)
** ADCs for scenarios 2 to 16 have
been adjusted with the multiplier
High
680
27
7
3
Midpoint
347
14
3
2
Low
14
1
0.1
0.1
Chronic MOE (24hr HEC99 =
17.2 mg/m3)
Total UF or Benchmark MOE=10
High
0.025
1
3
5
Midpoint
0.050
1
5
10
Low
1
31
123
246
Note: MOEs below benchmark MOE indicating risk are denoted in bold text.
Page 103 of 279
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Table 3 28. Occupational Non Cancer Risks for Automotive Refinishing Following Chronic
Exposure to DCM (Scenarios 1, 3, 15 and 16)
^
A
Lowest Exposure Highest Exposure
Automotive
Refinishing
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
ADC (mg/m3)
** ADCs for scenarios 2 to 16 have
been adjusted with the multiplier
Mean
58
2
1
0.3
High
95
4
1
0.5
Midpoint
58
2
1
0.3
Low
21
1
0.2
0.1
Chronic MOE (24hr HEC99 =
17.2 mg/m3)
Total UF or Benchmark MOE=10
Mean
0.3
7
30
59
High
0.2
5
18
36
Midpoint
0.3
7
30
59
Low
0.8
20
82
164
Note: MOEs below benchmark MOE indicating risk are denoted in bold text.
Table 3 29. Occupational Non Cancer Risks for Furniture Refinishing Following Chronic
Exposure to DCM (Scenarios 1, 3, 15 and 16)
A
A
Lowest Exposure Highest Exposure
Furniture
Refinishing
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
ADC (mg/m3)
** ADCs for scenarios 2 to 16 have
been adjusted with the multiplier
Mean
114
5
1
0.6
High
513
21
5
3
Midpoint
257
10
3
1
Low
0.9
0.04
0.01
0.005
Chronic MOE (24hr HEC99 =
17.2 mg/m3)
Total UF or Benchmark MOE=10
Mean
0.2
4
15
30
High
0.03
0.8
3
7
Midpoint
0.1
2
7
13
Low
19
478
1911
3822
Page 104 of 279
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Table 3 30. Occupational Non Cancer Risks for Art Restoration and Conservation Following
Chronic Exposure to DCM (Scenarios 1, 3, 15 and 16)
*
/s
V
Lowest Exposure Highest Exposure
Art Restoration/
Conservation
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
ADC (mg/m3)
** ADCs for scenarios 2 to 16 have
been adjusted with the multiplier
Mean3
0.5
0.02
0.005
0.0025
Chronic MOE (24hr HEC99 =
17.2 mg/m3)
Total UF or Benchmark MOE=10
Mean3
34
860
3440
6880
Note:
a Based on one 8-hr TWA data point reported in the OSHA IMIS database.
Note: MOEs below benchmark MOE indicating risk are denoted in bold text.
Table 3 31. Occupational Non Cancer Risks for Aircraft Stripping Following Chronic Exposure to
DCM (Scenarios 1, 3, 15 and 16)
^
A
Lowest Exposure Highest Exposure
Aircraft Paint
Stripping
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
ADC (mg/m3)
** ADCs for scenarios 2 to 16 have
been adjusted with the multiplier
High
868
35
9
4
Midpoint
444
18
4
2
Low
20
1
0.2
0.1
Chronic MOE (24hr HEC99 =
17.2 mg/m3)
Total UF or Benchmark MOE=10
High
0.02
0.5
2
4
Midpoint
0.04
1
4
8
Low
0.9
22
86
172
Page 105 of 279
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Table 3 32. Occupational Non Cancer Risks for Graffiti Removal Following Chronic Exposure to
DCM (Scenarios 1, 3, 15 and 16)
>
A
V
Lowest Exposure Highest Exposure
Graffiti Removal
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
ADC(mg/m3)
** ADCs for scenarios 2 to 16 have
been adjusted with the multiplier
Mean
59
2
1
0.3
High
271
11
3
1
Midpoint
138
6
1
0.7
Low
4
0.2
0.04
0.02
Chronic MOE (24hr HEC99 =
17.2 mg/m3)
Total UF or Benchmark MOE=10
Mean
0.3
7
29
58
High
0.1
2
6
13
Midpoint
0.1
3
12
25
Low
4
105
420
839
Note: MOEs below benchmark MOE indicating risk are denoted in bold text.
Table 3 33. Occupational Non Cancer Risks for Non Specif ic Workplace Settings (Immersion
Stripping of Wood) Following Chronic Exposure to DCM (Scenarios 1, 3, 15 and 16)
>
A
Lowest Exposure Highest Exposure
Non-Specific
Workplace
Settings -
Immersion
Stripping of Wood
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
ADC (mg/m3)
** ADCs for scenarios 2 to 16 have
been adjusted with the multiplier
High
1,598
64
16
8
Midpoint
803
32
8
4
Low
8
0.3
0.08
0.04
Chronic MOE (24hr HEC99 =
17.2 mg/m3)
Total UF or Benchmark MOE=10
High
0.01
0.3
1
2
Midpoint
0.02
0.5
2
4
Low
2
54
215
430
Page 106 of 279
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Table 3 34. Occupational Non Cancer Risks for Non Specif ic Workplace Settings (Immersion
Stripping of Wood and Metal) Following Chronic Exposure to DCM (Scenarios 1, 3,
15 and 16)
>
A
V
Lowest Exposure Highest Exposure
Non-Specific
Workplace
Settings -
Immersion
Stripping of Wood
and Metal
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16 (Respirator
APF 50, midpoints of
ranges for EFand WY)
ADC (mg/m3)
** ADCs for scenarios 2 to 16 have
been adjusted with the multiplier
High
232
9
2
1
Midpoint
188
8
2
1
Low
145
6
1
1
Chronic MOE (24hr HEC99 =
17.2 mg/m3)
Total UF or Benchmark MOE=10
High
0.07
2
7
15
Midpoint
0.1
2
9
18
Low
0.1
3
12
24
Note: MOEs below benchmark MOE indicating risk are denoted in bold text.
Table 3 35. Occupational Non Cancer Risks for Non Specif ic Workplace Settings (Unknown)
Following Chronic Exposure to DCM (Scenarios 1, 3, 15 and 16)
*
A
Lowest Exposure Highest Exposure
Non-Specific
Workplace
Settings -
Unknown
Scenario 1
[No respirator, high
ends of ranges for
exposure frequency (EF)
and working years (WY)]
Scenario 3
(Respirator APF 25, high
ends of ranges for EF
and WY)
Scenario 15
(Respirator APF 25,
midpoints of ranges for
EFandWY)
Scenario 16
(Respirator APF 50,
midpoints of ranges for
EFandWY)
ADC (mg/m3)
** ADCs for scenarios 2 to 16 have
been adjusted with the multiplier
Mean
81
3
1
0.41
High
98
4
1
0.49
Midpoint
81
3
1
0.41
Low
65
3
0.65
0.33
Chronic MOE (24hr HEC99 =
17.2 mg/m3)
Total UF or Benchmark MOE=10
Mean
0.21
5
21
42
High
0.18
4
18
35
Midpoint
0.21
5
21
42
Low
0.27
7
26
53
Page 107 of 279
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3.4.4 Human Health Risk Characterization Summary
This risk assessment focused on the occupational and consumer uses of DCM-containing paint
strippers. The population of interest consisted of workers and consumers with direct (users) or
indirect (bystander) exposure to DCM. Only the inhalation route of exposure was considered in
this risk assessment.
The occupational and consumer exposure assessments generated the DCM exposure levels
required to derive non-cancer risk estimates associated with acute and chronic exposures to
DCM. In addition, cancer risks were estimated for occupational scenarios and expressed as
lifetime risks, meaning the risk of developing cancer as a result of the occupational exposure
over a normal lifetime of 70 yrs. Lifetime cancer risks from DCM exposure were compared to
benchmark cancer risks ranging from 10~6 to 10~4.
Many of the occupational scenarios exceeded the target cancer risks of 10~6, 10~5 and 10~4 when
workers employed at various industries handled DCM-paint strippers for 250 days/year for
40 years with no respiratory protection. Adequate respiratory protection and reduced exposure
conditions (e.g., exposure to 125 day/year for 20 years) resulted in reduced cancer risks for
workers when compared to conditions of no respiratory protection while working with paint
strippers for a 250 days/year for a working lifetime (i.e., 40 years).
To characterize the risks of adverse health effects other than cancer, MOEs were used to
evaluate non-cancer risks for both acute and chronic exposures using hazard values derived
from peer-reviewed hazard/dose-response assessments. Health protective hazard values were
derived from the SMAC and the California acute REL hazard/dose-response assessments,
whereas hazard values for non-disabling (AEGL-1) and incapacitating (AEGL-2) effects were
obtained from the AEGL hazard/dose-response assessment for DCM.
Workers employed at most industries showed non-cancer risks for liver effects when using
DCM-based strippers on a repeated basis. The exception was the art renovation and
conservation industry which did not show non-cancer risks for the different scenarios evaluated
in the assessment.
Most workers handling DCM-based paint strippers are at risk of developing non-cancer effects
when they handle the product on a repeated basis with or without wearing respiratory
protection. These observations were seen under various exposure conditions (i.e., exposure
frequency and working years) in facilities reporting central tendency or high-end DCM air levels.
Of special interest are workers using DCM-containing paint strippers engaging in long-term use
of the product (i.e., 250 days/year for 40 years) with no respiratory protection as they showed
the greatest risk concern for non-cancer risks.
On the contrary, non-cancer risks were not observed in workers that reduced their chronic
exposure to DCM by doing all of the following: (1) wearing adequate respiratory protection (i.e.,
Page 108 of 279
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APF 50 respirator), (2) limiting exposure to central tendency exposure conditions (i.e.,
125 days/year for 20 years), and (3) working in facilities with low-end DCM air concentrations.
Most occupational and residential users of DCM-based paint strippers reported acute risks for
CNS effects when the SMAC and California's acute REL hazard values were used for risk
estimation. These risks were observed in workers with or without respiratory protection and
residential bystanders indirectly exposed to DCM.
There were concerns for discomfort/non-disabling (AEGL-1) and incapacitating (AEGL-2) effects
for residential users exposed to DCM for shorter (10-min, 30-min, 1-hr) or longer exposure
durations (4-hr, 8-hr) while doing the product application or staying in the residence after
completion of the stripping task. These concerns were present for upper-end exposure
conditions in the residential scenario as well as some of the upper-end exposure scenarios for
affected bystanders.
Moreover, there were concerns for incapacitating effects (AEGL-2 effects) in workers handing
DCM-containing paint strippers on an acute/short-term basis with no respiratory protection
while employed in most industries involved in paint stripping. Concerns for incapacitating
effects (AEGL-2 effects) were also observed for workers wearing respirators (i.e., APF 10 or
APF 25) while performing paint stripping activities in industries with high DCM air
concentrations [i.e., professional contractors, furniture refinishing, aircraft paint stripping, and
immersion stripping of wood (non-specific workplace settings)].
The bathroom consumer modeling indicated that application of DCM-based paint strippers in a
bathroom generate unsafe exposure conditions for the user of the product. Risk concerns for
discomfort/non-disabling (AEGL-1) and incapacitating effects (AEGL-2) were seen in users
exposed to DCM for shorter (10-min, 30-min, 1-hr) or longer exposure durations (4-hr, 8-hr)
while doing the product application or staying in the residence after completion of the stripping
task. However, residential bystanders did not report risk concerns for AEGL-1 and AEGL-2
effects.
Page 109 of 279
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3.5 DISCUSSION OF KEY SOURCES OF UNCERTAINTY AND DATA
_^
The characterization of variability and uncertainty is fundamental to the risk assessment.
Variability refers to "the true heterogeneity or diversity in characteristics among members of a
population (i.e., inter-individual variability) or for one individual over time (infra-individual
variability)'''(EPA, 2001). The risk assessment was designed to reflect critical sources of
variability to the extent allowed by available methods and data and given the resources and
time available.
On the other hand, uncertainty is "the lack of knowledge about specific variables, parameters,
models, or other factors" (EPA, 2001) and can be described qualitatively or quantitatively.
Uncertainties in the risk assessment can raise or lower the confidence of the risk estimates. In
this assessment, the uncertainty analysis also included a discussion of data gaps/limitations.
Below is a discussion of the uncertainties and data gaps in the exposure, hazard/dose-response
and risk characterization.
3.5.1 Uncertainties in the Occupational Exposure Estimates
Uncertainties in the occupational exposure assessment arise from the following sources:
1. Inhalation Exposure Estimates: EPA/OPPT did not find enough data to determine complete
statistical distributions of actual exposure concentrations for the exposed workers using
DCM-based paint strippers. Ideally, EPA/OPPT would like to know 50th and 95th percentiles
for each population. In the absence of percentile data, the air concentration means and
midpoints (means are preferred over midpoints) of the data sets served as substitutes for
50th percentiles of the actual distributions, whereas high ends of ranges served as
substitutes for 95th percentiles of the actual distributions.
However, these substitutes are highly uncertain and are weak substitutes for the ideal
percentiles. For instance, in the few cases where enough data were found to determine
statistical means and 95th percentiles (Appendix G, Table G-2), the associated substitutes
(i.e., midpoints and high ends of ranges) were shown to overestimate exposures,
sometimes significantly. While it is clear that the air concentration data represent real
exposure levels (Appendix G, Table G-2), EPA/OPPT cannot determine whether these
concentrations are representative of the statistical distributions of actual DCM air
concentrations generated at the workplace during paint stripping activities.
The hypothetical scenario multipliers for workers have significant limitations. EPA/OPPT
cannot determine how accurately the hypothetical scenario multipliers reflect real world
reductions to exposure concentrations presented for the highest exposed population due to
protective equipment and actual exposure frequencies and working years. Moreover, a
Page 110 of 279
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probabilistic exposure approach is inappropriate for this assessment due to the lack of
statistical data for most of the parameters used in the ADC and LADC equation and the
hypothetical scenario multipliers.
In addition, the worker exposure assessment is limited to include exposures from DCM-
based strippers only and does not include exposures to DCM from other sources. Evaluation
of other DCM uses did not fall within the scope of this assessment.
2. Population Exposed: The estimates of numbers of exposed workers are uncertain. The
most uncertain parameter used in the method is the number of workers using strippers
designated for each particular model plant. EPA/OPPT cannot determine whether the
assumed numbers of workers designated for these model plants may underestimate or
overestimate numbers of workers. However, the inclusion of only numbers of workers who
actually use the strippers will underestimate the total number of workers exposed because
non-users (bystanders) are excluded.
3. Dermal Exposure: The worker exposure assessment only includes inhalation exposures
from DCM-based strippers. The exclusion of dermal exposure from the assessment is likely
to underestimate risks to workers, more so for workers who use respirators. This is also an
uncertainty for the consumer exposure assessment.
3!,.5,.^
The inhalation exposure assessment is composed of modeled exposure scenarios for which the
inputs are based on experimental data, survey information, and a number of assumptions with
varying degrees of uncertainty. The results are characterized as either plausible estimates of
individual exposure, e.g., central tendency, or possibly greater than the distribution of actual
exposures, e.g., bounding. These individual estimates are based on exposures to the modeled
area concentrations in the room of product use (user), and in the rest of house (bystanders, and
some user wait periods).
The extent of all of the uncertainties identified below is not known, so the total impact for the
parameters that are discussed could result in either larger or smaller exposure estimates.
There is a high degree of confidence in the weight fraction and product density data for the
paint stripper products. These values are based on currently available consumer products, as
identified in (Brown, 2012). However, these values were not weighted by percent market share.
Similarly, there is a high degree of confidence in the values chosen to represent the house
volume and air exchange rate, as they are based on scientifically defensible data cited in the
EPA's 2011 EFH (EPA. 2011a).
Page 111 of 279
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The confidence level is similarly high for the amount of product applied and application rates,
with data ties to surveys cited in the EFH as well as experiments conducted by EPA (1994a);
note that the upper-end amount of product applied is less than the 80th percentile value, which
should tend to reduce the total exposure estimate.
For the stripping sequence, the wait time per segment has a high level of confidence because
the time is based on what is shown on current product labels. The application and scraping
times have a lower confidence level because they are based on the EPA (1994a) study, which
only included a limited number of experiments using flat panels, which could be considered to
require less application and scraping time than more complex shapes. If so, the impact would
be to lower the exposure duration. However, no data were available to reasonably determine a
range of application and scraping times. This potential impact was mitigated for the upper-end
scenarios by either locating the user in the workshop during the wait periods, or by specifying a
larger project, which would require more stripper—the most sensitive model input parameters
were user location and product amount.
High-quality EPA (1994a) data were available as a quantitative basis for development of the
estimates for the fraction of applied chemical mass that is released to the indoor air (see
Appendix H-l - Estimation of Emission Profiles), but there were only a few cases on which the
estimates were based. These cases included products with and without vapor retardant
ingredients, therefore provide some representation of both types.
Given the potential variability across paint stripping scenarios for estimating consumer
exposure, not only for airflow rates, e.g., interzonal air flows, but also for factors such as
amount of product used, and application rates and locations in the house, there is some
unknown degree of uncertainty in the percentiles of the exposure distribution that are
represented by the modeled scenarios. However, as discussed above, input parameter values
for the greater-than-central-tendency scenarios were selected to avoid unlikely combinations
of high-end or greater values—a "worst-case" scenario.
Therefore, for these scenarios, the general term "upper-end"—instead of more definitive
descriptors, e.g., high-end—was used to characterize plausible exposure values greater than
central tendency; the more definitive descriptors would imply an inappropriate level of
accuracy.
The bathtub stripping scenario is an occupational exposure for the user that was modeled to
estimate potential exposures for residential bystanders occupying the ROH during bathtub
refinishing. Given the model's sensitivity of concentrations in the ROH to room-of-use air
exchange and interzonal air flow, there is uncertainty about the likelihood that a bystander
would be exposed to this scenario's ROH concentrations. Thus, EPA characterized the non-user
exposures as upper-end to bounding.
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3.^.3jynj^
3.5.3.1 Uncertainties in the Cancer Hazard/Dose-Response Assessments
The cancer IUR for DCM was based on mouse liver and lung tumors reported in a cancer
inhalation bioassay (Mennear et al., 1988; NTP, 1986). There is high confidence in the IUR
because it was based on the best available dose-response data for liver and lung cancer in mice
(EPA, 2011c). In addition, DCM-induced tumorigenesis is supported by both animal and human
studies. For instance, female and male rodents (i.e., rats and mice) have reported hepatic and
lung cancer following oral or inhalation exposure to DCM. Further support for DCM's
carcinogenicity comes from epidemiological studies providing evidence for an association
between occupational exposure to DCM and increased risk form some specific cancers (EPA,
2011c). Moreover, multiple in vivo and in vitro studies support DCM's mutagenic mode of
action (EPA. 2011c).
There are a number of uncertainties in the cancer dose-response models and animal-to-human
extrapolation methods used to derive the IUR. The major uncertainties are briefly listed and
summarized in Table 3-36 from information discussed in the DCM IRIS assessment (EPA, 2011c).
Note that the information in Table 3-36 was extracted from Table 5-26 in the DCM IRIS
assessment, which covered uncertainties for both oral and inhalation cancer values. Table 3-36
is only summarizing uncertainties for the cancer IUR. Please refer to the DCM IRIS assessment
for detailed discussion of these uncertainties (EPA, 2011c).
Table 3 36. Summary of the Uncertainties in the Derivation of the Cancer Inhalation Unit
Risk
Consideration and impact
on cancer risk value Decision Justification and Discussion
Selection of data set
(Selection of an alternative data
set could change the
recommended cancer risk
values.)
NTP (1986) selected as
principal inhalation study
to derive the cancer IUR.
NTP (1986) inhalation mouse bioassay provides
the strongest cancer responses (liver and lung
tumors) and the best dose-response data in
the animal database.
Selection of target organ
(Selection of a target organ
could change the
recommended cancer risk
values.)
Liver and lung were
selected as the target
organs. Cancer risk values
were considered for
mammary gland tumors.
Potential brain cancer risk
and hematopoietic cancer
risk were identified as data
gaps.
The evidence for DCM-induced mammary
gland tumors is less consistent than evidence
for liver and lung tumors. Inhalation cancer risk
values based on mammary tumors in rats are
about one order of magnitude higher than risk
values based on liver or lung tumors in mice.
No data are available to allow derivation of
unit risks based on brain or hematopoietic
cancers.
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Table 3 36. Summary of the Uncertainties in the Derivation of the Cancer Inhalation Unit
Risk
Selection of extrapolation
approach
(Selection of extrapolation
approach could change the
recommended cancer risk
values.)
Inhalation data was used to
derive IUR.
Uncertainty is lower when deriving cancer IUR
from inhalation exposure data rather than
using route-to-route extrapolation from oral
data.
Selection of dose metric
(Selection of dose metric could
change the recommended
cancer risk values.)
Tissue-specific GST-
metabolism was used as
dose metric. Cancer risk
estimates based on
alternative (whole-body)
metrics also examined.
The contribution of CYP pathway to cancer risk
is unknown, but strong evidence of GST role in
carcinogenesis supports focus on this pathway.
Values based on tissue-specific GST
metabolism recommended based on evidence
of site locality of effects.
Dose-response modeling
(Human risk values could
increase or decrease,
depending on fits of alternative
models)
The multistage dose-
response model was used
to derive BMD and BMDL
values.
The multistage model has biological support
and is the model most consistently used in EPA
cancer assessments.
Low-dose extrapolation
(Human risk values would be
expected to decrease with the
application of nonlinear tumor
responses in low-dose regions
of dose-response curves.)
Inhalation cancer
assessment used linear
extrapolation of risk in low-
dose region.
PBPK model incorporates the metabolic shift
and expected nonlinearity (GST dose
attenuation) in the exposure-dose relationship
across exposure levels. DCM's mutagenic
mode of action is supported by in vivo and in
vitro studies, resulting in support for the linear
low-dose extrapolation approach used in the
inhalation cancer assessment.
Interspecies extrapolation of
dosimetry and risk
(Alternative values for PBPK
model parameters and cross-
species scaling factor could
increase or decrease human
cancer risk values.)
PBPK model and allometric
scaling factor were used
for the primary dose
metric.
Use of rodent and human PBPK models
reduced uncertainty due to interspecies
differences in toxicokinetics. Examination of
impact of different values for key parameters
in human model, and sensitivity analysis of
rodent PBPK model parameters identified
influential metabolic parameters for which
limited experimental data exist.
Sensitive subpopulations
(Differences in CYP and GST
metabolic rates could change
cancer risk values.)
Risk estimates generated
for presumed most
sensitive (GST-T1+/+)
genotype. The CYP
variability incorporated
into PBPK model.
No data are available to determine the range
of human toxicodynamic variability or
sensitivity, including whether children are
more sensitive than adults.
Source: Adapted from EPA (2011c) (Table 5-26).
3.5.3.2 Uncertainties in the Non-Cancer Hazard/Dose-Response Assessments
3.5.3.2.1 Uncertainties in the Acute Hazard/Dose-Response Assessments
Neurotoxicity in adults was the endpoint used to derive the different acute PODs used in the
acute inhalation risk assessment. It is possible that younger individuals may respond differently
Page 114 of 279
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to DCM exposure in terms of dose, magnitude of response, or different response. Thus, the
MOEs presented for the acute occupational and consumer exposure scenarios may under- or
overestimate risk to younger age groups for this endpoint.
Furthermore, there are uncertainties about the selected acute PODs since the values (e.g.,
NOAEL, LOAEL) depend on the current available data and could change as additional studies are
published. These uncertainties are minimized in the SMAC POD by considering multiple human
observations reporting increased COHb levels after DCM exposure and the extensive CO
database supporting a NOAEL COHb level. Likewise, the derivations of the AEGL-1 and -2 PODs
considered the DCM and CO human literature in combination with PBPK modeling when setting
the AEGL-1 and-2 PODs.
The California acute REL and AEGL PODs were time scaled with the ten Berge equation
(Cn*t=k)20 and PBPK modeling, respectively, to adjust the experimental exposure duration to
the desired acute exposure duration relevant for risk assessment purposes. It is possible that
the time extrapolation approach may not accurately represent the concentration-time-
response relationship of DCM.
3.5.3.2.2 Uncertainties in the Chronic Hazard/Dose-Response Assessments
There is general high confidence on the hazard database supporting the non-cancer hazard
value based on liver toxicity (EPA, 2011c). The inhalation database for DCM includes several
well-conducted chronic inhalation studies reporting the liver as the most sensitive target organ
(Bureketal.. 1984: Nitschke et al.. 1988a: NTP. 1986). Both studies identified 500 ppm as the
lowest inhalation LOAEL for non-cancer liver lesions.
There is uncertainty about chronic exposure impacts on the nervous system function. The
nervous system has been well studied and identified as very sensitive for acute effects.
However, there is a paucity of data on chronic neurological impacts, especially developmental
neurotoxicity. Likewise, there is limited information about immunotoxicity following chronic
exposure to DCM. Existing hazard studies are not sufficient for dose response analysis to
provide a lower point of departure than existing adverse findings in the liver from chronic
exposures.
A DCM PBPK model was used to extrapolate internal dosimetry from rat liver responses to
human risk. Uncertainties in the rat and human dosimetry can arise from the various steps of
model development. The DCM PBPK model had a number of uncertainties related to the data
set, parameters and assumptions used to simulate the toxicokinetics of DCM for animals and
humans (EPA, 2011c). These uncertainties are fully described in the DCM IRIS assessment (EPA,
2011c).
20 In the ten Berge equation (Cn * T = k, n = 2), C = concentration of the chemical of interest, n=chemical-specific
exponent, t=time, and k=constant (NRC, 2001).
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The dose metric used in the models is the rate of metabolism to a putative toxic metabolite
rather than its concentration expressed as the average or area under the concentration curve
of the metabolite. The selected dose-metric fails to account for rodent-to-human differences in
clearance or removal of the toxic metabolite. A scaling factor based on body weight (BW) ratios
was used to account for this difference assessment (EPA, 2011c). There is uncertainty about the
most relevant dose-metric for the noncancer liver effects. This basic research question
represents a data gap, and the DCM IRIS assessment did not address this uncertainty
quantitatively or qualitatively (EPA, 2011c).
One of the advantages of the DCM PBPK model is that it used a human probabilistic approach
to quantitatively address human variability due to pharmacokinetic differences. The model and
resulting distributions considered the known differences in human physiology and metabolic
capability with regard to DCM dosimetry. The first percentile value of the distributions of HECs
served as the non-cancer POD to protect toxicokinetically sensitive individuals. The model did
not address toxicodynamic differences in the human population (EPA, 2011c).
3^5^^
MOEs were used to express non-cancer risks associated with acute or chronic exposures to
DCM. MOEs are obtained by comparing the hazard values (i.e., PODs) for DCM-related health
effects with the exposure concentrations for the specific use scenarios. Given that the MOE is
the ratio of the hazard value divided by the exposure, the confidence in the MOEs is directly
dependent on the uncertainties in the hazard/dose-response and exposure assessments that
supported the hazard and exposure estimates used in the MOE calculations.
The total UF for each acute or chronic POD was the benchmark MOE used to interpret the MOE
risk estimates for each use scenario. The UFs accounted for various endpoint and study-specific
uncertainties in the hazard values, such as:
1. Animal-to-human extrapolation (UFA): The UFA accounts for the uncertainties in
extrapolating from rodents to humans. In the absence of data, the default UFA of 10 is
adopted which breaks down to a factor of 3 for toxicokinetic variability and a factor of 3 for
pharmacodynamic variability.
For the non-cancer POD reported in the DCM IRIS assessment (i.e., chronic exposure to
DCM), the PBPK model accounted for the interspecies extrapolation using rodent
pharmacokinetic data to estimate internal doses for a particular dose metric, thus reducing
the interspecies toxicokinetic uncertainty to 1. Since the PBPK model did not address
interspecies toxicodynamic differences, the total UFA of 3 was retained (EPA, 2011c).
2. Inter-individual variation (UFh): The UFn accounts for the variation in sensitivity within the
human population. In the absence of data, the default UFn of 10 is adopted which breaks
Page 116 of 279
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down to a factor of 3 for toxicokinetic variability and a factor of 3 for toxicodynamic
variability.
For the non-cancer POD reported in the DCM IRIS assessment (i.e., chronic exposure to
DCM), the PBPK model reduced the human toxicokinetic variability to 1, but not the human
toxicodynamic variability. Thus, the total UFn was 3. This is because the PBPK model does
not address the uncertainties regarding the susceptibility of the human subpopulations to
DCM exposure and the extent of toxicodynamics variability (EPA, 2011c).
In the absence of PBPK modeling, a UFh of 10 was retained for the SMAC and the California
acute REL POD to account for variability within the human population.
As for the AEGL PODs, PBPK modeling was used to derive the AEGL PODs and a UFH of 3 and
1 were used for the AEGL-1 and -2 PODs, respectively. Since susceptibility for gross CNS-
depressing effects do not vary by more than a factor of 2- to 3-fold in humans, a UFn of 3
was applied for the AEGL-1 POD (NAC, 2008). On the other hand, a UFH of 1 was considered
sufficient for the AEGL-2 POD since the toxic effects studied were less severe than those
defined for AEGL-2 and the application of a greater value would result in values that were
inconsistent with the available human data. Similarly, an intraspecies UF of 1 was applied
for the effects associated with COHb formation because the POD was based on
experimental data on the most susceptible individuals (i.e., coronary artery disease
patients), which is also protective for other human subpopulations (NRC, 2008, 2010).
3. LOAEL-to-NOAEL extrapolation (UFi_): The UFi accounts for the uncertainty in extrapolating
from a LOAELto a NOAEL. A value of 10 is the standard default UFi value, although lower
values (e.g., 3) can be used if the effect is considered minimally adverse at the LOAEL or is
an early marker for an adverse effect.
OEHHA applied a UFL of 6 to the California acute REL POD to generate a NOAEL (OEHHA.
2008), but the basis for the value selection was not explained. EPA/OPPT retained the UFi_ of
6 as part of the composite factors comprising the total UF (i.e., benchmark MOE).
Unlike cancer risks, an MOE exceeding the benchmark MOEs is an indicator that there is a
potential risk and cannot be translated to a probability that certain adverse health effects
would occur. Also, those MOEs that exceed but remain close to the benchmark MOE do not
necessarily mean that adverse effects would occur.
The non-cancer risks for the occupational chronic exposures assumed that the human health
risks are constant for specific hypothetical scenarios based on variations of exposure conditions
(i.e., type of respiratory, exposure frequency, working years). However, risks could be under- or
over-estimated depending on the real exposure profile of the workers using DCM-paint
strippers.
Page 117 of 279
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Regarding exposure to DCM through the skin, the impact of dermal exposures on human health
risks was not assessed in this assessment for the consumer and occupational scenarios.
Exclusion of dermal exposures is expected to underestimate the risks of the selected DCM use.
This would likely be an issue of concern in those exposure scenarios that resulted in a "no-risk"
finding, especially those that reported MOEs close to the benchmark MOE, but still above the
benchmark.
The assessment did not consider the cumulative exposure from other uses of DCM around the
house or at the workplace setting. Thus, the current risk assessment on the use of DCM-based
paint strippers is likely to underestimate the human risks.
As discussed previously, the cancer risk estimates were based on the assumption of linearity in
the relationship between DCM exposure and probability of cancer. Uncertainties are introduced
in the cancer risks when there is limited information justifying the liner cancer dose-response
model when compared to other available models. In the case of DCM, the cancer IUR was
based on multiple in vivo and in vitro studies supporting a mutagenic mode of action (EPA,
2011c).
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3-6jDO^^
EPA/OPPT's risk assessment focuses on the occupational and consumer use of DCM-based paint
strippers. In this assessment, EPA/OPPT estimates that over 230,000 workers nationwide are
directly exposed to DCM from DCM-based strippers. This estimate only accounts for workers
performing the paint stripping using DCM and does not include other workers ("occupational
bystanders") within the facility who are indirectly exposed. No data were available to estimate
the number of consumers and residential bystanders exposed to DCM during the use of paint
strippers.
In summary, the risk assessment showed the following risk findings:
Cancer Risks Associated With Chronic Exposures to DCM:
• There are cancer risk concerns for workers exposed to DCM that are employed at various
industries handling DCM-containing paint strippers.
• Many of the occupational scenarios exceed at least one of the target cancer risks of 10"4,
10-5andlO-6.
• The greatest cancer risks occur for workers handling DCM-based paint strippers with no
respiratory protection for an extended period of time.
Non-Cancer Risks Associated With Chronic Exposures to DCM:
• There are non-cancer risks for liver effects for most workers using DCM-based paint
strippers in relevant industries, with the exception of the art renovation and conservation
industry.
• Non-cancer risks occur for most workers handling DCM-based paint strippers with or
without respiratory protection for various exposure scenarios. Among all of the
occupational scenarios, the greatest risk concern is for workers engaging in long-term use of
the product (i.e., 250 days/year for 40 years) with no respiratory protection.
• Non-cancer risks are not found when workers reduce their exposure to DCM-based
strippers by taking all three of the following actions; wearing respiratory protection (i.e.,
respirator with at least an assigned protection factor of 50), limiting exposure to central
tendency exposure conditions (i.e., 125 days/year for 20 years) and working in facilities with
low-end DCM air concentrations.
Non-Cancer Risks Associated With Acute Exposures to DCM:
• There are acute risks for neurological effects for most workers using DCM-based paint
strippers. These risks are apparent in the presence or absence of respiratory protection.
• There are concerns for incapacitating effects in workers handing DCM-containing paint
strippers on an acute/short-term basis with no respiratory protection. These concerns are
Page 119 of 279
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also present for workers wearing different types of respirators (e.g., APF 10, APF 25) while
performing paint stripping in industries with high exposure to DCM.
• There are acute risks for neurological effects for consumers of DCM-based paint strippers at
residential settings. Also, bystanders are at risk while staying in the residence when paint
strippers are being applied.
• There are concerns for discomfort/non-disabling and incapacitating effects for consumers
exposed to DCM while applying the product or staying in the residence after completion of
the stripping task. These concerns are also present for residential bystanders in some
scenarios when exposure conditions are at the highest in the rest of the house after
completing the paint stripping task.
• Application of DCM-based paint strippers in a bathroom generates unsafe exposure
conditions for the user of the product, but not residential bystanders. DCM concentrations
may reach levels associated with non-disabling and incapacitating effects for the user
applying the product. User relocation to the rest of the house after completing the paint
stripping task may also produce non-disabling and incapacitating effects as DCM's internal
dose builds up in the body over time.
Page 120 of 279
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APPENDICES
Appendix A REGULATORY HISTORY OF DCM IN THE U.S. AND
ABROAD
A-l^
DCM has been the subject of US federal regulations by the Environmental Protection Agency
(EPA), the Consumer Product Safety Commission (CPSC), the Food and Drug Administration
(FDA), and the Occupational Safety and Health Administration (OSHA).
EPA lists DCM as a toxic (i.e., non-acute) hazardous waste under the Resource Conservation and
Recovery Act (RCRA) (Code U080) (EPA, 2012c), and DCM is listed on the Toxics Release
Inventory (TRI) pursuant to section 313 of the Emergency Planning and Community Right-to-
Know Act (EPCRA) (EPA, 2014). DCM is also listed on the TSCA Inventory of Chemical Substances
and is subject to reporting under the TSCA Chemical Data Reporting (CDR) rule (EPA, 2011e).
