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United States EPA Document# 740-R1-4003

Environmental Protection Agency August 2014 

Office of Chemical Safety and 

 Pollution Prevention

TSCA Work Plan Chemical Risk Assessment

Methylene Chloride:

Paint Stripping Use

CASRN: 75-09-2

August 2014
Page 2 of 279

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 of DCM’s Human Health Hazards ...................................................................28

1.2.4 Overview EPA’s Regulatory History of DCM.............................................................................................29

1.3 SCOPE OF THE 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 of DCM-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 FOR THE 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 FOR THE 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.............................................................................. 111

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 OF THE HUMAN HEALTH RISK ASSESSMENT ................................................................. 119

4 REFERENCES ......................................................................................................................................................121

APPENDICES................................................................................................................................................................144

Appendix A REGULATORY HISTORY OF DCM IN THE U.S. AND ABROAD ..................................................................144

A-1 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-1 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-1 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-1 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-1 Data Needs, Data Collection Strategy and Data Quality Criteria for the Occupational Exposure Analysis ............. 170

G-1-1 Data Needs.............................................................................................................................................................. 170

G-1-2 Data Collection Strategy.......................................................................................................................................... 171

G-1-3 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 OSHA IMIS Data .................................................................................................................................. 205

Appendix H RESIDENTIAL/CONSUMER EXPOSURE ASSESSMENT .............................................................................209

H-1 Estimation of Emission Profiles for Paint Removers/Strippers................................................................................ 209

H-1-1 Conceptual Approach.............................................................................................................................................. 210

H-1-1-1 MRI Chamber Study (EPA, 1994a)........................................................................................................................... 212

H-1-1-2 LBL Chamber Study (LBL, 1986)............................................................................................................................... 216

H-1-1-3 van Veen Chamber Study (van Veen et al., 2002) and EC Chamber Study (EC, 2004)............................................. 218

H-1-1-4 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 Modeling 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

I-1 EPA/IRIS Toxicological Review................................................................................................................................. 265

I-1-1 Risk Assessment Guidelines .................................................................................................................................... 265

I-1-2 Literature Search Strategy....................................................................................................................................... 266

I-1-3 Study Selection and Data Quality Criteria ............................................................................................................... 266

I-2 Acute Exposure Guideline Levels (AEGLs) ............................................................................................................... 269

I-3 Spacecraft Maximum Allowable Concentrations (SMACs)...................................................................................... 269

I-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-1 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-1 Spacecraft Maximum Allowable Concentrations (SMAC) ....................................................................................... 275

K-2 California’s Acute Reference Exposure Level (REL) ................................................................................................. 276

K-3 Acute Exposure Level Guidelines (AEGL)................................................................................................................. 277
Page 6 of 279

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 AEGL2 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 1, 3, 15 and 16).................................. 99

Table 3-23. Occupational Cancer Risks for Non-Specific Workplace Settings—Immersion Stripping of Wood 

(Scenarios 1, 3, 15 and 16)........................................................................................................... 100

Table 3-24. Occupational Cancer Risks for Non-Specific Workplace Settings—Immersion Stripping of Wood 

and Metal (Scenarios 1, 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 1, 3, 15 and 16)........................................................................................................... 103

Table 3-28. Occupational Non-Cancer Risks for Automotive Refinishing Following Chronic Exposure to DCM 

(Scenarios 1, 3, 15 and 16)........................................................................................................... 104

Table 3-29. Occupational Non-Cancer Risks for Furniture Refinishing Following Chronic Exposure to DCM 

(Scenarios 1, 3, 15 and 16)........................................................................................................... 104

Table 3-30. Occupational Non-Cancer Risks for Art Restoration and Conservation Following Chronic Exposure 

to DCM (Scenarios 1, 3, 15 and 16).............................................................................................. 105
Page 8 of 279

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 1, 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 1, 3, 15 and 16)................... 107

Table 3-35. Occupational Non-Cancer Risks for Non-Specific Workplace Settings (Unknown) Following 

Chronic Exposure to DCM (Scenarios 1, 3, 15 and 16)................................................................. 107

Table 3-36. Summary of the Uncertainties in the Derivation of the Cancer Inhalation Unit Risk ................... 113

Table C-1. 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-1. Household Products Containing DCM from NIH’s Household Products Database ........................ 150

Table E- 1. Environmental Fate Characteristics of DCM1................................................................................. 153

Table F-1. 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-1. Data Quality Criteria and Acceptance Specifications for Occupational Data................................. 173
Page 9 of 279

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-11. Summary of Worker Exposures to DCM During Furniture Paint Stripping using a Dip Tank after 

Implementation of NIOSH-Recommended Slotted Hood Ventilation Systema........................... 200

Table G-12. Summary by Industry of OSHA IMIS Personal Monitoring Data for DCM from 1992 to 2012 ..... 207

Table H-1. 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 for the 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
Page 10 of 279

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-1. 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-1. 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-11. Example of the Exposure Concentration Calculation as Defined in Equation H-11.................... 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
Page 11 of 279

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 I-1. Study Quality Considerations for Epidemiological Studies............................................................. 267

Figure I-2. Study Quality Considerations for Animal Studies........................................................................... 268

Figure J-1. Process of deriving the DCM’s cancer inhalation unit risk ............................................................. 272

Figure K- 1. Illustration of the Different AEGL Threshold Levels...................................................................... 277
Page 12 of 279

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:

Stanley Barone Jr., OPPT/RAD

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

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.
Page 13 of 279

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

Paul Schlosser ORD/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. 

Connecticut Department of Public Health

Thomas W. Armstrong, Ph.D.

TWA8HR Occupational Hygiene Consulting, LLC

Frank A. Barile, Ph.D.

St. John’s University College of Pharmacy 

and Health Sciences

Anneclaire J. De Roos, PhD.

Drexel University School of Public Health 

Ronald D. Hood, Ph.D.

Ronald D. Hood and Associates, 

Toxicology Consultants

Dale Hattis, Ph.D.

George Perkins Marsh Institute, 

Clark University 

John C. Kissel, Ph.D.

University of Washington

Stephen B. Pruett, Ph.D.

College of Veterinary Medicine, 

Mississippi State University

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.
Page 14 of 279

GLOSSARY OF TERMS AND ABBREVIATIONS

μg Microgram(s)

μg/m3 Microgram(s) per cubic meter

AC Acute concentration

ACGIH American Conference of Governmental Industrial Hygienists

ACH Air changes per hour

ADC Average daily concentration

AEGL Acute exposure guideline level

AEGL-1 Discomfort/non-disabling threshold

AEGL-2 Disability threshold

AEGL-3 Death threshold

APF Assigned protection factor

AT Averaging time

atm Atmosphere(s)

ATSDR Agency for Toxic Substances and Disease Registry

BAF Bioaccumulation factor

BCF Bioconcentration factor

BMD Benchmark dose

BMD10 Benchmark dose at 10% response

BMDL Benchmark dose, lower confidence limit(s)

BMDL10 Benchmark dose, lower confidence limit(s) at 10% response

BMDS Benchmark Dose Software

BMR Benchmark response

BOD Biochemical oxygen demand

BW Body weight

C Contaminant concentration

°C Degree Celsius

CROH Concentration in the rest of the house

Cal EPA California Environmental Protection Agency

CASRN Chemical abstracts service registry number

CBI Confidential business information

CDC Centers for Disease Control and Prevention

CCD Chemical Control Division

CCRIS Chemical Carcinogenesis Research Information System

CDR Chemical data report

cm Centimeter(s)

cm2 Square centimeter(s)

cm3 Cubic centimeter(s)

CNS Central nervous system

CO Carbon monoxide

CO2 Carbon dioxide

COHb Carboxyhemoglobin
Page 15 of 279

CPSC Consumer Product Safety Commission

CYP Cytochrome P450

CYP2E1 Cytochrome P450, family 2, subfamily E, polypeptide 1

DART/ETIC Developmental and Reproductive Toxicology/Environmental Teratology 

Information Center

DCM Dichloromethane

DEM Department of Environmental Management

DIY Do-it-yourself

DNA Deoxyribonucleic acid

DNA SSB Single stranded DNA-binding protein

DOE U.S. Department of Energy

DOSH Division of Occupation Safety and Health

E Emission rate

E0 Initial emission rate

EC European Commission

EC50 Effective concentration necessary to produce a 50% response

ECi,i+1 Exposure concentration over the time interval i to i+1

ECscenario1 Exposure concentration for scenario 1

ECscenario 2→4 Exposure concentration for scenario 2, 3 or 4

ECscenario 2→16 Exposure concentration for scenario 2 through 16

ECG Electrocardiogram

ED Exposure duration

EETD Economics, Exposure and Technology Division

EF Exposure frequency

EFH Exposure Factors Handbook

EPA U.S. Environmental Protection Agency

EPCRA Emergency Planning and Community Right-to-Know Act

ERG Eastern Research Group

EU European Union

F Fraction of time spent in the use zone

°F Degrees Fahrenheit

FACE Fatality Assessment and Control Evaluation

FDA Food and Drug Administration

ft Foot/feet

ft2 Square foot/feet

ft3 Cubic foot/feet

FTIR Fourier transform infrared

g Gram(s) 

g/cm2 Gram(s) per square centimeter

g/cm3 Grams(s) per cubic centimeter

GENE-TOX Genetic Toxicology Data Bank

g/ft2, g/sq ft Grams(s) per square foot

g/L Gram(s) per liter

GLP Good Laboratory Practices
Page 16 of 279

g/minute Grams(s) per minute

g/mol Gram(s) per mole

GC/ECD Gas chromatography and electron capture detector

GST Glutathione S-transferase

GST-T1 GST-theta1-1

GWP Global warming potential

HEC Human equivalent concentration

HEC99 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

HFC-32 Hydrofluorocarbon-32

HHE Health hazard evaluation

HQ Hazard quotient

HPLC High-performance liquid chromatography

hr(s) Hour(s)

HSDB Hazardous Substances Data Bank

HSIA Halogenated Solvents Industry Alliance, Inc. 

HVAC Heating, ventilation, and air conditioning

IDLH Immediately dangerous to life and health

IMIS Integrated Management Information Systems

IPCC Intergovernmental Panel on Climate Change

IRIS Integrated Risk Information System

IRTA Institute for Research and Technical Assistance

IUR Inhalation unit risk 

IURR Inventory Update Reporting Rule

K (upper-case) Kelvin

k (lower-case) first-order rate constant

Koc Soil organic carbon partition coefficient

Kow Octanol:water partition coefficient

kPa kilopascal(s)

L Liter (s)

lb(s) Pound(s)

LADC Lifetime average daily concentration 

LBL Lawrence Berkeley Laboratory

LC50 Median lethal concentration

LOAEL Lowest-observed-adverse-effect level

LOEC Lowest-observed-effect concentration

m Meter(s)

m2 Square meter(s)

m3 Cubic meter(s)

Macute Scenario-specific acute exposure modifier

Mchronic Scenario-specific chronic exposure modifier

m3/hr Cubic meter(s) per hour

MATC Maximum acceptable toxicant concentration
Page 17 of 279

MCCEM Multi-Chamber Concentration and Exposure Model

MCL Maximum contaminant level

mg Milligram(s)

mg/L Milligram(s) per liter

mg/m3 Milligram(s) per cubic meter

min Minute(s)

MITI Ministry of International Trade and Industry

mM Millimolar

mm Hg Millimeters of mercury

mL Milliliter(s)

MMWR Morbidity and Mortality Weekly Report

MOE Margin of exposure

MR Mass released

MRI Midwest Research Institute

MSDS Material safety data sheets

MSU Michigan State University

NAICS North American Industry Classification System

NAS National Academies

NESHAP National Emission Standards for Hazardous Air Pollutants

NHANES National Health and Nutrition Examination Survey

NIH National Institutes of Health

NIOSH National Institute for Occupational Safety and Health

NLS Non-linear least squares

NMP N-Methylpyrrolidone

NOAEL No-observed-adverse-effect level

NRC National Research Council

NTP National Toxicology Program

OCSPP Office of Chemical Safety and Pollution Prevention

OECD Organization for Economic Cooperation and Development

OEHHA Office of Environmental Health Hazard Assessment

OEM Original Equipment Manufacturing

OPPT Office of Pollution Prevention and Toxics

OSHA Occupational Safety and Health Administration

PMN Premanufacture Notification Program

PBPK Physiologically-based pharmacokinetic

PEL Permissible exposure limit

PFT Perfluorocarbon tracer

POD Point of departure

ppb parts per billion

ppm Parts per million

psi Pound per square inch

Q Compartment ventilation rate or air flow rate in and out of the chamber

RAD Risk Assessment Division

RCRA Resource Conservation and Recovery Act
Page 18 of 279

REL Reference exposure level

RfC Reference concentration

RIA Regulatory impact analysis

ROH Rest of the house

RTECS Registry of Toxic Effects of Chemical Substances

SCG The Scientific Consulting Group, Inc.

SDWA Safe Drinking Water Act

SIC Standard Industry Classification

SMAC Spacecraft maximum allowable concentration

SNAP Significant New Alternatives Policy

SRC Syracuse Research Corporation

STEL Short-term exposure limit

sq ft Square foot (feet)

t Time

TLV Threshold limit value

TOXLINE Toxicology Literature Online

TRI Toxics Release Inventory

TSCA Toxic Substances Control Act

TSCATS Toxic Substance Control Act Test Submission Database

TWA Time-weighted average

UF Uncertainty factor

UFA Interspecies uncertainty factor

UFD Database uncertainty factor

UFH Intraspecies uncertainty factor

UFL LOAEL-to-NOAEL uncertainty factor

UFtotal Total uncertainty factor

US or U.S. United States

UK United Kingdom

V Volume

VOC Volatile organic compound

wt Weight

WY Working years

yr Year(s)
Page 19 of 279

EXECUTIVE SUMMARY

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 

 

1 http://www.epa.gov/oppt/existingchemicals/pubs/workplans.html
Page 20 of 279

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.
Page 21 of 279

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

Range for acute 

8-hr concentration: 

Scenario 1→4

(mg/m3)

ADC range:

Non-Cancer Effects 

Following Chronic 

Exposure

Scenarios 1→16

(mg/m3)

LADC range:

Cancer Effects 

Following Chronic 

Exposure

Scenarios 1→16

(mg/m3)

LOW-END 

ESTIMATE

HIGH-END 

ESTIMATE

LOW-END 

ESTIMATE

HIGH-END 

ESTIMATE

LOW-END 

ESTIMATE

HIGH-END 

ESTIMATE

Professional Contractors 1.2 2,980 0.07 680 0.04 389

Automotive Refinishing 1.8 416 0.1 95 0.06 54

Furniture Refinishing 0.08 2,245 0.005 513 0.003 293

Art Restoration and 

Conservation

0.04 2 0.003 0.5 0.002 0.3

Aircraft Paint Stripping 1.7 3,802 0.1 868 0.06 496

Graffiti Removal 0.4 1,188 0.02 271 0.01 155

Non-Specific Workplace 

Settings – Immersion 

Stripping of Wood

0.7 7,000 0.04 1,598 0.02 913

Non-Specific Workplace 

Settings – Immersion 

Stripping of Wood and 

Metal

13 1,017 0.7 232 0.4 133

Non-Specific Workplace 

Settings – Unknown

5.7 428 0.3 98 0.2 56

Note: Airborne concentration conversion factor for DCM is 3.47 mg/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 
Page 22 of 279

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 (ROH) 

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 ROH. 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) Toxicological 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 μg/m3 (EPA, 2011c). 
Page 23 of 279

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

(SMACs)(NRC, 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 1

st percentile of the distribution of 

human equivalent concentrations (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 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). 
Page 24 of 279

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.
Page 25 of 279

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-containing paint strippers.

 Many of the occupational scenarios exceed at least one of the target cancer risks of 10-4, 

10-5 and 10-6.

 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 
Page 26 of 279

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 27 of 279

1 BACKGROUND AND SCOPE

1.1 INTRODUCTION

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
Page 28 of 279

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 (lbs) with a projected 

demand of 181 million lbs for 2010 (HSIA, 2008; ICIS, 2007). The 2012 non-confidential business 

information (CBI) Chemical Data Reporting (CDR) indicated 261.5 million lbs 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).
Page 29 of 279

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 Toxicological 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., nonacute) 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 30 of 279

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 31 of 279

Table 1-1. Primary Uses of DCM and Selection Criteria

Use Category

Percent 

DCM 

Content

Population

Exposed a

Considered in this Assessment?

Adhesives 60-100

Small commercial 

shop workers, 

consumers [including 

do-it-yourself (DIYs)]; 

industrial workers

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.

Paint stripping 25-100

Small commercial 

shop workers, 

consumers (including 

“DIYs”); industrial 

workers

Yes – Relatively high percent content range, 

broad range of stripping and removal 

applications (automotive, furniture, marine, 

wall paint, similar coating removal).

Pharmaceuticals N/AbIndustrial workers

No – Industrial use settings which are 

generally believed to be better controlled and 

monitored.

Metal cleaning 15-40

Small commercial 

shop workers, 

consumers (including 

“DIYs”); industrial 

workers

No – Small market percentage (7 percent) and 

likely lower exposure levels compared to paint 

stripping.