EPA's Office of Air Quality Planning and Standards issued a final rule in January 2008, under the
National Emission Standards for Hazardous Air Pollutants (NESHAP) that established national
emission standards for using DCM to remove dried paint (i.e., including, but not limited to:
paint, enamel, varnish, shellac, and lacquer) from wood, metal, plastic, and other substrates
(EPA, 2008). The NESHAP also implemented management practices that minimize DCM
emissions.
Additionally, the Safe Drinking Water Act (SDWA) requires EPA to determine the level of
contaminants in drinking water at which no adverse health effects are likely to occur. EPA has
set an enforceable maximum contaminant level (MCL) for DCM at 0.005 mg/L or 5 ppb (EPA,
2010b).
In 1987, CPSC issued a statement of policy regarding its decision to require labeling of
consumer products that contain DCM (CPSC, 1987). Labels indicated that inhalation of DCM
vapor has caused cancer in certain laboratory animals, and the labels specified precautions to
be taken during use by consumers.
DCM was previously used in aerosol cosmetic products, such as hairspray. In 1989, FDA banned
DCM as an ingredient in all cosmetic products because of its animal carcinogenicity and likely
hazard to human health (FDA, 1989).
OSHA also took steps to reduce the DCM exposure in occupational settings. OSHA lowered the
permissible exposure limit (PEL) for DCM from 500 parts per million (ppm) to 25 ppm (OSHA,
1997a. 1997b).
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DCM is listed as an informational initial candidate chemical under California's Safer Consumer
Products regulations (DISC, 2010). The chemical is also listed on the state's Proposition 65 list
because it is known to cause cancer or birth defects or other reproductive harm (OEHHA,
2014b). In addition, California lists DCM as a designated chemical for biomonitoring (OEHHA,
2014a). The States of Washington and Minnesota classify DCM as a chemical of high concern
(MDH. 2013: WSDE. 2013).
A-2 DCM Regulatory History in Canada and Europe
In 2003, the Canadian Minister of the Environment published a Notice under Part 4 of the
Canadian Environmental Protection Act, 1999 (CEPA 1999) requiring the preparation and
implementation of pollution prevention plans for DCM (Environment Canada, 2003b). This
Notice targets persons involved in the use of DCM for the following activities: aircraft paint
stripping; flexible polyurethane foam blowing; Pharmaceuticals and chemical intermediates
manufacturing and tablet coating; industrial cleaning; and adhesive formulations.
Also in 2003, Environment Canada published a Code of Practice for the reduction of
dichloromethane emissions from the use of paint strippers in commercial furniture refinishing
and other stripping applications (Environment Canada, 2003a). The Code of Practice was
developed by a multi-stakeholder technical working committee, which consisted of industry
representatives (i.e., furniture strippers, auto body shops, paint stripper formulators, solvent
recovery firms), government personnel, and environmental non-governmental organizations.
The European Commission (EC) amended its Registration, Evaluation, Authorization, and
Restriction of Chemical substances in 2010 to incorporate restrictions for the use of DCM in
paint strippers (EC, 2010). DCM is banned from: (1) placement on the market in a new product
for consumers/professionals after December 2010, (2) placement on the market in any product
for consumers/professionals after December 2011, and (3) use by professionals after June
2012, unless the professionals are appropriately licensed and trained in the following:
awareness, evaluation and management of risks, use of adequate ventilation, and use of
appropriate personal protective equipment. In addition, industrial installations using DCM must
have effective ventilation, minimize evaporation from tanks, and have measures for safe
handling of DCM in tanks, adequate personal protective equipment, and adequate information
and training for operators. Pain strippers containing DCM in a concentration equal to or greater
than 0.1% by weight must include a label: "Restricted to industrial use and to professionals
approved in certain EU Member States - verify where use is allowed. (EC, 2010)"
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Appendix B SUMMARY OF ENVIRONMENTAL EFFECTS:
AQUATIC TOXICITY
The aquatic toxicity of DCM for fish, aquatic invertebrates, and aquatic plants is low based on
EPA/OPPT criteria described in the TSCA Work Plan Chemicals Methods Document (EPA, 2012d)
and the Classification Criteria for Environmental Toxicity and Fate of Industrial Chemicals (EPA,
1992a). The sections below summarize the aquatic toxicity studies considered in the evaluation
of environmental hazards of DCM.
B-l Acute Toxicity to Fish
Fathead minnows (Pimephales promelas) were exposed to unspecified measured
concentrations of DCM under flow-through conditions for 96 hrs. A 96-hr LCso of 99 mg/L was
reported (Alexander et al., 1978).
Fathead minnows (P. promelas) were exposed to unspecified measured concentrations of DCM
under flow-through conditions for 96 hrs. A 96-hr LCso of 193 mg/L was reported (Alexander et
al.. 1978).
Fathead minnows (P. promelas) were exposed to unspecified nominal concentrations of DCM
under static conditions for 96 hrs. A 96-hr LCso of 310 mg/L was reported (Alexander et al.,
1978).
Fathead minnows (P. promelas) were exposed to unspecified measured concentrations of DCM
under flow-through conditions for 96 hours. A 96-hr LCso of 193 mg/L was reported (Geiger et
al.. 1986).
Fathead minnows (P. promelas; 10/replicate) were exposed to measured concentrations of 79,
135, 207, 357, 527, and 855 DCM under flow-through conditions for 96 hrs. A 96-hr LCso of 502
mg/L was reported (Dilletal., 1987).
Sheepshead minnows (Cyprinodon variegates) were exposed to unspecified nominal
concentrations of DCM under static conditions for 96 hrs. A 96-hr LCso of 330 mg/L was
reported (Heitmuller et al., 1981).
Zebrafish (Danio rerio) were exposed to unspecified concentrations of DCM under unspecified
conditions for 96 hrs. The 96-hr LCso of 254 mg/L was reported (Roederer, 1990).
Bluegill sunfish (Lepomis macrochirus) were exposed to unspecified nominal concentrations of
DCM under static conditions for 96 hrs. A 96-hr LCso of 220 mg/L was reported (Buccafusco et
al.. 1981).
Page 146 of 279
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B-2 Chronic Toxicity to Fish
Fathead minnows (P. promelas) were exposed to measured concentrations 29, 55, 82, 142, 209,
and 321 mg/L of DCM under flow-through conditions for 28 days. The 28-day lowest-observed-
effect concentration (LOEC) ranged between 82.5 and 142 mg/L and a maximum acceptable
toxicant concentration (MATC) of 108 mg/L was reported (Dill etal., 1987).
_B-3
Water fleas (Daphnia magna) were exposed to unspecified nominal concentrations of DCM
under static conditions for 48 hrs. A 48-hr EC5o of 1,682 mg/L was reported (Kuhn etal., 1989).
Water fleas (D. magna) were exposed to unspecified nominal concentrations of DCM under
static conditions for 48 hrs. A 48-hr ECso of 1,250 mg/L was reported (von Bringmann and
Meinck. 1964).
Water fleas (D. magna) were exposed to unspecified nominal concentrations of DCM under
static conditions for 48 hrs. A 48-hr EC5o of 220 mg/L was reported (LeBlanc, 1980).
Opossum shrimp (Americamysis bahia) were exposed to unspecified nominal concentrations of
DCM under static conditions for 96 hrs. A 96 hr EC5o of 256 mg/L was reported (SRC, 1978).
B-4 THo^
Green algae (Pseudokirchneriella subcapitata) were exposed to unspecified nominal
concentrations of DCM under static conditions for 96 hrs. A 96-hr ECso of 500 mg/L was
reported (EPA. 1978).
Diatoms (Skeletomema costatum) were exposed to unspecified nominal concentrations of DCM
under static conditions for 96 hrs. A 96-hr EC5o of 662 mg/L was reported (SRC, 1978).
Green algae (Scenedesmus subspicatus) were exposed to unspecified nominal concentrations of
DCM under static conditions for 96 hrs. A 96-hr ECso of 1,000 mg/L was reported (Merlin et al.,
1992).
Page 147 of 279
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Appendix C
INVENTORY UPDATE REPORTING RULE DATA
FOR DCM
EPA's 2012 Chemical Data Report (CDR) reported a DCM production volume of 261.5 million
pounds. Two companies reported domestic manufacturing of DCM: Dow Chemical Company
and Occidental Chemical Corporation (EPA, 2013). There were also some companies that
reported to 2012 CDR, but much of this information was claimed confidential business
information and cannot be made available to the public. Data in tables C-l to C-3 were
extracted from the 2012 CDR records (EPA. 2013).
Table C 1. National Chemical Information for DCM from 2012 CDR
Production Volume (aggregate)
Maximum Concentration (at manufacture or import site)
Physical form(s)
Number of reasonably likely to be exposed industrial manufacturing,
processing, and use workers (aggregated)
Was industrial processing or use information reported?
Was commercial or consumer use information reported?
261.5 million pounds
>90%
Liquid
>1,000
Yes
Yes
Table C 2. Summary of Industrial DCM Uses from 2012 CDR
Industrial Sector
(Based on NAICS)
Adhesive Manufacturing
Adhesive Manufacturing
All Other Basic Organic
Chemical Manufacturing
All Other Basic Organic
Chemical Manufacturing
All Other Basic Organic
Chemical Manufacturing
All Other Basic Organic
Chemical Manufacturing
All Other Chemical Product
and Preparation
Manufacturing
Industrial Function
Solvents (for cleaning or
degreasing)
Not Known or Reasonably
Ascertainable
Solvents (for cleaning or
degreasing)
Processing aids, not otherwise
listed
Solvents (for cleaning or
degreasing)
Processing aids, specific to
petroleum production
Propellants and blowing agents
Type of Processing
Use-non-incorporative activities
Processing-incorporation into
formulation, mixture, or
reaction product
Processing-incorporation into
formulation, mixture, or
reaction product
Use-non-incorporative activities
Processing-incorporation into
formulation, mixture, or
reaction product
Use-non-incorporative activities
Processing-incorporation into
formulation, mixture, or
reaction product
Page 148 of 279
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Table C 2. Summary of Industrial DCM Uses from 2012 CDR
Industrial Sector
(Based on NAICS)
All Other Chemical Product
and Preparation
Manufacturing
All Other Chemical Product
and Preparation
Manufacturing
All Other Chemical Product
and Preparation
Manufacturing
Paint and Coating
Manufacturing
Pesticide, Fertilizer, and
Other Agricultural Chemical
Manufacturing
Pesticide, Fertilizer, and
Other Agricultural Chemical
Manufacturing
Petrochemical Manufacturing
Plastics Material and Resin
Manufacturing
Plastics Material and Resin
Manufacturing
Industrial Function
Solvents (for cleaning or
degreasing)
Adhesives and sealant chemicals
Solvents (which become part of
product formulation or mixture)
Solvents (which become part of
product formulation or mixture)
Processing aids, not otherwise
listed
Processing aids, specific to
petroleum production
Processing aids, not otherwise
listed
Processing aids, not otherwise
listed
Processing aids, specific to
petroleum production
Type of Processing
Use-non-incorporative activities
Processing-incorporation into
formulation, mixture, or
reaction product
Processing-incorporation into
formulation, mixture, or
reaction product
Processing-incorporation into
formulation, mixture, or
reaction product
Use-non-incorporative activities
Use-non-incorporative activities
Processing-incorporation into
formulation, mixture, or
reaction product
Use-non-incorporative activities
Use-non-incorporative activities
Abbreviations: NAICS=North American Industry Classification System
Table C 3. DCM Commercial/Consumer Use Category Summary
Commercial/Consumer
Product Category
Adhesives and Sealants
Automotive Care Products
Metal Products not
covered elsewhere
Paints and Coatings
Intended for Commercial
and/or Consumer Uses or
Both
Both
Both
Commercial
Both
Intended for Use in
Children's Products in
Related Product Category
Not Known or Reasonably
Ascertainable
No
No
No
Page 149 of 279
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Appendix D HOUSEHOLD PRODUCTS DATA FOR DCM
EPA/OPPT searched the National Institute of Health (NIH) Household Database, which links over
13,000 consumer brands to health effects reported in Material Safety Data Sheets (MSDS)
(DHHS, 2012). The database also allows scientists and consumers to research products based on
chemical ingredients. Table D-l lists the household products containing DCM in their
formulations.
Table D 1. Household Products Containing DCM from NIH's Household Products Database
Product Brand
Jasco Brushable Semi-Paste Premium Paint &
Epoxy Remover
Savogran Liquid Kutzit-08/31/2007
Carb Medic Carburetor Choke and Valve Cleaner-
08/01/2002-old product
Sprayway Industrial Gasket Remover No. 719
Gunk Carb Medic Carburetor and Choke Cleaner-
04/07/2010
Carb Medic Carb/Choke/Valve Cleaner-old
product
Gumout Professional Non Flammable Brake Parts
Cleaner
EspreeTire Shine
Lectra Motive Auto Care-old product
Anti-Seize Lubricant-old product
Carb Medic Carburetor Choke and Valve Cleaner-
old product
Champion Sprayon Degreasing Solvent
ProsALL Prosolv
Zinsser Brush & Roller Wash
Crown Handi-Strip All Purpose Liquid Stripper
Crown Tuff-Strip Heavy Duty Semi-Paste Stripper
UGL ZAR Paint and Varnish Remover
Savogran Prepaint Deglosser
Savogran Water Rinsing Kwikeeze
Savogran Sprayable Strypeeze-08/22/2001
Klean-Strip Klean Kutter
Klean-Strip Metal & Masonry Paint Remover
Klean-Strip Premium Stripper, Aerosol
Klean-Strip Deep Down Stain Stripper-old product
Zinc It Electric Grade Lubricant
Category
Arts and crafts
Arts and crafts
Auto products
Auto products
Auto products
Auto products
Auto products
Auto products
Auto products
Auto products
Auto products
Auto products
Auto products
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Form
Liquid
Liquid
Liquid
Aerosol
Aerosol
Aerosol
Aerosol
Aerosol
Aerosol
Aerosol
Liquid
Aerosol
Aerosol
Liquid
Liquid
Liquid
Liquid
Liquid
Liquid
Aerosol
Liquid
Liquid
Aerosol
Aerosol
Aerosol
%DCM
Content by
Weight
(as of June
2014)a
60-100
20-25
60-70
70-80
15-40
40-50
5-30
50
1-20
60-65
40-50
70-75
70-75
40-60
80-90
90
35-40
5-10
85-90
25-30
75-85
70-95
<60
32
Page 150 of 279
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Table D 1. Household Products Containing DCM from NIH's Household Products Database
Product Brand
Savogran Kutzit Paint & Varnish Remover-old
product
Champion Sprayon Paint Off
Sprayway Vandalism Mark and Stain Remover No.
870
Zinsser Adhesive Remover
Crown Solu-Strip Semi-Paste Adhesive Remover
Crown Handi-Strip All Purpose Sprayable Stripper,
Aerosol
Savogran Adhesive Remover
Savogran Paint Stripper, Aerosol
Savogran Heavy Duty SuperStrip
Klean-Strip Brush Cleaner
Klean-Strip KS-3 Premium Stripper
Klean-Strip Premium Sprayable Stripper
Klean-Strip Strip-X Stripper
Jasco Semi-Paste Varnish & Stain Remover
Klean-Strip Graffiti Remover-old product
Savogran Strypeeze Paint/Varnish Remover-old
product
Parks Pro Liquid Paint Stripper-discontinued
Paint & Varnish Remover No. 2600, Aerosol
Klean-Strip Adhesive Remover
Aqua Mix Sealer and Adhesive Remover-old
product
Parks Adhesive Remover-discontinued
Radio Shack Rosin Flux Stripper
Parks Adhesive Remover-09/04/1998-
discontinued
Monsanto Amplify Herbicide (agricultural)
Category
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Home maintenance
Inside the home
Inside the home
Inside the home
Inside the home
Inside the home
Pesticides
Form
Liquid
Aerosol
Aerosol
Liquid
Liquid
Aerosol
Liquid
Aerosol
Liquid
Liquid
Liquid
Liquid
Liquid
Liquid
Aerosol
Liquid
Liquid
Aerosol
Liquid
Liquid
Liquid
Liquid
Liquid
Granules
%DCM
Content by
Weight
(as of June
2014)a
>24
80-85
43
71
80-90
45-60
85-90
25-30
85-90
1-3
60-100
70-85
30-50
25-40
75-80
>10
40-90
60-100
40-90
39.83
65-70
<16
Notes:
a EPA/OPPT searched the NIH Household Products Database in August 2012 and June 2014 (DHHS, 2012). Both
searches reported the same list of consumer products and %DCM content with the exception of one product
that showed up in the 2014 search, but not in the 2012 search. This product is Canberra Husky 1229
Vandalism Mark and Stain Remover. It is a home maintenance product available in aerosol form with 40-50%
DCM content. In addition, five products had different category classifications in the 2012 and 2014 searches.
Below are the product names and their categories (in parenthesis) as of June 2014.
1. Savogran Liquid Kutzit-08/31/2007 (Inside Home)
2. Savogran Sprayable Strypeeze-08/22/2001 (Arts/Crafts)
3. Savogran Heavy Duty SuperStrip (Arts/Crafts)
4. Aqua MixSealer and Adhesive Remover-old product (Home maintenance)
5. Parks Adhesive Remover-09/04/1998-discontinued (Arts/crafts)
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Appendix E ENVIRONMENTAL FATE OF DCM
Knowledge of the environmental fate (transport and transformation) of a compound is
important to understanding its potential impact on specific environmental media (e.g., water,
sediment, soil) and exposures to target organisms of concern.
Releases of DCM to soil can volatilize from soil surfaces or migrate through soil and
contaminate groundwater. DCM has high mobility in soil. It is not readily biodegradable, but
biodegrades at varying rates under both aerobic and anaerobic conditions. The rate of
hydrolysis is negligible.
The high vapor pressure and Henry's Law constant, 2.19 x 10~3 atm-m3/mole, indicate DCM has
a tendency to partition to the atmosphere. DCM is expected to undergo slow photooxidation in
the atmosphere and is considered moderately persistent and has low bioaccumulation
potential (EPA. 1999. 2012b: NITE. 2002: OECD. 2011).
Due to its volatility, DCM enters the atmosphere where it reacts slowly enough to undergo
atmospheric transport and act as a greenhouse gas. DCM has been reported to the
Intergovernmental Panel on Climate Change (IPCC) as a global warming potential (GWP)
chemical with a value of 8.7 [i.e., or approximately 8.7 times more heat absorptive than carbon
dioxide (C02)] GWP (Forster. 2007).
Table E-l provides a summary of the environmental fate information for DCM. The sections
below summarize current knowledge of the transport, persistence, bioaccumulation, and
bioconcentration of DCM in the environment including biological and abiotic reactions and
environmental distribution.
Page 152 of 279
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Table E 1. Environmental Fate Characteristics of DCM1
Property
CASRN
Photodegradation Half-life
Hydrolysis Half-life
Biodegradation
Bioconcentration Factor (BCF)
Log Koc
Fugacity (Level III Model)3
Air (%)
Water (%)
Soil (%)
Sediment (%)
Persistence4
Bioaccumulation4
Value
79-09-2
107 days (estimated)
18 months (measured)
13 % in 28 days (not readily biodegradable)2
BCF = 2.0 to 5.4 (measured in carp)2;
BCF = <6.4 to 40.0 (measured in carp)2
BAF = 2.6 (estimated)3
1.4 (estimated)3
43.8
45.0
11.0
0.1
Moderate
Low
Sources: * OECD (2011) 2 NITE (2002) 3 EPA(2012b) 4 EPA (1999)
E-l
Fate in Air
If released to the atmosphere, DCM is expected to exist solely in the vapor-phase based on its
vapor pressure. Vapor-phase DCM is degraded slowly in air by reaction with photochemically
produced hydroxyl radicals. The half-life of this reaction is approximately 107 days. Thus, it is
considered persistent in the atmosphere and subject to transport (OECD, 2011).
E-2
Fate in Water
The low soil organic carbon partition coefficient (Koc) value (i.e., 25) suggests that DCM is not
expected to adsorb to suspended solids and sediment when released to water. In the water
column, DCM's rate of volatilization is expected to be high based on a Henry's Law constant of
2.19 x 10"3 atm-m3/mole (OECD, 2011). A volatilization half-life of 21 minutes was measured for
DCM when stirred in distilled water in a laboratory beaker at 25 °C (Pilling et al., 1975). The
volatilization half-life increased to over 90 minutes when the solution was not stirred.
The rate of hydrolysis of DCM under environmental conditions is expected to be negligible. The
hydrolysis half-life reported at neutral pH, is approximately 18 months at 25 °C (Pilling et al.,
1975). Biodegradation is expected to occur slowly under aerobic conditions, but DCM may
degrade more rapidly in anaerobic waters. A half-life of 11 days was reported for DCM in a 2
month laboratory study using bacteria isolated from an anaerobic aquifer as inoculum
(Hazardous Substance Data Bank (HSDB, 2012). A half-life of 108 days was observed for DCM in
contaminated groundwater under methanogenic conditions (HSDB, 2012).
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E-3 Fate in Soil/Sediment
Based on its low soil organic carbon partitioning coefficient (Koc=25), DCM is likely to possess
high mobility in soils and may be expected to leach from soils into groundwater (ATSDR, 2000).
This is supported by the results of screening studies measuring DCM's biodegradability.
DCM present at 100 mg/L achieved 13 percent of its theoretical biochemical oxygen demand
(BOD) using an activated sludge inoculum at 30 mg/L and the modified Ministry of International
Trade and Industry (MITI) test (OECD 301C) over the course of a 4-week incubation period. The
study findings indicated that DCM is not readily biodegradable (NITE, 2002).
DCM was shown to degrade under aerobic conditions in static culture screening studies that
used domestic wastewater amended with yeast as inoculum (Tabak et al., 1981). Complete loss
of DCM was observed within 7 days in the static culture tests. However, up to 25% of the loss
could have arisen from volatilization. Taken together, these studies suggest that DCM is mobile
in soils and persists long enough to migrate to groundwater given its low affinity for soil and
potential to degrade somewhat slowly.
E-4 Bioconcentration and Persistence
Bioconcentration and persistence are qualitatively characterized according to the criteria set
forth in EPA'sTSCA New Chemical Premanufacture Notification Program (PMN) (EPA, 1999).
Though biodegradation tests of this substance found DCM not readily biodegradable, there is
evidence that metabolism occurs under both aerobic and anaerobic conditions (HSDB, 2012;
Tabak etal.. 1981).
Bioconcentration factor (BCF) values ranging from 2.0 to 5.4 were measured for DCM in carp
over a 6 week incubation period at an initial concentration of 0.25 mg/L (NITE, 2002). BCF
values of <6.4 to 40.0 were observed when the concentration was 0.025 mg/L. Based on these
studies, DCM is not expected to bioconcentrate significantly in aquatic organisms.
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Appendix F
PAINT STRIPPING PROCESSES AND ASSOCIATED
WORKERS ACTIVITIES, AND FACILITY AND
POPULATION INFORMATION
Appendix F presents information about industries engaging in paint stripping activities,
stripping processes, and facility and worker population data. This information serves as
background information for the worker exposure estimates described in Appendix G.
F-l
Identification of Industrial Sectors
Because a variety of industries include paint stripping among their business activities, an effort
was made to determine and characterize these industries, especially for the "small commercial
shops" of interest to EPA/OPPT. Note that the terms for commercial, industrial, and small shops
often are difficult to distinguish, particularly as related to exposure data.
EPA/OPPT reviewed the published literature and evaluated the 2007 North American Industry
Classification System (NAICS) codes to determine industries that likely included paint stripping
activities. These industries are presented in Table F-l.
Table F 1. 2007 NAICS Codes Identified that Include Paint Stripping Activities
2007
NAICS a
238320
238330
811121
811420
711510
712110
2007 NAICS Title
Painting and wall
covering contractors
Flooring contractors
Automotive body, paint,
and interior repair and
maintenance
Reupholstery and
furniture repair
Independent artists,
writers, and performers
Museums
Rationale for Inclusion of NAICS
with Paint Stripping Activities
US Census reports an index entry of "Paint and wallpaper
stripping" (USDOC. 2007b).
US Census reports index entries of "Floor laying, scraping,
finishing, and refinishing" and "Resurfacing hardwood
flooring" (USDOC, 2007b). NIOSH (1993) cites the paint
stripping of flooring by a wood flooring and restoration
company.
NAICS code 811121 is identified as the NAICS code for
automobile refinishing per the Organisation for Economic
Co-operation and Development (OECD) Coating Application
via Spray-Painting in the Automotive Refinishing Industry
BSD (OECD. 2010).
US Census reports index entries of "Furniture refinishing
shops" and "Restoration and repair of antique furniture"
(USDOC. 2007b).
US Census reports index entries of "Painting restorers,
independent" and "Conservators (i.e., art, artifact restorers),
independent" (USDOC. 2007b). Research has shown art
conservation to use paint strippers based on DCM or NMP
(Wollbrinck. 1993).
Research has shown art conservation to use paint strippers
based on DCM or NMP (Wollbrinck. 1993).
Page 155 of 279
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Table F 1. 2007 NAICS Codes Identified that Include Paint Stripping Activities
2007
NAICS a
2007 NAICS Title
Rationale for Inclusion of NAICS
with Paint Stripping Activities
336411
Aircraft manufacturing
US Census reports an index entry of "Aircraft rebuilding (i.e.,
restoration to original design specifications)" (USDOC.
2007b). Paint removal during the restoration process may
use PCM- or NMP-based paint strippers.
336611
Ship building and
repairing
US Census NAICS definition includes shipyards involved in the
construction of ships as well as "their repair and conversion
and alteration" (USDOC. 2007b). Any paint removal activities
during repair, conversion, and alteration may use DCM- or
NMP-based paint strippers.
Note:
a NAICS codes were identified by performing general internet searches to identify workplace-related activities
that involve paint stripping, and searching the U.S. Census 2007 NAICS website for keywords related to paint
stripping, including those determined from the general internet search, such as "refinish," "stripping,"
"paint," "restorer," and "conservator" (USDOC, 2007b).
F-2 Descriptions of Paint Stripping Processes and Activities in
Relevant Industries
Techniques for paint stripping typically include manual coating, tank dipping, and spray
application (EC, 1999). Pouring, wiping, and rolling are also possible application techniques, and
application can be manual or automated (ECHA, 2011). An individual's exposure to paint
stripping chemicals greatly depends on control measures taken and work practices adopted (EC,
1999). The following sections summarize processes and activities for the industries found to
employ paint stripping.
F-2-1
Paint Stripping By Professional Contractors
Paint strippers can be used by professional contractors to strip paint and varnish from walls,
wood flooring, and kitchen and wood cabinets. Professional contractors are expected to
purchase strippers in commercially available container sizes that commonly range from
one liter up to 5 gallons, although they may also purchase consumer paint stripper products
from hardware stores.
Stripper is typically applied to wall or floor surfaces using a hand-held brush. Strippers used in
these applications often have a high viscosity since they can be applied to vertical surfaces.
After application, the stripper is allowed to set and soften the old coating. Once the stripper has
finished setting, the old coating is removed from the surface by scraping and brushing. During
wood floor stripping, old coating and stripper may also be removed using an electric floor
buffer. After the old coating is removed, the surface is wiped clean before moving to the next
stages of the job. The stripping process is often completed on an incremental basis with
treatment for one section of wall or flooring being completed before moving to the next section
Page 156 of 279
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(CDHS/EPA. 2006: EC. 1999: EU. 2007: NIOSH. 1993). Professional contractors can use portable
local exhaust ventilation machines to increase ventilation in the vicinity of the paint stripping
(EU. 2007).
Professional contractors may also be employed to refinish or reglaze bathtubs. Various health
case studies have noted the use of DCM-based strippers during bathtub refinishing or reglazing
(CDC. 2012: Chester et al.. 2012: MSU/MIFACE. 2011). Case studies have identified professional
bathtub refinishers that repaired and resurfaced countertops, tubs, and sinks in both apartment
buildings and private homes (Chester et al.. 2012: MSU/MIFACE. 2011).
In addition, the OSHA IMIS data identified two OSHA or state health inspections in 2004 and
2007 of two bathtub reglazers/refinishers. The bathtub reglazers' company in the 2007
inspection was identified under NAICS code 811420 - Reupholstery and Furniture Repair (CDC,
2012). However, this assessment discusses bathtub reglazing/refinishing in the context of
professional contractors, as professional contractors and professional bathtub refinishers or
reglazers are both expected to perform their work at customer sites (for example, in the cited
case studies of bathtub refinishers/reglazers, apartment buildings, and private homes). This
professional contractor-type work differs from furniture refinishing, which typically entails the
refinishing of customer furniture at fixed furniture refinishing facilities.
Bathtub refinishing or reglazing can involve a worker pouring and brushing stripper onto a
bathtub using a paintbrush. The worker then scrapes the finish from the bathtub after leaving
the stripper in contact with the bathtub for 20 to 30 minutes (Chester et al., 2012;
MSU/MIFACE, 2011). This information was obtained from a case study that noted a stripper
DCM concentration of 60 to 100 percent (Chester et al., 2012; MSU/MIFACE, 2011). However,
multiple health case studies have reported the use of aircraft and marine coating remover in
bathtub refinishing/reglazing (CDC, 2012).
F-2-2
Unlike fixed facility operations, graffiti removal is expected to employ similar job-site
characteristics as professional contractors. Swedish studies of graffiti removal companies (using
both DCM- and NMP-based solvents) identified that solvents are either spray or brush applied.
Sprayed solvents can be swabbed or wiped with a cloth or tissue. After spraying and wiping or
brushing the solvent on the surface, the surface is then washed with heated (70°C) wash water
using a high-pressure spray.
The observed work was performed in train depots and underground stations and included
confined spaces, such as elevators and train cars. The study authors noted poor ventilation in
the confined spaces. The authors also noted the potential for members of the general public to
be indirectly exposed as work was conducted during the day while travelers were occupying the
train depots and stations (Anundi et al., 2000; Anundi et al., 1993). The prevalence of graffiti
removal companies in the U.S. is uncertain. Graffiti removal in the U.S. may be performed by
public works municipal workers or contractors.
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F-2-3 Paint Stripping at Automotive Body Repair and Maintenance Shops
Automotive refinishing shops apply coatings to motor vehicles subsequent to the original
manufacturing process. The overall refinishing process typically involves the following steps:
• Structural repair;
• Surface preparation (cleaning and sanding);
• Primer coat mixing;
• Spray application of primer coat;
• Curing;
• Sanding;
• Solvent wipe-down;
• Topcoat (basecoat color and clearcoat) mixing;
• Spray application of topcoat; and
• Curing.
As stated in OECD (2010), the surface preparation step of the refinishing process involves
"removing residual wax, grease, or other contaminants from the surface to be painted, to
ensure adhesion of the new coating. The new coating may be applied over an existing coating if
it is free of chips or cracks after it has been roughened through sanding. Alternatively, the
previous coating may be removed using a mechanical method (e.g., sanding) or a paint-
removing solvent. After the coating is roughened or removed, the surface is typically wiped
down with a solvent- or water-based surface preparation product".
F-2-4 Wood Furniture Stripping
During furniture stripping, paint stripper may be applied to the furniture by either dipping the
furniture in an open tank containing the stripper, brushing or spraying the stripper onto the
furniture surface, or manually applying the stripper. Larger facilities may pump the stripper
through a brush. The application method depends on the size and structure of the furniture as
well as the capabilities of the facility.
The application area typically has a sloped surface to allow for collection and recycling of
unused stripper. Larger facilities use a flow tray to apply the stripper to parts. The flow tray is a
sloped, shallow tank with a drain at the lower end.
After application, the stripper is left to soak on the furniture surface to soften the surface
coating. Once soaking is complete, the unwanted coating is scraped and brushed from the
furniture surface. The furniture is then transferred to a washing area where residuals are
washed from the furniture.
Washing can be performed using low-pressure washing operations or high-pressure water jets
or high-pressure wands. Wash water may contain oxalic acid to brighten the wood surface.
Wash water is collected and either recycled or disposed of as waste. After washing, the
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furniture is transferred to a drying area where it is allowed to dry before being transferred to
other refinishing processes (e.g., sanding, painting, reupholstery)(CDHS/EPA, 2006; HSE, 2001;
NIOSH. 1990. 1993).
Larger facilities likely purchase stripper in drum quantities from suppliers. Smaller facilities that
use hand stripping instead of stripping equipment likely purchase their stripper from hardware
and home improvement stores. Stripper applied using application equipment has low viscosity,
so it can be pumped through the pumps in the flow tray. Strippers applied using hand stripping
are typically more viscous, so they will remain on the part long enough to strip the coating
(CDHS/EPA. 2006).
Figure F-l shows a typical flow tray used by larger furniture strippers to apply stripper to
furniture parts, obtained from CDHS/EPA (2006). Figure F-2 shows a typical water wash booth
used to wash stripper and coating residue from stripped furniture, obtained from (CDHS/EPA,
2006). Figure F-3 shows an example diagram of a dipping tank for furniture stripping complete
with local exhaust ventilation, obtained from (HSE, 2001).
Figure F-l. Typical Flow Tray for Applying Stripper to Furniture
Source: CDHS/EPA (2006)
Figure F-2. Typical Water Wash Booth Used to Wash Stripper and Coating Residue from
Furniture
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Source: CDHS/EPA (2006)
(Cxi
lOOOfpm
plenum velocity
Source: HSE (2001)
Page 160 of 279
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F-2-5 Art Restoration and Conservation
Art restoration and conservation can include the care and maintenance of paintings to reverse
negative effects of aging and dirt accumulation. It can also include repairing paintings that have
suffered paint loss, weakened canvas, tears, water damage, fire damage, and insect damage
(Smithsonian, 2012b). Art restoration and conservation can include paint cleaning, which can
entail removing dirt and other obscuring material, removing varnish, or removing overpaint
while maintaining the original layer of paint (Smithsonian, 2012a). These activities can involve
the use of paint strippers.
Although paint strippers used in this field can contain DCM, the use of DCM is not always
favored, as DCM can penetrate through the overpaint layer that is being removed and into the
original paint layer that is being conserved. Products marketed for use in this field that do not
contain DCM may contain N-Methylpyrrolidone (NMP) (Wollbrinck, 1993). More detailed
information on the use of paint strippers in art restoration and conservation was not identified.
It is anticipated that paint strippers are applied manually in this field.
F-2-6
During aircraft paint stripping, paint stripper is pumped from bulk storage containers or tanks
and applied to the body of the aircraft using hoses. Once the paint stripper has been applied, it
is allowed to set for a certain period of time (usually about 30 minutes) to allow the paint to
soften. Once setting is complete, the stripper and loose paint are scraped down into a
collection area. Any remaining stripper and paint residue are then brushed or washed away
with water and brushes. Once the surface of the aircraft has dried, a new layer of primer, paint,
and top coat are applied (NIOSH, 1977).
F-2-7 Ship^aintStripping
Process description information for paint stripping of ships has not been identified. It is
anticipated that paint stripping of ships may involve similar processes as the paint stripping of
aircraft.