Chemical 

processing N/Ab

Industrial workers

No – Industrial use settings which are 

generally believed to be better controlled and 

monitored.

Aerosols

(propellant use) <25

Small commercial 

shop workers, 

consumers (including 

“DIYs”); industrial 

workers

No – Relatively low percent content range, 

small market percentage (5 percent), and 

likely lower exposure levels compared to paint 

stripping.

Polyurethane 

foam N/Ab

Industrial workers

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 32 of 279

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 

Paint Strippers

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.
Page 33 of 279

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

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 physicalchemical properties of DCM. 

Table 2-1. Physical-Chemical Properties of DCM a

Molecular formula CH2Cl2

Molecular weight 84.93

Physical form Colorless liquid; sweet, pleasant odor resembling chloroform

Melting point -95°C

Boiling point 39.7°C

Vapor pressure 351.8 mmHg at 25°C

Log KOW 5.3 ("slow stirring" method); 5.9 at 25°C (measured; OECD 117b)

Water solubility 13.7 g/L at 20°C

Density 1.33 g/cm3 at 20°C

Flash point none

Notes:

a

 Information obtained from (ECB, 2000)

b

 OECD Test Number 117: Partition Coefficient (n-octanol/water), High Performance Liquid Chromatography 

(HPLC) Method

H

H Cl

Cl
Page 34 of 279

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. 

2.2.1 Market Trends and Uses

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 lbs in the mid1980s to approximately 181 million lbs currently (ICIS, 2007). In 1984, there were four domestic 

producers of DCM selling around 501 million lbs. 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 lbs by industry sources with a 

projected demand of 181 million lbs for 2010 (HSIA, 2008; ICIS, 2007). The 2012 nonconfidential business information (CBI) CDR indicated 261.5 million lbs of DCM that were 

produced and imported into the U.S. (EPA, 2013). DCM imports were estimated at 20 million lbs 

in 2006 (ICIS, 2007). Thus, the production volume of DCM makes up 80 to 96 percent of the 
Page 35 of 279

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 lbs 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 stripper a

 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 

used b

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 PEL a

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-22e

 Fluorocarbon production accounts for less than 10 percent of 

DCM use f

Sources: 

a OSHA (2010)

b CPSC (1992)

c Pauli (1996)

d Mannsville (1999)

e HSIA (2010)

f

ICIS (2007)
Page 36 of 279

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 Usesa Minor Usesa Overall Benefits

 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)

 Extraction solvent 

for oils, waxes, fats, 

spices, and hops

 Tablet coating for 

pharmaceuticals

 Low flammabilityb

 Non-corrosive to many 

substratesb

 Strong solvency propertiesb

 No flash point under normal use 

conditions and can be used to 

reduce the flammability of other 

substancesc

 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 37 of 279

Table 2-4. Major Uses of DCM in the U.S.

Major Uses Percent of DCM Consumed in End Products

Adhesives 37

Paint stripping 25

Pharmaceuticals 10

Metal cleaning 7

Chemical processing 7

Aerosols 5

Polyurethane foam blowing 5

Miscellaneous 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  Paint thinnersa

 Paint removers and strippersb

 Varnish removersb

 Graffiti removersb

Aerosol applications  Aerosol paintsc

 Automotive productsc

 Spray shoe polisha

 Rust removersa

 Primersa

Cleaners/protectors  Water repellant/protectorsa

 Spot removersa

 Wood floor and panel cleanersa

 Specialized electronic cleaners 

 (for TV, VCR, razor, etc.)

a

 Wood stainsa

 Transmission cleanersa

 Battery terminal protector

a

 Brake quieter/cleanera

 Gasket removersa

Adhesives  Contact cementa

 Super gluesa

 Spray adhesivesa

 Adhesive removers (general 

 purpose, tile and wallpaper)a

Miscellaneous  Silicone lubricants 

 (excluding automotive)a

 Outdoor water repellantsa

 Gasket removersa

Sources: a NIH (2005)

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 
Page 38 of 279

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 lbs of 

DCM, while 1,000 facilities used products containing > 2,000 lbs of the chemical (EPA, 2008).

2.3 SUMMARY OF ENVIRONMENTAL FATE

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.
Page 39 of 279

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-1).
Page 40 of 279

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 95

th 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 DCMcontaining products. Refer to Appendix G for a detailed discussion of the OSHA IMIS data.
Page 41 of 279

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 timeweighted 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 Respirator APF a 8-hr TWA ConcentrationMultiplier b

Scenario Description

1 0 1 No respirator

2 10 0.1 Respirator APF 10

3 25 0.04 Respirator APF 25

4 50 0.02 Respirator APF 50

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 (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.

 

6 APF assumptions are the same for both acute and chronic scenarios.
Page 42 of 279

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). 

Table 3-2. Chronic Occupational Exposure Scenarios for the Use of DCM-Based Paint 

Strippers

Chronic 

Scenario

Respirator 

APF a

Exposure 

Frequency 

(EF) (days/yr)

Working 

Years 

(WY) 

(years)

ADC/LADC

Multiplier b

Scenario Description

1 0 250 40 1

No respirator, high ends of 

ranges for EF and WY

2 10 250 40 0.1 Respirator APF 10, high ends 

of ranges for EF and WY

3 25 250 40 0.04 Respirator APF 25, high ends 

of ranges for EF and WY

4 50 250 40 0.02 Respirator APF 50, high ends 

of ranges for EF and WY

5 / 9 0 250/ 125 20/ 40 0.5

No respirator, one midpoint 

and one high end of range for 

EF and WY

6 / 10 10 250/ 125 20/ 40 0.05

Respirator APF 10, one 

midpoint and one high end of 

range for EF and WY

7 / 11 25 250/ 125 20/ 40 0.02

Respirator APF 25, one 

midpoint and one high end of 

range for EF and WY

8 / 12 50 250/ 125 20/ 40 0.01

Respirator APF 50, one 

midpoint and one high end of 

range for EF and WY

13 0 125 20 0.25 No respirator, midpoints of 

ranges for EF and WY

14 10 125 20 0.025 Respirator APF 10, midpoints 

of ranges for EF and WY

15 25 125 20 0.01 Respirator APF 25, midpoints 

of ranges for EF and WY

16 50 125 20 0.005 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).
Page 43 of 279

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/m3reported 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

 C = contaminant concentration in air for relevant industry (central tendency, 

low- or high-end 8-hr TWA in mg/m3from Appendix G, Table G-2 or G-5);
Page 44 of 279

Equation 3-2 was used to calculate the acute exposure estimates for scenarios 2 through 4.

EC scenario 2→ 4= EC 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;

 EC scenario 1 = single (acute) exposure concentration for relevant industry (8-hr 

 TWA in mg/m3from 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 scenariospecific 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/m3reported 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).

EC scenario 1 =

C × ED × EF × WY

AT

 (Equation 3-3)

where:

 EC scenario 1 = exposure concentration (mg/m3) for Scenario 1 = ADC for chronic noncancer 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/m3from 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;
Page 45 of 279

 WY = working years per lifetime (yrs) = 40 yrs for high end of range

for both ADC and LADC calculations; and

 AT = averaging time (years × 365 days/years × 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.

EC scenario 2→ 16 = EC scenario 1 × 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 1 = chronic exposure concentration (ADC or LADC) for relevant 

 industry, chronic scenario 1 (in mg/m3from 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 DCMbased 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 46 of 279

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.
Page 47 of 279

Table 3-3. DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers – Scenario 1 –

Highest Exposed Scenario Group

Industry / 

Activity

Time 

Range of 

Studies

ACUTE EXPOSURE ESTIMATES

Single 8-hr Concentration 

(mg/m3)

a

CHRONIC EXPOSURE ESTIMATES

USED IN THE NON-CANCER RISK 

ESTIMATES

ADC (mg/m3)

b

CHRONIC EXPOSURE 

ESTIMATES USED IN THE 

CANCER RISK ESTIMATES

LADC (mg/m3)

b

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Professional 

Contractors

1981-

2004 -- 2,980 1,520 60 -- 680 347 14 -- 389 198 7.8

Bathtub 

Refinishing -- -- -- -- -- -- -- -- -- -- -- --

Automotive 

Refinishing 2003 253 416 253 90 58 95 58 21 33 54 33 12

Furniture 

Refinishing 1989-

2007 499

2,245

(1,266)

c

1,125 4.0 114

513

(289)

c

257 0.9 65

293

(165)

c

147 0.5

Art 

Restoration 

and 

Conservation

2005 2.0 0.5 0.3

Aircraft 

Paint 

Stripping

1977-

2006 -- 3,802 1,944 86 -- 868 444 20 -- 496 254 11

Ship Paint 

Stripping 1980 -- -- -- -- -- -- -- -- -- -- -- --

Graffiti 

Removal 1993 260 1,188 603 18 59 271 138 4.1 34 155 79 2.3

Non-Specific 

Workplace 

Settings -

Immersion 

Stripping of 

Wood

1980-

1994 -- 7,000 3,518 35 -- 1,598 803 8.0 -- 913 459 4.6
Page 48 of 279

Table 3-3. DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers – Scenario 1 –

Highest Exposed Scenario Group

Industry / 

Activity

Time 

Range of 

Studies

ACUTE EXPOSURE ESTIMATES

Single 8-hr Concentration 

(mg/m3)

a

CHRONIC EXPOSURE ESTIMATES

USED IN THE NON-CANCER RISK 

ESTIMATES

ADC (mg/m3)

b

CHRONIC EXPOSURE ESTIMATES

USED IN THE CANCER RISK 

ESTIMATES

LADC (mg/m3)

b

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Non-Specific 

Workplace 

Settings -

Immersion 

Stripping of 

Wood and 

Metal

1980 -- 1,017 825 633 -- 232 188 145 -- 133 108 83

Non-Specific 

Workplace 

Settings -

Immersion 

Stripping of 

Metal

-- -- -- -- -- -- -- -- -- -- -- --

Non-Specific 

Workplace 

Settings –

Unknown

1997-

2004 357 428 357 285 81 98 81 65 47 56 47 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.
Page 49 of 279

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 Limit Type Exposure Limit

OSHA PEL 

PEL (8-hr TWA) b 25 ppm c

STEL (15-minute TWA) 125 ppm

Action Level (8-hr TWA) 12.5 ppm

NIOSH exposure limits IDLH d 2,300 ppm

REL e Ca

ACGIH TLV f 8-hr TWA 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 50 of 279

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 (ROH). 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.
Page 51 of 279

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 52 of 279

3.2.3 MCCEM Input Parameters and Assumptions

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-1-3 and Table H-1). 

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 53 of 279

3.2.3.2 Method of Application

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 brushon 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/ft2for 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 upperend 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 54 of 279

 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. Upperend 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.

3.2.3.4 Stripping Sequence

The stripping sequence was based in part on product label instructions, which for some DCMcontaining 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-ft

2 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

 Riley et al. (2001) represents the most current use-pattern survey available for paint strippers. Refer to Appendix

H for more information on this study.
Page 55 of 279

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), Riley et al. (2001), EPA (1995a),

Matthews et al. (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 ROH (438 m3) is determined by subtraction (492 m3 -

54 m3). For the bathtub scenario, the bathroom volume was set at 9 m3for consistency with 

that reported in CDC (2012). 

The air exchange rate (ACH) values for the ROH 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; Riley et al., 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 56 of 279

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 ROH as a central-tendency assumption or in the room of use as an upper-end 

assumption. However, residential bystanders are located in the ROH. 

Riley et al. (2001) supports the reasonableness of placing the user in the ROH 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. Riley et 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.

3.2.4 MCCEM Modeling Scenarios 

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 57 of 279

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.

3.2.4.1 Sensitivity Analysis 

The sensitivity analysis was conducted using an approach that has been termed a “nominal 

range sensitivity analysis” (Frey and 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 × 30 ft, two-story house with 8-ft ceiling);

 Workshop (area of product use) volume of 54 m3(corresponds to a 20 ft × 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 ROH, 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 ROH 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 58 of 279

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

Figure 3-2. Example of Time-Varying Residential Bystander Exposure Concentration and 

Maximum TWA Values for Selected Averaging Times

0

50

100

150

200

250

300

350

400

450

500

550

600

650

700

750

800

850

900

950

0 1 2 3 4 5 6 7 8

Concentration, mg/m3

Time, hours

User Exposure Concentration

10-min max

30-min max

1-hr max

4-hr max

0

50

100

150

200

0 1 2 3 4 5 6 7 8

Concentration, mg/m3

Time, hours

Non-user Exposure Concentration

10-min max

30-min max

1-hr max

4-hr max
Page 59 of 279

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 ROH) irrespective 

of whether the user is exposed to DCM for 1- and 24-hrs. 

 The model response is somewhat sensitive to the ROH air exchange rate with outdoor air

(ROH 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 ROH 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

Notes:

Chem Mass= Chemical mass

ROH ACH= Rest of the house air exchange rate

Non-user= Residential bystander

% change from base case response
Page 60 of 279

Figure 3-4. Model Sensitivity Results: Percent Change from Base-case Response for 24-hr 

TWA for User and Residential Bystander

Notes:

Chem Mass= Chemical mass

ROH 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.

% change from base case response
Page 61 of 279

Table 3-5. Consumer Exposure Scenarios for the DCM Inhalation Exposure Assessment

Scenario ID

Scenario Description

Type of Application Location of Product Use Concentration

Characterizationa

1 Brush-on Workshop Central tendency

2 Brush-on Workshop User Upper-end

3 Brush-on Workshop User and Bystander upper-end

4 Spray-on Workshop Central tendency

5 Spray-on Workshop User Upper-end

6 Spray-on Workshop User and Bystander Upper-end

7 Brush-on Bathroom 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 (ROH) air exchange rate with outdoor air.

Table 3-6. Summary of DCM Consumer Paint Stripping Scenario Descriptions and Parameters

Scenario 

ID

Conc. 

Characterization

DCM Released

Stripping Method

Room of Use House User 

Location 

During 

Wait 

Period b

Bystander 

Location

Weight 

Fraction

Surface 

Area 

Treated a, 

ft2

Application 

Rate, g/ft2

Release 

Fraction

Volume, 

m3

Ventilation/ACH, 

1/hr

Volume, 

m3

ROH 

ACH, hr-1

Brush-on Exposure Scenarios in Workshop

1 Central 0.53

(central)

10

coffee 

table

(central)

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)

ROH

ROH 

(entire 

time)

2

Upper-end 

for user c

0.88

(upperend)

Workshop

3

Upper-end 

for user 

and 

bystander c

25

chest of 

drawers

(upperend)

0.18

(lowend)ROH
Page 62 of 279

Table 3-6. Summary of DCM Consumer Paint Stripping Scenario Descriptions and Parameters

Scenario 

ID

Conc. 

Characterization

DCM Released

Stripping Method

Room of Use House User 

Location 

During 

Wait 

Period b

Bystander 

Location

Weight 

Fraction

Surface

Area 

Treated a, 

ft2

Application 

Rate, g/ft2

Release 

Fraction

Volume, 

m3

Ventilation/ACH, 

1/hr

Volume, 

m3

ROH 

ACH, hr-1

Spray-on Exposure Scenarios in Workshop

4 Central 0.80

(central)

10

coffee 

table

(central)

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/ 

1.26

(professional 

judgment, 90th 

percentile)

492 

(central)

0.45

(central)

ROH

ROH 

(entire 

time)

5

Upper-end 

for user c

0.87

(upperend)

Workshop

6

Upper-end 

for user 

and 

bystander c

25

chest of 

drawers

(upperend)

0.18

(lowend)ROH
Page 63 of 279

Table 3-6. Summary of DCM Consumer Paint Stripping Scenario Descriptions and Parameters

Scenario 

ID

Conc. 