F-2-8 RespiM^^
OSHA requires NIOSH-approved supplied-air respirators when respiratory protection is required
to protect against DCM. Air-purifying respirators do not provide adequate respiratory
protection against DCM (OSHA. 1997b).
EPA/OPPT examined 13 MSDS for paint strippers and checked the recommendations for
respiratory protection. Ten of the MSDS were for DCM-containing paint strippers. Eight of the
10 MSDS recommended a NIOSH-approved, self-contained breathing apparatus or air-supplied
respirator if respiratory protection is required. One MSDS recommended NIOSH-approved
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respiratory protection for organic solvent vapors, which may include the use of supplied air.
The remaining MSDS only recommended a NIOSH-approved respirator for organic solvent
vapors without further specification of the respirator type (WM Barr, 2008, 2009a, 2009b,
2010a. 2010b. 2011a. 2011b. 2011c. 2012).
F-3
Facility and Worker Population Data
This section summarizes data on the number of facilities and workers nationwide that perform
DCM-based paint stripping activities. It also includes data on the number of workers per facility,
which can be a factor in determining shop sizes.
F-3-1
Potentially Exposed Population in the U.S.
EPA/OPPT estimated that over 230,000 workers, who directly use DCM-based strippers, are
potentially exposed to DCM from these products (Table F-2). EPA/OPPT cannot estimate the
numbers of workers exposed in each of the individual industries that may use DCM-based
strippers. EPA/OPPT cannot estimate the numbers of workers exposed in small shops. Also,
there was no information that EPA/OPPT could use to estimate the number of additional
workers within the facility who are indirectly exposed to DCM.
Table F 2. Calculation of Population of Workers that Potentially Perform Paint Stripping
with DCM
Model Plant Type
Workers per site (assumed)
Total number of sites a
Total number of workers b
AREA SOURCE FACILITIES
Model Plant Type
1
2
1,470
2,940
2
7
780
5,460
3
20
750
15,000
MAJOR SOURCE
FACILITIES
Assumed Model
Plant Type
3
20
10,500
210,000
TOTAL FACILITIES
NATIONWIDE
—
-
-
13,500
233,400
Notes:
a A total of 3,000 area source facilities is obtained by summing the number of sites for model plants #1, 2 and 3
(i.e., 1,470 + 780 + 750, respectively).
b A total of 23,400 workers is obtained by summing the number of workers for model plants #1, 2 and 3 (i.e.,
2,940 + 5,460 + 15,000, respectively).
Workers who are bystanders and not directly involved in using DCM-based strippers were not
included in this estimate. The remainder of this section and Table F-2 describe EPA/OPPT's
approach for estimating this population.
EPA/OPPT estimates given above were based on the following data and assumptions. EPA/OPPT
compiled information from the exposure literature sources and the technical support document
for the National Emission Standards for Hazardous Air Pollutants (NESHAP) Paint Stripping
Operations at Area Sources proposed rule (EPA, 2007).
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The NESHAP technical support document estimated the number of workers performing paint
stripping using DCM at area source facilities, specifically a total of 23,400 workers among 3,000
area source facilities. In the NESHAP analysis, area sources were defined as facilities that emit
less than 10 tons/yr of DCM, and major sources were defined as facilities that emit at least
10 tons/yr of DCM. When estimating the number of workers, and area source facilities, the
NESHAP document assumed three types of model plants (each with a different average number
of workers per site) and estimated the number of each model plant type (Table F-2).
However, the estimate of 3,000 area source facilities represented only 22 percent of the total
facilities nationwide that use DCM in paint stripping operations. The remaining facilities (78%)
include major source facilities (or area sources covered by other area source rules) and
consumer uses. The estimate of 3,000 area source facilities did not include paint stripping
operations in private-sector aircraft maintenance or military maintenance activities. It also did
not include paint stripping during original equipment manufacturing (such as the manufacture
of automobiles, furniture, and other equipment).
The total number of all paint stripping facilities (excluding consumer uses) that use DCM has
been previously estimated at approximately 13,500 (Johnson, 2007)(Table F-2). Assuming the
additional 10,500 facilities not accounted for in the area source estimate are larger, major
source facilities, and assuming major source facilities are equal in size to Model Plant Type 3,
the total number of workers nationwide that perform paint stripping using DCM could be well
over 230,000 (Table F-2).
The estimates of numbers of exposed workers are highly uncertain. The most uncertain
parameter used in the method is the number of workers using strippers designated for each
particular model plant. EPA/OPPT cannot determine whether the assumed numbers of workers
designated for these model plants may underestimate or overestimate the numbers of workers.
However, the inclusion of only numbers of workers who actually use the strippers would
underestimate the total number of workers exposed because non-users (bystanders) are
excluded.
F-3-2 Numbers of Workers per Facility by Industry
This section summarizes data on the number of establishments, number of paid employees and
workers, and production hours and work day estimates (for manufacturing industries). Some of
these data are useful for determining the average number of workers per establishment, which
can indicate relative sizes of the businesses.
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F-3-2-1 Paint Stripping By Professional Contractors, Bathtub Refinishing, and
Graffiti Removal
Table F-3 summarizes the number of establishments and average number of workers for
painting and wall covering contractors and flooring contractors according to the 2007 U.S.
Economic Census (USDOC, 2007a).
Table F 3. 2007 U.S. Economic Census Data for Painting and Wall Covering and
Flooring Contractors
2007 NAICS
238320
238330
2007 NAICS Title
Painting and wall covering
contractors
Flooring contractors
2007 Number of
Establishments
35,619
14,575
2007 Average Number of
Construction Workers
174,276
49,085
Source: USDOC (2007a)
The Census data did not include hours worked for construction industry sectors nor data about
bathtub refinishers/reglazers or graffiti removal. Also, there were no data about the number of
painting and wall covering contractors and flooring contractors who use DCM-based paint
strippers, the number of jobs per year a contractor uses DCM-based paint strippers, and the
number of workers within a job site exposed to DCM-based paint strippers.
The number of establishments and workers from the U.S. Census provided some context for
potential numbers of establishments and workers potentially exposed to DCM during paint
stripping. While some fraction of these workers may be exposed to DCM, the Census data did
not include self-employed, single person businesses, and some of these workers may also be
exposed to DCM. The Census data indicated an average of approximately 4 to 5 workers per
establishment.
Many bathtub refinishers are self-employed or a small business (Chester et al., 2012). Past
investigations of fatalities that occurred during bathtub refinishing indicate it is likely that only
one contractor refinishes a bathtub at a time (CDC, 2012; Chester et al., 2012; MSU/MIFACE,
2011).
Swedish studies of graffiti removal companies identified one company with 12 workers (Anundi
et al., 1993), and a separate study monitored a total of 38 workers over five companies (an
average of seven to eight workers monitored per company)(Anundi et al., 2000). As previously
discussed, the prevalence of graffiti removal companies in the U.S. is uncertain as graffiti
removal may be performed by public works municipal workers or contractors.
F-3-2-2
Paint Stripping at Automotive Body Repair and Maintenance Shops
Table F-4 summarizes the number of establishments and average number of paid employees
for automotive body, paint, and interior repair and maintenance according to the 2007 U.S.
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Economic Census (USDOC, 2007a). The Census data did not include hours worked for this
industry sector.
Table F 4. 2007 U.S. Economic Census Data for Automotive Body, Paint, and Interior
Repair and Maintenance
2007 NAICS
2007 NAICS Title
2007 Number of
Establishments
2007 Number of Paid
Employees
811121
Automotive body, paint,
and interior repair and
maintenance
35,581
223,942
Source: USDOC (2007a)
The Census data indicated an average of approximately 6 employees per facility (USDOC,
2007a). A 2003 Rhode Island study observed two comparably-sized vehicle repainting shops.
One of the two shops had a total of 14 employees (Enander et al., 2004).
In 1998, the Rhode Island Department of Environmental Management (DEM) surveyed over
350 body shops and found that 20 percent of the shops still used DCM as a paint stripper at
that time. It is unknown if this fraction of body shops in Rhode Island in 1998 (that used DCM) is
representative of body shops within the entire U.S. Rhode Island DEM recommends eliminating
the use of DCM-based paint strippers as a pollution prevention measure (RIDEM, 2011).
Therefore, it is uncertain if the 20 percent of shops that used DCM in 1998 is representative of
the fraction of shops that use DCM in the present day.
EPA/OPPT did not find information about the current number of automotive body repair and
maintenance shops within the U.S. that use DCM-based paint strippers, nor the number of
employees within an establishment exposed to DCM-based paint strippers. Therefore, the
number of establishments and employees from the U.S. Census are possibly overestimates of
the number of establishments and employees potentially exposed to DCM during paint
stripping.
A 2003 Rhode Island study that monitored exposures to DCM in a vehicle repainting shop noted
a use rate of DCM of 1 to 2 gallons per week for that particular facility (Enander et al., 2004).
F-3-2-3
Wood Furniture Stripping
Table F-5 summarizes the number of establishments and average number of paid employees
for reupholstery and furniture repair according to the 2007 U.S. Economic Census (USDOC,
2007a). The Census data also indicated an average of approximately 3 employees per facility
(USDOC, 2007a). However, the Census data did not include hours worked for this industry
sector.
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Table F 5. 2007 U.S. Economic Census Data for Reupholstery and Furniture Repair
2007 NAICS
811420
2007 NAICS Title
Reupholstery and furniture
repair
2007 Number of
Establishments
4,693
2007 Number of Paid
Employees
16,142
Source: USDOC (2007a)
A total of 10 furniture refinishing shops were identified among the exposure studies. Of these
10 shops, only one was confirmed to have greater than 10 total employees (this shop had 18
workers) (Grevenkamp, 2007). Three of the shop studies only monitored a single refinisher (one
shop was owned and operated by the single refinisher) (Estill and Spencer, 1996; McCammon et
al., 1991; NIOSH, 1990, 1991). The remaining shop studies monitored two to four refinishers
(and one shop was confirmed to have a total of only six emplovees)(Hall et al., 1995;
McCammon et al., 1991).
OSHA conducted a Regulatory Impact Analysis (RIA) in 1996 for the 1997 OSHA Methylene
Chloride Standard. In the RIA, OSHA estimated 6,152 establishments engaged in furniture paint
stripping using DCM and estimated 7,872 workers exposed during this activity. The 2010 OSHA
Regulatory Review of the Methylene Chloride Standard estimates that the number of
reupholstery and furniture repair facilities decreased to fewer than 6,000 by 2003. The 2007
U.S. Economic Census reported a further decline in the total number of establishments.
However, it is unknown if these data are representative of the population of establishments
and workers that use DCM in the present day (OSHA, 2010).
EPA/OPPT did not have information about the current population of reupholstery and furniture
repair establishments that use DCM-based paint strippers and the number of employees within
an establishment exposed to DCM-based paint strippers. Therefore, the number of
establishments and employees from the U.S. Census are possibly overestimates of the
population of establishments and employees potentially exposed to DCM during paint
stripping.
The Institute for Research and Technical Assistance (IRTA) surveyed the furniture stripping
industry in the South Coast Basin in Southern California to determine the usage of DCM-based
strippers (Table F-6). IRTA then used these data to estimate the number of firms in the state of
California that use DCM-based strippers (Table F-6)(CDHS/EPA, 2006). The source did not
identify the year in which these data were obtained. It is unknown the representativeness of
the distribution of facility annual use rate of stripper across the entire U.S.
CDHS/EPA (2006) identifies the facilities that use >200 gallons/yr of stripper as larger facilities
that purchase stripper in drum quantities from suppliers. The firms that use <200 gallons/yr of
stripper likely use hand stripping and purchase their stripper from hardware and home
improvement stores (CDHS/EPA, 2006).
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Table F 6. Estimated Annual DCM Based Stripper Usage in California a
Annual Stripper Usage (Gallons per Year)
1,200-2,000
700-1,200
200-700
5-200
<5
Total
Number of Firms in California
6
30
40
172
248
596 b
Notes:
a Source: CDHS/EPA (2006)
b CDHS/EPA (2006)notes a total of 596 firms in California. However, an actual summation
of the firms gives a total of 496.
F-3-2-4
Art Restoration and Conservation
Table F-7 summarizes the number of establishments and average number of paid employees
for independent artists, writers, and performers and museums according to the 2007 U.S.
Economic Census (USDOC, 2007a). The Census data did not include hours worked for these
industry sectors.
Table F 7. 2007 U.S. Economic Census Data for Industry Sectors that May Engage in
Art Restoration and Conservation Activities
2007 NAICS
711510
712110
2007 NAICS Title
Independent Artists,
Writers, and Performers
Museums
2007 Number of
Establishments
20,612
4,664
2007 Number of Paid
Employees
48,321
83,899
Source: USDOC (2007a)
NAICS code 711510 includes a wide variety of professions, including independent art restorers
and independent conservators. According to the U.S. Census Bureau, the majority of the
professions listed within this NAICS code are not expected to engage in paint stripping.
Furthermore, the extent that art restorers and conservators engage in paint stripping is
unknown particularly for the use of DCM-based paint strippers.
Similarly, it is unknown the number of museums within NAICS code 712110 that use DCM-
based paint strippers. Therefore, the number of establishments and employees from the U.S.
Census are likely overestimates of the number of establishments and employees potentially
exposed to DCM during paint stripping.
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F-3-2-5
Aircraft Paint Stripping
Table F-8 summarizes the number of establishments, average number of production workers,
and production workers hours for aircraft manufacturing according to the 2007 U.S. Economic
Census (USDOC, 2007a). The table also estimates the average worker days per yr and average
worker hrs per day. These parameters were estimated from the production workers hours and
the average number of production workers. The calculations for the average worker days per
year assumed 8 worker hrs per day. The calculations also assumed 250 worker days per yr when
estimating the average worker hours per day. The estimates of worker days per yr and worker
hrs per day were within 10 percent of the EPA/OPPTs' New Chemicals Program default values
of 250 days/yr and 8 hr/day, respectively (EPA, 1993a).
The Census data indicated an average of approximately 320 production workers per facility.
This observation is consistent with the exposure studies identified in the literature. A 1977
NIOSH study of an aircraft refinishing facility observed approximately 1,400 employees working
in the dock area, which constituted seven refinishing docks but appeared to exclude workers
and employees associated with security checkpoints, the front lobby, cafeterias, the credit
union, the turbine shop, the medical bay, and maintenance activities (NIOSH, 1977). Similarly, a
1994 French study of an aeronautical workshop monitored 30 painters, although the total
number of employees was not identified (Vincent et al., 1994).
Table F 8. 2007 U.S. Economic Census Data for Aircraft Manufacturing
2007 Economic Census Data
2007
NAICS
Code
336411
2007
NAICS Title
Aircraft
manufact-
uring
Number of
Establishments
254
Average
Number of
Production
Workers
81,456
Production
Workers
Hours
(1,000 hr)
157,589
Parameters Calculated from
the Corresponding 2007
Economic Census Data
Average
Worker Days
per Year
(Assuming
8 hr/day)
242
Average
Worker Hrs
per Day
(Assuming
250 days/year)
7.74
Source: USDOC (2007a)
In the 1996 RIA, OSHA estimated 300 establishments engaged in paint stripping of aircrafts
using DCM and estimated 2,470 workers potentially exposed during this activity. Further, the
1996 RIA estimate of number of establishments using DCM-using establishments was similar to
the estimate provided by the 2007 U.S. Economic Census (i.e., 254). However, the 2007 U.S.
Economic Census presented a much greater number of workers (i.e., 81,456) than the RIA
estimate of number of workers exposed to DCM (i.e., 2,470). It is unknown if these data are
representative of the number of establishments and workers that use DCM in the present day
(OSHA. 2010).
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EPA/OPPT did not have information about the current number of aircraft manufacturing
establishments that use DCM-based paint strippers and the number of employees within an
establishment exposed to DCM-based paint strippers. Therefore, the number of establishments
and employees from the U.S. Census are possibly overestimates of the number of
establishments and employees potentially exposed to DCM during paint stripping.
F-3-2-6
Ship Paint Stripping
Table F-9 summarizes the number of establishments, average number of production workers,
and production workers hours for ship building and repairing according to the 2007 U.S.
Economic Census (USDOC, 2007a). The table also estimates the average worker days per year
and average worker hours per day. These parameters were estimated from the production
workers hours and the average number of production workers. The calculations for the average
worker days per year assumed 8 worker hrs per day. The calculations also assumed 250 worker
days per yr when estimating the average worker hrs per day. The estimates of worker days per
yr and worker hours per day were within 10 percent of the EPA/OPPTs' New Chemicals Program
default values of 250 days/yr and 8 hr/day, respectively (EPA, 1993a).
The Census data also indicated an average of approximately 100 production workers per
facility.
Table F 9. 2007 U.S. Economic Census Data for Ship Building and Repairing
2007 Economic Census Data
2007
NAICS
Code
336611
2007
NAICS
Title
Ship
building
and
repairing
Number of
Establishments
656
Average
Number of
Production
Workers
65,737
Production
Workers
Hours
(1,000 hr)
136,929
Parameters Calculated from
the Corresponding 2007
Economic Census Data
Average
Worker Days
per Year
(Assuming
8 hr/day)
260
Average
Worker Hrs per
Day (Assuming
250 days/year)
8.33
Source: USDOC (2007a)
EPA/OPPT did not have information about the number of ship building and repair
establishments that use DCM-based paint strippers and the number of employees within an
establishment exposed to DCM-based paint strippers. Therefore, the number of establishments
and employees from the U.S. Census are possibly overestimates of the number of
establishments and employees potentially exposed to DCM during paint stripping.
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Appendix G OCCUPATIONAL EXPOSURE LITERATURE DATA
AND EXPOSURE CALCULATIONS
G-l Data Needs, Data Collection Strategy and Data Quality Criteria
for the Occupational Exposure Analysis
G-l-l Data Needs
EPA/OPPT defined the data needs for the completion of the occupational exposure assessment
for the use of DCM-based strippers before starting data collection. These data needs included
both quantitative data (e.g., exposure measurements) and qualitative information (e.g.,
descriptions of worker activities).
The following data needs were required for the occupational exposure assessment:
• Inhalation exposure monitoring data of DCM during paint stripping, specifically full-shift
8-hour (hr) time-weighted average (TWA) personal breathing zone samples
- Monitoring of over 5-hr duration was assumed adequate to represent full-shift exposure
levels. Area and short-term samples were found and presented in the discussions of
literature data for perspective and completeness but were not used in the occupational
exposure concentration calculations and risk analyses. Personal samples provide a
better representation of the amount of DCM inhaled by the worker when compared to
area samples.
• Description of processes and worker activities used to perform paint stripping
• Description of engineering controls and personal protective equipment used during paint
stripping
• Estimates of number of workers exposed to DCM during paint stripping in the U.S.
• Estimates of the number of facilities that perform DCM-based paint stripping in the U.S.
In general, the inhalation exposure monitoring data were from occupational settings
representing the relevant industry. However, there were instances that surrogate personal
inhalation data were used when no data were available for the relevant industry. These cases
are discussed below in the summary of the occupational literature and corresponding
uncertainties.
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The following data were not considered in the occupational analysis:
• Modeling results: Monitoring data were preferred to modeling unless there were known
data quality issues, including data representativeness, or if modeling results were expected
to be useful for filling data gaps or addressing other data weaknesses;
• Biological measurements (e.g., blood or urine samples): The types of approaches used in
this risk assessment did not require these types of data;
• Recreated exposure conditions from case studies: Monitoring data were preferred to
recreated exposure conditions unless the monitoring data had known data quality issues or
the data representativeness was believed to be weak;
• Exposure data from non-paint stripping industries: Paint stripping exposure data would
better reflect the exposure conditions when compared to exposures from non-paint
stripping industries.
The detailed summaries of the literature studies presented below in this appendix include
mention of some data that did not meet the data needs described above (e.g., there is mention
of modeled, and not measured, exposure data that were discussed in an investigation of a
bathtub refinishing fatality). These data are presented for perspective only. The data in the
detailed summaries and in Table G-2 meet the first bulleted data need above (breathing zone
monitoring data of DCM during paint stripping).
G-l -2 Data Collection Strategy
EPA/OPPT's literature search comprised a general Internet search and a targeted search of
specific Internet resources. To begin the literature search, EPA/OPPT defined primary keywords
to use in the search queries. The defined primary keywords were:
• dichloromethane
• methylene chloride
• paint stripp*
EPA/OPPT included the preferred chemical name "dichloromethane" as well as the chemical
synonym "methylene chloride." The wildcard (*) allows for variations of the word "strip",
including "stripper" and "stripping." To sort through extensive search results, EPA/OPPT used
secondary keywords including, but not limited to, the following:
• expos*
• inhal*
• breathing zone
Here, the wildcard (*) allows for the variations: "exposure", "exposures", "exposed", "inhale",
and "inhalation."
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EPA/OPPT used these keywords in queries performed in an Internet search engine (e.g.,
Google) for the general Internet search and in the following targeted NIOSH online resources.
• NIOSH Workplace Survey Reports: http://www.cdc.gov/niosh/surveyreports/
• NIOSH Health Hazard Evaluations (HHEs): http://www2a.cdc.gov/hhe/
EPA/OPPT obtained inhalation exposure data from OSHA and state health inspections from the
OSHA's Integrated Management Information System (IMIS) database. Also, some additional
studies were identified during the public and peer reviews of the 2012 draft DCM risk
assessment.
EPA/OPPT defined criteria to evaluate the quality of collected data. Also, EPA/OPPT developed
and used acceptance specifications for each data quality criterion to determine if the collected
data were of acceptable quality for use in this risk assessment. Table G-l summarizes the data
quality criteria, the definition or description of each criterion, and the corresponding
acceptance specifications used to determine if the data were acceptable for use.
EPA/OPPT accepted surrogate data for two industries (professional contractors and art
restoration and conservation) for use in the occupational exposure assessment. For
professional contractors, EPA/OPPT accepted for use some consumer paint stripping exposure
data from U.S. and European studies. The uncertainties associated with these surrogate data
are described in the Paint Stripping by Professional Contractors section of this appendix.
EPA/OPPT also accepted surrogate data for art restoration and conservation because no other
data were identified in the literature search. The surrogate data for air restoration and
conservation were obtained from the OSHA IMIS database. Although the relevance of the
surrogate data is uncertain, the data point met the data need of personal, inhalation
monitoring of DCM (see section G-3-6for more information).
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Table G 1. Data Quality Criteria and Acceptance Specifications for Occupational Data
Quality Criterion
Description/Definition
Acceptance Specification
Currency
(up to date)
The information reflects present
conditions.
Data from all years are acceptable.
Geographic Scope
The information reported reflects an area
relevant to the assessment.
Exposure and process description data from
the United States and the rest of world are
acceptable.
Only US estimates of number of workers
and number of facilities that perform paint
stripping are acceptable.
Reliability
The information reported is reliable. For
example, this criterion may include the
following acceptance specifications:
• The information or data are from a
peer-reviewed, government, or industry-
specific source.
• The source is published.
• The author is engaged in a relevant
field such that competent knowledge is
expected (i.e., the author writes for an
industry trade association publication
versus a general newspaper).
• The information was presented in a
technical conference where it is subject to
review by other industry experts.
Data are reliable if they are from one of the
following sources:
US or other government publication.
Sources by an academic researcher where:
• Publication is in peer-reviewed journal;
or
• Presented at a technical conference; or
• Source has documented qualifications or
credentials to discuss particular topic.
Sources by an industry expert or trade
group where:
• Presented at a technical conference
where the information is subject to
review by other industry experts; or
• Source has documented qualifications or
credentials to discuss particular topic; or
• Source represents a large portion of the
industry of interest.
Unbiased
The information is not biased towards a
particular product or outcome.
• Objective of the information is clear.
• Methodology is designed to answer a
specific question.
Comparability
The data are comparable to other sources
that have been identified.
Data sources will not be accepted or
rejected based on their comparison to data
from other sources.
Representativeness
The data reflect the typical industry
practices. The data are based on a large
industry survey or study, as opposed to a
case study or sample from a limited
number of sites.
Literature sources are not rejected based on
the sample size of sites. Large industry
surveys as well as case studies and limited
sample sizes are acceptable.
Applicability
For surrogate data, the data are expected
to be similar for the industry or property
of interest.
Surrogate data deemed applicable if they
are inhalation exposure or airborne
concentration data of DCM measured
during paint stripping.
Page 173 of 279
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G-2 Approach and Methodology for Estimating Occupational
Exposure
G-2-1 Identification of Relevant Industries
Because a variety of industries include paint stripping among their business activities,
EPA/OPPT made the effort to determine and characterize these industries, with a special
interest in small commercial shops.21
EPA/OPPT reviewed the published literature and evaluated the 2007 North American Industry
Classification System (NAICS) codes to determine industries that likely include paint stripping
activities (see Appendix F, Table F-l).
The identified industries were the following:
• Professional contractors;
• Bathtub refinishing;
• Automotive refinishing;
• Furniture refinishing;
• Art restoration and conservation;
• Aircraft paint stripping;
• Ship paint stripping; and
• Graffiti removal
By identifying these industries, EPA/OPPT determined worker subpopulations that may be
exposed to DCM due to the use of these strippers. Appendix F details the industries identified
and processes and worker activities that may contribute to worker exposures.
G-2-2 Estimation of Potential Workplace Exposures for DCM-Based Paint
Strippers
G-2-2-1 Workplace Exposures Based on Monitoring Data
EPA/OPPT used air concentration data and estimates found in literature sources to serve as
exposure concentrations for occupational inhalation exposures to DCM. These air
concentrations were used to estimate the exposure for workers exposed to DCM as a result of
the use of DCM-based paint strippers.
21 Please note that differences among commercial, industrial, and small shops are often difficult to distinguish,
particularly as related to exposure data. For more information about shop size determination, see section
3.1.1.2 and Appendix F.
Page 174 of 279
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EPA/OPPT did not find enough monitoring data to determine complete statistical distributions
of actual exposure concentrations for the exposed populations. Ideally, EPA/OPPT would like to
know 50th and 95th percentiles for each population. The air concentration means and midpoints
(means are preferred over midpoints) served as substitutes for 50th percentiles, and high ends
of ranges served as substitutes for 95th percentiles.
In compiling the results from the individual literature sources into the results summary for this
risk assessment, EPA/OPPT classified exposure durations of 5 hrs or greater as "8-hr TWA"
exposures. Exposure durations less than 5 hrs and unknown durations were classified as "STEL,
peak, short-task based, and unknown" exposures.
Data sources did not often indicate whether exposure concentrations were for occupational
users or bystanders. Therefore, EPA/OPPT assumed that occupational exposures were for a
combination of users and bystanders. Some bystanders may have lower exposures than users,
especially when they are further away from the source of exposure.
Additionally, inhalation exposure data from OSHA and state health inspections were obtained
from the OSHA IMIS database. However, OSHA IMIS data were generally excluded to estimate
workplace exposure estimates, except where noted, because (1) inhalation exposures for DCM
found in IMIS may or may not be caused by DCM-based strippers; and (2) data from literature
were deemed adequate to estimate exposures from DCM-based strippers. In this assessment,
the IMIS data were useful for examining the impact of the OSHA PEL update in 1997 on
exposures in the industries that are most likely to employ DCM-based strippers (see section G-
3-10).
Table G-2 presents a summary of the exposure data collected for each industry. The risk
characterization of occupational exposures was based on the 8-hr TWA data in Table G-2. The
data met the data needs and data quality criteria described in section G-l.
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Table G 2. DCM 8 hr TWA Air Concentrations Used for Estimating Occupational Acute and Chronic Exposure Concentrations for Non
Cancer and Cancer Risks and Non 8 hr Air Concentration Data from the Literature
Industry/ Activity
Professional
Contractors
Bathtub
Refinishing
Automotive
Refinishing
Furniture
Refinishing
Art Restoration
and Conservation'
Aircraft Paint
Stripping
Ship Paint
Stripping
Number
of
Studies
4
1
1
7
1
5
1
Time
Range of
Studies
1981-2004
Unk
2003
1989-2007
2005
1977-2006
1980
Number
of Sites
Unk
1
1
>10
1
>5
1
Total Number of
Measurements c
>4 (8-hr TWA);
>38(STEL/Other)
2
2 (8-hr TWA);
3 (STEL/Other)
43 (8-hr TWA);
>63 (STEL/Other)
1
>35 (8-hr TWA);
130 (STEL/Other)
>=1
8-hr TWA (mg/m3)3
Mean
-
-
253
499
High
2,980
416
2,245
(1,266)
e
Midpoint d
1,520
-
253
1,125
Low
60
-
90
4.0
2.0
-
-
3,802
-
1,944
-
86
-
STEL, Peak, Short-Tasked Based,
and Unknown (mg/m3)b
Mean
-
-
330
-
-
-
215
High
14,100
7,565
416
6,992
-
5,400
-
Mid-
point
7,050
7,252
333
3,506
-
2,719
-
Low
QS
6,940
250
19
-
38
-
Data Source
for 8-hr TWA
and short-
term values
EPA(1994a);
EU (2007) EC
(1999)
MSU/MIFACE
(2011)
Enander et al.
(2004)
Estilland
Spencer
(1996);
Grevenkamp
(2007); Hall
etal. (1995);
McCammon
etal. (1991);
NIOSH (1990,
1991, 1993)
OSHA (2012a)
EU (2007);
IARC (2010);
Vincent et al.
(1994) EC
(1999)
IARC (2010)
Page 176 of 279
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Table G 2. DCM 8 hr TWA Air Concentrations Used for Estimating Occupational Acute and Chronic Exposure Concentrations for Non
Cancer and Cancer Risks and Non 8 hr Air Concentration Data from the Literature
Industry/ Activity
Graffiti Removal
Non-Specific
Workplace
Settings -
Immersion
Stripping of Wood
Non-Specific
Workplace
Settings -
Immersion
Stripping of Wood
and Metal
Non-Specific
Workplace
Settings -
Immersion
Stripping of Metal
Non-Specific
Workplace
Settings -
Unknown
Number
of
Studies
1
>1
1
>=1
>=6
Time
Range of
Studies
1993
1980-1994
1980
Unk
1997-2004
Number
of Sites
Unk
>2
>=1
>=1
>=6
Total Number of
Measurements c
12 (8-hr TWA);
>-10
(STEL/Other)
>4
7
>=1
2 (8-hr TWA);
>=227
(STEL/Other)
8-hr TWA (mg/m3)3
Mean
260
-
-
-
357
High
1,188
7,000
1,017
-
428
Midpoint d
603
3,518
825
-
357
Low
18
35
633
-
285
STEL, Peak, Short-Tasked Based,
and Unknown (mg/m3)b
Mean
1,117
-
-
-
-
High
5,315
-
-
350
3,035
Mid-
point
2,661
-
-
-
1,518
Low
6.0
-
-
-
0.25
Data Source
for 8-hr TWA
and short-
term values
Anundi et al.
(1993)
EC (1999)
IARC (2010)
EC (1999)
EU (2007)
Page 177 of 279
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Table G 2. DCM 8 hr TWA Air Concentrations Used for Estimating Occupational Acute and Chronic Exposure Concentrations for Non
Cancer and Cancer Risks and Non 8 hr Air Concentration Data from the Literature
Industry/ Activity
Number
of
Studies
Time
Range of
Studies
Number
of Sites
Total Number of
Measurements c
8-hr TWA (mg/m3)3
Mean
High
Midpoint d
Low
STEL, Peak, Short-Tasked Based,
and Unknown (mg/m3)b
Mean
High
Mid-
point
Low
Data Source
for 8-hr TWA
and short-
term values
Notes:
Data sources are reported in this table and discussed in section G-3.
a These concentrations include 8-hr TWA concentrations from personal sampling that were either directly measured or calculated from shorter time frame (5 to < 8 hr) exposures by the
study authors; area samples and modeling results are not included. Airborne concentration conversion factor for DCM is 3.47 mg/m3 per ppm (NIOSH, 2011b).
b These concentrations include 15-minute STEL and other short, task-based concentrations from personal sampling that are less than 5 hrs in duration, as well as unidentified exposure
durations. These values are not used in the risk analyses but are presented for perspective and for completeness only.
c The total number of measurements come from the studies reviewed for each industry. In some cases, the study descriptions in Appendix F may not identify every instance of number of
measurements.
d EPA/OPPT calculated the midpoint values from the reported low and high ends of ranges and also the mean values when the data were adequate.
e The value in parentheses is the 95th percentile of the collected 8-hr TWA exposure concentrations for this industry.
f The data point provided for this industry was obtained from OSHA IMIS. No other literature data were obtained.
8 The study that reported this zero value did not specify the detection limit.
— Indicates no data found for low or high values and no calculation could be made for means or midpoints.
Unk- Unknown
Page 178 of 279
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G-2-2-2
Workplace Exposure Scenarios Evaluated in this Assessment
Occupational scenarios for acute and chronic exposures: Workers performing DCM-based
stripping might or might not use a respirator or be exposed to DCM at different exposure
frequencies (days per year) or working years. Thus, EPA/OPPT assessed acute risks for 4
occupational scenarios and chronic risks for 16 occupational scenarios based on 8-hr TWA
exposure concentrations and different variations in exposure conditions.
For the acute scenarios, EPA/OPPT defined 4 scenarios to reflect a combination of the following
(Table G-3):
• No use of a respirator (APF = zero);
• Use of a respirator with an APF of 10, 25, or 50.
Table G 3. Acute Occupational Exposure Scenarios for the Use of DCM Based Paint
Strippers
Acute
Scenario
1
2
3
4
Respirator APF a
0
10
25
50
8-hr TWA Acute Exposure
Concentration Multiplier a
1
0.1
0.04
0.02
Scenario Description
No respirator, APF = 0
Respirator APF 10
Respirator APF 25
Respirator APF 50
Notes:
3 APF= assigned protection factor. APFs of 10, 25 or 50 mean that the respirator reduced the personal
breathing concentration by 10-, 25- or 50-fold (i.e., 0.1, 0.04, 0.02).
b As indicated in equation G-2, these multipliers are applied to the 8-hr time-weighted average (TWA) acute
exposure concentrations in Table G-5.
For the chronic scenarios, EPA/OPPT defined 16 scenarios to reflect a combination of the
following (Table G-4):
• No use of a respirator (APF = zero)22;
• Use of a respirator with an APF of 10, 25, or 50;
• An exposure frequency (EF) of the assumed Scenario 1 value of 250 days per year or half of
the assumed Scenario 1 value (the midpoint between the assumed Scenario 1 value and
zero: 125 days per year); and
• Exposed working years (WY) of the assumed Scenario 1 value of 40 years or half of the
assumed Scenario 1 value (the midpoint between the assumed Scenario 1 value and zero:
20 years).
22
APF assumptions are the same for both acute and chronic scenarios.
Page 179 of 279
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Table G 4. Chronic Occupational Exposure Scenarios for the Use of DCM Based Paint
Strippers
Chronic
Scenario
1
2
3
4
5/9
6/10
7/11
8/12
13
14
15
16
Respirator
APF
0
10
25
50
0
10
25
50
0
10
25
50
Exposure
Frequency
(EF)
(days/yr)
250
250
250
250
250/ 125
250/ 125
250/ 125
250/ 125
125
125
125
125
Working
Years (WY)
(years)
40
40
40
40
20/40
20/40
20/40
20/40
20
20
20
20
ADC/LADC
Multiplier3
1
0.1
0.04
0.02
0.5
0.05
0.02
0.01
0.25
0.025
0.01
0.005
Scenario Description
No respirator, high ends of
ranges for EF and WY
Respirator APF 10, high ends
of ranges for EF and WY
Respirator APF 25, high ends
of ranges for EF and WY
Respirator APF 50, high ends
of ranges for EF and WY
No respirator, one midpoint
and one high end of range for
EFand WY
Respirator APF 10, one
midpoint and one high end of
range for EF and WY
Respirator APF 25, one
midpoint and one high end of
range for EF and WY
Respirator APF 50, one
midpoint and one high end of
range for EF and WY
No respirator, midpoints of
ranges for EF and WY
Respirator APF 10, midpoints
of ranges for EF and WY
Respirator APF 25, midpoints
of ranges for EF and WY
Respirator APF 50, midpoints
of ranges for EF and WY
Note:
a As indicated in equation G-4, these multipliers are applied to the chronic average daily concentrations (ADCs)
and lifetime average daily concentrations (LADCs) shown in Table G-5.
The multipliers in Tables G-3 and G-4 were used to adjust the exposure estimates of acute and
chronic Scenario 1 to obtain the exposure estimates for the other exposure scenarios.
Additional information is presented below in the sections discussing the approach to calculate
the acute and chronic exposure estimates used in the risk characterization.
EPA/OPPT made assumptions about types of respirators used because no data were found
about the overall prevalence of the use of respirators to reduce DCM exposures. While it was
Page 180 of 279
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not possible to estimate the numbers of workers who have reduced exposures due to the use
of respirators, EPA/OPPT believes that the prevalence of respirator use would be high for most
industries conducting paint stripping.
Likewise, EPA/OPPT made assumptions about the exposure frequencies and working years
because data were not found to allow statistical distributions to be characterized for these
parameters. Thus, EPA/OPPT evaluated occupational risks by developing hypothetical scenarios
under varying exposure conditions (i.e., different respiratory protection factors, exposure
frequencies and working years).
Approach for calculating acute and chronic workplace exposures: To facilitate the exposure
calculations for the occupational scenarios, EPA/OPPT first estimated the acute and chronic
exposure estimates for Scenario 1 (highest exposure group). Equations are described below.
The exposure estimates for Acute Scenarios 2 to 4 and Chronic Scenarios 2 to 16 were obtained
by adjusting scenario 1 (highest exposure group) with various multipliers (Tables G-3 and G-4
for acute and chronic, respectively). The acute multipliers reflected the numerical reduction in
exposure when respirators were used. The chronic multipliers reflected the numerical
reduction in exposure when respirators were used and/or other EF and WY values were used.
Although 16 chronic scenarios were possible, scenarios 5 through 8 and 9 through 12 resulted
in the same multiplier regardless of whether the scenario used an EF of 250 days/year and a WY
of 20 years or an EF of 125 days/year and a WY of 40 years.
Acute occupational exposure estimates
For single (acute) workplace exposure estimates, the DCM single (acute) exposure
concentration was set to the 8-hour time-weighted average (TWA) air concentration in mg/m3
reported for the various relevant industries. EPA/OPPT assumed that some workers could be
rotating tasks and not necessarily using DCM-based paint strippers on a daily basis. This type of
exposure was characterized as acute in this assessment as the worker would clear DCM and its
metabolites before the next encounter with the DCM-containing paint stripper. Equation G-l
was used to estimate the single (acute) exposure estimates for acute scenario 1 (EPA, 2009).
scenario 1 — L. (Equation G-l)
where:
EC scenario i = exposure concentration for a single 8-hr exposure to DCM (mg/m3) for
scenario 1;
C = contaminant concentration in air for relevant industry (central tendency,
low- or high-end 8-hr TWA in mg/m3 from Table G-2 or G-5).
Page 181 of 279
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Equation G-2 was used to calculate the acute exposure estimates for scenarios 2 through 4.
tiL- scenario 2-» 4— t'L- scenario 1 * M acute (Equation G-2)
where:
EC scenario 2^4 = exposure concentration for a single 8-hr exposure to DCM
(mg/m3) for acute scenarios 2 through 4;
ECscenarioi = single (acute) exposure concentration for relevant industry (8-hr
TWA in mg/m3 from Table G-2 or G-5);
M acute = Scenario-specific acute exposure multiplier (unitless) for relevant
industry (see Table G-3).
Acute exposure estimates for scenario 1 are presented in Table G-5. Acute exposure estimates
for scenarios 2 through 4 were integrated into the risk calculations by applying the scenario-
specific multipliers. Thus, separate tables listing the acute exposure estimates for scenarios 2
through 4 are not provided in this section, but are available in a supplemental Excel
spreadsheet documenting the risk calculations for this assessment (DCM Exposure and Risk
Estimates_081 1 1 4.xlsx) .
Chronic occupational exposure estimates
The worker exposure estimates for the non-cancer and cancer risk calculations were estimated
as average daily concentrations (ADCs) and lifetime average daily concentrations (LADCs),
respectively. Both ADC and LADC calculations for Scenario 1 were based on the 8-hr TWA air
concentration in mg/m3 reported for the various relevant industries (Table G-5). EPA/OPPT
assumed that the worker would be doing paint stripping activities during the entire 8-hr work
shift on a daily basis. Equation G-3 was used to estimate the chronic ADCs and LADCs for
Scenario 1 (EPA. 2009).
_ C x ED x EF x WY
scenario 1 — ~ (Equation G-3)
f\ L
where:
EC scenario i = exposure concentration (mg/m3) for Scenario 1 = ADC for chronic non-
cancer risks or LADC for chronic cancer risks for Scenario 1;
C = contaminant concentration in air for relevant industry (low- or high-end
8-hr TWA in mg/m3 from Table G-2);
ED = exposure duration (hrs/day) = 8 hrs/day;
EF = exposure frequency (days/year) = 250 days/year for high-end of range
for both ADC and LADC calculations;
WY = working years per lifetime (years) = 40 years for high end of range
for both ADC and LADC calculations; and
Page 182 of 279
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AT = averaging time (years x 365 days/years x 24 hrs/day) = 40 years for high
end of range for ADC calculations; 70 years for LADC calculations, which is
used to match the years used to calculate EPA's cancer inhalation unit
risk(IUR).
Equation G-4 was used to estimate the chronic ADCs and LADCs for scenarios 2 through 16.
tiL- scenario 2-» 16 = t'L- scenario 1 * M chronic (Equation G-4)
where:
EC scenario 2 -> 16 = exposure concentration for chronic exposure concentration (ADC
or LADC) to DCM (mg/m3) for chronic scenarios 2 through 16
EC scenario i = chronic exposure concentration (ADC or LADC) for relevant
industry, chronic scenario 1 (in mg/m3 from Table G-5);
M chronic = scenario-specific ADC/LADC chronic multiplier for relevant
industry (see Table G-4)
Non-cancer and cancer exposure estimates (i.e., ADC and LADC, respectively) for scenario 1 are
in presented in Table G-5. The estimates for scenarios 2 through 16 were integrated into the
risk calculations by applying the scenario-specific ADC/LADC multipliers. Thus, separate tables
listing the chronic exposure estimates for scenarios 2 through 16 are not provided in this
section, but are available in a supplemental Excel spreadsheet documenting the risk
calculations for this assessment (DCM Exposure and Risk Estimates_081114.xlsx).
Page 183 of 279
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Table G 5. DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers Scenario 1 Highest Exposed
Scenario Group
Industry/ Activity
Professional
Contractors
Bathtub
Refinishing
Automotive
Refinishing
Furniture
Refinishing
Art Restoration
and Conservation
Aircraft Paint
Stripping
Ship Paint
Stripping
Graffiti Removal
Non-Specific
Workplace Settings
- Immersion
Stripping of Wood
Non-Specific
Workplace Settings
- Immersion
Stripping of Wood
and Metal
Non-Specific
Workplace Settings
- Immersion
Stripping of Metal
Time Range
of Studies
1981-2004
2003
1989-2007
2005
1977-2006
1980
1993
1980-1994
1980
ACUTE EXPOSURE ESTIMATES
Single 8-hr Concentration (mg/m3)3
Mean
-
-
253
499
High
2,980
-
416
2,245
(1,266) c
Midpoint
1,520
-
253
1,125
Low
60
-
90
4.0
2.0
-
-
260
-
-
-
3,802
-
1,188
7,000
1,017
-
1,944
-
603
3,518
825
-
86
-
18
35
633
-
CHRONIC EXPOSURE ESTIMATES
USED IN THE NON-CANCER RISK
ESTIMATES [ADC |mg/m3)b]
Mean
-
-
58
114
High
680
-
95
513
(289)
C
Midpoint
347
-
58
257
Low
14
-
21
0.9
0.5
-
-
59
-
-
-
868
-
271
1,598
232
-
444
-
138
803
188
-
20
-
4.1
8.0
145
-
CHRONIC EXPOSURE ESTIMATES
USED IN THE CANCER RISK
ESTIMATES [LADC |mg/m3)b]
Mean
-
-
33
65
High
389
-
54
293
(165)
C
Midpoint
198
-
33
147
Low
7.8
-
12
0.5
0.3
-
-
34
-
-
-
496
-
155
913
133
-
254
-
79
459
108
-
11
-
2.3
4.6
83
-
Page 184 of 279
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Table G 5. DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers Scenario 1 Highest Exposed
Scenario Group
Non-Specific
Workplace Settings 1997-2004 357 428 357 285 | 81 98 81 65 | 47 56 47
- Unknown
37
Notes:
Sources are reported in Table G-2 and discussed in section G-3.
a Calculated acute single 8-hr concentrations are only estimated from 8-hr TWA exposures; see Equation 3-1 or F-l. Airborne concentration conversion factor for DCM is
3.47 mg/m3 per ppm (NIOSH, 2011b).
b Calculated ADCs and LADCs are only calculated from 8-hr TWA exposures; see Equation 3-3 or F-3.
c The values in parentheses are the 95th percentiles of the calculated acute single 8-hr concentrations and the calculated ADCs and LADCs.
— Indicates no data found.
Page 185 of 279
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G-2-3
Worker Exposure Limits for DCM
Both regulatory and non-regulatory worker exposure limits have been established for DCM by
OSHA, the National Institute for Occupational Safety and Health (NIOSH), and the American
Conference of Governmental Industrial Hygienists (ACGIH). Table G-6 provides a summary of
the occupational exposure values established. Appendix F presents additional background on
processes, respiratory protection, facilities and worker populations.
OSHA's amended regulatory occupational exposure limits for DCM were effective April 10,
1997. The amendments included reducing the permissible exposure limit (PEL), reducing and
changing the averaging time of the short-term exposure limit (STEL), adding an Action Level,
and removing the ceiling limit (OSHA, 1997a). Our analysis showed that the OSHA PEL and
Action Level values were exceeded for some industries using DCM-based strippers when the
OSHA values were compared to the air concentrations. Workplaces may consider these levels
when instituting respiratory protections. Table G-6 also includes the pre-1997 OSHA limits to
provide context when analyzing exposure data measured on or before 1997.
Table G 6. Regulatory and Recommended Exposure Limits for DCM a
Source
OSHA PEL
(1997 and forward)
OSHA PEL
(pre-1997)
NIOSH exposure limits
ACGIH TLV f
Limit Type
PEL (8-hr TWA) b
STEL (15-minute TWA)
Action Level (8-hr TWA)
PEL (8-hr TWA)
Ceiling
STEL (5-minute average in any 2-hr period)
IDLHd
RELe
8-hr TWA
Exposure Limit
25 ppm c
125 ppm
12.5 ppm
500 ppm
1,000 ppm
2,000 ppm
2,300 ppm
Ca
50 ppm
Notes:
a Source: OSHA(1997a)
b PEL= Permissible exposure limit ; TWA= Time-weighted average
c Airborne concentration conversion factor for DCM is 3.47 mg/m3 per ppm (NIOSH, 2011b).
d IDLH = Immediately dangerous to life and health. IDLH values are based on effects that might occur from a
30-minute exposure.
e REL = Recommended Exposure Limit. The REL notation "Ca" is for a potential occupational carcinogen. The
NIOSH Pocket Guide website has detailed policy recommendations for chemicals with "Ca" notations
(NIOSH, 2011a).
f TLV = Threshold limit value
Page 186 of 279
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G-3 Summary of Inhalation Monitoring Data
Data summaries from the literature search are presented below by sector. Inhalation exposure
monitoring data of DCM during paint stripping, specifically full-shift 8-hr TWA breathing zone or
personal samples, were used for risk analyses. Data monitoring of over 5 hour duration are
assumed adequate to represent full shift exposure levels. Area and short-term samples were
found and presented in the discussions of literature data for perspective and completeness, but
were not used in the occupational exposure concentration calculations and risk analyses.
Personal breathing zone samples provide a better representation of the amount of DCM
inhaled by the workers when compared to area samples.
G-3-1 Bathtub Refinishing Exposures and Fatalities
In 2012, the U.S. Centers for Disease Control and Prevention (CDC) reported on bathtub
refinisher fatalities associated with DCM-based stripping agents. Key excerpts from the CDC
Morbidity and Mortality Weekly Report (MMWR) are discussed below (CDC, 2012).
In addition to 3 deaths identified by the Michigan Fatality Assessment and Control Evaluation
(FACE) program, OSHA identified 10 other bathtub refinisher fatalities associated with DCM-
based stripping agents that had been investigated in 9 states during 2000 to 2011. Each death
occurred in a residential bathroom with inadequate ventilation. Protective equipment,
including a respirator, either was not used or was inadequate to protect against DCM vapor.
Inhalation of DCM vapors has been recognized as potentially fatal to furniture strippers and
factory workers, but has not been reported previously as a cause of death among bathtub
refinishers (CDC. 2012).
A review of the IMIS, a database for federal and state OSHA investigations, identified 12
DCM-related deaths associated with professional bathtub refinishing operations during 2000 to
2011. One of the 3 deaths identified by the Michigan program was not in IMIS because the
decedent was self-employed and was therefore outside OSHA's enforcement jurisdiction. The
ages of the 13 decedents ranged from 23 to 57 years (median: 39 years) and 12 were male. Ten
different products were associated with the 13 deaths. Six of the products were marketed for
use in the aircraft industry, the rest for use on wood, metal, glass, and masonry. None of the
product labels mentioned bathtub refinishing. The percentage of DCM in the products ranged
from 60 to 100 percent (CDC. 2012).
Moreover, analysis of IMIS data regarding deaths from inhalation of DCM vapor showed an
increase in cases involving bathtub refinishing since 2000. During 1976 to 1999, only two of all
DCM deaths (i.e., 8 percent) investigated by OSHA were linked to bathtub refinishing. Since
2000, 13 of the DCM deaths (i.e., 75 percent) investigated by OSHA occurred during bathtub
refinishing (CDC. 2012).
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The Michigan FACE program estimated DCM exposure concentrations as part of an
investigation of a bathtub refinishing fatality reported in May 2010 (MSU/MIFACE, 2011).
The concentration of DCM vapor was estimated at 92,949 ppm to 154,916 ppm (322,533 to
537,559 mg/m3) in the bathtub and 5,099 ppm to 8,499 ppm (17,694 to 29,492 mg/m3) in the
bathroom. The concentration ranges were estimated using a simple modeling technique that
considered the size of the bathroom, size of the tub, and an estimate that six fluid ounces
(177 ml) of DCM-based stripper were used during a typical job. Also, the product used was an
aircraft paint stripper product containing 60 to 100 percent DCM. The estimated concentrations
exceeded the NIOSH Immediately Dangerous to Life and Health (IDLH) level of 2,300 ppm
(7,981 mg/m3) (CDC, 2012). Further details about the fatality case are available in the MMWR
(CDC. 2012). the NIOSH FACE Program Michigan Case Report 10MI013 (Chester et al.. 2012).
and the Michigan State University (MSU)/FACE Report (MSU/MIFACE. 2011).
The MSU/Michigan FACE reported a case of high DCM exposure while stripping a bathtub
(MSU/MIFACE, 2011). The case was noted after an inspection conducted by the Washington
State's Department of Labor and Industries Division of Occupational Safety and Health (DOSH).
Although the exact date of the Washington DOSH inspection was not cited, the inspection
occurred between April 2003 and August 2008 (Lofgren etal., 2010).
During the inspection, a bathtub refinishing employee was monitored while stripping a
residential bathtub with Kleen Strip Aircraft Remover. The product contained less than 85
percent DCM based on the MSDS. The product information sheets recommended the use of
supplied air while using the stripper. The employee had purchased ventilation equipment,
which was in use at the time of monitoring, and wore a half-face air purifying respirator. Two
personal samples were taken in the breathing zone of the employee for 15 minutes during the
stripping task. The DCM concentrations for the personal breathing samples were 2,180 ppm
(7,565 mg/m3) and 2,000 ppm (6,940 mg/m3)23. Two area samples were also taken and the
DCM concentrations were 545 ppm (1,891 mg/m3) and 314 ppm (1,090 mg/m3). All of the
samples significantly exceeded the OSHA 15-minute TWA STEL of 125 ppm (434 mg/m3), and
the two breathing zone samples were close to the NIOSH IDLH value of 2,300 ppm
(7,981 mg/m3) (MSU/MIFACE. 2011).
DCM exposure data for paint stripping conducted by professional contractors were not
identified in the literature search. However, EC (1999) reported some DCM exposure data for
consumer use of DCM-based paint strippers. The EU report states that there is "probably. ..no
fundamental difference between the application of paint removers by professional painters and
consumers" and goes on to further state that, in regard to the cited consumer exposure studies,
23 The 15-min DCM air concentrations of 6,940 mg/m3 (2,000 ppm) and 7,565 mg/m3 (2,180 ppm) were selected to
represent the low and high ends of the range of short-term and other non-8-hr TWA values, respectively, for
the breathing zone of bathtub refinishers in Table G-2 (MSU/MIFACE, 2011). EPA/OPPT calculated midpoint
values from the high and low values reported by the study authors.
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"the test situations and data described...are assumed valid for occupational exposure during
professional use as well" (EC, 1999).
There are differences between the consumer and occupational use of DCM-based paint
strippers by professional contractors. For instance, professional contractors are expected to
have higher frequencies and durations of exposure, and a likely higher prevalence of respirator
use, as compared to consumers. It is also not clear whether overall activity patterns and
practices of contractors match those of consumers or whether the overall distributions of
exposures of contractors and consumers have any semblance to one another. Despite these
uncertainties, EPA/OPPT considered some of the literature data for consumers in the
occupational exposure assessment of paint strippers.
The EU report conducted a literature review and identified the following consumer exposures
to DCM during paint stripping (EC, 1999):
• A 1990 EPA investigation estimated consumer exposure levels ranging from 35 mg/m3
(10 ppm) to a few short-term exposures of over 14,100 mg/m3 (4,063 ppm)24. The majority
of the exposures were below 1,770 mg/m3 (510 ppm) (EC, 1999).
• A separate study conducted by a solvent manufacturer measured DCM exposures during
testing in a small room. One test conducted with ventilation measured a 2-hr TWA exposure
of 289 mg/m3 (83.3 ppm), but the ventilation rate or air change rate was not specified. The
peak exposure during application was 460 mg/m3 (133 ppm). The peak exposure during
scrape-off ranged from 710 to 1,410 mg/m3 (205 to 406 ppm), and the observed maximum
during the study was 3,530 mg/m3 (1,017 ppm). When no ventilation was used, the worst-
case exposure exceeded 14,000 mg/m3 (4,035 ppm). Based on the solvent manufacturer,
8-hr TWA exposures under supplier-recommended ventilation would be 187 to 226 mg/m3
(54 to 65 ppm) (EC. 1999).
• A literature review conducted by the United Kingdom (UK) in 1998 identified 1-hr TWA
exposures of 840 to 2,765 mg/m3 (240 to 790 ppm) in an unventilated room, and 129.5 to
948 mg/m3 (37 to 270 ppm) with the door open (EC, 1999).
24 The short-term exposure of over 14,100 mg/m3 (4,063 ppm) was selected to represent the high end of the range
of short-term and other non-8-hr TWA values for professional contractors in Table G-2 (EC, 1999). EPA/OPPT
calculated the midpoint values from the high-end values reported by the study authors.
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• An older study from 1981 found 8-hr TWA exposures of 460 to 2,980 mg/m3 (133 to
859 ppm)25 in unventilated rooms and 60 to 400 mg/m3 (17 to 115 ppm)21 in ventilated
rooms (EC. 1999).
Another EU report described a 2004 study that cited several case studies of DCM monitoring
during paint stripping of buildings in the UK (EU, 2007).
• An average personal DCM exposure of 182 mg/m3 (52 ppm), ranging from 21 to 318 mg/m3
(6 to 92 ppm), was reported for "paint stripping at a block of flats" (EU, 2007).
• A case study of paint stripping in a building stairway reported an average personal DCM
exposure of 86 mg/m3 (25 ppm) (EU, 2007).
• Another case study observed an average personal DCM exposure of 710 mg/m3 (205 ppm)
while paint stripping a ceiling. The DCM air concentration was measured during brush
application and stripping over approximately 40 minutes (EU, 2007).
• A 2003 case study of the paint stripping of an external facade observed personal monitoring
DCM concentrations with a maximum of 400 mg/m3 (115 ppm) and a minimum of zero
mg/m3 26. The average of all of the reported means was approximately 62 mg/m3 (18 ppm)
(EU. 2007).
Midwest Research Institute (MRI) prepared a report for EPA in 1994 that documented an
experimental investigation of consumer exposures to solvents used in paint stripping products
with eliminated or reduced DCM content. MRI investigated five paint strippers, two of which
contained DCM (along with other solvents, but the concentrations were not specified). The
paint stripping was conducted in a laboratory-based, environment-controlled, room-sized test
chamber. The paint strippers were used on a plywood panel coated with a primer coat and two
finish coats. The air exchange rate for the experiments ranged from 0.54 to 0.76 air changes per
hr (ACH), with an average of 0.58 ACH. The air exchange rate of approximately 0.5 ACH was
intended to replicate the ventilation rate of an enclosed room in a typical residence as a worst-
case scenario (EPA, 1994a).
During each experiment, the following samples were taken for the spray and brush
applications: a personal breathing zone sample of the test subject using the paint stripper; two
stationary air samples for the duration of the paint stripping task; and one stationary air sample
25 The DCM air concentrations of 60 mg/m3 (17 ppm) and 2,980 mg/m3 (859 ppm) were selected to represent the
low and high ends of the range of 8-hr TWA values, respectively, for professional contractors in Table G-2 (EC,
1999). EPA/OPPT calculated midpoint values from the high and low values reported by the study authors.
26 The short-term exposure of 0 mg/m3 was selected to represent the low end of the range of short-term and other
non-8-hr TWA values for professional contractors in Table G-2 (EC, 1999).
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beginning at the start of the paint stripping and lasting for 8 hrs (EPA, 1994a). The results are
summarized below.
• For the spray application of the DCM-based paint stripper, MRI reported breathing zone
DCM concentrations of 3,000 and 3,400 mg/m3 (865 and 980 ppm) over 1.7- and 1.5-hour
sampling times, respectively. The stationary length-of-task concentrations ranged from
2,900 to 3,600 mg/m3 (836 to 1,037 ppm). The stationary, 8-hr TWA concentration ranged
from 1,700 to 2,000 mg/m3 (490 to 576 ppm) (EPA. 1994a).
• MRI reported breathing zone concentrations of 380 and 430 mg/m3 (110 and 124 ppm) over
sampling times of approximately 2 hours for the brush application. The stationary length-of-
task concentrations ranged from 300 to 490 mg/m3 (86 to 141 ppm). The stationary, 8-hr
TWA concentration ranged from 230 to 270 mg/m3 (66 to 78 ppm) (EPA, 1994a).
G-3-3^
Anundi et al. (1993) described a study of personal monitoring conducted on 12 workers of a
Swedish graffiti removal company. The study authors observed the workers remove graffiti
from underground stations and noted that some of the graffiti removal was conducted in
confined spaces. None of the workers were observed to wear respirators.
The study authors measured half-day DCM concentrations for the 12 workers and then
calculated an 8-hr TWA concentration for each worker. Additionally, the study authors
measured 15-min samples for 10 of the 12 workers (Anundi et al., 1993). Table G-7 summarizes
the DCM personal sample concentration results for the 12 graffiti removal workers.
The study authors noted that the highest 15-min sample concentration (5,315 mg/m3) was
measured while the worker was working in an elevator (Anundi et al., 1993). This observation
illustrates how working in a confined space, with limited ventilation, can lead to high DCM
exposures
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Table G 7. Summary of DCM Personal Concentrations during Graffiti Removal
Arithmetic Mean
Geometric Mean
High Value
Midpoint c
Low Value
Geometric
Standard Deviation
Number of Workers
Calculated 8-hr TWA
Concentrations (mg/m3)
(values in parentheses are in ppm)b
260 (75) d
127 (37)
1,188 (342) d
603 (174) d
18(5.2)d
3.6(1.0)
12
Notes:
a Source: Anundi et al. (1993)
15-min Sample Concentrations
(mg/m3)
(values in parentheses are in ppm)b
1,117 (322) e
400 (115)
5,315 (l,532)e
2,661 (767) e
6(1.7)e
5.6(1.6)
10
b EPA/OPPT converted concentrations reported by the study authors in units of mg/m3 to units of ppm.
c EPA/OPPT calculated midpoint values from the high and low values reported by the study authors.
d The DCM air concentrations of 18 mg/m3, 260 mg/m3, 603 mg/m3, and 1,188 mg/m3 were selected to
represent the low end of range, mean, midpoint, and high end of range for 8-hr TWA values, respectively,
for graffiti removal in Table G-2.
e The DCM air concentrations of 6 mg/m3, 1,117 mg/m3, 2,661 mg/m3, and 5,315 mg/m3 were selected to
represent the low end of range, mean, midpoint, and high end of range for short-term values,
respectively, for graffiti removal in Table G-2.
G-3-4
Paint Stripping at Automotive Body Repair and Maintenance Shops
Enander et al. (2004) described a study in Rhode Island that conducted personal air sampling of
workers in two complete vehicle repainting facilities 27 and one vocational technical school. The
DCM monitoring was conducted on a single worker in a vehicle repainting shop for one day in
the spring and one day in the fall. This worker engaged in paint stripping one to two times per
week and 3 to 4 hrs per day. The spring 8-hr TWA exposure was 26 ppm (90 mg/m3)28 and the
fall 8-hr TWA exposure was 120 ppm (416 mg/m3). These exposures exceeded OSHA's 8-hr TWA
action level (12.5 ppm or 43 mg/m3) and PEL (25 ppm or 87 mg/m3), respectively.
Additionally, three task-based samples were taken in the spring (with sampling times ranging
from 9 to 18 minutes). These exposures were 72 ppm (250 mg/m3)29, 93 ppm (323 mg/m3), and
27 Repainting facilities are shops that specialize in repainting the entire surface of cars and small trucks.
28 The DCM air concentrations of 90 mg/m3 and 416 mg/m3 were selected to represent the low and high ends of
range for 8-hr TWA values, respectively, for automotive refinishing in Table G-2 (Enander et al., 2004). EPA/OPPT
calculated the mean and the midpoint values from the high and low values reported by the study authors. The
mean and the midpoint values are the same because there are only two samples for this data set.
29 The DCM air concentrations of 250 mg/m3 and 416 mg/m3 were selected to represent the low and high ends of
the range for short-term and other non-8 hr TWA values, respectively, for automotive refinishing in Table G-2.
EPA/OPPT calculated the mean value for the three task-based samples, as well as the midpoint value from the
high and low values reported by the study authors.
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120 ppm (416 mg/m3), which had a mean value of 95 ppm (330 mg/m3) and were all below the
OSHA STEL (125 ppm or 434 mg/m3) (Enander et al.. 2004).
NIOSH surveyed a furniture refinishing shop located in Littleton, Colorado after receiving an
invitation from the facility owner (NIOSH, 1993). The facility employed 5 refinishers, although
the total number of workers was not specified. The facility stripped furniture in a separate
room using a pump and brush technique to apply paint stripper and remove the paint. The
stripper was pumped from a 55-gallon drum to the brush, collected from the table, and
recycled. The stripping time of each worker averaged at a few hours per week, but reached as
high as 3 to 4 hrs in a day. While stripping, the workers wore rubber aprons, full-length rubber
gauntlets, a face shield, and plastic upper arm covers, and they also may have worn the safety
goggles they wore in the wood shop area (NIOSH, 1993).
NIOSH surveyed the facility three times: an initial survey on October 10, 1992; a second survey
on November 20, 1992 after an exhaust ventilation system was installed on the furniture
stripping booth; and a third survey on February 10, 1993 after an exhaust ventilation system
was installed on the wash booth (NIOSH, 1993). Tables G-8, G-9, and G-10 present the
measurements that NIOSH made during these three surveys.
The results indicate that the addition of engineering controls reduced exposure concentrations
in both the personal and area samples. For instance, the initial survey indicated that personal
exposure concentrations associated with stripping activities ranged from 83 ppm (288 mg/m3)
to 523 ppm (1815 mg/m3) over a range of sampling times with an average of 347 ppm
(1,204 mg/m3) (Table G-8). After the addition of the stripping booth exhaust ventilation system,
the second survey indicated that personal exposure concentrations associated with stripping
activities dropped to a range of 10 ppm (35 mg/m3) to 110 ppm (382 mg/m3) over a range of
sampling times with an average of 72 ppm (249 mg/m3) (Table G-9). This range and average
concentration are generally consistent with the personal exposure concentrations associated
with stripping activities observed on the third survey (after controls were added to the wash
booth) (Table G-10) (NIOSH. 1993).
Personal samples were not taken during washing activities, and area samples were not taken at
consistent, wash-booth area locations during all surveys. However, the area samples altogether
do indicate a reduction in concentrations after installation of the ventilation systems. The 8-hr
TWA exposures, which were 8-hr averages of the individual samples and not the samples
themselves, were below the pre-1997 OSHA PEL of 500 ppm (1,735 mg/m3) but above the
ACGIH Threshold Limit Value (TLV) of 50 ppm (174 mg/m3). NIOSH noted that after the
ventilation systems were installed, the 8-hr TWA exposures were all below 50 ppm (174 mg/m3)
(NIOSH. 1993).
Grevenkamp (2007) described follow-up activities by OSHA in the inspection of a small business
that repaired and restored custom-made furniture. The facility employed 18 workers, but only a
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single worker worked 3 to 4 days per week using DCM to remove paint and varnish from
furniture in one section of the facility. The worker used a compressed-air system to spray DCM
onto the furniture on a shallow tray. Excess stripper drained through the tray and was
recirculated into a 208-L drum for reuse.
OSHA conducted personal monitoring of the worker while he was wearing a full-face
elastomeric respirator with organic vapor cartridges and impervious gloves and an apron. OSHA
measured an 8-hr TWA exposure of 108 ppm (375 mg/m3), which was above the OSHA PEL of
25 ppm (87 mg/m3). OSHA also measured 7 STEL sampling results, which ranged from 153 ppm
(531 mg/m3) to 662 ppm (2,297 mg/m3), with an average of 404 ppm (1,402 mg/m3). These
measurements were all above the OSHA STEL of 125 ppm (434 mg/m3). The facility was cited
for the overexposure and required to implement controls, including work practice and
engineering controls and the use of a NIOSH-approved supplied-air respirator (Grevenkamp,
2007).
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Table G 8. Summary of Personal and Area Concentrations in a Furniture Refinishing Shop
that Uses a Pump and Brush Stripping Technique Measured Before Engineering
Controls were Added
Initial Survey (Before Controls Added) a
Personal Samples
Activity
Stripping large
chest
Stripping
headboard
Stripping
wicker chairs
Stripping large
dresser and
drawers
Stripping large
dresser and
drawers
Hand strip
table with
Palco gel
stripper
Hand strip
table with gel
Concentration
(mg/m3)
(values in parentheses
are in ppm) b
1,437
(414)
1,815
(523)
1,381
(398)
1,544
(445)
1,364
(393)
288
(83)
604
(174)
Notes:
a Source: NIOSH (1993)
Sampling
Time
(Minutes)
78
101
23
58
30
14
16
Area Samples
Location
Door at room
entrance
Door at room
entrance
Edge of
stripping booth
above recycle
can
Above water
reservoir
between wash
booth and
outside wall
Workbench
south of wash
booth
Above drum of
bulk stripper
Above drum of
bulk stripper
Concentration
(mg/m3)
(values in parentheses
are in ppm) b
576
(166)
579
(167)
854
(246)
180
(52)
128
(37)
416
(120)
298
(86)
Sampling
Time
(Minutes)
102
78
59
62
182
60
102
b EPA/OPPT converted concentrations reported by the study authors in units of ppm to units of mg/m3.
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Table G 9. Summary of Personal and Area Concentrations in a Furniture Refinishing Shop
that Uses a Pump and Brush Stripping Technique Measured After Engineering
Controls were Added to the Stripping Booth
Second Survey (After Controls Added to Stripping Booth) a
Personal Samples
Activity
Stripping six
chairs
Stripping
crib
Strip large
desk
Concentration
(mg/m3)
(values in
parentheses
are in ppm) b
35
(10)
330
(95)
382
(110)
Sampling
Time
(Minutes)
35
33
103
Notes:
a Source: NIOSH (1993)
Area Samples
Location
Center of room (before
ventilation system turned
on)
Above newly stripped chairs
South central part of room
near newly stripped crib
Near newly stripped desk
drawers
Edge of wash booth (near
worker breathing zone)
Edge of wash booth (near
worker breathing zone)
Edge of wash booth (near
worker breathing zone)
On work bench behind wash
booth
Above DCM waste buckets
Above wash sludge tank
Concentration
(mg/m3)
(values in
parentheses
are in ppm) b
111
(32)
295
(85)
87
(25)
111
(32)
416
(120)
201
(58)
205
(59)
16
(4.6)
52
(15)
22
(6.3)
Sampling
Time
(Minutes)
18
82
42
59
33
34
101
102
215
57
b EPA/OPPT converted concentrations reported by the study authors in units of ppm to units of mg/m3.