Characterization

DCM Released

Stripping Method

Room of Use House User 

Location 

During 

Wait 

Period b

Bystander 

Location

Weight 

Fraction

Surface 

Area 

Treated a, 

ft2

Application 

Rate, g/ft2

Release 

Fraction

Volume, 

m3

Ventilation/ACH, 

1/hr

Volume, 

m3

ROH 

ACH, hr-1

Brush-on Exposure Scenario in Bathroom

7

Simulation 

for 

bystander 

exposure

0.88

(upperend)

36

bathtub

(upperend)

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

(lowend) d

Window closed, 

no exhaust fan/ 

0.18 e

(low-end)

492 

(central)

0.18

(lowend)

ROH ROH 

(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 upperend surface area of 25 ft2

).

b For all scenarios, the user is in the treatment room during the application and scraping times and in ROH 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 m3for 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 64 of 279

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 

(ROH) 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 ROH 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 “upperend” exposure estimate is above central tendency and may include the high end of the exposure distribution.
Page 65 of 279

3.2.5 Consumer Model Results

Table 3-7 provides the scenario-specific DCM air concentrations for the consumer user of DCMcontaining 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 oneminute 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 66 of 279

Table 3-7. Modeled DCM Air Concentrations to Which Consumer Users and Residential Bystanders are Exposed

Scenario Individuala

Maximum Values for Averaging Period, mg/m3(ppm)

1 Minute 10 

Minutes

30 

Minutes 1 Hour 4 Hours 8 Hours 24 Hours

1. Brush application in workshop, 

central parameter estimates

User 630 (180) 380 (110) 270 (78) 220 (64) 120 (35) 69 (20) 23 (6.7)

Bystander 130 (38) 130 (38) 130 (37) 120 (36) 82 (24) 49 (14) 17 (4.8)

2. Brush application in workshop, 

upper-end user estimates b

User 1,300 

(370)

1,300 

(360)

1,100 

(330)

1,100 

(300)

420 (120) 220 (64) 75 (22)

Bystander 220 (63) 220 (63) 220 (62) 210 (59) 140 (39) 82 (24) 28 (8.0)

3. Brush application in workshop, 

upper-end user and bystander 

estimates b

User 1,800 

(520)

1,200 

(340)

900 (260) 760 (220) 560 (160) 400 (120) 160 (45)

Bystander 470 (140) 470 (140) 470 (140) 460 (130) 380 (110) 290 (83) 120 (34)

4. Spray application in workshop, 

central parameter estimates

User 1,500 

(430)

780 (220) 600 (170) 490 (140) 270 (77) 150 (44) 52 (15)

Bystander 300 (87) 300 (87) 300 (86) 280 (82) 190 (54) 110 (32) 38 (11)

5. Spray application in workshop, 

upper-end user estimates b

User 2,000 

(570)

1,900 

(550)

1,800 

(510)

1,600 

(460)

620 (180) 330 (96) 110 (32)

Bystander 330 (95) 330 (95) 320 (93) 310 (89) 200 (59) 120 (35) 42 (12)

6. Spray application in workshop, 

upper-end user and bystander 

estimates b

User 2,800 

(810)

1,600 

(470)

1,300 

(360)

1,100 

(320)

810 (230) 580 (170) 230 (66)

Bystander 710 (210) 710 (210) 710 (200) 700 (200) 580 (170) 430 (120) 180 (51)

7. Brush application in bathroom, 

simulation

User 2,428 

(699)

1,455 

(419)

887 (255) 799 (230) 536 (154) 340 (98) 135 (39)

Bystander 224 (64) 224 (64) 222 (64) 218 (63) 187 (54) 150 (43) 70 (20)

Notes:

a The bystander was assumed to be in Rest-of-House (ROH).

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 67 of 279

3.3 HAZARD/DOSE-RESPONSE 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 68 of 279

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 I-1), AEGL (section I-2), SMAC (section I-3) and the 

California acute REL (section I-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 μg/m3 in air (EPA, 

2011c). There is high confidence in the IUR because it was based on the best available doseresponse 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 (BMDL10 = 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 69 of 279

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 of once-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. 

3.3.1.2.2 Non-Cancer Effects Following Chronic Exposure to DCM

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 1

st percentile of the distribution of human equivalent 

concentrations (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 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 1

st 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 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 noncancer 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 70 of 279

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 (UFH) 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) ÷ (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 71 of 279

Table 3-8. Cancer and Non-Cancer Hazard Values Used in the Risk Evaluation of Chronic Exposures to Workers Using DCMBased Paint Strippers

Effects 

Category

Target 

Organ/ 

System

Species

Route of 

Exposure and 

Exposure

Concentrations1

Duration POD Type Effect

Uncertainty

Factors (UFs) 

for 

Benchmark 

MOE2

Hazard Value 

Used in 

Chronic Risk 

Assessment

Additional 

Information3

Reference

CANCER

Liver

and 

lung

Mouse

(male)

Inhalation

0 ppm, 

2,000 ppm,

4,000 ppm

6 hrs/day, 

5 days/week 

for 2 years, 

beginning at 

7-8 weeks of 

age

Male liver tumors:

Mouse internal BMD10 and 

BMDL10 = 913.9 and 

544.4 mg DCM metabolized 

via GST pathway/liter 

tissue/day, respectively

Male lung tumors:

Mouse internal BMD10 and 

BMDL10 = 61.7 and 48.6 mg 

DCM metabolized via GST 

pathway/liter tissue/day, 

respectively

Liver

and 

lung 

tumors

Not 

applicable

Inhalation 

Unit Risk

(IUR):

4 x 10-5 per 

ppm

(1 x 10-5 per 

mg/m3)

Internal dose 

BMDL10 values 

for each type of 

tumor were 

converted into 

an IUR that 

combined both 

types of 

tumors.

Mennear 

et al. 

(1988)

NTP 

(1986)

NON-CANCER

Liver Rat

(female)

Inhalation

0 ppm, 

50 ppm, 

200 ppm, 

500 ppm

6 hrs/day, 

5 days/week 

for 2 years

Rat internal BMDL10 = 

531.82 mg DCM 

metabolized via 

cytochrome P450 (CYP) 

pathway/liter liver 

tissue/day

Hepatic 

effects 

(vacuol

ation)

UFA= 3;

UFH=3; 

Total UF=10

1

st percentile 

human 

equivalent 

concentratio

n (HEC) i.e. 

the HEC99: 

17.2 mg/m3

(4.8 ppm)

Allometric 

scaling and 

probabilistic 

modeling were 

used to 

calculate the 

hazard value 

(i.e., HEC99) 

from the rat 

internal 

BMDL10.

Nitschke 

et al. 

(1988a)

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) ÷ (Human Exposure). The benchmark MOE is used to interpret the MOEs and consists of the interspecies (UFA) and 

intraspecies (UFH) uncertainty factors. UF values were those used in the DCM IRIS assessment (EPA, 2011c). 

3

 for further information see Appendix J
Page 72 of 279

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 (SMACs)(NRC, 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 DCMcontaining 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-1-1-4).

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 concentrationtime 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 73 of 279

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 SMAC’s 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; Putz et al., 1979; Ratney et al., 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 

(CO2). 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 et al., 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 

et al., 1973; Aronow et al., 1972; Kleinman et al., 1989; Kleinman et al., 1998; Sheps et al., 

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 74 of 279

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 (Putz et al., 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 75 of 279

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 76 of 279

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

Target 

Organ/ 

System

Species

Route of 

Exposure

and 

Exposure 

Concentrations1

Duration POD Type Effect

Hazard Value 

Used in Acute 

Risk 

Assessment

Uncertainty

Factors (UFs) 

for 

Benchmark 

MOE 2,3

Additional 

Information Reference

SMAC

Central 

Nervous 

System

Human

Inhalation

COHb data 

from 

several 

sources

1 hr

NOAEL = 100 ppm 

(350 mg/m3)

supported by 

various human 

studies

CNS depression 

related to 

formation of 3% 

COHb in blood

100 ppm

(350 mg/m3)

UFs were not 

applied to the 

1-hr SMAC. 

However, 

EPA/OPPT 

applied a

UFH=10 in the 

acute risk 

assessment 

to account 

for human 

variability.

NOAELs for CNS 

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)

NRC 

(1996, 

2008)

California 

Acute REL

Central 

Nervous 

System

Human

Inhalation

195 ppm

(696 

mg/m3)

90 min 

(1.5 hrs)

LOAEL = 195 ppm 

(696 mg/m3) at 90 

minutes (Putz et al., 

1979) or 240 ppm 

(840 mg/m3) when 

time adjusted to a 

60-min exposure

Impaired 

performance on 

dual-task and 

auditory 

vigilance tests in 

humans

1-hr REL POD=

240 ppm

(840 mg/m3)

8-hr REL POD=

80 ppm

(290 mg/m3)

UFH=10; 

UFL=6;

Total UF=60

ten Berge equation 

(Cnxt = k, n = 2) was 

used for time 

adjustment from 90 

to 60 min or 480 min 

(8 hrs).

OEHHA 

(2008)

AEGL-1 

(threshold 

for 

discomfort/ 

nondisabling 

effects)

Central 

Nervous 

System

(Direct 

effect in 

brain)

Human

Inhalation

213 to 

986 ppm

60 -

120 min

(1-2 hrs)

No observed effect 

for slight CNS 

effects at 1-hr 

exposure to 514 

ppm (1,840 mg/m3) 

equivalent to a 

brain concentration 

of 0.063 mM.

No effect level 

for lightheadedness, 

difficulties in 

enunciation

10-min = 

870 ppm 

(3,000 mg/m3)

4

UFH = 3

Total UF = 3

PBPK model was 

used. Time scaling 

was based on 

maximum DCM 

concentration in 

human brain. AEGL 

PODs for 4-and 8-hr 

were not calculated 

since they would be 

above the 

corresponding AEGL2 values.

NAC 

(2008)

30-min = 

690 ppm 

(2,400 mg/m3)

4

1-hr = 

600 ppm

(2,130 mg/m3)

4
Page 77 of 279

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

Target 

Organ/ 

System

Species

Route of 

Exposure

and 

Exposure 

Concentrations1

Duration POD Type Effect

Hazard Value 

Used in Acute 

Risk 

Assessment

Uncertainty

Factors (UFs) 

for 

Benchmark 

MOE 2,3

Additional 

Information Reference

AEGL-2

(threshold 

for 

disability) 5

Central 

Nervous 

System

(Direct 

effect in 

brain or 

COHb 

formation 

in blood)

Human

Inhalation

CNS 

effects:

195 to 

751 ppm

COHb 

formation:

0, 117 or 

253 ppm

(0, 420, or 

900 

mg/m3)

CNS 

effects:

Up to 

230 min 

(3.8 hr)

COHb 

formation

50-70 

min

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

CNS effects:

Absence of CNS 

effects in 

humans

COHb formation:

COHb formation

in patients with 

coronary artery 

disease

10-min= 1,700 

ppm (6,000 

mg/m3)

6

30-min= 1,200 

ppm (4,200 

mg/m3)

6

1-hr= 560 

ppm (2,000 

mg/m3)

7

4-hr= 100 

ppm 

(350 mg/m3)

7

8-hr= 60 ppm 

(210 mg/m3)

7

UFH = 1

Total UF = 1

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)

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) ÷ (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 78 of 279

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.

3.3.2.1 Absorption, Distribution, Metabolism and Excretion

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 al., 

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 CO2, 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). 
Page 79 of 279

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 
Page 80 of 279

immunosuppressive effect in the lung resulting from inhalation DCM exposure was seen in CD-1 

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 noncancer 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 B6C3F1 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 B6C3F1 mice 

at 2,000 ppm, testicular atrophy in B6C3F1 mice at 4,000 ppm, and ovarian atrophy in B6C3F1

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)
Page 81 of 279

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; 

Heineman et al., 1994; Tomenson, 2011), liver cancer (Lanes et al., 1990; Lanes et al., 1993), 

non-Hodgkin lymphoma (Barry et al., 2011; Miligi et al., 2006; Seidler et al., 2007; Wang et al., 

2009), and multiple myeloma (Gold et al., 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 cancerassessment, 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).
Page 82 of 279

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 GST theta-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.
Page 83 of 279

Table 3-10. Summary of Inhalation Hazard Information Used in the Risk Evaluation of Acute 

and Chronic Scenarios

Exposure 

Duration 

for Risk 

Analysis

Hazard Value Used in Risk Assessment Effect

Total 

Uncertainty

Factor (UF) for 

Benchmark 

MOE

CHRONIC

EXPOSURE

Inhalation Unit Risk (IUR):

4 x 10-5 per ppm

(1 x 10-5 per mg/m3)

Liver and lung 

tumors

Not applicable

1

st percentile human equivalent concentration (HEC) i.e. the HEC99:

17.2 mg/m3

(4.8 ppm)

Liver effects Total UF=10

ACUTE 

EXPOSURE

1-hr SMAC POD= 100 ppm

(350 mg/m3)

Central nervous 

system (CNS)

depression related 

to the formation of 

3% COHb in blood

Total UF=10

1-hr California REL POD= 240 ppm

(840 mg/m3)

8-hr California REL POD=80 ppm

(290 mg/m3) (for occupational scenarios)

Impairment of the 

CNS

Total UF=60

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)

1-hr= 600 ppm (2,130 mg/m3)

CNS effects

(light headedness, 

difficulty in 

enunciation)

Total UF=3

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

1-hr= 560 ppm (2,000 mg/m3)

7

4-hr= 100 ppm (350 mg/m3)

7

8-hr= 60 ppm (210 mg/m3)

7

CNS effects for 10-

and 30-min AEGL-2 

PODs

COHb formation for 

1-, 4- and 8-hr 

AEGL-2 PODs

Total UF=1
Page 84 of 279

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-ofevidence analysis for the cancer endpoint was sufficient to conclude that DCM-induced tumor 

development operates through a mutagenic mode of action (EPA, 2011c).
Page 85 of 279

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.

Health Effects of Concern, 

Concentration and Time 

Duration

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

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

UF for SMAC PODs= 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 DCMbased 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. 
Page 86 of 279

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):

1

st 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

(1 x 10-5 per mg/m3)

Uncertainty Factors (UF) 

used in Non-Cancer 

Margin of Exposure (MOE) 

calculations

UF for the HEC99 = 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 DCMbased 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.
Page 87 of 279

Acute or chronic MOEs (MOEacute or MOEchronic) were used in this assessment to estimate noncancer 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., interindividual 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 × 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)
Page 88 of 279

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. sprayon 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 
Page 89 of 279

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 Individual

Maximum 

Value for

1-hr 

Averaging 

Period

(mg/m3)

Margin of Exposure (MOE)

1-hr SMAC POD

Total UF or 

Benchmark 

MOE=10*Preferred 

Approach

1-hr California REL POD

Total UF or 

Benchmark MOE=60

Scenario #1

Brush application in 

workshop, 

central parameter values

User 220 1.6 3.8

Bystander 120 2.9 7.0

Scenario #2

Brush application in 

workshop, 

upper-end values for user

User 1,100 0.3 0.8

Bystander 210 1.7 4.0

Scenario #3

Brush application in 

workshop, upper-end 

values for user and 

bystander estimates

User 760 0.5 1.1

Bystander 460 0.8 1.8

Scenario #4

Spray application in 

workshop, central 

parameter values

User 490 0.7 1.7

Bystander 280 1.3 3.0

Scenario #5

Spray application in 

workshop, upper-end 

values for user

User 1,600 0.2 0.5

Bystander 310 1.1 2.7

Scenario #6

Spray application in 

workshop, upper-end 

values for user and 

bystander estimates

User 1,100 0.3 0.8

Bystander 700 0.5 1.2

Scenario #7

Brush application in 

bathroom, simulation

User 799 0.4 1.1

Bystander 218 1.6 3.9
Page 90 of 279

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 Individual

Maximum Values for Averaging 

Period, mg/m3

Margin of Exposure (MOE)

10-

min

30-

min 1-hr 4-hr 8-hr

AEGL-1 PODs

Total UF or Benchmark 

MOE =3

AEGL-2 PODs

Total UF or Benchmark MOE =1

10-min 

(3,000 

mg/m3)

30-min 

(2,400 

mg/m3)

1-hr 

(2,130 

mg/m3)

10-min 

(6,000 

mg/m3)

30-min 

(4,200 

mg/m3)

1-hr 

(2,000 

mg/m3)

4-hr 

(350 

mg/m3)

8-hr 

(210 

mg/m3)

Scenario #1:

Brush 

application in 

workshop, 

central 

parameter 

estimates

User 380 270 220 120 69 7.9 8.9 9.7 15.8 15.6 9.1 2.9 3.0

Bystander 130 130 120 82 49 23.1 18.5 17.8 46.2 32.3 16.7 4.3 4.3

Scenario #2:

Brush 

application in 

workshop, 

upper-end user 

estimates

User 1,300 1,100 1,100 420 220 2.3 2.2 1.9 4.6 3.8 1.8 0.8 1.0

Bystander 220 220 210 140 82 13.6 10.9 10.1 27.3 19.1 9.5 2.5 2.6

Scenario #3:

Brush 

application in 

workshop, 

upper-end user 

and bystander 

estimates

User 1,200 900 760 560 400 2.5 2.7 2.8 5.0 4.7 2.6 0.6 0.5

Bystander 470 470 460 380 290 6.4 5.1 4.6 12.8 8.9 4.3 0.9 0.7

Scenario #4:

Spray 

application in 

User 780 600 490 270 150 3.8 4.0 4.3 7.7 7.0 4.1 1.3 1.4
Page 91 of 279

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 Individual

Maximum Values for Averaging 

Period, mg/m3

Margin of Exposure (MOE)

10-

min

30-

min 1-hr 4-hr 8-hr

AEGL-1 PODs

Total UF or Benchmark 

MOE =3

AEGL-2 PODs

Total UF or Benchmark MOE =1

10-min 

(3,000 

mg/m3)

30-min 

(2,400 

mg/m3)

1-hr 

(2,130 

mg/m3)

10-min 

(6,000 

mg/m3)

30-min 

(4,200 

mg/m3)

1-hr 

(2,000 

mg/m3)

4-hr 

(350 

mg/m3)

8-hr 

(210 

mg/m3)

workshop, 

central 

parameter 

estimates

Bystander 300 300 280 190 110 10.0 8.0 7.6 20.0 14.0 7.1 1.8 1.9

Scenario #5:

Spray 

application in 

workshop, 

upper-end user 

estimates

User 1,900 1,800 1,600 620 330 1.6 1.3 1.3 3.2 2.3 1.3 0.6 0.6

Bystander 330 320 310 200 120 9.1 7.5 6.9 18.2 13.1 6.5 1.8 1.8

Scenario #6:

Spray 

application in 

workshop, 

upper-end user 

and bystander 

estimates

User 1,600 1,300 1,100 810 580 1.9 1.8 1.9 3.8 3.2 1.8 0.4 0.4

Bystander 710 710 700 580 430 4.2 3.4 3.0 8.5 5.9 2.9 0.6 0.5

Scenario #7:

Brush 

application in 

bathroom, 

simulation

User 1,455 887 799 536 340 2.1 2.7 2.7 4.1 4.7 2.5 0.7 0.6

Bystander 224 222 218 187 150 13.4 10.8 9.8 26.8 18.9 9.2 1.9 1.4
Page 92 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-containing 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 (nonspecific workplace settings when DCM air concentrations were as high as 7,000 mg/m3

.
Page 93 of 279

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

Acute 8-hr concentration (mg/m3)

Acute MOE (8hr-REL POD=290 mg/m3) 

Total UF or Benchmark MOE=60

Acute MOE (8hr-AEGL-2 POD=210 mg/m3) 

Total UF or Benchmark MOE=1

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 (No 

respirator, APF=0)

2,98

0

1,520 60 0.1 0.2 5 0.07 0.1 4

Scenario 2 

(Respirator, APF 10) 298 152 6 1 2 48 0.7 1.4 35

Scenario 3 

(Respirator, APF 25) 119 61 2 2 5 121 1.8 4 88

Scenario 4 

(Respirator, APF 50) 60 30 1 5 10 242 4 7 175

Automotive 

Refinishing

Acute 8-hr concentration (mg/m3)

Acute MOE (8hr-REL POD=290 mg/m3) 

Total UF or Benchmark MOE=60

Acute MOE (8hr-AEGL-2 POD=210 mg/m3) 

Total UF or Benchmark MOE=1

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 (No 

respirator, APF=0) 253 416 253 90 1 0.7 1 3 0.8 0.5 0.8 2

Scenario 2 

(Respirator, APF 10) 25 42 25.3 9 12 7 12 32 8 5 8 23

Scenario 3 

(Respirator, APF 25) 10 17 10 4 29 17 29 81 21 13 21 58

Scenario 4 

(Respirator, APF 50) 5 8 5 2 57 35 57 161 42 25 42 117

Furniture 

Refinishing

Acute 8-hr concentration (mg/m3)

Acute MOE (8hr-REL POD=290 mg/m3) 

Total UF or Benchmark MOE=60

Acute MOE (8hr-AEGL-2 POD=210 mg/m3) 

Total UF or Benchmark MOE=1

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 (No 

respirator, APF=0) 499 2,245

1,125 4 0.6 0.1 0.3 73 0.4 0.1 0.2 53

Scenario 2 

(Respirator, APF 10) 49.9 225 113 0.4 6 1.3 2.6 725 4 0.9 2 525

Scenario 3 

(Respirator, APF 25) 20 90 45 0.2 15 3 6 1813 11 2 5 1312

Scenario 4 

(Respirator, APF 50) 10 45 23 0.1 29 6 13 3625 21 5 9 2625
Page 94 of 279

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

Acute 8-hr concentration (mg/m3)

Acute MOE (8hr-REL POD=290 mg/m3) 

Total UF or Benchmark MOE=60

Acute MOE (8hr-AEGL-2 POD=210 mg/m3) 

Total UF or Benchmark MOE=1

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 (No 

respirator, APF=0) 2 145 105

Scenario 2 

(Respirator, APF 10) 0.2 1450 1050

Scenario 3 

(Respirator, APF 25) 0.1 3625 2625

Scenario 4 

(Respirator, APF 50) 0.04 7250 5250

Aircraft Paint 

Stripping

Acute 8-hr concentration (mg/m3)

Acute MOE (8hr-REL POD=290 mg/m3) 

Total UF or Benchmark MOE=60

Acute MOE (8hr-AEGL-2 POD=210 mg/m3) 

Total UF or Benchmark MOE=1

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 (No 

respirator, APF=0)

3,80

2

1,944 86 0.1 0.2 3 0.1 0.1 2

Scenario 2 

(Respirator, APF 10) 380 194 9 1 1.5 34 0.6 1 24

Scenario 3 

(Respirator, APF 25) 152 78 3 2 4 84 1 3 61

Scenario 4 

(Respirator, APF 50) 76 39 2 4 7 167 3 5 122

Graffitti 

Removal

Acute 8-hr concentration (mg/m3)

Acute MOE (8hr-REL POD=290 mg/m3) 

Total UF or Benchmark MOE=60

Acute MOE (8hr-AEGL-2 POD=210 mg/m3) 

Total UF or Benchmark MOE=1

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 (No 

respirator, APF=0) 260 1,188

603 18 1 0.2 0.5 16 0.8 0.2 0.4 12

Scenario 2 

(Respirator, APF 10) 26 118.8

60.3 1.8 11 2 5 161 8 2 3 117

Scenario 3 

(Respirator, APF 25) 10 48 24 0.7 28 6 12 403 20 4 9 292

Scenario 4 

(Respirator, APF 50) 5 24 12 0.4 56 12 24 806 40 9 17 583
Page 95 of 279

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

Acute 8-hr concentration (mg/m3)

Acute MOE (8hr-REL POD=290 mg/m3) 

Total UF or Benchmark MOE=60

Acute MOE (8hr-AEGL-2 POD=210 mg/m3) 

Total UF or Benchmark MOE=1

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 (No 

respirator, APF=0)

7,00

0

3,518 35 0.04 0.1 8 0.03 0.1 6

Scenario 2 

(Respirator, APF 10) 700 352 4 0.4 0.8 83 0.3 0.6 60

Scenario 3 

(Respirator, APF 25) 280 141 1 1 2 207 0.8 1.5 150

Scenario 4 

(Respirator, APF 50) 140 70 0.7 2 4 414 2 3 300

Non-Specific 

Workplace Settings 

- Immersion 

Stripping of Wood 

and Metal

Acute 8-hr concentration (mg/m3)

Acute MOE (8hr-REL POD=290 mg/m3) 

Total UF or Benchmark MOE=60

Acute MOE (8hr-AEGL-2 POD=210 mg/m3) 

Total UF or Benchmark MOE=1

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 (No 

respirator, APF=0)

1,01

7

825 633 0.3 0.4 0.5 0.2 0.3 0.3

Scenario 2 

(Respirator, APF 10)

101.

7

83 63 3 4 5 2 3 3

Scenario 3 

(Respirator, APF 25) 41 33 25 7 9 11 5 6 8

Scenario 4 

(Respirator, APF 50) 20 17 13 14 18 23 10 13 17

Non-Specific 

Workplace Settings 

- Unknown

Acute 8-hr concentration (mg/m3)

Acute MOE (8hr-REL POD=290 mg/m3) 

Total UF or Benchmark MOE=60

Acute MOE (8hr-AEGL-2 POD=210 mg/m3) 

Total UF or Benchmark MOE=1

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 (No 

respirator, APF=0) 357 428 357 285 0.8 0.7 0.8 1 0.6 0.5 0.6 0.7

Scenario 2 

(Respirator, APF 10) 36 43 36 29 8 7 8 10 6 5 6 7

Scenario 3

(Respirator, APF 25) 14 17 14 11 20 17 20 25 15 12 15 18

Scenario 4 

(Respirator, APF 50) 7 9 7 6 41 34 41 51 29 25 29 37
Page 96 of 279

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 Toxicological 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 1x10-4 and 1x10-6for 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. 1x10-6: the probability of 1 chance in 1 million of an individual developing cancer;

2. 1x10-5: the probability of 1 chance in 100,000 of an individual developing cancer, which 

is equivalent to 10 cancer cases in 1 million;

3. 1x10-4: 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 DCMbased 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 1x10-6target level.
Page 97 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) Lowest Exposure Highest Exposure

Professional

Contractors

LADC (mg/m3) 

** LADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Excess Cancer Risk 

(Inhalation Unit Risk =

1x10-5 per mg/m3)

High Midpoint Low High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

389 198 8 3.9E-03 2.0E-03 7.8E-05

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

16 8 0.31 1.6E-04 7.9E-05 3.1E-06

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

4 2 0.08 3.9E-05 2.0E-05 7.8E-07

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

2 1 0.04 1.9E-05 9.9E-06 3.9E-07
Page 98 of 279

Table 3-19. Occupational Cancer Risks for Automotive Refinishing (Scenarios 1, 3, 15 and 16) Lowest Exposure Highest Exposure

Automotive 

Refinishing

LADC (mg/m3) 

** LADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Excess Cancer Risk 

(Inhalation Unit Risk =

1x10-5 per mg/m3)

Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

33 54 33 12 3.3E-04 5.4E-04 3.3E-04 1.2E-04

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF

and WY)

1 2 1 0.48 1.3E-05 2.2E-05 1.3E-05 4.8E-06

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

0.3 1 0.33 0.12 3.3E-06 5.4E-06 3.3E-06 1.2E-06

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

0.2 0.3 0.2 0.1 1.7E-06 2.7E-06 1.7E-06 6.0E-07

Table 3-20. Occupational Cancer Risks for Furniture Refinishing (Scenarios 1, 3, 15 and 16) Lowest Exposure Highest Exposure

Furniture 

Refinishing

LADC (mg/m3) 

** LADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Excess Cancer Risk 

(Inhalation Unit Risk =

1x10-5 per mg/m3)

Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

65 293 147 0.5 6.5E-04 2.9E-03 1.5E-03 5.0E-06

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

3 12 6 0.02 2.6E-05 1.2E-04 5.9E-05 2.0E-07

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

1 3 1 0.01 6.5E-06 2.9E-05 1.5E-05 5.0E-08

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

0.3 1.5 0.7 0.003 3.3E-06 1.5E-05 7.4E-06 2.5E-08
Page 99 of 279

Table 3-21. Occupational Cancer Risks for Aircraft Stripping (Scenarios 1, 3, 15 and 16) Lowest Exposure Highest Exposure

Aircraft Paint 

Stripping

LADC (mg/m3) 

** LADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Excess Cancer Risk 

(Inhalation Unit Risk =

1x10-5 per mg/m3)

High Midpoint Low High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

496 254 11 5.0E-03 2.5E-03 1.1E-04

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF

and WY)

20 10 0.44 2.0E-04 1.0E-04 4.4E-06

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

5 3 0.11 5.0E-05 2.5E-05 1.1E-06

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

2 1 0.06 2.5E-05 1.3E-05 5.5E-07

Table 3-22. Occupational Cancer Risks for Graffiti Removal (Scenarios 1, 3, 15 and 16) Lowest Exposure Highest Exposure

Graffiti Removal

LADC (mg/m3) 

** LADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Excess Cancer Risk 

(Inhalation Unit Risk =

1x10-5 per mg/m3)

Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

34 155 79 2.3 3.4E-04 1.6E-03 7.9E-04 2.3E-05

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

1 6 3 0.092 1.4E-05 6.2E-05 3.2E-05 9.2E-07

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

0.340 2 1 0.023 3.4E-06 1.6E-05 7.9E-06 2.3E-07

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

0.2 0.8 0.4 0.012 1.7E-06 7.8E-06 4.0E-06 1.2E-07
Page 100 of 279

Table 3-23. Occupational Cancer Risks for Non-Specific Workplace Settings—Immersion 

Stripping of Wood (Scenarios 1, 3, 15 and 16)

Lowest Exposure Highest Exposure

Non-Specific 

Workplace 

Settings -

Immersion 

Stripping of Wood

LADC (mg/m3) 

** LADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Excess Cancer Risk 

(Inhalation Unit Risk =

1x10-5 per mg/m3)

High Midpoint Low High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

913 459 4.6 9.1E-03 4.6E-03 4.6E-05

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

37 18 0.184 3.7E-04 1.8E-04 1.8E-06

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

9 5 0.046 9.1E-05 4.6E-05 4.6E-07

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

5 2 0.023 4.6E-05 2.3E-05 2.3E-07
Page 101 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)

Lowest Exposure Highest Exposure

Non-Specific 

Workplace 

Settings -

Immersion 

Stripping of Wood 

and Metal

LADC (mg/m3) 

** LADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Excess Cancer Risk 

(Inhalation Unit Risk =

1x10-5 per mg/m3)

High Midpoint Low High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

133 108 83 1.3E-03 1.1E-03 8.3E-04

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

5 4 3 5.3E-05 4.3E-05 3.3E-05

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

1 1 1 1.3E-05 1.1E-05 8.3E-06

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

1 1 0.415 6.7E-06 5.4E-06 4.2E-06

Table 3-25. Occupational Cancer Risks for Non-Specific Workplace Settings—Unknown 

(Scenarios 1, 3, 15 and 16)

Lowest Exposure Highest Exposure

Non-Specific 

Workplace 

Settings -

Unknown

LADC (mg/m3) 

** LADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Excess Cancer Risk 

(Inhalation Unit Risk =

1x10-5 per mg/m3)

Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

47 56 47 37 4.7E-04 5.6E-04 4.7E-04 3.7E-04

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

2 2 2 1 1.9E-05 2.2E-05 1.9E-05 1.5E-05

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

0.5 1 0.5 0.4 4.7E-06 5.6E-06 4.7E-06 3.7E-06

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

0.2 0.3 0.2 0.2 2.4E-06 2.8E-06 2.4E-06 1.9E-06
Page 102 of 279

Table 3-26. Occupational Cancer Risks for Art Restoration and Conservation (Scenarios 1, 3, 15 

and 16)

Lowest Exposure Highest Exposure

Art Restoration 

and Conservation

LADC (mg/m3) 

** LADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Excess Cancer Risk 

(Inhalation Unit Risk =

1x10-5 per mg/m3)

Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years 

(WY)]

0.3 3.0E-06

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

0.012 1.2E-07

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

0.003 3.0E-08

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

0.0015 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 noncancer 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-
Page 103 of 279

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

ADC (mg/m3) 

** ADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Chronic MOE (24hr HEC99 =

17.2 mg/m3)

Total UF or Benchmark MOE=10

High Midpoint Low High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

680 347 14 0.025 0.050 1

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

27 14 1 1 1 31

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

7 3 0.1 3 5 123

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

3 2 0.1 5 10 246

Note: MOEs below benchmark MOE indicating risk are denoted in bold text.
Page 104 of 279

Table 3-28. Occupational Non-Cancer Risks for Automotive Refinishing Following Chronic 

Exposure to DCM (Scenarios 1, 3, 15 and 16)

Lowest Exposure Highest Exposure

Automotive 

Refinishing

ADC (mg/m3) 

** ADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Chronic MOE (24hr HEC99 =

17.2 mg/m3)

Total UF or Benchmark MOE=10

Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

58 95 58 21 0.3 0.2 0.3 0.8

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

2 4 2 1 7 5 7 20

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

1 1 1 0.2 30 18 30 82

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

0.3 0.5 0.3 0.1 59 36 59 164

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)

Lowest Exposure Highest Exposure

Furniture 

Refinishing

ADC (mg/m3) 

** ADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Chronic MOE (24hr HEC99 =

17.2 mg/m3) 

Total UF or Benchmark MOE=10

Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

114 513 257 0.9 0.2 0.03 0.1 19

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

5 21 10 0.04 4 0.8 2 478

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

1 5 3 0.01 15 3 7 1911

Scenario 16 

(Respirator APF 50,

midpoints of ranges for 

EF and WY)

0.6 3 1 0.005 30 7 13 3822
Page 105 of 279

Table 3-30. Occupational Non-Cancer Risks for Art Restoration and Conservation Following 

Chronic Exposure to DCM (Scenarios 1, 3, 15 and 16)

Lowest Exposure Highest Exposure

Art Restoration/ 

Conservation

ADC (mg/m3) 

** ADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Chronic MOE (24hr HEC99 =

17.2 mg/m3) 

Total UF or Benchmark MOE=10

Mean a Mean a

Scenario 1

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

0.5 34

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

0.02 860

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

0.005 3440

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

0.0025 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)

Lowest Exposure Highest Exposure

Aircraft Paint 

Stripping

ADC (mg/m3) 

** ADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Chronic MOE (24hr HEC99 =

17.2 mg/m3) 

Total UF or Benchmark MOE=10

High Midpoint Low High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

868 444 20 0.02 0.04 0.9

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

35 18 1 0.5 1 22

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

9 4 0.2 2 4 86

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

4 2 0.1 4 8 172
Page 106 of 279

Table 3-32. Occupational Non-Cancer Risks for Graffiti Removal Following Chronic Exposure to 

DCM (Scenarios 1, 3, 15 and 16)

Lowest Exposure Highest Exposure

Graffiti Removal

ADC (mg/m3) 

** ADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Chronic MOE (24hr HEC99 =

17.2 mg/m3) 

Total UF or Benchmark MOE=10

Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

59 271 138 4 0.3 0.1 0.1 4

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

2 11 6 0.2 7 2 3 105

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

1 3 1 0.04 29 6 12 420

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

0.3 1 0.7 0.02 58 13 25 839

Note: MOEs below benchmark MOE indicating risk are denoted in bold text.