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Table G 10. Summary of Personal and Area Concentrations in a Furniture Refinishing Shop
that Uses a Pump and Brush Stripping Technique Measured After Engineering
Controls were Added to the Stripping Booth and Wash Booth
Third Survey (After Controls Added to Stripping Booth and Wash Booth) a
Personal Samples
Activity
Stripping rocking
chair
Stripping seven
chairs
Stripping chairs
Stripping large
dresser
Stripping dresser
drawers
Concentration
(mg/m3)
(values in
parentheses
are in ppm) b
66
(19)
312
(90)
125
(36)
243
(70)
382
(110)
Sampling
Time
(Minutes)
24
52
97
113
61
Area Samples
Location
Center of room
Near entrance to
room
Above door to
entrance of room
Above door to
entrance of room
Above stripping
drum
Above stripping
drum
Above stripping
drum
Above stripping
drum
Above wash sludge
tank
Near drying chairs
Above dresser while
drying
Concentration
(mg/m3)
(values in
parentheses
are in ppm) b
7
(2.0)
19
(5.5)
14
(4.0)
29
(8.4)
<14
(<4.0)
9
(2.6)
17
(4.9)
NDC
17
(4.9)
38
(11)
62
(18)
Sampling
Time
(Minutes)
30
102
84
178
25
75
87
182
92
113
107
Notes:
a Source: NIOSH (1993)
b EPA/OPPT converted concentrations reported by the study authors in units of ppm to units of mg/m3.
c ND - not detected at a limit of 0.01 mg per sample
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OSHA followed-up with the facility 10 months later and found the worker using a supplied-air
respirator, but the facility had only added a wall-mounted fan to blow vapors away from the
work area towards the ventilation hood at the rear of the tray. OSHA measured an 8-hr TWA
personal exposure of 61 ppm (212 mg/m3), which was still above the OSHA PEL. OSHA also
measured two STEL exposures of 330 ppm (1,145 mg/m3) and 380 ppm (1,319 mg/m3), which
were still above the OSHA STEL (Grevenkamp, 2007).
The facility hired a consultant who would recommend the installation of engineering controls
and the implementation of exposure reduction work practices. The consultant's preliminary
investigation of the facility observed an 8-hr TWA exposure of 208 ppm (722 mg/m3) and a STEL
exposure of 1,072 ppm (3,720 mg/m3). Subsequently, the facility installed additional fans, and
the consultant made a series of 6 visits to the facility to conduct personal monitoring during the
paint stripping and further advice on the exposures. Over these six visits, the consultant
measured five 8-hr TWA exposures ranging from 44 ppm (153 mg/m3) to 647 ppm
(2,245 mg/m3)30 with an average of 278 ppm (965 mg/m3). The consultant also measured 12
STEL or task-based samples (approximately 3 hrs), ranging from 298 ppm (1,034 mg/m3) to
2,015 ppm (6,992 mg/m3)31 with an average of 926 ppm (3,213 mg/m3) (Grevenkamp, 2007).
OSHA visited the facility again and measured an 8-hr TWA exposure of 192 ppm (666 mg/m3)
and three STEL exposures ranging from 300 ppm (1,041 mg/m3) to 811 ppm (2,814 mg/m3) with
an average of 481 ppm (1,669 mg/m3). OSHA then recommended improved engineering
controls consisting of a combination of a slotted back draft hood coupled with a downdraft
ventilation system. After the facility implemented these controls, OSHA measured an 8-hr TWA
exposure of 1.16 ppm (4 mg/m3)32 and a STEL exposure of 5.5 ppm (19 mg/m3)33, both of which
were well below their respective OSHA limits (Grevenkamp, 2007). This case study illustrates
that the implementation of engineering controls to reduce DCM exposures during furniture
paint stripping may not be a trivial exercise and careful engineering may be required to achieve
reduced exposures.
Hall et al. (1995) described a NIOSH visit to a furniture stripping and refinishing facility. The
purpose of the visit was to evaluate the facility's current ventilation system and recommend a
new system, if needed. The facility employed a total of 6 full-time employees, including two co-
owners. Two employees regularly stripped furniture on a daily basis while the other employees
performed other refinishing operations. The facility used a dip tank for stripping, followed by a
rinse, drying, and then applying the new finish. The stripping solutions were prepared by the
facility and contained 60 to 80 percent DCM.
30 The DCM air concentrations of 2,245 mg/m3 was selected to represent the high end of the range of 8-hr TWA
values for furniture refinishing in Table G-2 (Grevenkamp, 2007).
31 The DCM air concentrations of 6,992 mg/m3 was selected to represent the high end of the range of short-term
and other non-8-hr TWA values for furniture refinishing in Table G-2 (Grevenkamp, 2007).
32 The DCM air concentrations of 4 mg/m3 was selected to represent the low end of the range of 8-hr TWA values
for furniture refinishing in Table G-2 (Grevenkamp, 2007).
33 The DCM air concentrations of 19 mg/m3 was selected to represent the low end of the range of short-term and
other non-8-hr TWA values for furniture refinishing in Table G-2 (Grevenkamp, 2007).
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NIOSH reported that DCM levels were 2,160 ppm (7,495 mg/m3) without the ventilation
system, which prompted the facility to activate the existing ventilation system. The existing
ventilation system reduced DCM levels to 230 ppm (798 mg/m3). After completing the initial air
sampling, NIOSH evaluated the existing ventilation system and recommended a new design.
The facility installed the NIOSH-recommended design and NIOSH evaluated this new slotted
hood ventilation system. During this evaluation, NIOSH measured the exposures of the 2
workers performing the stripping operations over a period of 3 days (Hall et al., 1995).
Table G-ll summarizes NIOSH's personal monitoring results of the two workers. NIOSH noted
that, after the implementation of the recommended ventilation system, the exposures during
rinsing were greater than exposures during stripping since the rinsing area was still not being
locally ventilated. The NIOSH researchers felt that exposures could be reduced to meet the (at
the time proposed) OSHA PEL of 25 ppm (87 mg/m3) if the rinse area controls were improved
(Hall etal.. 1995).
McCammon et al. (1991) described a NIOSH industrial hygiene survey of 14 furniture stripping
workers exposed to DCM across 5 furniture stripping shops. The number of workers monitored
per shop ranged from 1 to 4. These monitored workers performed tasks including stripping,
washing, and refinishing.
Personal air sampling of these facilities reported TWA exposures to DCM ranging from 15 ppm
(52 mg/m3) to 366 ppm (1270 mg/m3) over 5 to 8 hrs with an overall average of 133 ppm
(462 mg/m3). A shop where a single worker was monitored (who performed both stripping and
washing) had a 4-hr TWA exposure of 57 ppm (198 mg/m3). The highest average exposures to
DCM by job category were: 191 ppm (663 mg/m3) for strippers; 145 ppm (503 mg/m3) for
washers; and 31 ppm (108 mg/m3) for refinishers. These TWA exposures were below the pre-
1997 OSHA PEL of 500 ppm (1,735 mg/m3). However, NIOSH noted that the monitoring was
conducted in the summer and the shop doors were open to allow increased ventilation. The
NIOSH researchers postulated that the exposures may be among the lowest for the work year
since the doors were open and if all other relevant parameters were constant throughout the
year (McCammon et al., 1991).
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Table G 11. Summary of Worker Exposures to DCM During Furniture Paint Stripping using a
Dip Tank after Implementation of NIOSH Recommended Slotted Hood
Ventilation System3
Number
of
Samples
Sample Concentration
Ranges (mg/m3)
(values in parentheses
are in ppm) b
Total
Time
Sampled
(min)
Total
Time
Sampled
(hr)
Personal
TWA Concentration (mg/m3) c
(values in parentheses
are in ppm) b
WORKER A
Dayl
Day 2
Day 3
5
4
3
35-274
(10-79)
21-115
(6-33)
90-239
(26-69)
407
224
227
6.78
3.73
3.78
125
(36)
49
(14)
160
(46)
WORKER B
Dayl
Day 2
Day 3
Notes:
a Source
5
6
4
45-278
(13-80)
45-323
(13-93)
28-239
(8-69)
Hall etal. (1995)
461
549
287
7.68
9.15
4.78
243
(70)
160
(46)
167
(48)
b EPA/OPPT converted concentrations reported by the study authors in units of ppm to units of mg/m3.
c The personal samples over 5 hours (300 minutes) were assumed to be representative of full-shift 8-hr TWA
exposure concentrations.
In 1990, NIOSH conducted surveys in 2 furniture stripping facilities: one in Pennsylvania and the
other one in Ohio. These surveys are described below.
• Furniture stripping workshop in Meadow Lands, Pennsylvania: The workshop used a flow-
over tank with a solution recycling system to strip furniture. The furniture was placed in
tank, covered with stripping solution, and then scrubbed by a worker. During scrubbing, the
worker alternated between brushing the furniture and covering it with more stripping
solution. After stripping, the furniture was rinsed and brushed, dried, sanded, and
refinished. The facility used a stripping solution that contained 60 volume percent DCM
(Estill and Spencer. 1996: NIOSH. 1991).
The workshop installed a ventilation system in response to the results of an OSHA
inspection. The NIOSH survey was conducted after installation of the ventilation system to
determine its adequacy. Measurements conducted by NIOSH found personal TWA exposure
levels ranging from 613 ppm (2,127 mg/m3) to 1,152 ppm (3997 mg/m3) during stripping
(averaged over stripping times of 177 to 260 minutes). NIOSH found the ventilation system
to be inadequate as exposure levels exceeded the pre-1997 OSHA PEL of 500 ppm
Page 200 of 279
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(1,735 mg/m3). After completing the air sampling, NIOSH made recommendations for
improving the ventilation system (Estill and Spencer, 1996; NIOSH, 1991).
After modifications to the ventilation system were made, NIOSH measured personal
exposures during stripping on 3 different days while varying the ventilation system
configuration between slot hood, downdraft, and combination modes on each day. The
three daily average DCM exposures were 25 ppm (87 mg/m3), 41 ppm (142 mg/m3), and
22 ppm (76 mg/m3), which were sampled during stripping operations over 4.6, 5.5, and
4.7 hrs, respectively. The ranges of breathing zone concentrations for the 3 days were: 13
to 64 ppm (45 to 222 mg/m3); 17 to 106 ppm (59 to 368 mg/m3); and 6 to 32 ppm (21 to
111 mg/m3), respectively. The corresponding calculated 8-hr TWA exposures were 15, 29,
and 13 ppm (52,101, and 45 mg/m3), respectively. The 9 individual measurements taken
over the 3 days and over the 3 different ventilation system configurations ranged from 7 to
59 ppm (24 to 205 mg/m3) averaged over time periods ranging from 49 to 147 minutes
(Estill and Spencer. 1996: NIOSH. 1991).
• Furniture stripping facility in Cincinnati, Ohio: This facility was operated solely by the owner.
The facility conducted dip-tank paint stripping using a DCM-based paint stripper (72 weight
percent DCM) and hand stripping using a paint stripper that did not contain DCM. NIOSH
measured 1-hr TWA concentrations of breathing zone and area samples. NIOSH observed
breathing zone concentrations of 100 ppm (347 mg/m3) and 77 ppm (267 mg/m3) of the
facility owner and the NIOSH employee, respectively. NIOSH observed three area
concentrations of 20 ppm (69 mg/m3), 63 ppm (219 mg/m3), and 90 ppm (312 mg/m3). The
highest area concentration was observed near the dip tank, the middle concentration was
observed near the rinse area, and the lowest concentration was observed near the doorway
to the stripping area. These measurements were below the pre-1997 OSHA PEL of 500 ppm
(1,735 mg/m3) (NIOSH. 1990).
• NIOSH noted the local exhaust near the dip tank had very low intake velocity and the air
movement in the stripping area was generally inadequate. NIOSH also noted that the facility
owner wore neoprene gloves and boots while stripping, rinsing, and handling the solution-
soaked furniture, but no other personal protective equipment was worn (NIOSH, 1990).
The EC (1999) report described a 1990 EPA source that cited exposure levels in furniture paint
stripping ranging from 258 to 3,812 mg/m3 (74 to 1,099 ppm) in the absence of adequate
control measures.
EPA/OPPT was able to calculate several key statistical values from the forty-three 8-hr TWA
samples reported in the literature for this industry. This data set was found to have a mean
value of 499 mg/m3 (144 ppm) and a 95th-percentile value of 1,266 mg/m3 (365 ppm) (Table G-
2).
Page 201 of 279
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G-3-6 Art Restoration and Conservation
EPA/OPPT did not identify exposure data associated with art restoration and conservation. The
exception was a single exposure data point reported in the OSHA IMIS data set (Table G-12).
The data point was an 8-hr TWA exposure of 2 mg/m3 (0.58 ppm) and corresponded to the
exposure of a manager (OSHA, 2012a). This is the only value reported for art restoration and
conservation in Table G-4. The relevance of this exposure to DCM-based paint stripping is
uncertain but is assumed to have been caused by a DCM-based stripper.
G-3-7_ A*I^^
NIOSH (1977) identified DCM exposure data corresponding to the breathing zone of workers
engaged in aircraft paint stripping in the U.S. in 1977. The breathing zone samples are
summarized below.
• Paint stripping of a wide body aircraft: A set of 23 breathing zone samples were collected
over a range of sampling times of 11 to 52 minutes. Personal air samples ranged from 79 to
950 mg/m3 (23 to 274 ppm) with a mean of 379 mg/m3 (109 ppm).
• Paint stripping of a narrow body aircraft: A set of 20 breathing zone samples were collected
over sampling times generally less than 33 minutes with one sampling time of 267 minutes.
Personal air samples ranged from 3834 to 2,820 mg/m3 (11 to 813 ppm) with a mean of
795 mg/m3 (229 ppm).
A UK study observed aircraft paint stripping using a spray process and found DCM 8-hr TWA
exposures of 29 to 95 ppm (101 to 330 mg/m3), with a mean of 62 ppm (215 mg/m3). Peak
levels were as high as 1,600 ppm (5,552 mg/m3)(EC. 1999: EU. 2007).
Vincent et al. (1994) observed the paint stripping of a Boeing 747 in an aeronautical workshop.
Personal monitoring of 30 painters, working in teams of 6 to 10 in three, 8-hr shifts, was
conducted over 2 work days. During paint stripping operations, DCM concentrations ranged
from 299.2 mg/m3 (86 ppm) to 1,888.9 mg/m3 (544 ppm) over 38 data points with a mean of
783.4 mg/m3 (226 ppm) for directly exposed workers performing the stripping operations.
These measurements were taken over sampling times ranging from 120 to 330 minutes. The
calculated 8-hr TWA exposures to DCM ranged from 86 mg/m3 (25 ppm)35 to 1,239.5 mg/m3
(357 ppm) with a mean of 382 mg/m3 (110 ppm).
Additional data points (n=7) were collected for indirectly exposed workers applying masking
film to non-stripped surfaces. These measurements ranged from 317.2 to 762.5 mg/m3 (91 to
220 ppm) with a mean concentration of 464 mg/m3 (134 ppm). The calculated 8-hr TWA
34 The DCM air concentration of 38 mg/m3 was selected to represent the low end of the range of short-term and
other non-8-hr TWA values for aircraft paint stripping in Table G-2 (NIOSH, 1977).
35 The DCM air concentration of 86 mg/m3 was selected to represent the low end of the range of 8-hr TWA values
for aircraft paint stripping in Table G-2 (Vincent et al., 1994).
Page 202 of 279
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exposures to DCM ranged from 97.2 to 174.6 mg/m3 (28 to 50 ppm) with a mean of
128.2 mg/m3 (37 ppmHEU. 2007: IARC. 1999: Vincent et al.. 1994).
Norwegian studies from 2001 and 2002 found 8-hr TWA exposures to DCM associated with
paint removal of aircraft of 1,444, 2,319, and 3,802 mg/m3 (416, 668, and 1,096 ppm,
respectively)36from personal samples (EU, 2007).
The EC (1999) report cited a 1998 UK study that reported 8-hour TWA exposures to DCM during
aircraft paint stripping. The 8-hr TWA air concentrations ranged from 101 to 330 mg/m3 (29 to
95 ppm) with a mean of 210 mg/m3 (61 ppm). The same study also stated that peak exposures
as high as 5,400 mg/m3 (1,556 ppm)37 were possible (EC, 1999).
A 2006 study cited DCM exposures during aircraft paint stripping in Taiwan. Personal samples
were collected during activities at 4 different locations of the aircraft: the ground, the nose, the
right wing, and the left wing. The number of personal samples taken at each location ranged
from 8 to 13. The resulting 2-hr average concentrations were 146, 75, 81, and 71 mg/m3 (42,
22, 23, and 20 ppm) for the ground, nose, right wing, and left wing, respectively. The standard
deviations of each average ranged from 40 to 111 mg/m3 (12 to 32 ppm), indicating a significant
degree of scatter for each data set (IARC, 2010).
G-5-8 ?!][^^
EPA/OPPT identified limited data for paint stripping of ships. IARC (2010) described a 1980 UK
monitoring study of 8 painters over two days in a dockyard. The study results included a mean
concentration of DCM of 214.7 mg/m3 (62 ppm). The exposure was associated with one painter
conducting paint stripping.
G-3-9^ ^!!!?M^PEi'?IL^L^^
EPA/OPPT identified EU exposure data that were characterized for "general industrial use."
However, more specific information on the industries (e.g., applicable NAICS or Standard
Industrial Classification [SIC] codes, primary industrial functions or products, or number of sites
or workers) was not provided in the identified references.
36 The DCM air concentration of 3,802 mg/m3 was selected to represent the high end of the range of 8-hr TWA
values for aircraft paint stripping in Table G-2 (EU, 2007).
37 The DCM air concentration of 5,400 mg/m3 was selected to represent the high end of the range of short-term
and other non-8-hr TWA values for aircraft paint stripping in Table G-2 (EC, 1999).
Page 203 of 279
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The EC (1999) report described a 1998 UK report that identified exposures during immersion
stripping of wood. The 8-hr TWA exposures ranged from 38.5 to 7,000 mg/m3 (11 to
2,017 ppm)38 with a mean of 700 mg/m3 (202 ppm) for the period of 1980 to 1994. The 8-hr
TWA exposures were lower during the period of 1990 and 1994, with a range of 35 to
2,100 mg/m3 (10 to 605 ppm)39 and a mean of 350 to 420 mg/m3 (101 to 121 ppm).
Moreover, the same 1998 UK report described in the EC (1999) document reported DCM
exposure data during the immersion stripping of metal. The exposures were characterized as
less than 350 mg/m3 (101 ppm)40 "if appropriate protection measures [were] implemented".
A 1980 U.S. study observed the breathing zone of 3 workers engaged in paint stripping from
wood and metal. Seven samples were collected and the 8-hr TWA DCM concentrations ranged
from 633 to 1,017 mg/m3 (182 to 293 ppm)41 (IARC. 2010).
A 2004 report reported concentration measurements of DCM during an activity described only
as "paint stripping from an article." The means of six different measurements were reported,
although sampling times were not reported. The range of these six means was 35 to 707 mg/m3
(10 to 204 ppm) with an overall average of 324 mg/m3 (93 ppm). Two maximums of 459 and
1,413 mg/m3 (132 and 407 ppm) were also presented (EU, 2007).
The EU (2007) report discussed a 2004 report about DCM exposure monitoring data in Germany
associated with both indoor and outdoor paint stripping in 1997. The 62 indoor measurements
ranged from 294 to 3,035 mg/m3 (85 to 875 ppm)42 over unknown sampling times. The mean
was 1,373 mg/m3 (396 ppm) and the 95th percentile was 2,457 mg/m3 (708 ppm). The 37
outdoor measurements were only slightly lower with a range of 158 to 2,275 mg/m3 (46 to
656 ppm) (the sampling times ranged from three to 295 minutes). The mean was 524 mg/m3
(151 ppm) and the 95th percentile was 1,339 mg/m3 (386 ppm).
The same report also cited 122 air measurements of DCM during non-specified paint stripping
in France from 1998 to 2002. The concentrations, sampled over a range of 1 to 8 hrs, ranged
from 0.25 to 2,723 mg/m3 (0.07 to 785 ppm)43. The arithmetic mean was 163 mg/m3 (47 ppm),
38 The DCM air concentration of 7,000 mg/m3 was selected to represent the high end of the range for 8-hr TWA
values for non-specific workplace settings (immersion stripping of wood) in Table G-2 (EC, 1999).
39 The DCM air concentration of 35 mg/m3 was selected to represent the low end of the range for 8-hr TWA values
for non-specific workplace settings (immersion stripping of wood) in Table G-2 (EC, 1999).
40 The DCM air concentration of 350 mg/m3 was selected as the high end of the range of short-term and other
non-8-hr TWA values for non-specific workplace settings (immersion stripping of metal) in Table G-2 (EC, 1999).
No other values of the range were given.
41 The DCM air concentrations of 633 and 1,017 mg/m3 were selected to represent the low and high ends of the
range for 8-hr TWA values, respectively, for non-specific workplace settings (immersion stripping of wood and
metal) in Table G-2 (IARC, 2010).
42 The DCM air concentration of 3,035 mg/m3 was selected as the high end of the range of short-term and other
non-8-hr TWA values for non-specific workplace settings (unknown) in Table G-2 (EC, 1999).
43 The DCM air concentration of 0.25 mg/m3 was selected as the low end of the range of short-term and other non-
8-hr TWA values for non-specific workplace settings (unknown) in Table G-2 (EU, 2007).
Page 204 of 279
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the geometric mean was 17.2 mg/m3 (5 ppm), the median was 17.5 mg/m3 (5 ppm), and the
95th percentile was 956 mg/m3 (276 ppm) (EU. 2007).
The EU (2007) report also discussed a 2004 report that documented two studies in Finland
related to the effectiveness of respirators during non-specified paint stripping. The first study
was conducted in 1997 and did not specify the respirator type. The 8-hr TWA concentrations
were 285 mg/m3 (82 ppm)44 and 5 mg/m3 (1.4 ppm) for outside and inside of the respirator,
respectively. This equates to a reduction of approximately 98.2 percent and a respirator
protection factor of approximately 57. The second study was conducted in 1998 and measured
8-hr TWA concentrations of 428 mg/m3 (123 ppm)39 and 2.2 mg/m3 (0.63 ppm) for outside and
inside the respirator, respectively. This equates to a reduction of approximately 99.5 percent
and a respirator protection factor of approximately 195 (EU, 2007).
OSHA IMIS data were among the data collected during the literature search for occupational
exposure data. The sources of DCM exposure in IMIS are generally not provided and may or
may not include DCM-containing paint stripping products. In some circumstances, EPA/OPPT
examined IMIS data to provide insights in some occupational categories where no other data
were found to be directly attributable to the use of DCM-containing paint stripping products.
Table G-12 summarizes the personal DCM measurements obtained from OSHA IMIS for the
industries of interest. Area measurements were excluded from this summary. Additionally, non-
detect results were excluded from this summary. A non-detect result is not meaningful for risk
analyses as it could be the result of the site not using any DCM as opposed to a lack of worker
exposure to DCM during its use.
Although not used in the risk analyses (except for art restoration and conservation), these
OSHA IMIS data were useful for providing perspective on the temporal variation of DCM
exposures. EPA/OPPT aggregated the exposure data into two categories: before and after the
1997 promulgation of the current OSHA PEL for DCM (25 ppm or 87 mg/m3).
For the industries that have data both before and after 1997 (aircraft refinishing, ship and boat
refinishing, automotive refinishing, and furniture refinishing), little variation was observed in
the statistics of the exposure data. There was little variation in the TWA and STEL maximum
values between the post-1997 and pre-1997 data sets. The other statistical values did not show
clear trends as a result of the change in PEL. In many cases, the post-1997 exposures were
greater than the pre-1997 exposures. Of note, the 90th percentile of TWA exposures in ship and
boat refinishing increased by more than 100 percent from pre-1997 to post-1997.
44 The DCM air concentrations of 285 and 428 mg/m3 were selected to represent the low and high ends of the
range for 8-hr TWA values, respectively, for non-specific workplace settings (unknown) in Table G-2 (EU, 2007).
EPA/OPPT calculated the mean and midpoint values from the high and low values reported by the study authors.
The mean and the midpoint values are the same because there are only two samples for this data set.
Page 205 of 279
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There are many reasons for OSHA or a State to conduct a health inspection. Reasons can
include (but are not limited to) random, programmatic selections within an industry; past
health problems at the facility; employee complaints; or a safety inspection in which the
inspector felt a health inspection was also warranted. The lack of randomness in the selection
of facilities for health inspections reduces the utility of the IMIS data of informing
representative temporal trends.
Page 206 of 279
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Table G 12. Summary by Industry of OSHA IMIS Personal Monitoring Data for DCM from 1992 to 2012
Bathtub
Refinishing
Professional
Contractors
Aircraft
Refinishing
Ship& Boat
Refinishing
Max
90th Percentile
Median
Min
Mean
Number of Data Points
Max
90th Percentile
Median
Min
Mean
Number of Data Points
Max
90th Percentile
Median
Min
Mean
Number of Data Points
Max
90th Percentile
Median
Min
Mean
Number of Data Points
Personal Measurements
Post-1997 PEL Update
TWA
mg/m3
—
-
-
-
-
ppm
-
-
-
-
-
None
28.2
23.2
13.9
0.0
12.8
8.1
6.7
4
0
3.7
5
34.5
32.4
15.6
0.0
17.8
9.9
9.3
4.5
0
5.1
15
33.7
32.4
6.1
0.0
11.3
9.7
9.3
1.8
0.0
3.3
11
STEL
mg/m3
0.0
N/A
N/A
0.0
N/A
ppm
0.0
N/A
N/A
0.0
N/A
3
27.8
13.8
0.0
0.0
5.1
8.0
4.0
0.0
0.0
1.5
7
31.2
29.5
12.7
0.0
15.2
9.0
8.5
3.7
0.0
4.4
6
10.4
6.2
0.0
0.0
2.1
3.0
1.8
0.0
0.0
0.6
5
Pre-1997 PEL Update
TWA
mg/m3
—
-
-
-
-
ppm
—
-
-
-
-
None
—
—
—
-
-
—
—
—
-
-
None
33.3
28.1
10.1
0.0
13.3
9.6
8.1
2.9
0.0
3.8
21
27.8
15.6
5.7
0.0
7.6
8.0
4.5
1.6
0.0
2.2
8
STEL
mg/m3
—
-
-
-
-
ppm
—
-
-
-
-
None
—
—
—
-
-
—
—
—
-
-
None
-
—
—
—
—
-
—
—
—
—
None
-
-
-
—
—
-
-
-
—
—
None
Page 207 of 279
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Table G 12. Summary by Industry of OSHA IMIS Personal Monitoring Data for DCM from 1992 to 2012
Automotive
Refinishing
Furniture
Refinishing
Art
Restoration
and
Conservation
Max
90th Percentile
Median
Min
Mean
Number of Data Points
Max
90th Percentile
Median
Min
Mean
Number of Data Points
Single Data Point
Personal Measurements
Post-1997 PEL Update
TWA
mg/m3
31.2
28.9
4.7
0.0
10.0
ppm
9.0
8.3
1.4
0.0
2.9
10
33.9
28.9
10.6
0.0
13.3
9.8
8.3
3.1
0.0
3.8
78
2.01
0.58
STEL
mg/m3
34.2
27.8
10.3
0.0
13.3
ppm
9.9
8.0
3.0
0.0
3.8
11
34.01
24.64
13.01
0.0
12.91
9.8
7.1
3.8
0.0
3.7
70
None
Pre-1997 PEL Update
TWA
mg/m3
24.3
20.1
12.3
1.1
11.1
ppm
7.0
5.8
3.6
0.3
3.2
5
31.2
30.2
17.2
3.5
18.8
9
8.7
5.0
1.0
5.4
12
None
STEL
mg/m3
27.8
N/A
N/A
6.9
17.4
ppm
8.01
N/A
N/A
2.0
5.0
2
31.2
N/A
N/A
0
15.6
9.0
N/A
N/A
0
4.5
2
None
Source: OSHA (2012a)
Page 208 of 279
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Appendix H RESIDENTIAL/CONSUMER EXPOSURE ASSESSMENT
Appendix H contains detailed information about the modeling approach used to estimate
consumer exposures for the use of DCM in paint strippers.
H-l Estimation of Emission Profiles for Paint
Removers/Strippers
Various studies were considered in developing DCM emission profiles as model inputs for
subsequent exposure-estimation efforts.
Four chamber studies were analyzed for DCM emission characteristics. Each of these studies
was reviewed to estimate the fraction of applied DCM mass that was emitted. In selected cases,
single-exponential representations of time-varying emission profiles were developed. The
studies are the following:
1. MRI Chamber Study — Midwest Research Institute. Consumer Exposure to Paint Stripper
Solvents, Final Report. Report to the USEPA, EPA Contract No. 68-DO-0137, Work
Assignment No. 4-06 (EPA, 1994a);
2. EC Chamber Study — European Commission, ETVAREAD. Effectiveness of vapour retardants
in reducing risks to human health from paint strippers containing dichloromethane (EC,
2004):
3. van Veen Chamber Study — van Veen, M.P., Fortezza, E.S. and Mensinga, T.T. Non-
professional paint stripping and experimental validation of indoor dichloromethane levels.
Indoor Air, 12:92-97 (van Veen et al.. 2002):
4. Lawrence Berkley Laboratory (LBL Chamber Study) — Girman, J.R. and Hodgson, A. T. Source
Characterization and Personal Exposure to Methylene Chloride from Consumer Products,
Lawrence Berkeley Laboratory, Report No. LBL-20227 (LBL, 1986).
Data from the MRI chamber study were used as the basis for developing emission profiles for
the brush-on and spray-on applications evaluated in this assessment (EPA, 1994a). The
advantages of the MRI study include the following: (1) the chamber data were adequate to
support the estimation effort; and (2) the products studied were considered to be the most
representative of paint strippers available in the U.S. consumer product market.
The EC (2004) chamber study was not used for the current assessment due to several
limitations, including: (1) too little information to confirm model parameters or study results;
(2) lack of information on study design and product formulation or percent DCM in the tested
products; (3) use of European products that may not be representative of U.S. products^ (4) use
Page 209 of 279
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of a ventilation rate considered to be high for indoor rooms, unless mechanical ventilation were
used (e.g., a fan venting directly to outdoors); and, (5) differences from typical U.S. room size
(i.e., U.S. room sizes may be larger) (EC, 2004).
The van Veen et al. (2002) chamber study was also reviewed but not used because it used non-
U.S. products. Moreover, the study had limitations similar to the EC study, although room
volumes and ventilation rates were more in line with values that might be expected for typical
uses in U.S. residences.
Subsequent to the preparation of the draft risk assessment, EPA/OPPT gained access to a report
on a chamber study conducted by Lawrence Berkeley Laboratory (LBL) (LBL, 1986). The study
used a protocol similar to that used in the MRI study45. The LBL data were analyzed and are
presented in section H-l-1-2, and were used for comparative purposes in section H-5.
The sections below present the analysis and fitted exponential representations of the MRI data
for both brush-on and spray-on applications. There are also descriptions of other chamber
studies, which were considered but not used in EPA/OPPT's modeling study. The discussion also
includes a comparison of the estimates from the MRI chamber study with those from the other
chamber studies.
H-l-1 Conceptual Approach
5. For each chamber test, the applied DCM mass was calculated by multiplying the applied
product mass by the assumed DCM content (% by weight). The DCM content (83 - 87%) was
determined analytically by LBL (LBL, 1986). In the van Veen study, the DCM content was
reported, but not its basis (van Veen et al., 2002). For the EC experiments, the DCM content
was assumed to be 82.5% (midpoint of range for their "typical formulation") (EC, 2004). For
the MRI experiments, DCM contents of 16.8% for a brush-on product and 85.0% for a spray-
on product were assumed based on formulation data (e.g., per MSDS) near the time when
these experiments were conducted (EPA, 1994a).
The DCM mass emitted per experiment was estimated by two alternative methods:
1. Mass-balance Calculation - this method consisted of (a) using the starting and ending
concentrations for successive brief (< 10-minute) time intervals, together with
knowledge of the airflow rate into and out of the chamber, to determine the mass
emitted during each interval; and (b) summing these estimates to determine the total
DCM mass emitted during the entire experiment.
2. Model Fit to Chamber Data - this method consisted of (a) using nonlinear least squares
(NLS) analysis to fit an incremental source model governed by a single exponential; and
(b) calculating the mass emitted by integrating the fitted model over the duration of the
experiment.
45 The MRI study cited the LBL protocol.
Page 210 of 279
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Mass-Balance Calculation
The mass released during chamber studies was estimated using a numerical mass-balance
integration method, where the mass released over each interval was determined as follows:
MR,; 1+1= (Ci+i - C/)*V + Q*(At)*(Ci+i + C/)/2) (Equation H-l)
Where:
MRi,i+i= Mass Released over interval /to \+i, mg = the change in mass in the
chamber plus the amount of mass removed through ventilation
C = concentration in the compartment, mg/m3
V= compartment volume, m3
Q= compartment ventilation rate, m3/hr
At = time interval from / to i+1, hr
The intervals were chosen such that the concentration was relatively well behaved (i.e., without
significant changes in slope) during each interval. The estimated masses for the intervals
covering the duration of interest were then summed to estimate the total mass released.
Model Fit to Chamber Data
An exponential representation of the time-varying emission rate was chosen in evaluating the
experimental data because of the general shape of the concentration profile and the similarity
to other emission behaviors (e.g., chemicals emitted from paint). The emission equation has the
following form:
E = E0e~kt (Equation H-2)
Where:
E = emission rate, mg/hr
Eo = initial emission rate (the emission rate at t = 0), mg/hr
k = first-order rate constant, hr1
t = time since application, hr
Integrating Equation H-2 to infinity gives the mass released according to the exponential, as
follows:
c>
Mass Released (mg) = — (Equation H-3)
K.
Or:
£"0 = (Mass Released) * k (Equation G-4)
Page 211 of 279
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Integrations of single-compartment, mass-balance equations for single- and double-exponential
representations of the emissions are given in Equations H-5 and H-6 (EPA, 1997), respectively:
Single-exponential representation
(Equation H-5)
Where:
C(t)= concentration, mg/m3
V = chambervolume, m3
Q = air flow rate in and out of the chamber, m3/hr
Double-exponential representation
Where:
Eoi = initial emission rate for the first exponential, mg/hr
£02 = initial emission rate for the second exponential, mg/hr
ki = first-order rate constant for the first exponential, hr1
l<2 = first-order rate constant for the second exponential, hr1
H-l-1-1
MRI Chamber Study (EPA, 1994a)
In 1993, MRI conducted a series of chamber experiments for EPA on paint stripping products
(EPA, 1994a). For each experiment, continuous air concentrations were measured using a
Fourier transform infrared (FTIR) spectrometer. In addition, three stationary samplers and a
personal sampler were used to collect time-integrated samples on activated charcoal. The
resultant data were analyzed and a process was undertaken to fit the data to equations with an
exponential to represent the time-varying emission profile that led to the air concentrations.
The MRI study tested five products, two of which contained DCM, as listed in Table H-l.
Table H 1. DCM containing Products Used in the MRI Chamber Studies
Product
BIX Spray-On Stripper
Strypeeze
Application Type
Spray
Brush
Chemical
DCM
DCM
Source: EPA(1994a)
Each product used in the study was applied in eight, approximately 1-minute segments, with
each 1-minute application followed by an approximately 10-minute wait time prior to the start
of the next, resulting in about 11 minutes between successive applications. In each case, the
Page 212 of 279
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emissions from each application were represented by a single exponential, with each
exponential identical to the other seven but with a different start time set at the midpoint of
the corresponding application period. Based on this approach, the start times for the eight DCM
exponentials were 0.5, 11.5, 22.5, 33.5, 44.5, 55.5, 66.5, and 77.5 minutes from the start of the
paint-stripping activity.
A single exponential was found to provide a good fit to the data corresponding to the two DCM
products reported in the MRI study. The fitting process involved:
1. Extracting measured concentration values from the MRI chamber study data and co-plotting
the points with fits to Equation H-5. The concentration values were extracted, for runs 4, 5,
and 6 for BIX Spray-on and for runs 7, 8, and 9 for Strypeeze Brush-on, at each 0.5-hr time
point as well as at times of peaks and significant changes in slope, resulting in eight or nine
data points per run.