Table 3-33. Occupational Non-Cancer Risks for Non-Specific Workplace Settings (Immersion 

Stripping of Wood) Following Chronic Exposure to DCM (Scenarios 1, 3, 15 and 16)

Lowest Exposure Highest Exposure

Non-Specific 

Workplace 

Settings -

Immersion 

Stripping of Wood

ADC (mg/m3) 

** ADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Chronic MOE (24hr HEC99 = 

17.2 mg/m3)

Total UF or Benchmark MOE=10

High Midpoint Low High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

1,598 803 8 0.01 0.02 2

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

64 32 0.3 0.3 0.5 54

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

16 8 0.08 1 2 215

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

8 4 0.04 2 4 430
Page 107 of 279

Table 3-34. Occupational Non-Cancer Risks for Non-Specific Workplace Settings (Immersion 

Stripping of Wood and Metal) Following Chronic Exposure to DCM (Scenarios 1, 3, 

15 and 16)

Lowest Exposure Highest Exposure

Non-Specific 

Workplace 

Settings -

Immersion 

Stripping of Wood 

and Metal

ADC (mg/m3) 

** ADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Chronic MOE (24hr HEC99 = 

17.2 mg/m3)

Total UF or Benchmark MOE=10

High Midpoint Low High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

232 188 145 0.07 0.1 0.1

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

9 8 6 2 2 3

Scenario 15 

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

2 2 1 7 9 12

Scenario 16 (Respirator 

APF 50, midpoints of 

ranges for EF and WY)

1 1 1 15 18 24

Note: MOEs below benchmark MOE indicating risk are denoted in bold text.

Table 3-35. Occupational Non-Cancer Risks for Non-Specific Workplace Settings (Unknown)

Following Chronic Exposure to DCM (Scenarios 1, 3, 15 and 16)

Lowest Exposure Highest Exposure

Non-Specific 

Workplace 

Settings -

Unknown

ADC (mg/m3) 

** ADCs for scenarios 2 to 16 have 

been adjusted with the multiplier

Chronic MOE (24hr HEC99 =

17.2 mg/m3)

Total UF or Benchmark MOE=10

Mean High Midpoint Low Mean High Midpoint Low

Scenario 1 

[No respirator, high 

ends of ranges for 

exposure frequency (EF) 

and working years (WY)]

81 98 81 65 0.21 0.18 0.21 0.27

Scenario 3 

(Respirator APF 25, high 

ends of ranges for EF 

and WY)

3 4 3 3 5 4 5 7

Scenario 15

(Respirator APF 25, 

midpoints of ranges for 

EF and WY)

1 1 1 0.65 21 18 21 26

Scenario 16 

(Respirator APF 50, 

midpoints of ranges for 

EF and WY)

0.41 0.49 0.41 0.33 42 35 42 53
Page 108 of 279

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 10-6to 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 109 of 279

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 110 of 279

3.5 DISCUSSION OF KEY SOURCES OF UNCERTAINTY AND DATA 

LIMITATIONS

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 (intra-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 111 of 279

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 DCMbased 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.

3.5.2 Uncertainties in the Consumer Exposure Estimates

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 112 of 279

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-1 – 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.
Page 113 of 279

3.5.3 Uncertainties in the Hazard and Dose-Response Assessments

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.
Page 114 of 279

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 GSTmetabolism 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 doseresponse 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 lowdose 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 crossspecies 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 115 of 279

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-timeresponse 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

(Burek et al., 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).
Page 116 of 279

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).

3.5.4 Uncertainties in the Risk Assessment

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 UFH accounts for the variation in sensitivity within the 

human population. In the absence of data, the default UFH of 10 is adopted which breaks 
Page 117 of 279

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 UFH 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 CNSdepressing effects do not vary by more than a factor of 2- to 3-fold in humans, a UFH 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 (UFL): The UFL accounts for the uncertainty in extrapolating 

from a LOAEL to a NOAEL. A value of 10 is the standard default UFL 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 UFL 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 118 of 279

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).
Page 119 of 279

3.6 CONCLUSIONS OF THE HUMAN HEALTH RISK ASSESSMENT

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, 

10-5 and 10-6.

 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 120 of 279

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 121 of 279

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Page 144 of 279

APPENDICES

Appendix A REGULATORY HISTORY OF DCM IN THE U.S. AND 

ABROAD

A-1 DCM Regulatory History in the U.S.

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-toKnow 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). 
Page 145 of 279

DCM is listed as an informational initial candidate chemical under California’s Safer Consumer 

Products regulations (DTSC, 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)”
Page 146 of 279

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-1 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 LC50 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 LC50 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 LC50 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 LC50 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 LC50 of 502 

mg/L was reported (Dill et al., 1987).

Sheepshead minnows (Cyprinodon variegates) were exposed to unspecified nominal 

concentrations of DCM under static conditions for 96 hrs. A 96-hr LC50 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 LC50 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 LC50 of 220 mg/L was reported (Buccafusco et 

al., 1981).
Page 147 of 279

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-observedeffect concentration (LOEC) ranged between 82.5 and 142 mg/L and a maximum acceptable 

toxicant concentration (MATC) of 108 mg/L was reported (Dill et al., 1987).

B-3 Acute Toxicity to Aquatic Invertebrates

Water fleas (Daphnia magna) were exposed to unspecified nominal concentrations of DCM 

under static conditions for 48 hrs. A 48-hr EC50 of 1,682 mg/L was reported (Kühn et al., 1989).

Water fleas (D. magna) were exposed to unspecified nominal concentrations of DCM under 

static conditions for 48 hrs. A 48-hr EC50 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 EC50 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 EC50 of 256 mg/L was reported (SRC, 1978).

B-4 Toxicity to Aquatic Plants

Green algae (Pseudokirchneriella subcapitata) were exposed to unspecified nominal 

concentrations of DCM under static conditions for 96 hrs. A 96-hr EC50 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 EC50 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 EC50 of 1,000 mg/L was reported (Merlin et al., 

1992).
Page 148 of 279

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-1 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) 261.5 million pounds

Maximum Concentration (at manufacture or import site) >90%

Physical form(s) Liquid

Number of reasonably likely to be exposed industrial manufacturing, 

processing, and use workers (aggregated)

>1,000

Was industrial processing or use information reported? Yes

Was commercial or consumer use information reported? Yes

Table C-2. Summary of Industrial DCM Uses from 2012 CDR

Industrial Sector

(Based on NAICS) Industrial Function Type of Processing

Adhesive Manufacturing Solvents (for cleaning or 

degreasing) Use-non-incorporative activities

Adhesive Manufacturing Not Known or Reasonably 

Ascertainable

Processing-incorporation into 

formulation, mixture, or 

reaction product

All Other Basic Organic 

Chemical Manufacturing

Solvents (for cleaning or 

degreasing)

Processing-incorporation into 

formulation, mixture, or 

reaction product

All Other Basic Organic 

Chemical Manufacturing

Processing aids, not otherwise 

listed Use-non-incorporative activities

All Other Basic Organic 

Chemical Manufacturing

Solvents (for cleaning or 

degreasing)

Processing-incorporation into 

formulation, mixture, or 

reaction product

All Other Basic Organic 

Chemical Manufacturing

Processing aids, specific to 

petroleum production Use-non-incorporative activities

All Other Chemical Product 

and Preparation 

Manufacturing

Propellants and blowing agents

Processing-incorporation into 

formulation, mixture, or 

reaction product

Table B-2. Sum
Page 149 of 279

Table C-2. Summary of Industrial DCM Uses from 2012 CDR

Industrial Sector

(Based on NAICS) Industrial Function Type of Processing

All Other Chemical Product 

and Preparation 

Manufacturing

Solvents (for cleaning or 

degreasing) Use-non-incorporative activities

All Other Chemical Product 

and Preparation 

Manufacturing

Adhesives and sealant chemicals

Processing-incorporation into 

formulation, mixture, or 

reaction product

All Other Chemical Product 

and Preparation 

Manufacturing

Solvents (which become part of 

product formulation or mixture)

Processing-incorporation into 

formulation, mixture, or 

reaction product

Paint and Coating 

Manufacturing

Solvents (which become part of 

product formulation or mixture)

Processing-incorporation into 

formulation, mixture, or 

reaction product

Pesticide, Fertilizer, and 

Other Agricultural Chemical 

Manufacturing

Processing aids, not otherwise 

listed Use-non-incorporative activities

Pesticide, Fertilizer, and 

Other Agricultural Chemical 

Manufacturing

Processing aids, specific to 

petroleum production Use-non-incorporative activities

Petrochemical Manufacturing Processing aids, not otherwise 

listed

Processing-incorporation into 

formulation, mixture, or 

reaction product

Plastics Material and Resin 

Manufacturing

Processing aids, not otherwise 

listed

Use-non-incorporative activities

Plastics Material and Resin 

Manufacturing

Processing aids, specific to 

petroleum production Use-non-incorporative activities

Abbreviations: NAICS=North American Industry Classification System

Table C-3. DCM Commercial/Consumer Use Category Summary

Commercial/Consumer 

Product Category

Intended for Commercial 

and/or Consumer Uses or 

Both

Intended for Use in 

Children's Products in 

Related Product Category

Adhesives and Sealants Both Not Known or Reasonably 

Ascertainable

Automotive Care Products Both No

Metal Products not 

covered elsewhere Commercial No

Paints and Coatings Both No
Page 150 of 279

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-1 lists the household products containing DCM in their 

formulations.

Table D-1. Household Products Containing DCM from NIH’s Household Products Database

Product Brand Category Form

% DCM

Content by 

Weight

(as of June 

2014)

a

Jasco Brushable Semi-Paste Premium Paint & 

Epoxy Remover

Arts and crafts Liquid 60-100

Savogran Liquid Kutzit-08/31/2007 Arts and crafts Liquid 20-25

Carb Medic Carburetor Choke and Valve Cleaner08/01/2002-old productAuto products Liquid 60-70

Sprayway Industrial Gasket Remover No. 719 Auto products Aerosol 70-80

Gunk Carb Medic Carburetor and Choke Cleaner04/07/2010Auto products Aerosol 15-40

Carb Medic Carb/Choke/Valve Cleaner-old 

product

Auto products Aerosol 40-50

Gumout Professional Non Flammable Brake Parts 

Cleaner

Auto products Aerosol 5-30

Espree Tire Shine Auto products Aerosol 50

Lectra Motive Auto Care-old product Auto products Aerosol 1-20

Anti-Seize Lubricant-old product Auto products Aerosol 60-65

Carb Medic Carburetor Choke and Valve Cleanerold productAuto products Liquid 40-50

Champion Sprayon Degreasing Solvent Auto products Aerosol 70-75

ProsALL Prosolv Auto products Aerosol 70-75

Zinsser Brush & Roller Wash Home maintenance Liquid

Crown Handi-Strip All Purpose Liquid Stripper Home maintenance Liquid 40-60

Crown Tuff-Strip Heavy Duty Semi-Paste Stripper Home maintenance Liquid 80-90

UGL ZAR Paint and Varnish Remover Home maintenance Liquid 90

Savogran Prepaint Deglosser Home maintenance Liquid 35-40

Savogran Water Rinsing Kwikeeze Home maintenance Liquid 5-10

Savogran Sprayable Strypeeze-08/22/2001 Home maintenance Aerosol 85-90

Klean-Strip Klean Kutter Home maintenance Liquid 25-30

Klean-Strip Metal & Masonry Paint Remover Home maintenance Liquid 75-85

Klean-Strip Premium Stripper, Aerosol Home maintenance Aerosol 70-95

Klean-Strip Deep Down Stain Stripper-old product Home maintenance Aerosol <60

Zinc It Electric Grade Lubricant Home maintenance Aerosol 32
Page 151 of 279

Table D-1. Household Products Containing DCM from NIH’s Household Products Database

Product Brand Category Form

% DCM

Content by 

Weight

(as of June 

2014)

a

Savogran Kutzit Paint & Varnish Remover-old 

product

Home maintenance Liquid >24

Champion Sprayon Paint Off Home maintenance Aerosol 80 – 85

Sprayway Vandalism Mark and Stain Remover No. 

870

Home maintenance Aerosol 43

Zinsser Adhesive Remover Home maintenance Liquid 71

Crown Solu-Strip Semi-Paste Adhesive Remover Home maintenance Liquid 80-90

Crown Handi-Strip All Purpose Sprayable Stripper, 

Aerosol

Home maintenance Aerosol 45-60

Savogran Adhesive Remover Home maintenance Liquid 85-90

Savogran Paint Stripper, Aerosol Home maintenance Aerosol 25-30

Savogran Heavy Duty SuperStrip Home maintenance Liquid 85-90

Klean-Strip Brush Cleaner Home maintenance Liquid 1-3

Klean-Strip KS-3 Premium Stripper Home maintenance Liquid 60-100

Klean-Strip Premium Sprayable Stripper Home maintenance Liquid 70-85

Klean-Strip Strip-X Stripper Home maintenance Liquid 30-50

Jasco Semi-Paste Varnish & Stain Remover Home maintenance Liquid 25-40

Klean-Strip Graffiti Remover-old product Home maintenance Aerosol 75-80

Savogran Strypeeze Paint/Varnish Remover-old 

product

Home maintenance Liquid >10

Parks Pro Liquid Paint Stripper-discontinued Home maintenance Liquid 40-90

Paint & Varnish Remover No. 2600, Aerosol Home maintenance Aerosol

Klean-Strip Adhesive Remover Inside the home Liquid 60-100

Aqua Mix Sealer and Adhesive Remover-old 

product

Inside the home Liquid

Parks Adhesive Remover-discontinued Inside the home Liquid 40-90

Radio Shack Rosin Flux Stripper Inside the home Liquid 39.83

Parks Adhesive Remover-09/04/1998-

discontinued

Inside the home Liquid 65-70

Monsanto Amplify Herbicide (agricultural) Pesticides Granules <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 Mix Sealer and Adhesive Remover-old product (Home maintenance)

5. Parks Adhesive Remover-09/04/1998-discontinued (Arts/crafts)
Page 152 of 279

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 × 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 (CO2)] GWP (Forster, 2007).

Table E-1 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 153 of 279

Table E- 1. Environmental Fate Characteristics of DCM1

Property Value

CASRN 79-09-2

Photodegradation Half-life 107 days (estimated)

Hydrolysis Half-life 18 months (measured)

Biodegradation 13 % in 28 days (not readily biodegradable)2

Bioconcentration Factor (BCF) 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

Log Koc 1.4 (estimated)3

Fugacity (Level III Model)3

Air (%)

Water (%)

Soil (%)

Sediment (%)

43.8

45.0

11.0

0.1

Persistence4 Moderate

Bioaccumulation4Low

Sources: 

1 OECD (2011) 2

 NITE (2002) 

3 EPA (2012b) 4 EPA (1999)

E-1 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 × 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 oC (Dilling 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 oC (Dilling 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). 
Page 154 of 279

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’s TSCA 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 et al., 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. 
Page 155 of 279

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-1 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-1.

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

238320 Painting and wall 

covering contractors

US Census reports an index entry of “Paint and wallpaper 

stripping” (USDOC, 2007b).

238330 Flooring contractors 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.

811121 Automotive body, paint, 

and interior repair and 

maintenance

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 

ESD (OECD, 2010).

811420 Reupholstery and 

furniture repair

US Census reports index entries of “Furniture refinishing 

shops” and “Restoration and repair of antique furniture”

(USDOC, 2007b).

711510 Independent artists, 

writers, and performers

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).

712110 Museums Research has shown art conservation to use paint strippers 

based on DCM or NMP (Wollbrinck, 1993).
Page 156 of 279

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 DCM- 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 157 of 279

(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 Graffiti Removal

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 (70oC) 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.
Page 158 of 279

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 paintremoving 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 
Page 159 of 279

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-1 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-1. 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
Page 160 of 279

 Source: CDHS/EPA (2006)

Source: HSE (2001)
Page 161 of 279

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 Aircraft Paint Stripping

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 Paint Stripping

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 Respiratory Protection

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 
Page 162 of 279

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

AREA SOURCE FACILITIES MAJOR SOURCE 

FACILITIES

TOTAL FACILITIES 

NATIONWIDE

Model Plant Type Assumed Model 

Plant Type

--

Model Plant Type 1 2 3 3 --

Workers per site (assumed) 2 7 20 20 --

Total number of sites a 1,470 780 750 10,500 13,500

Total number of workers b 2,940 5,460 15,000 210,000 233,400

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). 
Page 163 of 279

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.
Page 164 of 279

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 2007 NAICS Title 2007 Number of 

Establishments

2007 Average Number of 

Construction Workers

238320 Painting and wall covering 

contractors

35,619 174,276

238330 Flooring contractors 14,575 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.
Page 165 of 279

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. 
Page 166 of 279

Table F-5. 2007 U.S. Economic Census Data for Reupholstery and Furniture Repair

2007 NAICS 2007 NAICS Title 2007 Number of 

Establishments

2007 Number of Paid 

Employees

811420 Reupholstery and furniture 

repair

4,693 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 employees)(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).
Page 167 of 279

Table F-6. Estimated Annual DCM Based Stripper Usage in California a

Annual Stripper Usage (Gallons per Year) Number of Firms in California

1,200-2,000 6

700-1,200 30

200-700 40

5-200 172

<5 248

Total 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 2007 NAICS Title 2007 Number of 

Establishments

2007 Number of Paid 

Employees

711510 Independent Artists, 

Writers, and Performers

20,612 48,321

712110 Museums 4,664 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 DCMbased 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.
Page 168 of 279

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

Parameters Calculated from 

the Corresponding 2007 

Economic Census Data

2007 

NAICS 

Code

2007 

NAICS Title

Number of 

Establishments

Average 

Number of 

Production 

Workers

Production 

Workers 

Hours 

(1,000 hr)

Average 

Worker Days 

per Year 

(Assuming 

8 hr/day)

Average 

Worker Hrs 

per Day 

(Assuming 

250 days/year)

336411 Aircraft 

manufacturing

254 81,456 157,589 242 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). 
Page 169 of 279

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

Parameters Calculated from 

the Corresponding 2007 

Economic Census Data

2007 

NAICS 

Code

2007 

NAICS 

Title

Number of 

Establishments

Average 

Number of 

Production 

Workers

Production 

Workers 

Hours 

(1,000 hr)

Average 

Worker Days 

per Year 

(Assuming 

8 hr/day)

Average 

Worker Hrs per 

Day (Assuming 

250 days/year)

336611 Ship 

building 

and 

repairing

656 65,737 136,929 260 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.
Page 170 of 279

Appendix G OCCUPATIONAL EXPOSURE LITERATURE DATA 

AND EXPOSURE CALCULATIONS

G-1 Data Needs, Data Collection Strategy and Data Quality Criteria 

for the Occupational Exposure Analysis

G-1-1 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.
Page 171 of 279

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-1-2 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.”
Page 172 of 279

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.

G-1-3 Data Quality Criteria

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-1 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-3-6 for more information).
Page 173 of 279

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 industryspecific 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 174 of 279

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-1).

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 175 of 279

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 G3-10).

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-1.
Page 176 of 279

Table G-2. DCM 8-hr TWA Air Concentrations Used for Estimating Occupational Acute and Chronic Exposure Concentrations for NonCancer and Cancer Risks and Non-8 hr Air Concentration Data from the Literature

Industry / Activity 8-hr TWA (mg/m3

)

a

STEL, Peak, Short-Tasked Based, 

and Unknown (mg/m3)

b

Data Source

for 8-hr TWA 

and shortterm values

Number 

of 

Studies

Time 

Range of 

Studies

Number 

of Sites

Total Number of 

Measurements c Mean High Midpoint d

Low Mean High Midpoint Low

Professional 

Contractors 4 1981-2004 Unk >4 (8-hr TWA);

>38 (STEL/Other) -- 2,980 1,520 60 -- 14,100 7,050 0

g

EPA (1994a); 

EU (2007) EC 

(1999)

Bathtub 

Refinishing 1 Unk 1 2 -- -- -- -- -- 7,565 7,252 6,940 MSU/MIFACE (2011)

Automotive 

Refinishing 1 2003 1

2 (8-hr TWA);

3 (STEL/Other) 253 416 253 90 330 416 333 250 Enander et al. (2004)

Furniture 

Refinishing

7 1989-2007 >10 43 (8-hr TWA);

>63 (STEL/Other) 499

2,245

(1,266)

e

1,125 4.0 -- 6,992 3,506 19

Estill and 

Spencer 

(1996); 

Grevenkamp 

(2007); Hall 

et al. (1995); 

McCammon 

et al. (1991); 

NIOSH (1990, 

1991, 1993)

Art Restoration 

and Conservationf

1 2005 1 1 2.0 -- -- -- -- OSHA (2012a)

Aircraft Paint 

Stripping

5 1977-2006 >5 >35 (8-hr TWA);

130 (STEL/Other) -- 3,802 1,944 86 -- 5,400 2,719 38

EU (2007); 

IARC (2010); 

Vincent et al. 

(1994) EC 

(1999)

Ship Paint 

Stripping 1 1980 1 >=1 -- -- -- -- 215 -- -- -- IARC (2010)
Page 177 of 279

Table G-2. DCM 8-hr TWA Air Concentrations Used for Estimating Occupational Acute and Chronic Exposure Concentrations for NonCancer and Cancer Risks and Non-8 hr Air Concentration Data from the Literature

Industry / Activity 8-hr TWA (mg/m3

)

a

STEL, Peak, Short-Tasked Based, 

and Unknown (mg/m3)

b

Data Source

for 8-hr TWA 

and shortterm values

Number 

of 

Studies

Time 

Range of 

Studies

Number 

of Sites

Total Number of 

Measurements c Mean High Midpoint d

Low Mean High Midpoint Low

Graffiti Removal 1 1993 Unk

12 (8-hr TWA);

>=10 

(STEL/Other)

260 1,188 603 18 1,117 5,315 2,661 6.0 Anundi et al. 

(1993)

Non-Specific 

Workplace 

Settings -

Immersion 

Stripping of Wood

>1 1980-1994 >2 >4 -- 7,000 3,518 35 -- -- -- -- EC (1999)

Non-Specific 

Workplace 

Settings -

Immersion 

Stripping of Wood 

and Metal

1 1980 >=1 7 -- 1,017 825 633 -- -- -- -- IARC (2010)

Non-Specific 

Workplace 

Settings -

Immersion 

Stripping of Metal

>=1 Unk >=1 >=1 -- -- -- -- -- 350 -- -- EC (1999)

Non-Specific 

Workplace 

Settings –

Unknown >=6 1997-2004 >=6

2 (8-hr TWA);

>=227 

(STEL/Other)

357 428 357 285 -- 3,035 1,518 0.25 EU (2007)
Page 178 of 279

Table G-2. DCM 8-hr TWA Air Concentrations Used for Estimating Occupational Acute and Chronic Exposure Concentrations for NonCancer and Cancer Risks and Non-8 hr Air Concentration Data from the Literature

Industry / Activity 8-hr TWA (mg/m3

)

a

STEL, Peak, Short-Tasked Based, 

and Unknown (mg/m3)

b

Data Source

for 8-hr TWA 

and shortterm values

Number 

of 

Studies

Time 

Range of 

Studies

Number 

of Sites

Total Number of 

Measurements c Mean High Midpoint d

Low Mean High Midpoint Low

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.

g 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 179 of 279

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 Respirator APF a 8-hr TWA Acute Exposure Concentration Multiplier a

Scenario Description

1 0 1 No respirator, APF = 0

2 10 0.1 Respirator APF 10

3 25 0.04 Respirator APF 25

4 50 0.02 Respirator APF 50

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 (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 180 of 279

Table G-4. Chronic Occupational Exposure Scenarios for the Use of DCM-Based Paint 

Strippers

Chronic 

Scenario

Respirator 

APF

Exposure 

Frequency 

(EF) 

(days/yr)

Working 

Years (WY) 

(years)

ADC/LADC

Multiplier a

Scenario Description

1 0 250 40 1 No respirator, high ends of 

ranges for EF and WY

2 10 250 40 0.1 Respirator APF 10, high ends 

of ranges for EF and WY

3 25 250 40 0.04 Respirator APF 25, high ends 

of ranges for EF and WY

4 50 250 40 0.02 Respirator APF 50, high ends 

of ranges for EF and WY

5 / 9 0 250/ 125 20/ 40 0.5 No respirator, one midpoint

and one high end of range for 

EF and WY

6 / 10 10 250/ 125 20/ 40 0.05 Respirator APF 10, one 

midpoint and one high end of 

range for EF and WY

7 / 11 25 250/ 125 20/ 40 0.02 Respirator APF 25, one 

midpoint and one high end of 

range for EF and WY

8 / 12 50 250/ 125 20/ 40 0.01 Respirator APF 50, one 

midpoint and one high end of 

range for EF and WY

13 0 125 20 0.25 No respirator, midpoints of 

ranges for EF and WY

14 10 125 20 0.025 Respirator APF 10, midpoints 

of ranges for EF and WY

15 25 125 20 0.01 Respirator APF 25, midpoints 

of ranges for EF and WY

16 50 125 20 0.005 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 181 of 279

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-1 

was used to estimate the single (acute) exposure estimates for acute scenario 1 (EPA, 2009).

EC scenario 1 = C (Equation G-1)

where:

EC scenario 1 = 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/m3from Table G-2 or G-5).
Page 182 of 279

Equation G-2 was used to calculate the acute exposure estimates for scenarios 2 through 4.

EC scenario 2→ 4= EC 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;

EC scenario 1 = single (acute) exposure concentration for relevant industry (8-hr 

 TWA in mg/m3from 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 scenariospecific 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 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/m3reported 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).

EC scenario 1 =

C × ED × EF × WY

AT

 (Equation G-3)

where:

EC scenario 1 = exposure concentration (mg/m3) for Scenario 1 = ADC for chronic noncancer 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/m3from 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 183 of 279

AT = averaging time (years × 365 days/years × 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.

EC scenario 2→ 16 = EC 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 1 = chronic exposure concentration (ADC or LADC) for relevant 

 industry, chronic scenario 1 (in mg/m3from 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 184 of 279

Table G-5. DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers – Scenario 1- Highest Exposed 

Scenario Group

Industry / Activity Time Range 

of Studies

ACUTE EXPOSURE ESTIMATES

Single 8-hr Concentration (mg/m3)

a

CHRONIC EXPOSURE ESTIMATES

USED IN THE NON-CANCER RISK 

ESTIMATES [ADC (mg/m3)

b

]

CHRONIC EXPOSURE ESTIMATES

USED IN THE CANCER RISK 

ESTIMATES [LADC (mg/m3)

b

]

Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low

Professional 

Contractors 1981-2004 -- 2,980 1,520 60 -- 680 347 14 -- 389 198 7.8

Bathtub 

Refinishing -- -- -- -- -- -- -- -- -- -- -- --

Automotive 

Refinishing 2003 253 416 253 90 58 95 58 21 33 54 33 12

Furniture 

Refinishing 1989-2007 499 2,245

(1,266) c

1,125 4.0 114

513

(289)

c

257 0.9 65

293

(165)

c

147 0.5

Art Restoration 

and Conservation 2005 2.0 0.5 0.3

Aircraft Paint 

Stripping 1977-2006 -- 3,802 1,944 86 -- 868 444 20 -- 496 254 11

Ship Paint 

Stripping 1980 -- -- -- -- -- -- -- -- -- -- -- --

Graffiti Removal 1993 260 1,188 603 18 59 271 138 4.1 34 155 79 2.3

Non-Specific 

Workplace Settings 

- Immersion 

Stripping of Wood

1980-1994 -- 7,000 3,518 35 -- 1,598 803 8.0 -- 913 459 4.6

Non-Specific 

Workplace Settings 

- Immersion 

Stripping of Wood 

and Metal

1980 -- 1,017 825 633 -- 232 188 145 -- 133 108 83

Non-Specific 

Workplace Settings 

- Immersion 

Stripping of Metal

-- -- -- -- -- -- -- -- -- -- -- --
Page 185 of 279

Table G-5. DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers – Scenario 1- Highest Exposed 

Scenario Group

Non-Specific 

Workplace Settings 

– Unknown

1997-2004 357 428 357 285 81 98 81 65 47 56 47 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-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 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 186 of 279

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 Limit Type Exposure Limit

OSHA PEL 

(1997 and forward)

PEL (8-hr TWA) b 25 ppm c

STEL (15-minute TWA) 125 ppm

Action Level (8-hr TWA) 12.5 ppm

OSHA PEL 

(pre-1997)

PEL (8-hr TWA) 500 ppm

Ceiling 1,000 ppm

STEL (5-minute average in any 2-hr period) 2,000 ppm

NIOSH exposure limits IDLH d 2,300 ppm

REL e Ca

ACGIH TLV f 8-hr TWA 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 187 of 279

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 DCMbased 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).
Page 188 of 279

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 et al., 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).

G-3-2 Paint Stripping by Professional Contractors

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.
Page 189 of 279

“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 worstcase 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.
Page 190 of 279

 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 façade 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 worstcase 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).
Page 191 of 279

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-oftask 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 Graffiti Removal

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
Page 192 of 279

Table G-7. Summary of DCM Personal Concentrations during Graffiti Removal

Calculated 8-hr TWA 

Concentrations (mg/m3)

(values in parentheses are in ppm)b

15-min Sample Concentrations 

(mg/m3)

(values in parentheses are in ppm)b

Arithmetic Mean 260 (75) d 1,117 (322) e

Geometric Mean 127 (37) 400 (115)

High Value 1,188 (342) d 5,315 (1,532) e

Midpoint c 603 (174) d 2,661 (767) e

Low Value 18 (5.2) d 6 (1.7) e

Geometric 

Standard Deviation 3.6 (1.0) 5.6 (1.6)

Number of Workers 12 10

Notes:

a Source: Anundi et al. (1993)

b

 EPA/OPPT converted concentrations reported by the study authors in units of mg/m3to 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.
Page 193 of 279

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).

G-3-5 Wood Furniture Stripping

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 
Page 194 of 279

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).
Page 195 of 279

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 Area Samples

Activity

Concentration 

(mg/m3)

(values in parentheses 

are in ppm) b

Sampling 

Time 

(Minutes)

Location

Concentration 

(mg/m3)

(values in parentheses 

are in ppm) b

Sampling 

Time 

(Minutes)

Stripping large 

chest

1,437

(414) 78 Door at room entrance

576

(166) 102

Stripping 

headboard

1,815

(523) 101 Door at room entrance

579

(167) 78

Stripping 

wicker chairs

1,381

(398) 23

Edge of 

stripping booth 

above recycle 

can

854

(246) 59

Stripping large 

dresser and 

drawers

1,544

(445) 58

Above water 

reservoir 

between wash 

booth and 

outside wall

180

(52) 62

Stripping large 

dresser and 

drawers

1,364

(393) 30

Workbench 

south of wash 

booth

128

(37) 182

Hand strip 

table with 

Palco gel 

stripper

288

(83) 14 Above drum of bulk stripper

416

(120) 60

Hand strip 

table with gel

604

(174) 16 Above drum of bulk stripper

298

(86) 102

Notes:

a

 Source: NIOSH (1993)

b

 EPA/OPPT converted concentrations reported by the study authors in units of ppm to units of mg/m3.
Page 196 of 279

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 Area Samples

Activity

Concentration 

(mg/m3)

(values in 

parentheses 

are in ppm) b

Sampling 

Time 

(Minutes)

Location

Concentration 

(mg/m3)

(values in 

parentheses 

are in ppm) b

Sampling 

Time 

(Minutes)

Stripping six 

chairs

35

(10)

35

Center of room (before 

ventilation system turned 

on)

111

(32)

18

Stripping 

crib

330

(95)

33 Above newly stripped chairs 295

(85)

82

Strip large 

desk

382

(110)

103 South central part of room 

near newly stripped crib

87

(25)

42

Near newly stripped desk 

drawers

111

(32)

59

Edge of wash booth (near 

worker breathing zone)

416

(120)

33

Edge of wash booth (near 

worker breathing zone)

201

(58)

34

Edge of wash booth (near 

worker breathing zone)

205

(59)

101

On work bench behind wash 

booth

16

(4.6) 102

Above DCM waste buckets 52

(15)

215

Above wash sludge tank 22

(6.3)

57

Notes:

a

 Source: NIOSH (1993)

b

 EPA/OPPT converted concentrations reported by the study authors in units of ppm to units of mg/m3.
Page 197 of 279

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 Area Samples

Activity

Concentration 

(mg/m3)

(values in 

parentheses 

are in ppm) b

Sampling 

Time 

(Minutes)

Location

Concentration 

(mg/m3)

(values in 

parentheses 

are in ppm) b

Sampling 

Time 

(Minutes)

Stripping rocking 

chair

66

(19)

24 Center of room 7

(2.0) 30

Stripping seven 

chairs

312

(90)

52 Near entrance to 

room

19

(5.5) 102

Stripping chairs 125

(36)

97 Above door to 

entrance of room

14

(4.0) 84

Stripping large 

dresser

243

(70)

113 Above door to 

entrance of room

29

(8.4)

178

Stripping dresser 

drawers

382

(110)

61 Above stripping 

drum <14

(<4.0)

25

Above stripping 

drum

9

(2.6)

75

Above stripping 

drum

17

(4.9) 87

Above stripping 

drum NDc 182

Above wash sludge 

tank

17

(4.9) 92

Near drying chairs 38

(11)

113

Above dresser while 

drying

62

(18)

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
Page 198 of 279

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 coowners. 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). 
Page 199 of 279

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-11 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 et al., 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 pre1997 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).
Page 200 of 279

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 Systema

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

Day 1 5

35-274

(10-79) 407 6.78

125

(36)

Day 2 4

21-115

(6-33) 224 3.73

49

(14)

Day 3 3

90-239

(26-69) 227 3.78

160

(46)

WORKER B

Day 1 5

45-278

(13-80) 461 7.68

243

(70)

Day 2 6

45-323

(13-93) 549 9.15

160

(46)

Day 3 4

28-239

(8-69) 287 4.78

167

(48)

Notes:

a

 Source: Hall et al. (1995)

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 flowover 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 201 of 279

(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 solutionsoaked 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 G2). 
Page 202 of 279

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 Aircraft Paint Stripping

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 203 of 279

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 ppm)(EU, 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) 36 from 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-3-8 Ship Paint Stripping

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 Paint Stripping in Non-specific Workplace Settings

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 204 of 279

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 non8-hr TWA values for non-specific workplace settings (unknown) in Table G-2 (EU, 2007). 
Page 205 of 279

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).