2. Calculating the mass of DCM applied during the test and assigning l/8th of the applied mass
to each of the eight exponentials.
3. Iterating to find the best fit to the concentration data by varying the "fraction released" and
the first-order rate constant (k), using Equation H-5 and the following relationship:
EO = (Mass Applied^) * (Fraction Released^) * k (Equation H-7)
The analysis was conducted using Excel to solve the equations and plot the results. The best fit
to each data set was determined via visual comparison of the results of applying Equation H-5
to the extracted MRI data. Combined data for Runs 4, 5 and 6 (with very similar concentration
profiles; see Figure H-l) were used for the BIX spray-on product, attempting to fit the Equation
H-5 curve midway between maximum and minimum values of the data at each point in time.
Concentration profiles were more disparate for the Strypeeze brush-on product (Figure H-2). In
this case, the visual fit was applied only to the Run 7 data, which appeared to be better
behaved and also were approximately midway between the data from Runs 8 and 9.
In general, the height of the concentration curve is related primarily to the DCM mass released,
and the length and shape of the decay portion of the curve is closely related to the first-order
rate constant (k) and the chamber ventilation rate (Q). The resulting fit for the BIX Spray-on
product is shown in Figure H-l, and the fit for the Strypeeze Brush-on product is shown in
Figure H-2. In each figure, the underlying eight exponentials are shown in the lower part of the
figure, with the sum shown as the fitted, dashed line. The fitted parameters for these two DCM
cases are shown in Table H-2.
Page 213 of 279
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Figure H-l. Model Fit to Data Extracted from MRI Chamber Study for BIX Spray-on Product
Chamber DCM Concentration, ppm
±OU\J
1 cnn
IDUU
1 Ann
-L^fUU
1 ?nn
1 nnn
J.UUU
onn
OUU
cnn
DUU
Ann
M-UU
9nn
zuu
0 •
C
/A v ^— Sum of 8 Exponentials,
• \
%J V A MRI, Run 4
f X
-* • \ • MRI, Run 5
/ \^
' | x MRI, Run 6
' >1
/ •»
/ X. *
/ ^^
/^^ "^ — .
/ / / / ^^^"mraa """"""•
'111
) 1 2 3 4 5 1
Time, hours
Figure H-2. Model Fit to Data Extracted from MRI Chamber Study Report for Strypeeze Brush-
on Product
Q.
Q.
*.
O
'+-•
ro
350
300
£ 250
c
OJ
u
c
o
u
u
o
200
150
JK 100
cu
-Q
E
ro
50
0
•Sum of 8 Exponentials
MRI, Run 7
MRI, Run 8
MRI, Run 9
r
0
Time, hours
Page 214 of 279
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Table H 2. Fitted Parameters to MRI Study Results for Two DCM Containing Paint Strippers
Product
BIX Spray-On
Stripper
Strypeeze
(Brush-On)
Experiment
Runs 4, 5, 6
Run?
Product
Mass
Applied, g
540
724
DCM
Weight
Fraction
0.85b
0.168C
DCM Mass
Applied, g
459.0
121.62
DCM
Theoretical
Fraction
Released a
0.66
0.33
First-Order
Rate
Constant, hr *
10.0
3.9
Notes:
a The theoretical DCM fraction released was estimated by integrating the fitted exponential.
bEPA(1996a)
c EPA (2003)
Source: EPA(1994a)
A numerical integration of the fitted "sum of 8 exponentials" shown in Figures H-l and H-2 was
performed by using the average concentration for each one-minute interval. Then a mass-
balance calculation was conducted for the test chamber, which accounted for the mass in the
chamber and the mass that had been removed through ventilation. The estimated cumulative
mass released from the product as a function of time is shown in Figures H-3 and H-4 for the
BIX Spray-on and Strypeeze Brush-on strippers, respectively.
Figure H-3. Theoretical Cumulative Mass of DCM Released for BIX Spray-on Stripper
321,300
CuO
E
-a
(TJ
u
Q
4 6
Time, hours
10
12
Page 215 of 279
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Figure H-4. Theoretical Cumulative Mass of DCM Released for Strypeeze Brush-on Stripper
42,490
S? 36,420
111 minutes
35%
30%
25%
5%
0%
3 4
Time, hours
a
a.
20% -g
1/1
re
15% -32
Ol
ae
10% «
to
u
Q
H-l-1-2
LBL Chamber Study (LBL, 1986)
Brush-on product formulations used in the MRI and LBL studies are summarized in Table H-3.
The MRI and LBL studies used very similar experimental protocols, with the only notable
difference being their product formulations. The actual product formulation (from product label
or MSDS) was not reported by either study, but the LBL study did include a bulk analysis of the
paint-remover products. The 1988 and 2013 MSDS listed in Table H-3 for Strypeeze bracket the
1994 MRI study, with the 1988 MSDS likely more indicative of the actual composition of the
paint remover used by MRI. This inference is supported by a Strypeeze formulation (circa 1994)
in the Source Ranking Database (SRD), indicating 16.8% DCM by weight (EPA, 2003).
Table H 3. Comparison of Brush on Product Ingredients for the LBL and MRI Studies
Ingredient
DCM
Toluene
Methanol
Acetone
Paraffin Wax
Aliphatic Hydrocarbon
Isopropanol
Xylenes
Non-volatile
Strypeeze
1988 MSDS3
>10%
>35%
25%
<25%
<5%
Strypeeze
2013 MSDS3
25 - 30%
15 - 20%
25 - 30%
15 - 20%
0 - 5%
0 - 5%
LBL (1986),
Paint Remover (PR)-A
83.0%
Present15
Present15
3.6%
LBL (1986),
PR-B
86.6%
Present15
-
9.4%
2.8%
Notes:
a Proxies for the composition of the MRI product (EPA, 1994a).
b Indicates that the ingredient was determined to be present, but the exact mass was not quantified.
Page 216 of 279
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The LBL and MRI studies used similar ventilation rates — ~3.0 hr1 and 0.6 hr1 for LBL
Experiments 2 and 5, respectively; and ~0.55 hr1 for each of MRI Runs 7, 8 and 9. However, the
formulations used in the two studies are quite different, with the most noteworthy differences
being the amount of DCM applied as well as the presence of Paraffin Wax vapor retardant in
the MRI paint-remover product. Table H-4 summarizes the chamber characteristics, the DCM
mass applied, and the estimated percent of applied DCM mass that was released during each
LBL/MRItest.
Table H 4. Comparison of DCM Mass Released for LBL and MRI Studies of Brush on Products
Study and
Expt/Runa
LBL, Expt 2
LBL, Expt 5
MRI, Run 7
MRI, Run8
MRI, Run 9
Chamber
Vol, m3
20.0
20.0
35.7
35.7
35.7
ACH, hr -1
3.23
0.62
0.56
0.54
0.55
Duration,
mm
89
86
105
105
105
Applied Product
Mass, mg
363,000
325,000
724,000
676,000
765,000
Applied DCM
Mass, mg
314,358
269,750
121,632
113,568
128,520
%DCM
Released
83%
93%
35%
51%
30%
Note:
a Expt= Experiment
The results in Tables H-3 and H-4 provide some insights regarding the factors that can influence
DCM emissions:
• The two LBL studies contain high DCM weight fractions (83% and 86.6%) compared to the
MRI brush-on product (estimated to be 16.8 %).
• The applied product mass is lower for the LBL products as compared to the MRI product,
but the applied DCM mass is higher due to the higher DCM weight fraction.
• The MRI product contains a vapor retardant (Paraffin) whereas the LBL products do not.
Further insights from these observations and the chamber test results are as follows:
• The ventilation rate appears to have a minimal impact on the DCM emission rate and total
mass emitted. LBL Experiments 2 and 5 are very similar with the exception of the ventilation
rate. A greater fraction of the mass might be expected to be released in an environment
with a higher ventilation rate, but that does not occur in experiment 2.
• The vapor retardant appears to cause more than a 50% reduction in DCM emissions for the
MRI stripper, although the lower weight fraction could be contributing to the reduction.
Page 217 of 279
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H-1-1-3 van Veen Chamber Study (van Veen et al, 2002) and EC Chamber Study
(EC, 2004)
EC (2004) and van Veen et al. (2002) conducted chamber experiments with a brush-on paint
stripper. In the van Veen study, volunteers applied a commercially available paint stripper to a
1.28-m2 horizontal surface under a range of ventilation rates (0.26-0.73 hr1). The substrate
material was not specified. The study reported that the product mass and DCM weight fraction
(65.9%) were "measured from the product by GC and ECD detector46" with no additional details
provided in the report. Also, the product name and other ingredients in the paint stripper were
not specified. A single application of the paint stripper was made to the entire substrate, with
scraping of the entire substrate occurring after an effect time of approximately 60 minutes.
Figure H-5 shows the concentration profiles for each experiment. The DCM mass released
during the study was estimated for four of the experiments using the mass balance method,
described above, as shown in Table H-5. The estimated mass of DCM released ranged from 18%
to 39% (Table H-5). The results indicated no obvious correlation between the ventilation rate
and the mass released. The relatively low fraction released suggests that these paint stripper
products contain a vapor retardant.
Figure H-5. DCM Concentrations from van Veen et al. (2002) Chamber Study
O
Q
20001
1500
1000
500
1a
-ib
2a
3a
3b
Gas chromatography and electron capture detector (GC/ECD)
Page 218 of 279
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Table H 5. Estimated DCM Released for Four Experiments by van Veen et al. (2002)
van Veen
Experiment
la
Ib
3a
3b
Chamber
Vol, m3
47.65
47.65
47.65
47.65
ACH, hr1
0.31
0.26
0.53
0.75
Duration,
min
60
60
60
60
Applied
Product
Mass, mg
364,000
335,000
392,000
386,000
Applied
DCM Mass,
mg
239,876
220,765
258,328
254,374
%DCM
Released
28%
39%
18%
22%
The EC (2004) study was designed to assess health risks related to the use of defined vapor-
retarded, DCM-containing paint strippers. TWA concentrations were reported for ten such
products available on the European market, as shown in Figure H-6. Of these ten products, six
were described as "fluid" and the remaining four as "paste." The chamber was a 15 m3 room
with a ventilation rate of 60 m3/hr (4 hr1) for the standard-condition studies. The substrate was
a 1.0-m2 chipboard in a vertical orientation. The composition of specific products was not
provided, but the study reported a DCM content ranging from 75 to 90% for the typical
formulation of DCM-containing paint strippers on the European market. A single application of
the paint stripper lasting about 5 minutes was made to the entire substrate, with scraping
occurring after a typical "effecting" time of about 10 minutes.
Figure H-6. TWA Concentrations for Ten Paint Removing Products (Reproduced from EC, 2004)
TWA 25 min Active Carbon (ppm)
I I Test series 1, upper ventilation hole
| | Test series 2, lower ventilation hole
Figure 4: DCM Evaporation from different paint removing products
Page 219 of 279
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In summary, the data reported in EC (2004) were of marginal utility for this assessment, with
the exception of two primary contributions as discussed below.
Impact of vapor retardants: The Kluthe 3 product did not contain a vapor retardant while
Kluthe 2 contained an unspecified quantity of vapor retardant. Kluthe 1 contained twice the
vapor retardant as Kluthe 2.
Assuming that the formulations were similar with the exception of the quantity of vapor
retardant, a comparison of the three Kluthe products was used to establish the general impact
of the vapor retardant. The following observations are based on Figure H-6 together with the
Kluthe vapor-retardant ratios described above:
• The presence of vapor retardant appears to be able to reduce the emissions by
approximately 50%. It is possible that formulation with a larger percentage of vapor
retardant could lead to an even greater reduction in emissions.
• The first unit of vapor retardant (as represented by Kluthe 2) reduces DCM emissions by
approximately 40%. The second unit (as represented by Kluthe 1) reduces emissions by
another 10% of the total DCM applied.
The above observations collectively suggest that there may be an optimal vapor retardant
quantity for lowering DCM emissions.
Significance of vertical stratification: The chamber studies described in EC (2004) measured
DCM air concentrations at a lower ventilation hole (10 cm above the floor) and an upper
ventilation hole (1.5 m above the floor). DCM is significantly heavier than air since its molecular
weight is 84.9 g/mole. Therefore, some vertical stratification would be expected with higher
concentrations at lower heights.
Although this phenomenon is beyond the scope of the emissions analysis in this appendix, the
extent of stratification can be discerned from the results of the EC study. The ratio of upper to
lower concentrations ranged from 0.59 to 0.94 (mean=0.81) for the six products reporting DCM
TWA concentrations for both the lower and upper ventilation holes. The observed stratification
in the EC (2004) data may have been minimized by the relatively high ventilation rate (4 hr1).
The actual extent of stratification may be larger under lower ventilation rates.
H-1-1-4 Discussion and Conclusions
The four studies reviewed in section H-l (EC, 2004; EPA, 1994a; LBL, 1986; van Veen et al.,
2002) represent the available scientific literature on DCM emissions from consumer use of
paint-removal products. Although paint-stripper ingredients other than DCM are not well
quantified, the results across the studies appear to be consistent, with DCM-containing
products generally categorized as having or not having a vapor retardant. Other paint-stripper
ingredients appear to have less impact on DCM emissions.
Page 220 of 279
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Table H-6 summarizes the results of the analysis of these studies. Table H-6 also lists some
distinguishing features of each experiment along with DCM release fractions as estimated by
the two methods described in section H-l-1 (Conceptual Approach).
The following additional insights are apparent from Table H-6:
1. The estimated release fraction for the product used in the van Veen experiments ranges
from 15 to 39%, strongly suggesting the presence of a vapor retardant.
2. The two LBL tests have similar estimates, ranging from 84 to 97%, despite distinctly
different air exchange rates. These results indicate the absence of vapor retardants.
3. The results of the three MRI tests, with release-fraction estimates ranging from
approximately 25 to 50%, suggest the presence of a vapor retardant. As discussed in section
H-l-1-2, the assumed weight fraction of 16.8% was presented in the 1994 SRD (EPA, 2003),
which is a data source contemporary to the MRI study. The assumed weight fraction is also
approximately in the middle of the range indicated by the Strypeeze 1988 and 2013 MSDS
(Table H-3).
From the exponential fits to the MRI data (EPA, 1994a), it is estimated that 66 percent of the
applied DCM in the spray product (Figure H-l, Table H-2) was released to air, as compared to 33
percent of the applied DCM in the brush product (Figure H-2, Table H-2). Further, virtually all of
the DCM release occurs within two hours after application for both spray and brush products,
very shortly after the last scraping is finished due to DCM's relatively high volatility. Thus, the
concentration-decline part of the time series in Figures H-l and H-2, after the peak, is due
almost exclusively to ventilation rather than to declining emissions. Consequently, exposures
during this time period could be virtually eliminated through ventilation.
Page 221 of 279
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Table H 6. Summary of DCM Chamber Studies
Study
van Veen et al.
2002
LBL (1986)
MRI
(EPA, 1994a)
EC (2004)
Experiment
Title3
la
Ib
3a
3b
Exp2
Exp5
Run?
Run8
Run 9
VP03
Duration,
min
60
60
60
60
89
86
105
105
105
25
Applied
Product
Mass,
mg
364,000
335,000
392,000
386,000
363,000
325,000
724000
676000
765000
465500
DCM
Weight
Fraction
0.659
0.659
0.659
0.659
0.866
0.830
0.168
0.168
0.168
0.825 c
Applied
DCM Mass,
mg
239,876
220,765
258,328
254,374
314,358
269,750
121,632
113,568
128,520
384,038
Chamber
Volume,
m3
47.65
47.65
47.65
47.65
20.0
20.0
35.7
35.7
35.7
15
ACH
0.31
0.26
0.53
0.75
3.23
0.62
0.56
0.54
0.55
4
DCM Mass
Released at
Duration
27.6%
39.0%
17.6%
21.8%
83.3%
92.9%
35.0%
50.7%
29.5%
13.9%
NLS Fit b
Theoretical
Mass Released
25.5%
35.1%
14.9%
18.0%
83.9%
97.0%
34.4%
50.4%
24.6%
NA
Notes:
a These are the experiment names used in the reports.
b The nonlinear least squares (NLS) fit minimizes the squared difference between observations and model predictions using the model described in
section H-l-1. The theoretical mass released is determined by integrating the fitted exponential to infinity.
c The EC report did list product- specific formulations, instead providing a "typical formulation of vapour retarded paint strippers" with DCM
content ranging from 75-90%; the midpoint of this range was used.
Page 222 of 279
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H-2 Sensitivity Analysis for Inhalation Scenarios
For this analysis, each input that could be measured on a continuum (e.g., emission rate,
airflow rate) was first halved and then doubled while holding all others at their base-case
values. For an input to which the model output is directly and linearly proportional, and for
which the exposure measure for the base case is denoted as X, the result for the halved case
would be KX and the result for the doubled case would be 2X. Computing and averaging the
two differences from the base case gives the following result:
([X-1/2X] + [2X-X])/2)/X=%or 75percent (Equation H-8)
For an input that cannot be varied over a continuum, or that can be dealt with only discretely or
perhaps dichotomously (e.g., in the use zone or not at certain key times), the above procedure
can still be used, but the sensitivity measure reduces to:
/ Y-Xj /X (expressed as a percent) (Equation H-9)
where Y is the output associated with the change in location pattern from the base case.
H-3 Inhalation Exposure Scenario Inputs
Method of Application. A review of product labels and technical data sheets indicates that paint
stripping products can be applied using either brush-on or spray-on (i.e., aerosol or trigger-
pump) application methods. In this assessment, exposures were assessed for both brush-on
and spray-on products due to differences in chemical release characteristics, DCM weight
fraction of products, application rates, and time required for application.
Application Amount (Product Mass). The product application mass (grams of product) was
determined for each of the cases examined using application rates (g/ft2) and the surface areas
of objects to be stripped (ft2). The application rates were calculated from the MRI chamber
tests (EPA, 1994a). Surface areas were selected so that the resulting product mass
corresponded approximately to central (near the median) and upper-end estimates for the
amount of paint stripper product used per event from the large nationwide survey by CPSC
(1992). as reported in Table 17-20 of the Exposure Factors Handbook (EFHHEPA. 2011a).
The EFH reported a median value of 32 fluid ounces or % gallon of paint stripper product.
Conversion to metric units (3.75 liters per gallon) and consideration of the nominal product
density (~1.1 g/cm3) (calculated from Brown, 2012) yielded a product mass on the order of
1,000 grams as a central estimate. An upper-end application amount (~80th percentile) from the
same survey was 80 ounces or 2,500 g. Similarly, the Riley et al. (2001) survey reported
32 ounces as the median amount of paint stripper product used.
Page 223 of 279
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Median product masses of 900 and 680 g were input into the model for the brush-on and spray-
on scenarios, respectively. Upper-end product masses for the brush-on and spray-on scenarios
were 2,250 and 1700 g, respectively.
The bathroom scenario occurred in a confined space and was assumed to be performed by a
professional, as opposed to a consumer. A lower mass of 477 g was used for the brush-on
bathroom scenario. The lower mass value was derived from the largest application amount
identified in the NIOSH report (CDC. 2012).
The application amounts for Scenarios 1 through 6 were obtained by multiplying the application
rates calculated from the MRI experiments (EPA, 1994a) and the surface area of objects to be
treated. The calculated application rates were ~90 g/ft2for a brush-on application of a DCM-
containing product (722 g of product applied to 8 ft2) and ~68 g/ft2 for a spray-on application of
a DCM-containing product (540 g of product applied to 8 ft2). These application rates were
similar to those recommended on the Savogran Company website for paint strippers in
general—1 gallon per 50 to 100 ft2 (~42 to 83 g/ft2 based on a nominal density of 1.1 g/cm3)47.
The applied surface areas selected for central and upper-end values were 10 and 25 ft2. The
upper-end surface area was 2.5 times higher than the central surface area and provided
sufficient distinction from the central case. Application targets with surface areas close to the
two specified surface areas (10 and 25 ft2) were used in the exposure scenarios to reflect real-
world situations. A coffee table with nominal dimensions of 4 ft x 2.5 ft for the top surface was
selected for the central case (10 ft2)48. A chest of drawers with nominal dimensions of 4 ft high
by 2.5 ft wide by 1.5 ft deep49 was selected for the upper-end case (4 x 2.5 ft2 for front + 2.5 x
1.5 ft2 for top + 2 x 4 x 1.5 ft2 for sides ~ 25 ft2). For the bathroom scenario, a bathtub surface
area of 36 ft2 was calculated assuming nominal dimensions of 5 ft wide by 2.5 ft deep by 1.5 ft
high.
Stripping Sequence. The stripping sequence chosen to characterize product application was
based in part on product label instructions. Labeling information for some DCM-containing
products (i.e., Klean Strip® products) indicate that no more than 9 ft2should be stripped at a
time. Accordingly, the 10-ft2 surface for the coffee table was divided into two application
segments of 5 ft2 each. The 25-ft2 surface for the chest was divided into four application
segments of 6.25 ft2 each. The 36-ft2 surface for the bathtub was divided into four application
segments of 9 ft2 each.
The segments were assumed to be treated in sequence with a repeat application of the
sequence. Thus, in effect, there were four segments for the coffee table and eight segments
each for the chest and bathtub. Repeating the stripping sequence was consistent with
47 See the following URL: http://www.savogran.com/materials.html
48 See the following URL: http://furniture.about.eom/od/furnishingdesignresources/a/measurements.htm
49 See the following URL for an illustrative chest of drawers with nearly the same dimensions:
http://www.furnitureunfinished.com/product info.php?cPath=116 135&products id=1093
Page 224 of 279
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instructions on the majority of product labels indicating that the stripping procedures should be
repeated to remove multiple coats of paint or stubborn paint. All residuals from the scraping
were assumed to be removed from the house on completion of the last segment/application.
The entire stripping sequence for each segment consisted of applying the product to the target
surface followed by a wait period and then scraping the treated surface. The application and
scrape times were deduced from the protocol description in the MRI chamber study (EPA,
1994a). For both the coffee table and the chest scenarios, a two-minute applying time per
segment was used for brush applications and a one-minute applying time per segment was
used for spray applications. Application was followed by a 15-minute wait period and then a
four-minute scraping period per segment.
As an example, the timing of the entire sequence for a brush-on application to the chest surface
is shown in Table H-7. For this scenario, the total duration is 21 minutes per segment or
168 minutes for the entire episode of product use. For the coffee table, the duration was
84 minutes for the entire episode with half the number of segments. For the bathtub scenario,
the total duration increased to 24 minutes per segment or 192 minutes for the entire episode.
For the spray-on application (applicable to the coffee table and chest but not the tub), the
application time was cut in half (i.e., from two minutes to one) while retaining the waiting time
of 15 minutes and the scraping time of four minutes, resulting in slightly lower total durations
than the brush-on scenarios.
For the bathtub scenario (brush-on only) with a larger surface area, the applying time was
increased to three minutes per segment and the scraping time was increased to six minutes per
segment. The wait time remained the same at 15 minutes per segment. The wait time of
15 minutes was selected based on wait times on the product labels, which varied from five
minutes to two hours, with the majority of labels indicating a wait time of 15 minutes.
Back-to-back stripping sequences with no overlapping activities were modeled because it is
likely that the user takes breaks during the wait time. In the Riley survey, 65 percent of the
participants reported taking breaks outside the work area and 20 percent of the participants
reported taking breaks inside the work area, with break times ranging from five to 30 minutes
(Riley et al., 2001). The number of breaks was not reported. Additionally, conducting
overlapping stripping activities for multiple segments (i.e., applying or scraping one segment
during the wait period of another segment) would be unrealistic for most consumer users.
Page 225 of 279
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Table H 7. Schedule for Brush on Application to Chest Surface: Four Segments with
Repeat Application
Segment/Application
First 1/4, 1st time
Second 1/4, 1st time
Third 1/4, 1st time
Fourth 1/4, 1st time
First 1/4, 2nd time
Second 1/4, 2nd time
Third 1/4, 2nd time
Fourth 1/4, 2nd time
Elapsed Time from Time Zero, Minutes
Apply
0-2
21-23
42-44
63-65
84-86
105-107
126-128
147-149
Wait
2-17
23-38
44-59
65-80
86-101
107-122
128-143
149-164
Scrape
17-21
38-42
59-63
80-84
101-105
122-126
143-147
164-168
Note: The application and scrape times were deduced from the MRI chamber study (EPA, 1994a).
Amount of Chemical Released. The amount of chemical released during and after the stripping
event is the product of three parameters: amount applied (discussed above), weight fraction of
chemical in the applied product, and fraction of the chemical that is released to indoor air.
From the product list developed by Brown (2012), the median DCM weight fraction was
determined to be 0.53 for the brush-on application (range of 0.20 to 0.93) and 0.8 for the
spray-on application (range of 0.45 to 0.88). The corresponding 90th percentile weight fractions
were 0.88 for brush-on and 0.87 for spray-on. A weight fraction of 1.0 (maximum exposure
estimate derived from product label) was assumed for the bathtub application. The weight
fractions were determined from the Brown (2012) spreadsheet by using only products intended
for consumer use (i.e., adhesive removers, paint brush cleaners, deglossers, and
industrial/commercial use products were removed).
The application method (brush- or spray-on) for a product was determined by examining the
product labels/technical data sheets and product names, and through Internet research. If an
application method could not be determined through the above methods, then the product
was assigned to the brush category. Most paint stripping products are applied by the brush
method and formulations, such as semi-paste, would be difficult to apply using a sprayer. If a
weight-fraction range was provided in the product list, then the average of the minimum and
maximum weight fractions was used in the calculations. The weight fractions were not
weighted to reflect the market share of products.
This assessment used the DCM release fractions of 0.33 for brush-on and 0.66 for spray-on based
on the analysis of the MRI chamber data (EPA, 1994a) (see Section H-l). The resultant mass
released for the different application targets and methods is summarized in Table H-8.
Page 226 of 279
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Table H 8. DCM Mass Released, by Application Target and Method
Target (Surface Area)
and Method
Coffee table (10 ft2)
Brush-on
Spray-on
Chest of drawers (25 ft2)
Brush-on
Spray-on
Bathroom tub (36 ft2)
Brush-on
Application
Rate,g/ft2a
90
68
90
68
13.25
Weight
Fraction b
0.53 | 0.88
0.80 | 0.87
0.88
0.87
1.0
Release
Fraction
0.33
0.66
0.33
0.66
0.33
DCM Mass
Released, g
157.4 | 261.4
359.0 | 390.5
653.4
976.1
157.4
Notes:
a Reflects repeat application for each segment.
b For the coffee-table case, two weight fractions are given; one for central and one for near-high-end.
Airflow Rates and Volumes. The model run requires conceptualization of a residence in terms of
the number of zones and their respective volumes. The airflow rates needed to model the
central and upper-end scenarios are: (1) rates between indoors and outdoors for each zone;
and (2) rates between the zones. The bathroom scenario simulation is somewhat more complex
to conceptualize and is described below after the central and upper-end scenarios.
For the central and upper-end scenarios, the house in which the modeled stripper application
occurs is conceptualized as having two zones: (1) the workshop where application occurs; and
(2) the rest of the house (ROM). The house volume chosen for the model runs (492 m3) is the
central value listed in the 2011 EFH (EPA, 2011a). The volume assigned to the in-house
workshop area was 54 m3, corresponding to a 12 ft x 20 ft room with an 8-ft ceiling (20 x 12 x 8
= 1,920 ft3 or ~54 m3). This room volume is similar to the value reported in Riley et al. (2001) for
the mean volume of the room used for paint stripping (51 m3). The volume for the ROM
(438 m3) is determined by subtraction (492 m3 - 54 m3). For the bathtub scenario, the bathroom
volume was set at 9 m3 for consistency with that reported in (CDC, 2012).
The indoor-outdoor airflow for any zone of the house is governed by the choice of air exchange
rate (ACH).
The central and low-end ACH values were 0.45/hr and 0.18/hr and corresponded to the mean
and 10th percentile values, respectively, reported in the 2011 EFH (EPA, 2011a). These values
were used for assigning the indoor-outdoor airflow rate for the ROH. Note that a low-end ACH
would be expected to contribute to upper-end concentration estimates.
For the workshop, it was assumed that multiple windows were opened. The indoor-outdoor
airflow rate assigned to this zone (68 m3/hr) was obtained by multiplying the room volume of
54 m3 by the 90th percentile (1.26/hr) of the air-exchange-rate distribution from the 2011 EFH.
This indoor-outdoor airflow rate was thought to reasonably represent the open-window
assumption.
Page 227 of 279
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The use of open windows in the room of use is supported by both label instructions and survey
data. The majority of the labels indicate that adequate ventilation must be used and that, to
prevent build-up of vapors, windows and doors should be opened to achieve cross ventilation.
Additionally, Pollack-Nelson (1995) reported that an average of 70.7 percent of paint stripper
users (all products) kept a window or door open during use based on data from the EPA (1987)
survey. The CPSC (1992) survey reported that 88.8 percent of paint stripper users (all products)
kept a window or door open during use. The increase was significant between the survey years
(before and after CPSC labeling requirements took effect). The Riley et al. (2001) survey also
indicates that the majority of paint-stripper users (55 percent) opened a window.
Both Pollack-Nelson (1995) and Rileyet al. (2001) also reported that some users used an
exhaust fan during the stripping process, which would affect the air exchange rate. The
percentage of fan users was not reported in Pollack-Nelson (1995). The Riley et al. (2001) data
suggest that only ~27 percent of the users who worked indoors used an open window and fan.
Due to the small percentage of respondents who reported using a fan, coupled with the fact
that some of labels indicate that the product should be kept away from heat, sparks, flame, and
all other sources of ignition, none of the scenarios were assumed to involve use of a fan in the
room of product application.
The interzonal airflow rate was estimated using the following algorithm, developed by EPA
(1995a):
Q = (0.078 + 0.31*ACH) * house volume (Equation H-10)
where Q is the interzonal airflow rate, in m3/hr, and ACH is the air exchange rate, in 1/hr.
Substitution of the central air exchange rate of 0.45/hr and the house volume of 492 m3 yields
an estimated interzonal airflow rate of 107 m3/hr.
The algorithm was derived from empirical ventilation data collected in over 4,000 U.S.
residences by the perfluorocarbon tracer (PFT) technique (EPA, 1995a). In the EPA (1995a)
analysis, the doors between residential zones were generally considered to be open, and thus
EPA/OPPT set up the residential zones to be consistent with EPA (1995a).
The corresponding interzonal airflow rate for the upper-end scenario, with an air exchange rate
of 0.18/hr, is 65.8 m3/hr. Figure H-7 depicts the volumes and airflows that were used for the
workshop scenarios.
Page 228 of 279
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Figure H-7. Zone Volumes and Airflow Rates for Workshop Scenarios
Central Values
Values for Upper-end
6
m3/
Room of
3 Use 1(
'nr (54 m3) m3
17
/hr
ffesfo/
House
(438m3) m3
-^
37
/hr
Concentration
Room of
68 Use
m3/hr (54m3)
65.8
m3/hr
fc-
Scenarios
Rest of
House 78-8
(438m3) mVhr
-^ k.
^ ^
W
•^ ^- denotes air flow
As previously mentioned, the bathroom scenario is more complex (Figure H-8). While working
in close proximity to the target (bathtub) for an extended period, the product user is typically
exposed to elevated concentrations in the immediate vicinity of the application area, a concept
that has been termed the "source cloud" in the scientific literature. There is considerable
evidence of a source-cloud effect around sources (Cheng et al., 2011; Furtaw et al., 1996;
Matthews et al., 1989), which generally relates the size of the source cloud and the ratio of the
near- vs. far-field concentrations to the room turbulence (e.g., due to natural and mechanical
ventilation) and other mixing forces such as thermal gradients.
Figure H-8. Zone Volumes and Airflow Rates for Bathroom Scenario
1.6
m3/hr
Rest of
Bathroom
(8 m3)
m
35
3/[~>
Rest of
House
(483
6.9
3/hr
i
^
"Si
80
mj/nr
r
jurce
Cloud"
M m3^
Denotes airflow
Several studies have investigated methods for modeling a source cloud, including use of a
virtual compartment around the source (Cherrie, 1999), rough partitioning (Musy et al., 1999),
and a zero-equation turbulence model (Chen and Xu, 1998). The virtual-compartment method
also has been discussed in ASTM Standard Practice D 6178-97 (ASTM, 1997). Although the ideal
size of the virtual compartment has not been discussed in the literature, Furtaw et al. (1996)
successfully represented concentrations using a sphere around the source (with an unspecified
Page 229 of 279
-------
volume). Thus, both the presence of higher concentrations near a source and the concept of
using a source cloud to better represent these near-field elevated concentrations appear to be
well founded in the scientific literature.
For the purpose of this exposure assessment, a source cloud is used for the bathroom scenario
to better represent the user's exposure to DCM emitted from the paint stripper. The bathroom
scenario involves application of a relatively large amount of the product within a semi-enclosed,
concave workspace, resulting in accumulation of the heavier-than-air DCM vapors toward the
lower tub surfaces in particular (see the Vertical Stratification Analysis in section H-l-1-3).
Moreover, accessibility constraints and the concave shape of the workspace would require the
user to work in close proximity to the surface being stripped, particularly when working on the
lower portions of the tub. For these reasons, a source-cloud representation is appropriate for
the bathroom scenario.
The source cloud representation was not deemed necessary for the workshop scenarios
because work areas within such a space typically are not so confined and are less likely to
promote localized accumulation of DCM vapors. The MRI test chamber inlet and outlet
concentration values were consistently higher than those in the worker's breathing zone and at
the center of the chamber. On the other hand, the LBL test chamber results showed relatively
uniform mixing at lower ventilation rates and higher concentrations near the source at higher
ventilation rates. The ventilation rate in a chamber can be varied only by mechanical means
(e.g., via exhaust fans). In contrast, the ventilation rate in residential settings can be increased
by natural means such as opening windows. Air transfer with the ROM can be increased by
opening interior doors. The extent of concentration gradients within a workshop would be
highly dependent on physical characteristics such as the size, shape and orientation of the
stripping target (certainly less well defined than a bathtub) as well as conditions such as air
flows through windows and interior doors. Given this variability and dependency, modeling the
workshop scenario as a well-mixed zone is considered appropriate for a Tier 2 exposure
assessment.
Recognizing that the source cloud is not a well-defined area, but rather a gradual transition
between near- and far-field concentrations, and further recognizing that the purpose of this
volume is to represent average air concentrations in the breathing zone of the product user,
the approach to defining the virtual volume was to establish some geometry around the source
that represents the approximate work space. Figure H-9 shows a schematic representation of
the bathtub and virtual compartment representing the source cloud. Consistent with this
representation, a source-cloud volume of 1.0 m3 was assumed for the bathroom scenario.