G-3-10 Summary of OSHA IMIS Data

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, nondetect 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 206 of 279

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 207 of 279

Table G-12. Summary by Industry of OSHA IMIS Personal Monitoring Data for DCM from 1992 to 2012

Personal Measurements

Post-1997 PEL Update Pre-1997 PEL Update

TWA STEL TWA STEL

mg/m3 ppm mg/m3 ppm mg/m3 ppm mg/m3 ppm

Bathtub 

Refinishing

Max -- -- 0.0 0.0 -- -- -- --

90th Percentile -- -- N/A N/A -- -- -- --

Median -- -- N/A N/A -- -- -- --

Min -- -- 0.0 0.0 -- -- -- --

Mean -- -- N/A N/A -- -- -- --

Number of Data Points None 3 None None

Professional 

Contractors

Max 28.2 8.1 27.8 8.0 -- -- -- --

90th Percentile 23.2 6.7 13.8 4.0 -- -- -- --

Median 13.9 4 0.0 0.0 -- -- -- --

Min 0.0 0 0.0 0.0 -- -- -- --

Mean 12.8 3.7 5.1 1.5 -- -- -- --

Number of Data Points 5 7 None None

Aircraft 

Refinishing

Max 34.5 9.9 31.2 9.0 33.3 9.6 -- --

90th Percentile 32.4 9.3 29.5 8.5 28.1 8.1 -- --

Median 15.6 4.5 12.7 3.7 10.1 2.9 -- --

Min 0.0 0 0.0 0.0 0.0 0.0 -- --

Mean 17.8 5.1 15.2 4.4 13.3 3.8 -- --

Number of Data Points 15 6 21 None

Ship & Boat 

Refinishing

Max 33.7 9.7 10.4 3.0 27.8 8.0 -- --

90th Percentile 32.4 9.3 6.2 1.8 15.6 4.5 -- --

Median 6.1 1.8 0.0 0.0 5.7 1.6 -- --

Min 0.0 0.0 0.0 0.0 0.0 0.0 -- --

Mean 11.3 3.3 2.1 0.6 7.6 2.2 -- --

Number of Data Points 11 5 8 None
Page 208 of 279

Table G-12. Summary by Industry of OSHA IMIS Personal Monitoring Data for DCM from 1992 to 2012

Personal Measurements

Post-1997 PEL Update Pre-1997 PEL Update

TWA STEL TWA STEL

mg/m3 ppm mg/m3 ppm mg/m3 ppm mg/m3 ppm

Automotive 

Refinishing

Max 31.2 9.0 34.2 9.9 24.3 7.0 27.8 8.01

90th Percentile 28.9 8.3 27.8 8.0 20.1 5.8 N/A N/A

Median 4.7 1.4 10.3 3.0 12.3 3.6 N/A N/A

Min 0.0 0.0 0.0 0.0 1.1 0.3 6.9 2.0

Mean 10.0 2.9 13.3 3.8 11.1 3.2 17.4 5.0

Number of Data Points 10 11 5 2

Furniture 

Refinishing

Max 33.9 9.8 34.01 9.8 31.2 9 31.2 9.0

90th Percentile 28.9 8.3 24.64 7.1 30.2 8.7 N/A N/A

Median 10.6 3.1 13.01 3.8 17.2 5.0 N/A N/A

Min 0.0 0.0 0.0 0.0 3.5 1.0 0 0

Mean 13.3 3.8 12.91 3.7 18.8 5.4 15.6 4.5

Number of Data Points 78 70 12 2

Art 

Restoration 

and 

Conservation

Single Data Point 2.01 0.58 None None None

Source: OSHA (2012a)
Page 209 of 279

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-1 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. Nonprofessional 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 210 of 279

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 nonU.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-1-1-2, 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-1-1 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 sprayon 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 211 of 279

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:

MRi, i+1= (Ci+1 - Ci)*V + Q*(t)*(Ci+1 + Ci)/2) (Equation H-1)

 Where:

MRi, i+1=

C = 

V = 

Q = 

t = 

Mass Released over interval i to i+1, mg = the change in mass in the 

chamber plus the amount of mass removed through ventilation

concentration in the compartment, mg/m3

compartment volume, m3

compartment ventilation rate, m3/hr 

time interval from i 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

E0 = initial emission rate (the emission rate at t = 0), mg/hr

 k = first-order rate constant, hr-1

 t = time since application, hr

Integrating Equation H-2 to infinity gives the mass released according to the exponential, as 

follows:

Mass Released (mg) =

E0

k

(Equation H-3)

Or:

E0 = (Mass Released) ∗ k (Equation G-4)
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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

C(t) =

E0

V∗(

Q

V

−k)

( e

−kt − e

−

Q

V

t

) (Equation H-5)

Where:

 C(t)= concentration, mg/m3

V = chamber volume, m3

Q = air flow rate in and out of the chamber, m3/hr

Double-exponential representation

C(t) =

E01

V∗(

Q

V

−k1)

( e

−k1t − e

−

Q

V

t

) +

E02

V∗(

Q

V

−k2)

( e

−k2t − e

−

Q

V

t

) (Equation H-6)

Where:

E01 = initial emission rate for the first exponential, mg/hr

E02 = initial emission rate for the second exponential, mg/hr

k1 = first-order rate constant for the first exponential, hr-1

k2 = first-order rate constant for the second exponential, hr-1

H-1-1-1 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-1.

Table H-1. DCM-containing Products Used in the MRI Chamber Studies 

Product Application Type Chemical

BIX Spray-On Stripper Spray DCM

Strypeeze Brush 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 213 of 279

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 1/8th 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:

E0 = (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-1) 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-1, 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 214 of 279

Figure H-1. Model Fit to Data Extracted from MRI Chamber Study for BIX Spray-on Product

Figure H-2. Model Fit to Data Extracted from MRI Chamber Study Report for Strypeeze Brushon Product
Page 215 of 279

Table H-2. Fitted Parameters to MRI Study Results for Two DCM-Containing Paint Strippers

Product Experiment

Product 

Mass 

Applied, g

DCM 

Weight 

Fraction

DCM Mass 

Applied, g

DCM 

Theoretical 

Fraction 

Released a

First-Order 

Rate 

Constant, hr-1

BIX Spray-On 

Stripper Runs 4, 5, 6 540 0.85b 459.0 0.66 10.0

Strypeeze

(Brush-On) Run 7 724 0.168c 121.62 0.33 3.9

Notes:

a

 The theoretical DCM fraction released was estimated by integrating the fitted exponential.

b EPA (1996a)

c EPA (2003)

Source: EPA (1994a)

A numerical integration of the fitted “sum of 8 exponentials” shown in Figures H-1 and H-2 was 

performed by using the average concentration for each one-minute interval. Then a massbalance 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

111 minutes
Page 216 of 279

Figure H-4. Theoretical Cumulative Mass of DCM Released for Strypeeze Brush-on Stripper

H-1-1-2 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 Strypeeze

1988 MSDSa

Strypeeze 

2013 MSDSa

LBL (1986), 

Paint Remover (PR)-A

LBL (1986), 

PR-B

DCM >10% 25 - 30% 83.0% 86.6%

Toluene >35% 15 - 20%

Methanol 25% 25 - 30% Presentb Presentb

Acetone <25% 15 - 20%

Paraffin Wax <5% 0 - 5%

Aliphatic Hydrocarbon 0 - 5% --

Isopropanol 9.4%

Xylenes Presentb

Non-volatile 3.6% 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.

111 minutes
Page 217 of 279

The LBL and MRI studies used similar ventilation rates — ~3.0 hr-1 and 0.6 hr-1for LBL 

Experiments 2 and 5, respectively; and ~0.55 hr-1for 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/MRI test.

Table H-4. Comparison of DCM Mass Released for LBL and MRI Studies of Brush-on Products

Study and 

Expt/Runa

Chamber Duration, 

min

Applied Product 

Mass, mg

Applied DCM 

Mass, mg

% DCM 

Released Vol, m3 ACH, hr-1

LBL, Expt 2 20.0 3.23 89 363,000 314,358 83%

LBL, Expt 5 20.0 0.62 86 325,000 269,750 93%

MRI, Run 7 35.7 0.56 105 724,000 121,632 35%

MRI, Run 8 35.7 0.54 105 676,000 113,568 51%

MRI, Run 9 35.7 0.55 105 765,000 128,520 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 218 of 279

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 hr-1). 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

 

46

 Gas chromatography and electron capture detector (GC/ECD)
Page 219 of 279

Table H-5. Estimated DCM Released for Four Experiments by van Veen et al. (2002)

van Veen 

Experiment

Chamber Duration, 

min

Applied 

Product 

Mass, mg

Applied 

DCM Mass, 

mg

% DCM 

Vol, m Released 3 ACH, hr-1

1a 47.65 0.31 60 364,000 239,876 28%

1b 47.65 0.26 60 335,000 220,765 39%

3a 47.65 0.53 60 392,000 258,328 18%

3b 47.65 0.75 60 386,000 254,374 22%

The EC (2004) study was designed to assess health risks related to the use of defined vaporretarded, 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 m3room 

with a ventilation rate of 60 m3/hr (4 hr-1) for the standard-condition studies. The substrate was 

a 1.0-m2chipboard 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)
Page 220 of 279

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 hr-1). 

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-1 (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 221 of 279

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-1-1 (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-1-1-2, 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-1, 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-1 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 222 of 279

Table H-6. Summary of DCM Chamber Studies 

Study

Experiment Applied 

Product 

Mass, 

mg

DCM 

Weight 

Fraction

Applied 

DCM Mass, 

mg

Chamber DCM Mass 

Released at 

Duration

NLS Fit b

Theoretical

Title Mass Released a Duration, 

min

Volume, 

m3 ACH

van Veen et al. 

2002

1a 60 364,000 0.659 239,876 47.65 0.31 27.6% 25.5%

1b 60 335,000 0.659 220,765 47.65 0.26 39.0% 35.1%

3a 60 392,000 0.659 258,328 47.65 0.53 17.6% 14.9%

3b 60 386,000 0.659 254,374 47.65 0.75 21.8% 18.0%

LBL (1986)

Exp 2 89 363,000 0.866 314,358 20.0 3.23 83.3% 83.9%

Exp 5 86 325,000 0.830 269,750 20.0 0.62 92.9% 97.0%

MRI

(EPA, 1994a)

Run 7 105 724000 0.168 121,632 35.7 0.56 35.0% 34.4%

Run 8 105 676000 0.168 113,568 35.7 0.54 50.7% 50.4%

Run 9 105 765000 0.168 128,520 35.7 0.55 29.5% 24.6%

EC (2004) VP03 25 465500 0.825 c 384,038 15 4 13.9% 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-1-1. 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 223 of 279

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 1⁄2X 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 = 3⁄4 or 75 percent (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-X| / 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 triggerpump) 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 (EFH)(EPA, 2011a).

The EFH reported a median value of 32 fluid ounces or 1⁄4 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 224 of 279

Median product masses of 900 and 680 g were input into the model for the brush-on and sprayon 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/ft2 for a brush-on application of a DCMcontaining 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 realworld situations. A coffee table with nominal dimensions of 4 ft × 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 × 2.5 ft2 for front + 2.5 × 

1.5 ft2 for top + 2 × 4 × 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 ft2 should 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-ft2surface 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.com/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 225 of 279

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 226 of 279

Table H-7. Schedule for Brush-on Application to Chest Surface: Four Segments with 

Repeat Application

Segment/Application Elapsed Time from Time Zero, Minutes

Apply Wait Scrape

First 1/4, 1st time 0-2 2-17 17-21

Second 1/4, 1st time 21-23 23-38 38-42

Third 1/4, 1st time 42-44 44-59 59-63

Fourth 1/4, 1st time 63-65 65-80 80-84

First 1/4, 2nd time 84-86 86-101 101-105

Second 1/4, 2nd time 105-107 107-122 122-126

Third 1/4, 2nd time 126-128 128-143 143-147

Fourth 1/4, 2nd time 147-149 149-164 164-168

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-1). The resultant mass 

released for the different application targets and methods is summarized in Table H-8.
Page 227 of 279

Table H-8. DCM Mass Released, by Application Target and Method

Target (Surface Area)

and Method

Application

Rate, g/ft2 a

Weight 

Fraction b

Release 

Fraction

DCM Mass 

Released, g

Coffee table (10 ft2)

 Brush-on

 Spray-on

90

68

0.53 | 0.88

0.80 | 0.87

0.33

0.66

157.4 | 261.4

359.0 | 390.5

Chest of drawers (25 ft2)

 Brush-on

 Spray-on

90

68

0.88

0.87

0.33

0.66

653.4

976.1

Bathroom tub (36 ft2)

 Brush-on 13.25 1.0 0.33 157.4

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 (ROH). 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 × 20 ft room with an 8-ft ceiling (20 × 12 × 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 ROH 

(438 m3) is determined by subtraction (492 m3 - 54 m3). For the bathtub scenario, the bathroom 

volume was set at 9 m3for 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 228 of 279

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 Riley et 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 229 of 279

Figure H-7. Zone Volumes and Airflow Rates for Workshop Scenarios

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

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 

Room of 

Use

(54 m3)

68

m3/hr

107

m3/hr

Rest of 

House

(438 m3)

197

m3/hr

Central Values

Room of 

Use

(54 m3)

68

m3/hr

65.8

m3/hr

Rest of 

House

(438 m3)

78.8

m3/hr

Values for Upper-end 

Concentration Scenarios

denotes air flow

Denotes air flow

1.6

m3/hr

Rest of 

Bathroom

(8 m3)

35

m3/hr

Rest of 

House

(483 m3

)

“Source 

Cloud”

(1 m3)

86.9

m3/hr

80

m3/hr
Page 230 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-1-1-3). 

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 ROH 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 231 of 279

Figure H-9. Modeling Representation of the Bathtub and Virtual Compartment

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 232 of 279

Figure H-10. Air Velocity Distributions from Matthews et al. (1989)

With the fan cycling on and off the air velocity would be between 1.8 and 6.1 cm/sec, with the 

average velocity dependent on the on-time for the fan. As of 2008, at least 25% of U.S. homes 

did not have a central, forced-air heating system (EFH Table 19-13; EPA, 2011a). Homes with 

alternative systems (e.g., steam or hot-water system; baseboard/portable electric heat) would 

be expected to have a velocity similar to that for the fan-off case. Similarly, ~40% of U.S. homes 

had either no cooling equipment or room/window cooling units (EFH Table 19-15; EPA, 2011a). 

Consequently, a velocity of 1.8 cm/sec (65 m/hr) was used for the bathroom scenario, to 

represent such homes as well as those with a central forced-air system that is off during paint 

stripping either by intent or due to mild weather. 

The assumed airflow rate between the source cloud and the rest of the bathroom was based on 

a relationship developed by Matthews et al. (1989), who determined experimentally that such 

an airflow could be estimated as the product of the room air velocity (m/hr) and the entry/exit 

surface area (m2). An assumed air velocity of 65 m/hr, representing the fan-off case, together 

with an assumed entry/exit surface area of 5 ft by 2 ft, 8 in (13.35 ft2 or 1.24 m2) resulted in an 

estimated airflow rate of 80 m3/hr between the source cloud and the rest of the bathroom. 

HVAC OFF and ON flows

for Master Bedroom
Page 233 of 279

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 ROH 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 

ROH 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) (PollackNelson, 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 ROH 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 ROH 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 234 of 279

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, i to i +1, for i = 0 to 1,440:

ECi,i+1 = [

(C1,i + C1,i+1)

2

⁄ ] ∗ Fi,i+1 + [

(CROH,i + CROH,i+1)

2

⁄ ] ∗ (1 − Fi,i+1) (Equation H-11)

where: 

ECi,i+1 = the exposure concentration over the time interval i to i +1

C1,i and C1,i+1 = the concentrations in the use zone at times i and i+1, respectively

CROH,i and CROH,i+1 = the concentrations in the ROH zone at times i and i+1, respectively

Fi,i+1 = the fraction of time spent in the use zone during the time interval i to i +1

These calculations, illustrated in Figure H-11, were implemented in an Excel spreadsheet for 

each of the seven scenarios.

Figure H-11. Example of the Exposure Concentration Calculation as Defined in Equation H-11
Page 235 of 279

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 ROH (Zone 2) during wait times between applying and scraping. The nonuser’s exposure concentrations are the same as those in the ROH. 

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 × 0.8 × 0.66 = 359 g 

for the spray activity as compared to 900 g × 0.53 × 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 236 of 279

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/m3for spray-on vs. 1,300 mg/m3for 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/m3for spray application 

vs. 120 mg/m3for 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 ROH. Due to the higher dilution rate, the workshop concentrations fell more 

quickly after the stripping activity was completed than do the concentrations in the ROH.

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 237 of 279

a) Scenario 1, Brush Applied

b) Scenario 4, Spray Applied

Figure H-12. Modeled DCM Concentrations for Scenarios 1 and 4, Stripper Application in Workshop using Central Parameter 

Values
Page 238 of 279

a) Scenario 2, Brush Applied

b) Scenario 5, Spray Applied

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 239 of 279

a) Scenario 3, Brush Applied

b) Scenario 6, Spray Applied

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
Page 240 of 279

Figure H-15. Modeled DCM Concentrations for Scenario 7, Brush Application in Bathroom (Simulation)
Page 241 of 279

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 consumeruse 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/m3that 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 242 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-5-2 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 243 of 279

Table H-9. Estimated Exposures and Associated Conditions for Selected OPPT and LBL Cases

Room of Product 

Application 

(Volume)

Application 

Method -

Substrate

Theoretical 

DCM Mass 

Released, g

Length of 

Work 

Period, 

min

Ventilation 

Rate for Work 

Area, ACH

User 

Location 

during Wait 

Period

TWA Exposure during 

Work Period, mg/m3

User Non-user

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 ROH 174 25

Workshop (54 m3) Brush-Table 261.4 84 1.26 Workshop 917 42 

Workshop (54 m3) Brush-Chest 653.4 168 1.26 ROH 563 186

Workshop (54 m3) Spray-Table 359.0 80 1.26 ROH 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 ROH 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 ---

a 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 67 

Basement (60.7 m3) Brush-Panel 247.5 92 1.60 b 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 xxx indicates the most comparable non-user (bystander) exposures

 Non-user= Residential bystander
Page 244 of 279

H-6 MCCEM Inhalation Modeling Scenario Summaries

Formula: CH2Cl2

CAS Number: 75-09-2

Molecular Weight: 84.93 g/mol

Density: 1.33 g/cm2(liquid)

Appearance colorless liquid

Melting Point: -96.7 deg C = -142 deg F = 176 K

Boiling Point: 39.6 deg C = 103 deg F = 313 K 

Solubility in Water: 13 g/L @ 20 deg C

Vapor Pressure: 47 kPa = 352.535 Torr = 0.4639 atm = 6.817 psi

Conversion units: 1 ppm = 3.4736 mg/m3

Saturation Concentration: 463,862 ppm = 1,611,281 mg/m3

DCM Scenario 1. Coffee Table, Brush-On, Workshop, User in ROH during wait time, 0.45 ACH, 

0.53 Weight Fraction 

MCCEM Input Summary

Application Method: Brush-on

Volumes:

Workshop volume = 54 m3

ROH volume = 492 – 54 = 438 m3

Airflows:

Workshop-outdoors 68 m3/h

ROH-outdoors 197.1 m3/h (0.45 ACH)

Workshop-ROH 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 × 0.53 (wt fraction) × 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

Elapsed time from time zero, minutes

Apply Wait Scrape

first 1/2, 1st time 0-2 min 2-17 min 17-21 min

second 1/2, 1st time 21-23 min 23-38 min 38-42 min

first 1/2, 2nd time 42-44 min 44-59 min 59-63 min

second 1/2, 2nd time 63-65 min 65-80 min 80-84 min
Page 245 of 279

Model Run Time:

0-24 hrs

User takes out scrapings after 84 minutes

Activity Patterns:

User in workshop during application and scrape periods, in ROH during wait periods

User in ROH 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 1 min 10 min 30 min 1 hr 4 hr 8 hr 24 hr

User 632.4 376.1 269.4 224.0 120.5 68.6 23.3

Other 131.7 131.5 129.5 123.8 82.1 49.1 16.8

In ppm

Individual 1 min 10 min 30 min 1 hr 4 hr 8 hr 24 hr

User 182.1 108.3 77.6 64.5 34.7 19.7 6.7

Other 37.9 37.8 37.3 35.6 23.6 14.1 4.8

Plots:
Page 246 of 279

Non-user= Residential bystander
Page 247 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

ROH volume = 492 – 54 = 438 m3

Airflows:

Workshop-outdoors 68 m3/h

ROH-outdoors 197.1 m3/h (0.45 ACH)

Workshop-ROH 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 × 0.88 (wt fraction) × 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

Elapsed time from time zero, minutes

Apply Wait Scrape

first 1/2, 1st time 0-2 min 2-17 min 17-21 min

second 1/2, 1st time 21-23 min 23-38 min 38-42 min

first 1/2, 2nd time 42-44 min 44-59 min 59-63 min

second 1/2, 2nd time 63-65 min 65-80 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 ROH for the remainder of the run (22 hrs, 36 minutes)
Page 248 of 279

MCCEM Results Summary

Exposure Concentrations (maximum values over first 24 hrs):

In mg/m3

Individua

l 1 min 10 min 30 min 1 hr 4 hrs 8 hrs

24 hrs

User 1,292.4 1,251.7 1,136.7 1,058.0 416.7 223.8 75.3

Other 218.7 218.3 215.1 205.6 136.3 81.5 27.9

In ppm

Individual 1 min 10 min 30 min 1 hr 4 hrs 8 hrs 24 hrs

User 372.0 360.4 327.2 304.6 120.0 64.4 21.7

Other 63.0 62.9 61.9 59.2 39.2 23.5 8.0

Plots:
Page 249 of 279

Non-user= Residential bystander
Page 250 of 279

DCM Scenario 3. Chest, Brush-On, Workshop, User in ROH during wait time, 0.18 ACH, 0.88 

Weight Fraction

MCCEM Input Summary

Application Method: Brush-on

Volumes:

Workshop volume = 54 m3

ROH volume = 492 – 54 = 438 m3

Airflows:

Workshop-outdoors 68 m3/h

ROH-outdoors 78.8 m3/h (0.18 

ACH)

Workshop-ROH 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 × 0.88 (wt fraction) × 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

Elapsed time from time zero, minutes

Apply Wait Scrape

first 1/4, 1st time 0-2 min 2-17 min 17-21 min

second 1/4, 1st time 21-23 min 23-38 min 38-42 min

third 1/4, 1st time 42-44 min 44-59 min 59-63 min

fourth 1/4, 1st time 63-65 min 65-80 min 80-84 min

first 1/4, 2nd time 84-86 min 86-101 min 101-105 min

second 1/4, 2nd time 105-107 min 107-122 min 122-126 min

third 1/4, 2nd time 126-128 min 128-143 min 143-147 min

fourth 1/4, 2nd time 147-149 min 149-164 min 164-168 min

Model Run Time:

0-24 hrs

User takes out scrapings after 168 minutes

Activity Patterns:

User in workshop during application and scrape periods, in ROH during wait periods

User in ROH for the remainder of the run (21 hrs, 12 minutes)
Page 251 of 279

MCCEM Results Summary

Exposure Concentrations (maximum values over first 24 hrs):

In mg/m3

Individua

l 1 min 10 min 30 min 1 hr 4 hrs 8 hrs

24 hrs

User 1,810.4 1,178.1 898.3 762.4 562.8 400.1 157.1

Other 472.7 472.3 469.7 461.4 383.0 287.9 118.2

In ppm

Individual 1 min 10 min 30 min 1 hr 4 hrs 8 hrs 24 hrs

User 521.2 339.2 258.6 219.5 162.0 115.2 45.2

Other 136.1 136.0 135.2 132.8 110.2 82.9 34.0

Plots:
Page 252 of 279

Non-user= Residential bystander
Page 253 of 279

DCM Scenario 4. Coffee Table, Spray-On, Workshop, User in ROH during wait time, 0.45 ACH, 

0.8 Weight Fraction 

MCCEM Input Summary

Application Method: Spray-on

Volumes:

Workshop volume = 54 m3

ROH volume = 492 – 54 = 438 m3

Airflows:

Workshop-outdoors 68 m3/h

ROH-outdoors 197.1 m3/h (0.45 ACH)

Workshop-ROH 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 × 0.8 (wt fraction) × 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

Elapsed time from time zero, minutes

Apply Wait Scrape

first 1/2, 1st time 0-1 min 1-16 min 16-20 min

second 1/2, 1st time 20-21 min 21-36 min 36-40 min

first 1/2, 2nd time 40-41 min 41-56 min 56-60 min

second 1/2, 2nd time 60-61 min 61-76 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 ROH during wait periods

User in ROH for the remainder of the run (22 hrs, 40 minutes)
Page 254 of 279

MCCEM Results Summary

Exposure Concentrations (maximum values over first 24 hrs):

In mg/m3

Individual 1 min 10 min 30 min 1 hr 4 hrs 8 hrs 24 hrs

User 1,502.0 781.0 598.2 491.7 266.9 152.1 51.7

Other 303.1 302.5 298.0 284.8 187.8 112.0 38.3

In ppm

Individual 1 min 10 min 30 min 1 hr 4 hrs 8 hrs 24 hrs

User 432.4 224.8 172.2 141.6 76.8 43.8 14.9

Other 87.2 87.1 85.8 82.0 54.1 32.3 11.0

Plots:
Page 255 of 279

Non-user= Residential bystander
Page 256 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

ROH volume = 492 – 54 = 438 m3

Airflows:

Workshop-outdoors 68 m3/h

ROH-outdoors 197.1 m3/h (0.45 ACH)

Workshop-ROH 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 × 0.87 (wt fraction) × 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

Elapsed time from time zero, minutes

Apply Wait Scrape

first 1/2, 1st time 0-1 min 1-16 min 16-20 min

second 1/2, 1st time 20-21 min 21-36 min 36-40 min

first 1/2, 2nd time 40-41 min 41-56 min 56-60 min

second 1/2, 2nd time 60-61 min 61-76 min 76-80 min

Model Run Time:

0-24 hrs

User takes out scrapings after 80 minutes

Activity Patterns:

User in workshop during application, wait and scrape periods

User in ROH for the remainder of the run (22 hrs, 40 minutes)
Page 257 of 279

MCCEM Results Summary

Exposure Concentrations (maximum values over first 24 hrs):

In mg/m3

Individua

l 1 min 10 min 30 min 1 hr 4 hrs 8 hrs

24 hrs

User 1,991.0 1,926.4 1,760.8 1,609.4 619.4 332.4 111.9

Other 329.6 329.0 324.1 309.8 204.2 121.9 41.7

In ppm

Individual 1 min 10 min 30 min 1 hr 4 hrs 8 hrs 24 hrs

User 573.2 554.6 506.9 463.3 178.3 95.7 32.2

Other 94.9 94.7 93.3 89.2 58.8 35.1 12.0

Plots:
Page 258 of 279

Non-user= Residential bystander
Page 259 of 279

DCM Scenario 6. Chest, Spray-On, Workshop, User in ROH during wait time, 0.18 ACH, 0.87 

Weight Fraction

MCCEM Input Summary

Application Method: Spray-on

Volumes:

Workshop volume = 54 m3

ROH volume = 492 – 54 = 438 m3

Airflows:

Workshop-outdoors 68 m3/h

ROH-outdoors 78.8 m3/h (0.18 ACH)

Workshop-ROH 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 × 0.87 (wt fraction) × 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

Elapsed time from time zero, minutes

Apply Wait Scrape

first 1/4, 1st time 0-1 min 1-16 min 16-20 min

second 1/4, 1st time 20-21 min 21-36 min 36-40 min

third 1/4, 1st time 40-41 min 41-56 min 56-60 min

fourth 1/4, 1st time 60-61 min 61-76 min 76-80 min

first 1/4, 2nd time 80-81 min 81-96 min 96-100 min

second 1/4, 2nd time 100-101 min 101-116 min 116-120 min

third 1/4, 2nd time 120-121 min 121-136 min 136-140 min

fourth 1/4, 2nd time 140-141 min 141-156 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 ROH during wait periods

User in ROH for the remainder of the run (21 hrs, 20 minutes)
Page 260 of 279

MCCEM Results Summary

Exposure Concentrations (maximum values over first 24 hrs):

In mg/m3

Individua

l 1 min 10 min 30 min 1 hr 4 hrs 8 hrs

24 hrs

User 2,821.3 1,632.3 1,266.5 1,108.6 813.6 580.2 228.2

Other 713.5 713.0 709.0 696.5 575.9 431.3 176.6

In ppm

Individual 1 min 10 min 30 min 1 hr 4 hrs 8 hrs 24 hrs

User 812.2 469.9 364.6 319.1 234.2 167.0 65.7

Other 205.4 205.3 204.1 200.5 165.8 124.2 50.8

Plots:
Page 261 of 279

Non-user= Residential bystander
Page 262 of 279

DCM Scenario 7. Bathtub, Brush-On, Bathroom + Source Cloud, User in ROH 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

ROH volume = 492 – 9 = 483 m3

Airflows:

Source Cloud-Bathroom 80 m3/h (0 to outdoors/ROH)

Bathroom-outdoors 1.6 m3/h

ROH-outdoors 86.9 m3/h (0.18 ACH)

Bathroom-ROH 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 × 1.0 (wt fraction) × 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

Elapsed time from time zero, minutes

Apply Wait Scrape

first 1/4, 1st time 0-3 min 3-18 min 18-24 min

second 1/4, 1st time 24-27 min 27-42 min 42-48 min

third 1/4, 1st time 48-51 min 51-66 min 66-72 min

fourth 1/4, 1st time 72-75 min 75-90 min 90-96 min

first 1/4, 2nd time 96-99 min 99-114 min 114-120 min

second 1/4, 2nd time 120-123 min 123-138 min 138-144 min

third 1/4, 2nd time 144-147 min 147-162 min 162-168 min

fourth 1/4, 2nd time 168-171 min 171-186 min 186-192 min
Page 263 of 279

Model Run Time:

0-24 hrs

User takes out scrapings after 192 minutes

Activity Patterns:

User in source cloud during application and scrape periods, in ROH during wait periods

User in ROH 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

l

1 min 10 min 30 min 1 hr 4 hrs 8 hrs 24 hrs

User 2428.0 1455.3 886.6 798.9 536.4 339.6 135.3

Other 223.8 223.6 222.2 218.2 186.9 149.5 69.5

In ppm

Individual 1 min 10 min 30 min 1 hr 4 hrs 8 hrs 24 hrs

User 699.0 419.0 255.3 230.0 154.4 97.8 39.0

Other 64.4 64.4 64.0 62.8 53.8 43.0 20.0

Plots:
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Non-user= Residential bystander
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Appendix I RISK ASSESSMENT GUIDELINES, LITERATURE 

SEARCH STRATEGY AND DATA QUALITY 

CRITERIA USED IN THE HAZARD/DOSERESPONSE 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.

I-1 EPA/IRIS Toxicological Review

I-1-1 Risk Assessment Guidelines

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).

I-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).

I-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 I-1).
Page 267 of 279

 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 I-2).

Figure I-1. Study Quality Considerations for Epidemiological Studies
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Figure I-2. Study Quality Considerations for Animal Studies
Page 269 of 279

I-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).

I-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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I-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 NONCANCER 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 noncancer hazard value associated with chronic exposures to DCM (EPA, 2011c).

J-1 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-1 

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 BMD10 and BMDL1052

associated with 10% extra risk (EPA, 2011c).

The mouse internal BMDL10 (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 (BMDL10 = 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).

 BMD10= benchmark dose at the 10% response

 BMDL10=lower confidence limit of the benchmark dose at the 10% response
Page 272 of 279

Figure J-1. Process of deriving the DCM’s cancer inhalation unit risk

 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 BMDL10 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 BMDL10 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 BMDL10 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).
Page 273 of 279

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 μg/m3) exposures. The distribution of IURs 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 

μg/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 BMDL10 is 

1 × 10-8 per μg/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 BMDL10 for hepatic effects. In other words, the BMDL10

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 BMDL10 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 BMDL10 by

4.09 [(BWhuman)/(BWrat)

0.25 ≈ 4.09)]53 to obtain a human equivalent internal BMDL10 of 

130.03 mg DCM metabolized via CYP54 pathway/litter liver tissue/day (EPA, 2011c).

 

53 BW=body weight

54 CYP=cytochrome P450
Page 274 of 279

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 BMDL10 based on the responses in female SpragueDawley rats. Estimated HECs corresponding to the mean, 1st, and 5

th 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 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, 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-1 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
Page 276 of 279

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 (C x T) by forcing 

the fitted line through the origin. All the data in the above table [table not included in 

Appendix I-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 (Putz et 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 (Putz et 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).
Page 277 of 279

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 oncein-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-1 depicts the three AEGL tiers and the associated 

health effects.

Figure K- 1. Illustration of the Different AEGL Threshold Levels

 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 
Page 278 of 279

endpoint of interest would change over an exposure range of 10 minutes to 8 hrs. The AEGLvalues 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 CNSdepressing 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.
Page 279 of 279

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 CNSdepressing 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).