Page 230 of 279
-------
Figure H-9. Modeling Representation of the Bathtub and Virtual Compartment
Virtual Compartment
2'8"x 2'8;x5'0" (1m3)
Bathtub (Top = 2'8" x 5')
5ft
Matthews et al. (1989) analyzed the impact of a central, forced-air heating, ventilating and air
conditioning (HVAC) system on the distribution of air velocities in three of their six study
homes. The remaining three homes were not included in the analysis because in two cases the
fan was operated continuously and a probe malfunctioned in the third home. In Figure H-10,
the results for the three analyzed homes are presented at three different indoor locations
(basement, kitchen, and master bedroom). For the bedroom (most similar of the three
locations to the bathroom), the Matthews results include a median air velocity of 1.8 cm/sec
with the fan off and 6.1 cm/sec with the fan on.
Page 231 of 279
-------
Figure H-10. Air Velocity Distributions from Matthews et al. (1989)
0,
9ASCMCNT
MEDIAN MAXIMUM
-VAC FLOW FLOW
O Off 4.2 M»
• OM 15.0 !>.$
.ill
KITCHEN
OFF 6.3 M3
ON 7.3 36.1
0.4
O.Z
MASTER BEDROOM
HVAC OFF and ON flows
for Master Bedroom
*
A
-------
Locations of Exposed Individuals. Two location patterns were specified, one for a product user
and one for a non-user (bystander). The user was assumed to be in the work area for stripper
application and scraping for all scenarios. For the waiting phase of the stripping process, the
user was assumed to be in the ROM as a central-tendency assumption for the user (Scenarios 1
and 4), in the workshop as an upper-end assumption for the user (Scenarios 2 and 5), and in the
ROM for Scenarios 3, 6, and 7, which were developed to model upper-end concentrations
primarily for the non-user.
The user was placed in the remainder of the house during the waiting phase for Scenarios 1, 3,
4, 6, and 7 because the user was assumed to be aware of inhalation health concerns from the
label warnings ("Vapor Harmful"). Also, some labels such as the Klean Strip® products
specifically stated that the user should leave the room during the wait period.
As previously mentioned, the Riley et al. (2001) survey also reported that 65 percent of users
reported taking breaks outside the work area. Breaks typically involved a specific break activity
and location, such as going to the kitchen and making a sandwich or going outside to do yard
work.
For the upper-end Scenarios 2 and 5, it was assumed that the user would stay in the workshop,
based on the fact that some people do not read/skim labels (~28 percent in 1990) (Pollack-
Nelson, 1995) and may therefore not be aware of health concerns or precautionary techniques.
Many labels do not specifically state to leave room during the wait period, and the Riley et al.
(2001) survey indicated that 20 percent of participants reported taking breaks inside the work
area. For all scenarios, the user was assumed to leave the workroom immediately after the
stripping job was completed. This assumption was based on the EPA (1987) and CPSC (1992)
survey findings of a median value of zero minutes spent in the room after using the product.
The non-user (bystander) was assumed to be in the ROM throughout the model run, as was the
user for the portion of the run after all applying/scraping was completed. For the bathroom
scenario, the user was assumed to be in the ROM during the wait times. It was further assumed
that the scrapings were removed from the house as soon as scraping was completed for the last
segment. The implication for modeling purposes is that any remaining DCM emissions would be
truncated at that time. However, the modeled DCM emissions were not truncated as an
expedience. Given the high volatility of DCM (vapor pressure = 352.5 Torr), its emission rate
would essentially drop to zero in a relatively short time, on the order of 15-20 minutes, which
coincides with the end of the scraping period. Our calculations indicate that, at this time, less
than 1 % of the DCM mass released to air remains.
Page 233 of 279
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H-4
Inhalation Model Outputs and Exposure Calculations
H-4-1
Exposure Calculations
Maximum TWA concentrations for different averaging periods, described below, were
calculated from the one-minute averages for both the user and non-user (bystander) based on
their respective exposure concentration time series. The calculations took into account the
possibility that the user can change zones within a one-minute interval (e.g., at an elapsed time
of 6.25 minutes). The exposure concentration was calculated for each one-minute interval in
the modeling period (24 hours or 1,440 one-minute intervals) as follows:
For each time interval, / to i +1, for / = 0 to 1,440:
+i
(* c \ ic +• u n\
\*(l~Fi,i+i) (Equation H-ll)
where:
ECi,i+i = the exposure concentration over the time interval / to i +1
Ci/i and Ci/i+i = the concentrations in the use zone at times / and i+1, respectively
CROH,I and CROH,!+I = the concentrations in the ROM zone at times / and i+1, respectively
Fi,i+i = the fraction of time spent in the use zone during the time interval / to i +1
These calculations, illustrated in Figure H-ll, were implemented in an Excel spreadsheet for
each of the seven scenarios.
Figure H-ll. Example of the Exposure Concentration Calculation as Defined in Equation H-ll
Al
Model Results
H
I
Model Results
Activity Pattern and Personal Concentrations
Avg
Avg Z1 Cone
(Workshop)
(mgfm')
'g Z2 Cone
(ROM)
(mgfm'l
Outdoors „, , , , Z2IROH)
(Workshop)
0
0.0007
0.0014
0.0021
0.0028
0.0035
0.0042
0.0043
0.0056
O.OOS3
0.0063
0.0076
0.0083
0.003
0.0037
0.0104
0.0111
0.0113
0.0125
0.0132
nrrm
29.41855
139.41755
312.2135
478.1
0.0249428
0.21437
34
1.76231
s*
6.6164
8.6378:
10.7760:
12.333
15.2575!
17.543
13.8304!
22.100:
24.3411!
26.540'
23.6302!
30.783:
32.8161
34 7R35 1
713.1935
732..
'45
895.7135
325.3765
343.8035
352.997
954.6415
950.151
940.7115
927.317
910.799
831.853
871.0575
R4R RR3F
Fraction of Time
Spent in Use Zone
H5*J5 + l5*(i-J5)
919.744 27.6287
301.854 23.7518
881.852 31.8158
860.263 33.8164
R37 R74 3K 7RHR
0.02434285
0.21437235
0.7713345
1.762315
3.117595
4.757845
6.61641
8.63783
10.77608
12.3331
15.25755
17.5437
13.83045
22.1008
24.34115
28.5405
28.63025
30.7838
32.8161
34 7R3R
Page 234 of 279
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H-4-2 TWA Concentrations
In addition to the maximum one-minute concentration and the 24-hr average concentration to
which the user and non-user (bystander) were exposed, a maximum TWA exposure
concentration was calculated for each of the following averaging periods: 10 minutes,
30 minutes, one hour, four hours, and eight hours. The maximum TWA concentration for any
averaging period was defined as the highest value of the consecutive running averages for that
averaging period. For any averaging period, there are (1,440 minus length of the averaging
period) TWA concentration values within the 24-hr (1,440-minute) time series. For example,
there are 1,430 10-minute averaging periods (1,440-10), the first of which is for time zero to
10 minutes, the second of which is for time one to 11 minutes, and so on, with the last for time
1,430 to 1,440 minutes. The running averages for each averaging period were computed in an
Excel spreadsheet, from which the maximum value was determined.
H-4-3 Modeling Results
The zone-specific and exposure concentrations predicted by MCCEM are presented in Figures
H-12 though H-1550. Figure H-12 shows the zone-specific and the user's exposure-concentration
results for Scenario 1 (brush application in the workshop with central parameter values, top
two figures) and Scenario 4 (spray application) in the workshop using central parameter values.
The dips in the user's exposure concentration during the application periods reflect temporary
relocation to the ROM (Zone 2) during wait times between applying and scraping. The non-
user's exposure concentrations are the same as those in the ROM.
As indicated in Figure H-12 the peak concentrations were higher for the spray-application
scenario than those for the brush-application scenario, even though the mass of product
applied was higher for brush application (900 g stripper applied for brush as compared to 680 g
for spray). This difference is explained primarily by two factors: (1) the weight fraction of DCM
in the stripper product (0.8 for the spray product as compared to 0.53 for the brush product);
and (2) the higher fraction of the applied mass emitted, with the spray application double that
of the brush application (i.e., 66 percent as compared to 33 percent) based on analysis of the
MRI chamber data (EPA, 1994a). As a result, the DCM mass emitted for the spray stripping was
~2.25 times as high as the mass released during the brush stripping (680 g x 0.8 x 0.66 = 359 g
for the spray activity as compared to 900 g x 0.53 x 0.33 = 160 g for the brush activity).
Other than the mass of DCM emitted and some minor differences in application time,
Scenarios 1 and 4 were identical, which resulted in a similar ratio in air concentrations. For
example, for Scenario 4, the peak concentration in Zone 1 was 1,800 mg/m3, whereas the peak
for Scenario 1 was 780, a ratio of 2.30. The similar ratios for applied mass and resultant peak air
concentration apply when other model inputs, such as room volumes and air exchange rates,
were kept at the same or similar values. The shape of the user's exposure concentration profile
50 Figures H-12 through H-15 are provided at the end of this section.
Page 235 of 279
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reflected the location of the user at various times during the stripping, waiting, and scraping
activities.
Figure H-13 shows the zone and user exposure concentration results for Scenarios 2 and 5
(brush and spray application, respectively) for the workshop with parameter values selected to
estimate upper-end concentrations for the user. In this comparison, the emitted DCM mass was
390 g for the spray vs. 260 g for the brush application, a ratio of ~1.5. The peak concentrations
(2,000 mg/m3 for spray-on vs. 1,300 mg/m3 for brush-on) again had a ratio (1.54) that was
similar to that for the applied mass.
Figure H-14 shows the zone and user exposure concentration results for Scenarios 3 and 6
(brush and spray application, respectively) for the workshop with parameter values selected to
estimate upper-end exposure concentrations for the user as well as the non-user (bystander).
In this comparison, the spray-to-brush ratio of ~1.5 for applied mass translated directly to the
24-hr TWA concentration to which the non-user was exposed (180 mg/m3 for spray application
vs. 120 mg/m3 for brush application). The more pronounced crossover of the Zone 1 and 2
concentration time series for these scenarios, shortly after the user finishes the last scraping,
can be explained by the indoor-outdoor air exchange rates: 1.26/hr for the workshop vs.
0.18/hr for the ROM. Due to the higher dilution rate, the workshop concentrations fell more
quickly after the stripping activity was completed than do the concentrations in the ROM.
Figure H-15 shows the air concentrations for the simulation scenario, namely the bathtub
stripping activity with a modeled peak concentration of ~3,000 mg/m3. The saw-tooth
appearance of the concentration rise associated with the stripping activity—particularly
pronounced in this scenario but evident in the other scenarios as well—was due to the eight
application segments. Scenario 7 was intended, in part, to simulate the situation described in a
CDC/NIOSH case fatality assessment (CDC. 2012: Chester et al.. 2012).
The user's modeled maximum exposure concentration reported here for Scenario 7, on the
order of 2,500 ppm, is substantially lower than that calculated (155,000 ppm) for the fatality
assessment, but the value reported by CDC/NIOSH was a bounding estimate obtained by
assuming that all DCM mass was released instantaneously. By comparison, monitoring of a
bathtub application by Washington State Occupational Safety and Health staff, as described in
the CDC/NIOSH report (CDC, 2012; Chester et al., 2012), indicated a 15-minute TWA exposure
concentration for the applicator on the order of 2,000 ppm.
Page 236 of 279
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900
u
o
D
00
1
2
a) Scenario 1, Brush Applied
^^User Exposure
(Non-user assumed to be in the ROH)
12
Time, hours
16
20
24
-Zl (Workshop)
-Z2(ROHj
2000
^^User Exposure
(Non-user assumed to be in the ROH)
0 4
b) Scenario 4, Spray Applied
12
Time, hours
16
20
Figure H-12. Modeled DCM Concentrations for Scenarios 1 and 4, Stripper Application in Workshop using Central Parameter
Values
Page 237 of 279
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woo
User Exposure
(Non-user assumed to be in the ROM]
0 4
a) Scenario 2, Brush Applied
2 MM
2500
2000
8 12
Time, hours
b) Scenario 5, Spray Applied
^^User Exposure
(Non-user assumed to be in the ROM)
Figure H-13. Modeled DCM Concentrations for Scenarios 2 and 5, Stripper Application in Workshop using Parameter Values
selected for Upper-end User's Exposure.
Page 238 of 279
-------
2L.OO
o
1MO
2500
a) Scenario 3, Brush Applied
3500
3000
—Zl (Workshop!
-Z2(ROH)
3500
3000
8 12
Time, hours
b) Scenario 6, Spray Applied
^^User Exposure
(Non-user assumed to be in the ROM)
8 12
Time, hours
^^User Exposure
(Non-user assumed to be in the ROM)
12 16
Time, hours
20
Figure H-14. Modeled DCM Concentrations for Scenarios 3 and 6, Stripper Application in Workshop using Parameter Values
Selected for Upper-end-User's and Non-user (Bystander)'s Exposure
24
Page 239 of 279
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21 (Source Cloud)
22 (Bathroom)
Z3(ROH)
2500 -
2000
1500
1000
User Exposure
(Non-user assumed to be in the ROM)
12 16
Time, hours
Figure H-15. Modeled DCM Concentrations for Scenario 7, Brush Application in Bathroom (Simulation)
Page 240 of 279
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H-5 Comparison of Modeling-based and Monitoring-based
Exposure Estimates
This section discusses similarities and differences between the DCM consumer modeling
estimates from this assessment and the monitoring results from the Lawrence Berkeley
Laboratory house study (LBL, 1987). It also discusses the exposure estimates for the most
comparable scenarios.
H-5-1 Scenario Similarities and Differences
The LBL study (LBL, 1987) and a related chamber study (LBL, 1986) were conducted by LBL for
the U.S. Department of Energy (DOE) with support from the U.S. Consumer Product Safety
Commission (CPSC).
The LBL (1987) study includes both monitored and modeled exposure results from consumer-
use scenarios that share some similarities with those modeled in the EPA/OPPT risk assessment
for DCM. However, the LBL results are expressed in ppm-hr exposure units, as opposed to TWA
concentration units of mg/m3 that were calculated for the EPA/OPPT assessment. With
knowledge of the duration of each experiment (provided in the LBL report) and the molecular
weight of DCM (84.9 g/mole), it was possible to recast the LBL exposure estimates in the same
units as the EPA/OPPT modeling results. This was done by first dividing the ppm-hr estimates by
the experiment's duration (in hours) to obtain TWA estimates in ppm. Then the estimates were
converted to mass/volume units using the following relationship: 1 ppm DCM = 3.47 mg/m3
DCM.
LBL conducted a total of 21 experiments, some outdoors and others indoors (i.e., in a garage, a
basement workshop, and large and small rooms of a house). One of the study objectives was to
identify practical ways to reduce exposures to DCM when using a paint remover. Consequently,
the LBL base case for comparison was an upper-end exposure scenario with very conservative
assumptions, especially the closed-room configuration with all windows as well as the interior
door assumed to be closed. By comparison, all EPA/OPPT scenarios assumed an open interior
door together with some form of ventilation, in accordance with both label instructions and
predominant patterns of paint-stripper use based on household surveys (section H-3, Airflow
Rates and Volumes).
For all 6 workshop cases in the EPA/OPPT assessment, the interior door to the room of
application was assumed to be open, whereas the door was closed for 4 of the 5 LBL indoor
cases (i.e., bedroom, dining room, or basement). The ventilation rate for the workshop was
greater than 1.0 ACH for all 6 cases in the EPA/OPPT assessment versus 2 of the 5 LBL indoor
cases. At the opposite extreme, all LBL garage cases had high ventilation rates, ranging from ~ 2
to ~ 19 ACH.
Page 241 of 279
-------
There were greater similarities for the length of the work period, between 80 and 90 minutes
for 4 of the 6 cases in the EPA/OPPT assessment and for 4 of the 5 indoor LBL cases. Three of
the EPA/OPPT scenarios used a brush application and three used a spray application, whereas
all LBL experiments used a brush application. The applied product mass was greater for the
EPA/OPPT cases, whereas the fraction of DCM mass released to indoor air was greater for the
LBL cases (somewhat greater than EPA/OPPT spray-on cases but much greater than EPA/OPPT
brush-on cases).
H-S-2 Comparison of Exposure Estimates
Table H-9 lists the exposure estimates and associated test conditions for EPA/OPPT workshop
cases and LBL indoor cases. Despite the numerous differences, there were certain cases with a
good number of similarities. For example, in terms of the room volume and ventilation rate, the
EPA/OPPT workshop cases (volume = 54 m3 and ventilation rate = 1.26 ACH) were quite similar
to the LBL basement case.
Table H-9 highlights the most comparable cases for the user and non-user (bystander)
exposures. In addition to similar room volumes and ventilation rates, these user cases had
nearly identical theoretical estimates of DCM mass released to the indoor air, reflecting the
combined effects of applied product mass, DCM weight fraction in the product, and fraction of
applied DCM mass that is released to indoor air.
The most comparable cases for the non-user (bystander) exposure were similar with respect to
room-of-use volume and DCM mass released, but not in terms of ventilation rate. The much
lower ventilation rate for the LBL case (0.23 ACH) vs. the EPA/OPPT case (1.26 ACH) resulted in
a substantially longer residence time for the airborne DCM mass and, hence, greater
opportunity for transport to the rest of the house despite the closed-door configuration.
Page 242 of 279
-------
Table H-9. Estimated Exposures and Associated Conditions for Selected OPPT and LBL Cases
Room of Product Application Theoretical
Length of
Work
Ventilation
Exposure during
c Period, mg/m3
OPPT Cases (modeled with door to room of application assumed to be open in all cases)
Workshop (54 m3
Brush-Table
157.4
84
1.26
ROM
174
Workshop (54 m3
Brush-Table
261.4
84
1.26
Workshop
Workshop (54 m3)
Brush-Chest
653.4
168
1.26
ROM
Workshop (54 m3)
Spray-Table
359.0
80
1.26
ROM
383
55
Workshop (54 m3
Spray-Table
390.5
80
1.26
Workshop
1,418
59
Workshop (54 m3
Spray-Chest
976.1
160
1.26
ROM
808
264
LBL Cases (monitored with door to room of application closed in all cases except the 2nd)
Bedroom (22.6 m3
Brush-Panel
194.8
102
0.13
Bedroom
2,090
Bedroom (22.6 m3
Brush-Panel
223.4
89
Bedroom
771
143
Bedroom (22.6 m3)
Brush-Panel
253.8
90
1.57
Bedroom
982
Dining Room (73.2 m3)
Brush-Panel
231.4
88
0.23
Dining Room
574
Basement (60.7 m3)
Brush-Panel
247.5
92
1.60
Basement
818
Notes:
a Not measured but likely similar to the above case; bedroom window was closed in both cases.
b Measured in a separate experiment with the window closed and the stairway door open.
| | indicates the most comparable product user exposures and QJ indicates the most comparable non-user (bystander) exposures
Non-user= Residential bystander
Page 243 of 279
-------
H-6
MCCEM Inhalation Modeling Scenario Summaries
Formula:
CAS Number:
Molecular Weight:
Density:
Appearance
Melting Point:
Boiling Point:
Solubility in Water:
Vapor Pressure:
Conversion units:
Saturation Concentration:
CH2CI2
75-09-2
84.93 g/mol
1.33 g/cm2 (liquid)
colorless liquid
-96.7 deg C = -142 deg F = 176 K
39.6 deg C = 103 deg F = 313 K
13 g/L @ 20 deg C
47 kPa = 352.535 Torr = 0.4639 atm = 6.817 psi
1 ppm = 3.4736 mg/m3
463,862 ppm = 1,611,281 mg/m3
DCM Scenario 1. Coffee Table, Brush-On, Workshop, User in ROM during wait time, 0.45 ACH,
0.53 Weight Fraction
MCCEM Input Summary
Application Method: Brush-on
Volumes:
Workshop volume = 54 m3
ROM volume = 492 - 54 = 438 m3
Airflows:
Workshop-outdoors
ROM-outdoors
Workshop-ROM
68 m3/h
197.1 m3/h (0.45 ACH)
107 m3/h
DCM Mass Released:
Coffee table = 10 sq ft surface area
Applied product mass = 90 g/sq ft = 900 g
DCM mass = 900 g x 0.53 (wt fraction) x 0.33 (release fraction) = 157.4 g
For each of the 4 application sections:
k = 10/hr
Mass = 157.4/4 = 39.35 g
Eo = Mass * k = 393.5 g/hr (NOTE: only k and Mass are needed as MCCEM inputs)
Application Times by Section:
Episode
first 1/2, 1st time
second 1/2, 1st time
first 1/2, 2nd time
second 1/2, 2nd time
Elapsed time from time zero, minutes
Apply
0-2 min
21-23 min
42-44 min
63-65 min
Wait
2-17 min
23-38 min
44-59 min
65-80 min
Scrape
17-21 min
38-42 min
59-63 min
80-84 min
Page 244 of 279
-------
Model RunTime:
0-24 hrs
User takes out scrapings after 84 minutes
Activity Patterns:
User in workshop during application and scrape periods, in ROM during wait periods
User in ROM for the remainder of the run (22 hrs, 36 minutes)
MCCEM Results Summary
Exposure Concentrations (maximum values over first 24 hrs):
In mg/m3
Individual
User
Other
1 min
632.4
131.7
10 min
376.1
131.5
30 min
269.4
129.5
Ihr
224.0
123.8
4hr
120.5
82.1
8hr
68.6
49.1
24 hr
23.3
16.8
Inppm
Individual
User
Other
1 min
182.1
37.9
10 min
108.3
37.8
30 min
77.6
37.3
Ihr
64.5
35.6
4hr
34.7
23.6
8hr
19.7
14.1
24 hr
6.7
4.8
Plots:
900
800
m
,£
00
E
c"
o
u
o
u
u
Q
Page 245 of 279
-------
m
F
00
c"
o
S
•M
0>
u
C
o
U
^
U
D
ruu
onn
7 nn
finn
cnn
/inn
a no
inn
1 nn
0
^— User Exposure
(Non-user assumed to be in the ROM)
V ^
4 8 12 16 20 2
Time, hours
Non-user= Residential bystander
Page 246 of 279
-------
DCM Scenario 2. Coffee Table, Brush-On, Workshop, User in Workshop during wait time, 0.45
ACH, 0.88 Weight Fraction
MCCEM Input Summary
Application Method: Brush-on
Volumes:
Workshop volume = 54 m3
ROM volume = 492 - 54 = 438 m3
Airflows:
Workshop-outdoors
ROM-outdoors
Workshop-ROM
68 m3/h
197.1 m3/h (0.45 ACH)
107 m3/h
DCM Mass Released:
Coffee table = 10 sq ft surface area
Applied product mass = 90 g/sq ft = 900 g
DCM mass = 900 g x 0.88 (wt fraction) x 0.33 (release fraction) = 261.4 g
For each of the 4 application sections:
k = 10/hr
Mass = 261.4/4 = 65.35 g
Eo = Mass * k = 653.5 g/hr (NOTE: only k and Mass are needed as MCCEM inputs)
Application Times by Section:
Episode
first 1/2, 1st time
second 1/2, 1st time
first 1/2, 2nd time
second 1/2, 2nd time
Elapsed time from time zero, minutes
Apply
0-2 min
21-23 min
42-44 min
63-65 min
Wait
2-17 min
23-38 min
44-59 min
65-80 min
Scrape
17-21 min
38-42 min
59-63 min
80-84 min
Model Run Time:
0-24 hrs
User takes out scrapings after 84 minutes
Activity Patterns:
User in workshop during application, wait and scrape periods
User in ROM for the remainder of the run (22 hrs, 36 minutes)
Page 247 of 279
-------
MCCEM Results Summary
Exposure Concentrations (maximum values over first 24 hrs):
In mg/m3
Individua
1
User
Other
1 min
1,292.4
218.7
10 min
1,251.7
218.3
30 min
1,136.7
215.1
Ihr
1,058.0
205.6
4 hrs
416.7
136.3
8 hrs
223.8
81.5
24 hrs
75.3
27.9
Inppm
Individual
User
Other
1 min
372.0
63.0
10 min
360.4
62.9
30 min
327.2
61.9
Ihr
304.6
59.2
4 hrs
120.0
39.2
8 hrs
64.4
23.5
24 hrs
21.7
8.0
Plots:
1400
on
E
c~
o
c
01
I
u
Q
-Zl (Workshop)
-Z2(ROH)
8 12
Time, hours
16
Page 248 of 279
-------
1 ^nn
1ZLHJ
m 1 nnn
00
Eonn
oUU
I
S
c
a* Ann
c
3
1
c
J
1
)
^^User Exposure
X^^^
4 8 12 16 20 2
Time, hours
Non-user= Residential bystander
Page 249 of 279
-------
DCM Scenario 3. Chest, Brush-On, Workshop, User in ROM during wait time, 0.18 ACH, 0.88
Weight Fraction
MCCEM Input Summary
Application Method: Brush-on
Volumes:
Workshop volume = 54 m3
ROM volume = 492 - 54 = 438 m3
Airflows:
Workshop-outdoors
ROM-outdoors
Workshop-ROM
68 m3/h
78.8 m3/h (0.18
ACH)
65.8 m3/h
DCM Mass Released:
Chest = 25 sq ft surface area
Applied product mass = 90 g/sq ft = 2,250 g
DCM mass = 2,250 g x 0.88 (wt fraction) x 0.33 (release fraction) = 653.4 g
For each of the 4 application sections:
k = 10/hr
Mass = 653.4/8 = 81.675 g
Eo = Mass * k = 816.75 g/hr (NOTE: only k and Mass are needed as MCCEM inputs)
Application Times by Section:
Episode
first 1/4, 1st time
second 1/4, 1st time
third 1/4, 1st time
fourth 1/4, 1st time
first 1/4, 2nd time
second 1/4, 2nd time
third 1/4, 2nd time
fourth 1/4, 2nd time
Elapsed time from time zero, minutes
Apply
0-2 min
21-23 min
42-44 min
63-65 min
84-86 min
105-107 min
126-128 min
147-149 min
Wait
2-17 min
23-38 min
44-59 min
65-80 min
86-101 min
107-122 min
128-143 min
149-164 min
Scrape
17-21 min
38-42 min
59-63 min
80-84 min
101-105 min
122-126 min
143-147 min
164-168 min
Model RunTime:
0-24 hrs
User takes out scrapings after 168 minutes
Activity Patterns:
User in workshop during application and scrape periods, in ROM during wait periods
User in ROM for the remainder of the run (21 hrs, 12 minutes)
Page 250 of 279
-------
MCCEM Results Summary
Exposure Concentrations (maximum values over first 24 hrs):
In mg/m3
Individua
1
User
Other
1 min
1,810.4
472.7
10 min
1,178.1
472.3
30 min
898.3
469.7
Ihr
762.4
461.4
4 hrs
562.8
383.0
8 hrs
400.1
287.9
24 hrs
157.1
118.2
Inppm
Individual
User
Other
1 min
521.2
136.1
10 min
339.2
136.0
30 min
258.6
135.2
Ihr
219.5
132.8
4 hrs
162.0
110.2
8 hrs
115.2
82.9
24 hrs
45.2
34.0
Plots:
2500
-Zl (Workshop)
-Z2(ROH)
Page 251 of 279
-------
2500
^^User Exposure
(Non-user assumed to be in the ROM)
Non-user= Residential bystander
Page 252 of 279
-------
DCM Scenario 4. Coffee Table, Spray-On, Workshop, User in ROM during wait time, 0.45 ACH,
0.8 Weight fraction
MCCEM Input Summary
Application Method: Spray-on
Volumes:
Workshop volume = 54 m3
ROM volume = 492 - 54 = 438 m3
Airflows:
Workshop-outdoors
ROM-outdoors
Workshop-ROM
68 m3/h
197.1 m3/h (0.45 ACH)
107 m3/h
DCM Mass Released:
Coffee table = 10 sq ft surface area
Applied product mass = 68 g/sq ft = 680 g
DCM mass = 680 g x 0.8 (wt fraction) x 0.66 (release fraction) = 359 g
For each of the 4 application sections:
k = 10/hr
Mass = 359/4 = 89.75 g
Eo = Mass * k = 897.5 g/hr (NOTE: only k and Mass are needed as MCCEM inputs)
Application Times by Section:
Episode
first 1/2, 1st time
second 1/2, 1st time
first 1/2, 2nd time
second 1/2, 2nd time
Elapsed time from time zero, minutes
Apply
0-1 min
20-21 min
40-41 min
60-61 min
Wait
1-16 min
21-36 min
41-56 min
61-76 min
Scrape
16-20 min
36-40 min
56-60 min
76-80 min
Model Run Time:
0-24 hrs
User takes out scrapings after 80 minutes
Activity Patterns:
User in workshop during application and scrape periods, in ROM during wait periods
User in ROM for the remainder of the run (22 hrs, 40 minutes)
Page 253 of 279
-------
MCCEM Results Summary
Exposure Concentrations (maximum values over first 24 hrs):
In mg/m3
Individual
User
Other
1 min
1,502.0
303.1
10 min
781.0
302.5
30 min
598.2
298.0
Ihr
491.7
284.8
4 hrs
266.9
187.8
8 hrs
152.1
112.0
24 hrs
51.7
38.3
In ppm
Individual
User
Other
1 min
432.4
87.2
10 min
224.8
87.1
30 min
172.2
85.8
Ihr
141.6
82.0
4 hrs
76.8
54.1
8 hrs
43.8
32.3
24 hrs
14.9
11.0
Plots:
2000
-------
m
on
o
ra
2
E
.
J^,
4 8 12 16 20 2
Time, hours
Non-user= Residential bystander
Page 255 of 279
-------
DCM Scenario 5. Coffee Table, Spray-On, Workshop, User in workshop during wait time, 0.45
ACH, 0.87 Weight Fraction
MCCEM Input Summary
Application Method: Spray-on
Volumes:
Workshop volume = 54 m3
ROM volume = 492 - 54 = 438 m3
Airflows:
Workshop-outdoors
ROM-outdoors
Workshop-ROM
68 m3/h
197.1 m3/h (0.45 ACH)
107 m3/h
DCM Mass Released:
Coffee table = 10 sq ft surface area
Applied product mass = 68 g/sq ft = 680 g
DCM mass = 680 g x 0.87 (wt fraction) x 0.66 (release fraction) = 390.5 g
For each of the 4 application sections:
k = 10/hr
Mass = 390.5/4 = 97.625 g
Eo = Mass * k = 976.25 g/hr (NOTE: only k and Mass are needed as MCCEM inputs)
Application Times by Section:
Episode
first 1/2, 1st time
second 1/2, 1st time
first 1/2, 2nd time
second 1/2, 2nd time
Elapsed time from time zero, minutes
Apply
0-1 min
20-21 min
40-41 min
60-61 min
Wait
1-16 min
21-36 min
41-56 min
61-76 min
Scrape
16-20 min
36-40 min
56-60 min
76-80 min
Model RunTime:
0-24 hrs
User takes out scrapings after 80 minutes
Activity Patterns:
User in workshop during application, wait and scrape periods
User in ROM for the remainder of the run (22 hrs, 40 minutes)
Page 256 of 279
-------
MCCEM Results Summary
Exposure Concentrations (maximum values over first 24 hrs):
In mg/m3
Individua
1
User
Other
1 min
1,991.0
329.6
10 min
1,926.4
329.0
30 min
1,760.8
324.1
Ihr
1,609.4
309.8
4 hrs
619.4
204.2
8 hrs
332.4
121.9
24 hrs
111.9
41.7
Inppm
Individual
User
Other
1 min
573.2
94.9
10 min
554.6
94.7
30 min
506.9
93.3
Ihr
463.3
89.2
4 hrs
178.3
58.8
8 hrs
95.7
35.1
24 hrs
32.2
12.0
Plots:
2500
•Zl (Workshop)
•Z2(ROH)
12
Time, hours
16
20
24
Page 257 of 279
-------
2500
^^User Exposure
(Non-user assumed to be in the ROM)
12
Time, hours
16
20
24
Non-user= Residential bystander
Page 258 of 279
-------
DCM Scenario 6. Chest, Spray-On, Workshop, User in ROM during wait time, 0.18 ACH, 0.87
Weight Fraction
MCCEM Input Summary
Application Method: Spray-on
Volumes:
Workshop volume = 54 m3
ROM volume = 492 - 54 = 438 m3
Airflows:
Workshop-outdoors
ROM-outdoors
Workshop-ROM
68 m3/h
78.8 m3/h (0.18 ACH)
65.8 m3/h
DCM Mass Released:
Chest = 25 sq ft surface area
Applied product mass = 68 g/sq ft = 1,700 g
DCM mass = 1,700 g x 0.87 (wt fraction) x 0.66 (release fraction) = 976.1 g
For each of the 8 application sections:
k = 10/hr
Mass = 976.1/8 = 122.0 g
Eo = Mass * k = 1,220 g/hr (NOTE: only k and Mass are needed as MCCEM inputs)
Application Times by Section:
Episode
first 1/4, 1st time
second 1/4, 1st time
third 1/4, 1st time
fourth 1/4, 1st time
first 1/4, 2nd time
second 1/4, 2nd time
third 1/4, 2nd time
fourth 1/4, 2nd time
Elapsed time from time zero, minutes
Apply
0-1 min
20-21 min
40-41 min
60-61 min
80-81 min
100-101 min
120-121 min
140-141 min
Wait
1-16 min
21-36 min
41-56 min
61-76 min
81-96 min
101-116 min
121-136 min
141-156 min
Scrape
16-20 min
36-40 min
56-60 min
76-80 min
96-100 min
116-120 min
136-140 min
156-160 min
Model Run Time:
0-24 hrs
User takes out scrapings after 160 minutes
Activity Patterns:
User in workshop during application and scrape periods, in ROM during wait periods
User in ROM for the remainder of the run (21 hrs, 20 minutes)
Page 259 of 279
-------
MCCEM Results Summary
Exposure Concentrations (maximum values over first 24 hrs):
In mg/m3
Individua
1
User
Other
1 min
2,821.3
713.5
10 min
1,632.3
713.0
30 min
1,266.5
709.0
Ihr
1,108.6
696.5
4 hrs
813.6
575.9
8 hrs
580.2
431.3
24 hrs
228.2
176.6
Inppm
Individual
User
Other
1 min
812.2
205.4
10 min
469.9
205.3
30 min
364.6
204.1
Ihr
319.1
200.5
4 hrs
234.2
165.8
8 hrs
167.0
124.2
24 hrs
65.7
50.8
Plots:
3500
Zl (Workshop)
Z2(ROH)
Page 260 of 279
-------
3500
3000
« 2500 H
no
E 2000
^,
*= 1500
E
S 1000
u
Q
500
^^User Exposure
(Non-user assumed to be in the ROH)
12
Time, hours
16
20
24
Non-user= Residential bystander
Page 261 of 279
-------
DCM Scenario 7. Bathtub, Brush-On, Bathroom + Source Cloud, User in ROM During Wait
Time, 0.18 ACH, 1.0 Weight Fraction
MCCEM Input Summary
Application Method: Brush-on
Volumes:
Source Cloud = 1.0 m3
Rest of Bathroom volume = 9 -1 = 8 m3
ROM volume = 492 - 9 = 483 m3
Airflows:
Source Cloud-Bathroom
Bathroom-outdoors
ROM-outdoors
Bathroom-ROH
80 m3/h (0 to outdoors/ROM)
1.6 m3/h
86.9 m3/h (0.18 ACH)
35 m3/h
DCM Mass Released:
Tub = 36 sq ft surface area
Applied product mass = 90 g/sq ft = 3,240 g
DCM mass = 477 g x 1.0 (wt fraction) x 0.33 (release fraction) = 157.4 g
For each of the 8 application sections:
k = 10/hr
Mass = 157.4/8 = 19.7 g
Eo = Mass * k = 197 g/hr (NOTE: only k and Mass are needed as MCCEM inputs)
Application Times by Section:
Episode
first 1/4, 1st time
second 1/4, 1st time
third 1/4, 1st time
fourth 1/4, 1st time
first 1/4, 2nd time
second 1/4, 2nd time
third 1/4, 2nd time
fourth 1/4, 2nd time
Elapsed time from time zero, minutes
Apply
0-3 min
24-27 min
48-51 min
72-75 min
96-99 min
120-123 min
144-147 min
168-171 min
Wait
3-18 min
27-42 min
51-66 min
75-90 min
99-114 min
123-138 min
147-162 min
171-186 min
Scrape
18-24 min
42-48 min
66-72 min
90-96 min
114-120 min
138-144 min
162-168 min
186-192 min
Page 262 of 279
-------
Model RunTime:
0-24 hrs
User takes out scrapings after 192 minutes
Activity Patterns:
User in source cloud during application and scrape periods, in ROM during wait periods
User in ROM for the remainder of the run (20 hrs, 48 minutes)
MCCEM Results Summary
Exposure Concentrations (maximum values over first 24 hrs):
In mg/m3
Individua
1
User
Other
1 min
2428.0
223.8
10 min
1455.3
223.6
30 min
886.6
222.2
Ihr
798.9
218.2
4 hrs
536.4
186.9
8 hrs
339.6
149.5
24 hrs
135.3
69.5
In ppm
Individual
User
Other
1 min
699.0
64.4
10 min
419.0
64.4
30 min
255.3
64.0
Ihr
230.0
62.8
4 hrs
154.4
53.8
8 hrs
97.8
43.0
24 hrs
39.0
20.0
Plots:
3500
^Zl (Source Cloud)
— —Z2 (Bathroom)
ZS(ROH)
12
Time, hours
16
20
24
Page 263 of 279
-------
00
u
Q
3000
2500
2000
1500
1000
500
^^User Exposure
(Non-user assumed to be in the ROM)
12
Time, hours
16
20
24
Non-user= Residential bystander
Page 264 of 279
-------
Appendix I RISK ASSESSMENT GUIDELINES, LITERATURE
SEARCH STRATEGY AND DATA QUALITY
CRITERIA USED IN THE HAZARD/DOSE-
RESPONSE ASSESSMENTS OF METHYLENE
CHLORIDE
EPA/OPPT's work plan risk assessment for dichloromethane (DCM; methylene chloride) is based
on the peer-reviewed hazard and dose-response information published in the following reports:
• Toxicological Review of Methylene Chloride published in 2011 by the EPA's Integrated Risk
Information System (IRIS) (EPA. 2011c):
• Interim Acute Exposure Guideline Levels (AEGL) for methylene chloride (NAC, 2008);
• Spacecraft Maximum Allowable Concentrations (SMAC)for Selected Airborne Contaminants:
Methylene chloride (Volume 2) published by the U.S. National Academies (NRC, 1996);
• Acute Reference Exposure Level (REL) and Toxicity Summary for Methylene Chloride
published by the Office of Environmental Health Hazard Assessment (OEHHA, 2008).
The sections below contain a summary of the risk assessment guidelines, literature search
strategy and data quality criteria used in these assessments.
1-1 EPA/IRISJ^oxicologi^
/-l-l JRis/^^
The description below was extracted from the DCM IRIS assessment published in November
2011 (EPA. 2011c. pages 1-2).
Development of these hazard identification and dose-response assessments for DCM has
followed the general guidelines for risk assessment as set forth by the National Research
Council (NRC)(NRC, 1983). EPA's Guidelines and Risk Assessment Forum Technical Panel
Reports that may have been used in the development of the DCM IRIS assessment include the
following:
1. Guidelines for the Health Risk Assessment of Chemical Mixtures (EPA, 1986b);
2. Guidelines for Mutagenicity Risk Assessment (EPA, 1986a);
3. Recommendations for and Documentation of Biological Values for Use in Risk Assessment
(EPA, 1988);
4. Guidelines for Developmental Toxicity Risk Assessment (EPA, 1991);
5. Interim Policy for Particle Size and Limit Concentration Issues in Inhalation Toxicity (EPA,
1994b);
6. Methods for Derivation of Inhalation Reference Concentrations and Application of Inhalation
Dosimetry (EPA, 1994c);
7. Use of the Benchmark Dose Approach in Health Risk Assessment (EPA, 1995b);
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8. Guidelines for Reproductive Toxicity Risk Assessment (EPA, 1996b);
9. Guidelines for Neurotoxicity Risk Assessment (EPA, 1998a);
10. Science Policy Council Handbook: Risk Characterization (EPA, 2000c);
11. Benchmark Dose Technical Guidance Document (EPA, 2000b, 2012a);
12. Supplementary Guidance for Conducting Health Risk Assessment of Chemical Mixtures (EPA,
2000d);
13. A Review of the Reference Dose and Reference Concentration Processes (EPA, 2002)
14. Guidelines for Carcinogen Risk Assessment (EPA, 2005a);
15. Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to Carcinogens
(EPA. 2005b);
16. Science Policy Council Handbook: Peer Review (EPA, 2006b);
17. A Framework for Assessing Health Risks of Environmental Exposures to Children (EPA,
2006a).
1-1 -2 Literature Search Strategy
When developing the DCM IRIS assessment, the literature search strategy was based on the
chemical name, Chemical Abstracts Service Registry Number (CASRN), and multiple common
synonyms (EPA, 2011c). Any pertinent scientific information submitted by the public to the IRIS
Submission Desk was also considered in the development of this document.
Primary, peer-reviewed literature identified through September 2011 was included where that
literature was determined to be critical to the assessment. The relevant literature included
publications on DCM which were identified through Toxicology Literature Online (TOXLINE), the
U.S. National Library of Medicine's MEDLINE, the Toxic Substance Control Act Test Submission
Database (TSCATS), the Registry of Toxic Effects of Chemical Substances (RTECS), the Chemical
Carcinogenesis Research Information System (CCRIS), the Developmental and Reproductive
Toxicology/Environmental Teratology Information Center (DART/ETIC), the Hazardous
Substances Data Bank (HSDB), the Genetic Toxicology Data Bank (GENE-TOX), Chemical
abstracts, and Current Contents. Other peer-reviewed information, including health
assessments developed by other organizations, review articles, and independent analyses of
the health effects data were retrieved and included in the assessment when appropriate (EPA,
2011c).
1-1 -3 Study Selection and Data Quality Criteria
The following study selection and data quality criteria were used by the EPA's IRIS program
when developing the DCM IRIS assessment (EPA, 2011c). In addition, EPA/OPPT uses these
criteria when evaluating hazard/dose-response studies for chemical assessments.
• Epidemiology data: Study quality evaluation criteria include a review of factors such as the
study selection criteria, study power, potential bias in data collection, selection bias,
measurement biases associated with exposure and outcome, and consideration of potential
confounding and effect modification (Figure 1-1).
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• Animal toxicology data: Study quality evaluation criteria for animal studies (i.e., in vivo and
in vitro) include a review of factors such as the following:
- the adequacy of study design,
- test animals (e.g., species, strain, source, sex, age/lifestage/embryonic stage),
- environment (e.g., husbandry, culture medium),
- test substance (e.g., identification, purity, analytical confirmation of stability and
concentration),
- treatment (e.g., dose levels, controls, vehicle, group sizes, duration, route of
administration),
- endpoints evaluated (e.g., schedule of evaluation, randomization and blinding
procedures, assessment methods), and
- reporting (quality and completeness) (Figure 1-2).
Figure 1-1. Study Quality Considerations for Epidemiological Studies
Feature
Selection
Attrition
Detection
Participants
Comparability
Attrition Rate
Length of
Follow-Up
Exposure
Characteristics
Outcome
Assessment
Confounding
Variables or
Exposure
Statistical Tests
Example Questions
• Were inclusion and exclusion criteria applied consistently
across study groups?
• Are baseline characteristics similar between groups? If not,
did the analysis control for differences?
• Is the comparison group appropriate, including having both
exposed and non-exposed subjects drawn from the same
population:
• Was the attrition rate uniformly low?
• In cohort studies: Dose the length of follow-up differ
between groups?
• In case-control studies: Is the time period between
exposure between exposure/intervention and outcome the
same for cases and controls?
• Was follow-up long enough to assess the outcome of
interest?
• What is the level of exposure misclassification?
• Is there an adequate level of exposure variability to detect
an effect?
• Are there adequate numbers of persons exposed at various
exposure levels to detect a dose-response effect?
• What is the extent of reliance on imputed exposure levels?
• Were the outcome assessors blinded to the exposure or
intervention status of participants?
• Is there confidence that the outcome of interest preceded
exposure?
• Are confounding variables assessed using reliable and
consistent measures?
• Did researchers adjust or control for other exposures or
interventions that are anticipated to bias results?
• Are statistical analyses performed with reliable tests and
implemented consistently?
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Figure 1-2. Study Quality Considerations for Animal Studies
Feature
Example Questions
Exposure
Quality
• Were the exposures well designed and tightly
controlled?
•Was the test article/formulation adequately identified
and characterized? Are co-exposures expected as a
result of test article composition?
• Is the administration route relevant to human
exposure?
•Are the exposure levels relevant?
• I nhalation exposure: Were analytical concentrations in
the test animals' breathing zone measured and reported
(i.e., not just target or nominal concentrations)?
• I nhalation exposure: For aerosol studies, were the mass
median aerodynamic diameter and geometric standard
deviation reported?
• I nhalation exposure: Was the chamber type appropriate?
Dynamic chambers should be used; static chambers are not
recommended.
• Inhalation exposure: Were appropriate methods used to generate
the test article and measure the analytical concentration?
• Diet/Water Exposure: Was consumption measured to allow for
accurate dose determinations? Were stability and homogeneity
of the test substance maintained? Was palatability an issue?
•Gavage Exposure: Was an appropriate vehicle used? Are there
any toxicokinetic differences due to bolus dosing? Consider
relevance to human exposures.
Test Animals
• Were the test animals appropriate for evaluation of the
specified effect(s)?
• Were the species, strain, sex, and/or age of the test
animals appropriate for the effect(s) measured?
• Were the control and exposed populations matched in
all aspects other than exposure?
• Were an appropriate number of animals examined, based on
what is known about the particular endpoint(s) in question?
• Were there any notable issues regarding animal housing or food
and water consumption?
Study Design
• Is the study design appropriate for the effect(s) and
chemical analyzed?
• Were exposure frequency and duration appropriate for
the effect(s) measured?
• Were anticipated confounding factors caused by
selection bias controlled for in the study design (e.g.,
correction for potential litter bias; randomization of
treatment groups)?
•Was the timing of the endpoint evaluation (e.g., latency
from exposure) appropriate?
•Was it a Good laboratory Practices (GLP) study?
•Was it designed according to established guidelines (e.g., EPA,
OECD)? Was it designed to specifically test the endpoint(s) in
question?
• Did the study design include other experimental procedures (e.g.,
surgery) that may influence the results of the toxicity endpoint(s)
in question? Were they controlled for?
•Was the study design able to detect the most sensitive effects in
the most sensitive population(s)?
•Were multiple exposure groups tested? Was justification for
exposure group spacing given? Was recovery or adaptation
tested?
Toxicity
Endpoints
•Are the protocols used for evaluating a specific
endpoint reliable and the study endpoints chosen
relevant to humans?
•Are the endpoints measured relevant to humans? Do
the endpoints evaluate an adverse effect on the health
outcome in question?
• Were the outcomes evaluated accordingto established
protocols? If not, were the approaches biologically
sound? Were any key protocol details omitted?
•Were all necessary control experiments performed to allow for
selective examination of the endpoint in question?
•As appropriate, were steps taken to minimize experimenter bias
(e.g..blinding)?
• Does the methodology employed represent the most appropriate
and discriminating option for the chosen endpoint?
Data
Presentation
and Analysis
• Were statistical methods and presentation of data
sufficient to accurately define the direction and
magnitude of the observed effect(s)?
•Are the statistical methods and comparisons
appropriate?
• Was sufficient sampling performed to detect a
biologically relevant effect (e.g., appropriate number of
slides examined)?
• Does the data present pooled groups that should be displayed
separately (e.g., pooled exposure groups; pooled sexes) and/or
analyzed separately?
•Was an unexpectedly high/low level of within-study variability
and/or variation from historical measures reported or explained?
•As appropriate, were issues such as systemic and maternal
toxicity (e.g., body weight) considered?
Reporting
•Are descriptions of study methods and results for all
endpoints sufficient to allow for study quality
evaluations?
• Were the details of the exposure protocols and
equipment provided?
• Were test animal specifics adequately presented?
•Are the protocols for all study endpoints clearly
described? Is sufficient detail provided to reproduce the
experiment(s)?
•Are the statistical methods applied for data analysis provided and
applied in a transparent manner? Was variability reported?
• Did the study evaluate a unique cohort of animals (i.e., are
multiple studies linked)?
•Are group sizes and results reported quantitatively for each
exposure group, time-point, and endpoint examined?
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1-2 Acute Exposure Guideline Levels (AEGLs)
AEGLs are emergency response guideline levels for once-in-a-lifetime short-term exposures to
airborne chemicals (see Appendix K for more details). AEGL are developed based on the
procedures, methods and criteria documented in the Standing Operating Procedures (SOP) for
Developing Acute Exposure Guideline Levels for Hazardous Chemicals (NRC, 2001). Specifically,
the AEGL SOP contains the following information supporting the derivations of AEGLs, including
those for DCM (NRC. 2001):
• Empirical toxicological endpoints and methods for determining exposure concentrations
used to derive AEGLs 1,2, and 3 (Chapter 2.2 of the AEGL SOP);
• Guidelines and criteria for the search strategy, evaluation, selection, and documentation of
key data and supporting data used for the derivation of AEGL values (Chapter 2.3 of the
AEGL SOP);
• Dosimetry corrections from animal to human exposures (Chapter 2.4 of the AEGL SOP)
• Guidelines and criteria for selection of uncertainty factors to address the variability
between animals and humans and within the human population (Chapter 2.5 of the AEGL
SOP);
• Guidelines and criteria for time scaling (Chapter 2.7 of the AEGL SOP).
1-3 Spacecraft Maximum Allowable Concentrations (SMACs)
SMACs are guideline levels intended for spacecraft chemical exposures and developed
following the criteria and methods described in Guidelines for Developing Spacecraft Maximum
Allowable Concentrations for Space Station Contaminants (NRC, 1992). Chapter 6 of the SMAC
Guidelines contains information about the derivation of the SMAC values, including the
following (NRC. 1992):
• Sources of data for developing SMACs (i.e., chemical-physical properties, in vitro studies,
animal toxicity studies, epidemiological data),
• Types of data used in recommending SMACs (i.e., dosimetry, pharmacokinetics and
metabolism, biological markers and toxicity endpoints in humans and animals),
• Risk assessment (e.g., issues about animal to human extrapolation), and
• General approach to establishing SMACs.
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1-4 California's Acute Reference Exposure Levels (RELs)
An acute REL is defined as the concentration level at or below which no adverse health effects
are anticipated (i.e., 1 or 8 hrs) in a human population, including sensitive subgroups, exposed
on an intermittent basis (OEHHA, 1999). The Office of Environmental Health Hazard Assessment
(OEHHA) from the State of California has developed guidance on how to develop acute RELs
including guidance on the appropriate exposure durations and patterns for acute exposure,
hazard identification and dose-response, criteria for selecting key studies and identifying
adverse health effects, time extrapolation and characterization of uncertainties (OEHHA, 1999).
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Appendix J SUMMARY OF THE DERIVATIONS OF THE EPA
IRIS CANCER INHALATION UNIT RISK AND NON-
CANCER HUMAN EQUIVALENT CONCENTRATION
FOR CHRONIC EXPOSURES
The reader is referred to the DCM IRIS assessment for detailed explanations of the toxicological
studies and the derivation approaches supporting the cancer inhalation unit risk and the non-
cancer hazard value associated with chronic exposures to DCM (EPA, 2011c).
J-l Cancer Inhalation Unit Risk
DCM's cancer inhalation unit risk (IUR) of 4 x 10~5 per ppm (1 x 10~5 per mg/m3)51 was derived
from mouse liver and lung tumor incidence data (Mennear et al., 1988; NTP, 1986). Figure J-l
describes the steps that the EPA's IRIS program used to derive the DCM IUR using
physiologically-based pharmacokinetic (PBPK) modeling. Refer to the DCM IRIS assessment for a
full discussion of the IUR derivation (EPA, 2011c).
The derivation steps are the following:
1. Dose conversion: A deterministic mouse PBPK model was used to convert the mouse
inhalation exposures to long-term daily average internal doses in the liver or lung. The
selected internal dose-metric was long-term average daily mass of DCM metabolized via the
GST pathway per unit volume of liver or lung tissue. The choice of the dose metric was
based on evidence related to the involvement of the GST metabolites in DCM-induced
carcinogenicity (EPA, 2011c).
2. Dose-response modeling and extrapolation: The multistage dose-response model
(Benchmark Dose Software [BMDS] version 2.0) was used to fit the mouse liver tumor
incidence and PBPK-derived internal doses and derive a mouse internal BMDioand BMDLio52
associated with 10% extra risk (EPA, 2011c).
The mouse internal BMDLio(0.1/BMDL10) were used to derive inhalation risk factors for
lung and liver tumors by linear extrapolation. Consistent with EPA Guidelines for Carcinogen
Risk Assessment (EPA, 2005a), a linear low-dose extrapolation approach is used for
chemicals with DNA-reactive and mutagenic properties (EPA, 2011c).
51 The inhalation unit risk for dichloromethane should not be used with exposures exceeding the point of
departure (BMDLio = 7,700 mg/m3 or 2,200 ppm), because above this level the fitted dose-response model
better characterizes what is known about the carcinogenicity of dichloromethane.
52 The benchmark dose (BMD) is a dose or concentration that produces a predetermined change in response rate
of an adverse effect (called the benchmark response or BMR) compared to background (EPA, 2011b).
BMDio= benchmark dose at the 10% response
BMDLio=lower confidence limit of the benchmark dose at the 10% response
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Figure J-l. Process of deriving the DCM's cancer inhalation unit risk
Benchmark Dose Analysis
Rodent
odentDose PBPK ^[
esponse Data
i
f
Human Tumor Risk Factor ••
(internal obse)-1
E
Estimates of Rodent MO
Internal Dose ^~
Scaling
-"actor
L Rodent Tumor Risk Fac
t^— (internal dose)"1
(0.1/RodentBMDL,D)
TJ 0.5
?MD g 0,
deling, f 0.3
c
O 0.2
H 0.1
lil
Multistage r
T^"^
\^'Atg^^m ,
0 10 20 30 40 9] 60
Dose
^ Rodent Internal BMDLio
95% Lower Bound Estimate of Internal
Dose Associated with a 10% response
Multiply Human Tumor Risk Factor
By Distribution of Human Internal
Unit Doses
99
Distribution of Human Cancer
Oral Slope Factors or
Inhalation Unit Risks
Recommend mean value
+
Apply Age-Dependent Adjustment Factors
(ADAFs) for early life exposure
Probabilistic
Human PBPK
Model
Distribution of Human Internal
Doses from Unit Oral Doses
(Img/kg) or Inhalation
Concentrations (1ug/m3)
Monte Carlo
"\ Sampling from
Distributions of
Human PBPK
Model Parameters
Source: EPA (2011c. p. 212)
3. Application of allometric scaling factor: The chosen dose metrics is a rate of metabolism
rather than the concentration of putative toxic metabolites. Currently, there are no data
pertaining to the reactivity or clearance rate of the relevant metabolite(s). A scaling factor
was used to address the possibility that the rate of clearance for the metabolite is limited by
processes that are known to scale allometrically. The human BMDLio was derived by
applying a mouse:human dose-rate scaling factor of 7 [i.e., (Body Weight human/Body
Weight mouse)0-25 = 7] to adjust the mouse-based BMDLio values downward based on the
potential slower clearance per volume tissue in the human compared with the (EPA, 2011c).
A linear extrapolation approach using the internal human BMDLio for liver and lung tumors
was used to calculate human tumor risk factors by dividing the benchmark response (BMR)
of 0.1 by the human BMDL for each tumor type, given a 70-year lifetime exposure (EPA,
2011c). Currently, there are no data from chronic inhalation cancer bioassays in mice or rats
providing support for a nonlinear dose-response relationship (EPA, 2011c).
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4. Calculation of the inhalation unit risk and consideration of sensitive human
subpopulations: A probabilistic human PBPK model with Monte Carlo sampling was used to
determine a distribution of human internal doses lung, liver, or blood doses associated with
chronic unit inhalation (1 u.g/m3) exposures. The distribution of IDRs was derived by
multiplying the human inhalation tumor risk factors by the respective distributions of
human average daily internal doses resulting from chronic, unit inhalation exposures of one
u.g/m3 DCM. The mean of the distribution of candidate IUR values from the most sensitive
(GST-T1+/+) genotype (i.e., the group that would be expected to be most sensitive to the
carcinogenic effects of DCM) was chosen as the IUR for liver and lung tumors. A procedure
for combining risks for liver and lung tumors was used to derive DCM's IUR.
The slope of the linear extrapolation from the lower 95 percent bound estimate BMDLio is
1 x 10~8 per u.g/m3 (4 x 10~5 per ppm ), which represents an upper-bound estimate for
continuous lifetime exposure (70 years) without consideration of increased early-life
susceptibility due to DCM's mutagenic mode of action.
J-2 Non-Cancer Hazard Value
The EPA's IRIS program based the non-cancer hazard value for DCM on liver effects. These
effects were reported in female rats exposed to DCM for 6 hrs/day, 5 days/week for 2 years
(Nitschke et al., 1988a). The rat data were suitable for non-cancer dose-response analysis in the
DCM IRIS assessment.
Since the study was suitable for dose-response analysis, the EPA's IRIS program used a PBPK
model to estimate rat internal doses from the Nitschke et al. (1988a) study. Benchmark dose
modeling used the rat internal doses and their corresponding incidence data (i.e., hepatic
vacuolation) to estimate the rat internal BMDLio for hepatic effects. In other words, the BMDLio
is the lower 95% confidence limit of the benchmark dose at the 10% benchmark response
(BMR) (EPA, 2011c). A BMR of 10% was selected because, in the absence of information
regarding the magnitude of change in a response that is thought to be minimally biologically
significant, a BMR of 10% is generally recommended since it provides a consistent basis of
comparison across assessments. Moreover, there were no additional data to suggest that the
severity of the critical effect or the power of the study would warrant a lower BMR (EPA,
2011c).
The rat internal BMDLio was allometrically adjusted because the dose-metric is a rate of
metabolism and the clearance of these metabolites may be slower per volume tissue in the
human compared with the rat. This adjustment consisted of dividing the rat internal BMDLio by
4.09 [(BWhuman)/(BWrat)a25 ~ 4.09)]53 to obtain a human equivalent internal BMDLio of
130.03 mg DCM metabolized via CYP54 pathway/litter liver tissue/day (EPA. 2011c).
53 BW=body weight
54 CYP=cytochrome P450
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A probabilistic PBPK model for dichloromethane in humans was then used with Monte Carlo
sampling to calculate distributions of chronic human equivalent concentrations (HEC) (in units
of mg/m3) associated with the internal BMDLio based on the responses in female Sprague-
Dawley rats. Estimated HECs corresponding to the mean, 1st, and 5th percentiles of the
distribution were 48.5,17.2 and 21.3 mg/m3, respectively. The 1st percentile of the distribution
of HECs i.e. the HECgg the concentration at which there is 99% likelihood an individual would
have an internal dose less than or equal to the internal dose of hazard, 17.2 mg/m3, was chosen
as the point of departure (POD)55 for the non-cancer hazard value because it would protect
toxicokinetically sensitive individuals (EPA, 2011c).
55 A point of departure (POD) is a dose or concentration that can be considered to be in the range of observed
responses, without significant extrapolation. A POD is used to mark the beginning of extrapolation to determine
risk associated with lower environmentally relevant human exposures (EPA, 2011b).
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Appendix K THE DERIVATIONS OF THE ACUTE HAZARD
VALUES USED IN THE DCM RISK ASSESSMENT OF
PAINT STRIPPERS
The reader is referred to the U.S. National Academies' Spacecraft Maximum Allowable
Concentrations for Selected Airborne Contaminants (Volumes 2 and 5; NRC, 2008, 2010), the
Acute Reference Exposure Level (REL) and Toxicity Summary for Methylene Chloride from the
State of California, and the Interim Acute Exposure Guideline Levels technical support document
(NAC, 2008) for detailed explanations of toxicological studies and derivation approaches for
these values.
K-l Spacecraft Maximum Allowable Concentrations (SMAC)
SMACs are developed by the U.S. NAS to provide guidance on chemical exposures that may
occur during normal operations of spacecraft as well as emergency situations (NRC, 1996).
EPA/OPPT used the SMAC's dose-response assessment as the starting point for deriving
protective air concentrations for residential users of DCM-based paint strippers as well as other
residential occupants that may be indirectly exposed (e.g., children).
The 1-hr SMAC is the concentration of DCM which it is not expected to compromise the
performance of specific tasks by healthy astronauts during emergency conditions or cause
serious or permanent toxic effects. SMACs are designed for healthy individuals, and reversible
effects might occur but they are not expected to impair the astronauts' judgment or interfere
with proper responses to emergencies. By definition, the SMACs are not safe levels and are not
meant to protect the general population, including children and the elderly.
The following paragraphs were extracted from SMAC technical support document for DCM and
explain the dose-response evaluation leading to the selection of 100 ppm (350 mg/m3) as the
point of departure (POD) for the 1-hr SMAC (NRC. 1996):
"...one of the major acute effects of methylene chloride is CNS depression, which appears
to be due to carbon monoxide (CO) formed from methylene chloride's metabolism. A
4-hr exposure to methylene chloride at 200 ppm, which yields 5% carboxyhemoglobin
(COHb) in blood, impairs the hand-eye coordination and auditory vigilance (Peterson,
1978), but there are no data on the no-observed-adverse-effect level (NOAEL) of
methylene chloride. It makes sense to adopt the NOAEL of COHb used in setting the 1-h
and 24-h SMACs of CO as a potential basis for setting the 1-h and 24-h SMACs of
methylene chloride.
Three percent COHb is the target COHb concentration used to set both the 1-h and 24-h
SMACs for carbon monoxide (Wong, 1990). The task here is to determine the methylene
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chloride concentrations that produce about 3% COHb in 1 and 24 hr. Assuming a
baseline COHb concentration of 0.6% due to endogenous CO production, the task is to
determine the methylene chloride concentrations that would increase the COHb
concentration by 2.4%.
To derive the 1-hr SMAC based on CO formation, a linear regression line was fitted
through the data of percent COHb increase versus concentration x time (Cx T) by forcing
the fitted line through the origin. All the data in the above table /"table not included in
Appendix l-see NRC (1996)/ were used except the data points at 3750 and 1972 ppm-hr
because their corresponding responses of 10% and 9.3% increases in COHb were too far
away from the region of interest, 2.4%. The linear regression yielded a line with a slope
of 0.0038, r2 of 0.74, and a 95 % confidence limit of 100 ppm-hr at a 2.4% increase in
COHb. Accordingly, 100 ppm is selected as the 1-hr SMAC based on CO formation (NRC,
1996)."
The value of 100 ppm (350 mg/m3) was considered a NOAEL56 for CNS effects associated with
COHb formation and is used as the POD for acute inhalation risk estimates (NRC, 2008). The
application of UFs was not included in the derivation of the 1-hr SMAC value, which is
consistent with the intended purpose of the SMAC values.
K-2 California's Acute Reference Exposure Level (REL)
Acute RELs are developed by the Office of Environmental Health Hazard Assessment (OEHHA)
from the State of California. The acute REL is defined as the concentration level at or below
which no adverse health effects are anticipated (i.e., one or eight hrs) in a human population,
including sensitive subgroups, exposed on an intermittent basis (OEHHA, 1999). Since safety
factors are incorporated to address data gaps and uncertainties, exceeding the REL does not
automatically indicate an adverse health impact (OEHHA, 1999).
OEHHA developed a 1-hr acute REL based on (Putzet al., 1979). The study reported significant
performance decrements on dual-task and auditory vigilance tests in volunteers (n = 12)
exposed to 195 ppm DCM (696 mg/m3) for 1.5 hrs (Putzet al.. 1979). The blood COHb levels
increased from 1.35 percent pre-exposure to 5.1 percent post-exposure. The 1.5-hr exposure to
195 ppm was considered the LOAEL in the REL derivations.
A UF of 6 was applied to the LOAEL57 to develop a NOAEL and an intraspecies UF of 10 was
applied to account for variability in the human population. An equivalent 1-hr exposure was
estimated from the 1.5-hr exposure using the ten Berge equation (Cn * T = k, n = 2)58 resulting in
56 NOAEL= No-observed-adverse-effect level
57 The acute REL documentation does not provide the basis for the selection of a LOAEL-to-NOAEL UF of 6.
58 In the ten Berge equation (Cn * T = k, n = 2), C = concentration of the chemical of interest, n=chemical-specific
exponent, t=time, and k=constant (NRC, 2001).
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a 1-hr acute REL of 4 ppm (14 mg/m3). The rationale for the choice of n = 2 was not
documented in the OEHHA document.
K-3
Acute Exposure Level Guidelines (AEGL)
AEGLs represent threshold exposure limits for the general public, including infants and children
as well as other individuals who may be sensitive or susceptible. They are applicable for once-
in-a-lifetime acute exposures (i.e., <24 hrs) to airborne concentrations of toxic chemicals
typically occurring during emergency response situations. AEGL values are developed for three
different health effect end point tiers (discomfort = AEGL-1 threshold; disability = AEGL-2
threshold; and death = AEGL-3 threshold) at different durations of exposure (10 minutes;
30 minutes; 1 hr; 4hrs; and 8 hrs). Figure K-l depicts the three AEGL tiers and the associated
health effects.
Figure K-1. Illustration of the Different AEGL Threshold Levels
Threshold
Level
Health Effects
— Increasing likelihood of death
AEGL-3
— Impairment of ability to escape
Increasing severity of irreversible or other
serious long-lasting effects
DISABLING
AEGL-2 -
AEGL-1
— Increase in notable discomfort
— Increasing severity of reversible effects (with
or without signs/symptoms)
Increasing complaints of objectionable odor,
taste, sensory irritation or other mild, non-
sensory or asymptomatic effects
DISCOMFORT
Source: NRC(2001)
Two toxic endpoints were of importance for setting the AEGL-values for DCM: (1) CNS
depression caused by the concentration of the parent compound in brain and (2) the formation
of carboxyhemoglobin (COHb) from the carbon monoxide (CO) metabolite. A GST isozyme is
responsible for the metabolic pathway yielding CO. It is estimated that 20 percent of the U.S.
population lack this enzyme resulting in higher COHb levels in enzyme-deficient individuals
(NAC. 2008).
CNS effects are expected to occur soon after the onset of exposure, while peak levels of COHb
can be reached hours after cessation of exposure. Likewise, it was expected that the toxic
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endpoint of interest would change over an exposure range of 10 minutes to 8 hrs. The AEGL-
values for the shorter exposure durations would be triggered by the CNS effects, whereas the
formation of COHb would determine the AEGL values for longer exposure durations (NAC,
2008).
The following derivation summaries were extracted from the AEGL document for DCM (NAC,
2008).
AEGL-1 values
The AEGL-1 values were based on the observation in humans that exposure concentrations of
868 and 986 ppm (3,100 and 3,521 mg/m3) may lead to light-headedness and difficulties in
enunciation (Stewart et al., 1972). These effects were absent at a 1-hr exposure to 514 or
515 ppm (1,836 or 1,839 mg/m3). The concentration of 514 ppm was used as the POD for the
AEGL-1 derivations. These effects could be attributed to the DCM concentration in the brain
rather than to CO (NAC, 2008). A PBPK model estimated that 0.063 mM was the human brain
concentration of DCM following a 1-hr exposure to 514 ppm. Since susceptibility for gross CNS-
depressing effects do not vary by more than a factor of two- to three-fold in humans, an
intraspecies UF of three was applied, resulting in a maximum target concentration of DCM in
the human brain of 0.021 mM. The human PBPK model used this concentration to estimate the
AEGL values for the different time durations (i.e., 10 minutes to 8 hrs). Because the calculated
AEGL-1 values at 4- and 8- hrs (160 and 140 ppm, respectively) were at or above the
corresponding AEGL-2 values, no AEGL-1 values for these time periods were recommended
(NAC. 2008).
AEGL-2 values
AEGL-2 derivations were estimated for CNS effects based on a human study reporting the
absence of AEGL-2 related CNS effects59 during a DCM exposure to 751 ppm (2,682 mg/m3) for
230 minutes (Winneke, 1974). A PBPK model estimated that 0.137 mM was the human brain
concentration of DCM. AEGL-2 values were also estimated for the formation of COHb
formation, assuming a maximum COHb level of 4% in patients with coronary artery disease
humans (NAC, 2008; NRC, 2010). PBPK modeling was used to calculate exposure concentrations
for both types of effects (i.e., CNS effects and COHb formation). The lowest value was selected
as the AEGL-2 value for each time period. An intraspecies UF of 1 for the CNS effects was
considered sufficient since the toxic effects studied were less severe than those defined for
AEGL-2 and the application of a greater value would result in values that were inconsistent with
the available human data. Similarly, an intraspecies UF of 1 was applied for the effects
associated with COHb formation because the POD was based on experimental data on the most
susceptible individuals (i.e., coronary artery disease patients), which is also protective for other
human subpopulations (NAC, 2008; NRC, 2010).
59 This is an effect level and should not be considered as a NOAEL
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AEGL-3 values
AEGL-3 derivations were based on an animal study reporting no CNS-related mortality in rats
exposed to 11,000 ppm (39,286 mg/m3) DCM for 4-hrs (DuPont. 1982). A rat PBPK model
estimated that 3.01 mM was the maximum target DCM concentration in rat brain. AEGL-2
values were also estimated for the formation of COHb formation, assuming a maximum COHb
level of approximately 15 percent in humans (NRC, 2010). PBPK modeling was used to calculate
exposure concentrations for both types of effects. The lowest value was selected as the AEGL-2
value for each time period. An interspecies UF of 1 for the CNS effects was considered to be
sufficient since the differences in susceptibility regarding mortality between species appear to
be very small and because a human PBPK model is used to calculate the external human
exposure (NAC, 2008). An intraspecies UF of 3 was applied since the susceptibility for CNS-
depressing effects is not expected to vary by more than a factor of 2- to 3-fold in the human
population (NAC, 2008). Application of an overall UF of 3 results in a maximum target DCM
concentration in human brain of 1.0 mM. Similarly, an intraspecies factor of 3 was applied for
the effects associated with COHb formation because the POD was supported by information on
effects, such as myocardial infarction and stillbirths, reported in more susceptible
subpopulations (NRC, 2010).
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