United States EPA Document# 740

- R1

- 4003 Environmental Protection Agency August 2014 Office of Chemical Safety and Pollution Prevention



## TSCA Work P lan Chemical Risk Assessment

Methylene Chloride : Paint Stripping Use

CASRN: 75

- 09

- 2

August 2014Page 2 of 279



## TABLE OF CONTENTS

LIST OF TABLES

................................ ................................ ................................ ................................ .............................. 6

LIST OF FIGURES

................................ ................................ ................................ ................................ ............................ 10 AUTHORS/CONTRIBUTORS /ACKNOWLEDGEMENTS/RE VIEWERS

................................ ................................ ................. 12

GLOSSARY OF TERMS AN D ABBREVIATIONS

................................ ................................ ................................ ................. 14

EXECUTIVE SUM MARY

................................ ................................ ................................ ................................ .................. 19

1 BACKGROUND AND SCOPE

................................ ................................ ................................ ................................ .. 27

1.1 INTRODUCTION

................................ ................................ ................................ ................................ ........ 27 1.2 BACKGROUN D

................................ ................................ ................................ ................................ .......... 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 We re 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 AS SESSMENT

................................ ................................ ................................ .................... 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 Estima tion 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 Exposu re Scenarios for the DCM Inhalation Exposure Assessment

................................ ................................ .......... 6 0 3.2.5 Consumer Model Results

................................ ................................ ................................ .......................... 65 3.3 HAZARD/DOSE

- RESPONSE ASSESSMENT

................................ ................................ ................................ . 67Page 3 of 279

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, Dist ribution, Metabolism and Excretion

................................ ................................ ................................ 78 3.3.2.2 Human and Animal Toxicity Following Acute Exposure to DCM

................................ ................................ ............... 79 3.3.2.3 Human and Anima l 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 Asses sments

................................ ................................ ... 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 Tox icity 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

................................ ................................ ................................ ........................... 154Page 4 of 279

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 Rest oration 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 Contract ors, 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 fo r Estimating Occupational Exposure

................................ ................................ ...... 174 G

- 2

- 1 Identification of Relevant Industries

................................ ................................ ................................ ....................... 174 G

- 2

- 2 Estimation of Potential Workplace Exp osures for DCM

- Based Paint Strippers

................................ ....................... 174 G

- 2

- 2

- 1 Workplace Exposures Based on Monitoring Data

................................ ................................ ................................ ... 174 G

- 2

- 2

- 2 Workplace Exposure Scena rios 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

................................ ................................ ................................ ................................ ............ 20 2 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 Emi ssion 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 E xposure 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

................................ ................................ ................................ ...................... 241Page 5 of 279

H

- 5

- 2 Comparison of Exposure Estimates

................................ ................................ ................................ ......................... 242 H

- 6 MCCEM Inhalation Modeling Scenario Summaries

................................ ................................ ................................ . 244 Appendix I RISK ASSESSMEN T 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 Stud y Selection and Data Quality Criteria

................................ ................................ ................................ ............... 266 I

- 2 Acute Exposure Guideline Levels (AEGLs)

................................ ................................ ................................ ............... 269 I

- 3 Spacecraft Maximum Allowable Concent rations (SMACs)

................................ ................................ ...................... 269 I

- 4 California’s Acute Reference Exposure Levels (RELs)

................................ ................................ .............................. 270 Appendix J SUMMARY OF THE DERIVATIONS OF THE EPA I RIS 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)

................................ ................................ ................................ ................. 277Page 6 of 279



## LIST OF TABLES

Table ES

- 1. Ranges of DCM Occupational Exposure Estimates Used in the Risk Asses sment Based on

Monitoring Data

................................ ................................ ................................ ............................. 21

Table 1

- 1. Primary Uses of DCM and Selection Criteria

................................ ................................ ..................... 31

Table 2

- 1. Physical

- Chemical Properti es 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. A cute 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 DCM a

................................ ................................ ........................... 49

Table 3

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

................................ 61

T able 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

Expo sed

................................ ................................ ................................ ................................ .......... 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 Inhal ation 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

................................ ................................ ................................ ..... 86Page 7 of 279

Table 3

- 13. Margin of Exposure (MOE) Equation to Estimate Non

- Cancer Risks Following Acute or Chronic

Exposures to DCM

................................ ................................ ................................ .......................... 87

Table 3

- 14. Equat ion 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 pot ential health risks and are denoted in bold text

................................ ................................ ................................ ....................... 89

Table 3

- 16 . Acute Risk Estimates for Residential Exposures to DCM

- Based Paint Strippers: AEGL

- 1 and AEGL

2 PODs for Various Exposure Durati ons. 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 1 6)

................................ . 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 Stripp ing 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 D CM

(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)

................................ ................................ .............................. 105Page 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 Foll owing 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 Expo sure 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 Inf ormation for DCM from 2012 CDR

................................ ............................... 148

Table C

- 2. Summary of Industrial DCM Uses from 2012 CDR

................................ ................................ .......... 148

Table C

- 3. DCM Commercial/Consume r Use Category Summary

................................ ................................ ... 149

Table D

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

........................ 150

Table E

- 1. E nvironmental Fate Characteristics of DCM 1

................................ ................................ ................. 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 Con tractors

......... 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 D ata 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

................................ . 173Page 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

..................... 17 9

Table G

- 4. Chronic Occupational Exposure Scenarios for the Use of DCM

- Based Paint Strippers

.................. 180

Table G

- 5. DCM Acute and Chronic Expos ure 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 Refinis hing 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 S hop 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 Furnit ure 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 Expos ures to DCM During Furniture Paint Stripping using a Dip Tank after

Implementation of NIOSH

- Recommended Slotted Hood Ventilation System a

........................... 200

Table G

- 12. Summary by Industry of OSHA IMIS Person al 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 S urface: 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

...................... 243Page 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 Bas e

- 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

- o n Stripper

................................ ... 215

Figure H

- 4. Theoretical Cumulative Mass of DCM Released for Strypeeze Brush

- on Stripper

....................... 216

Figure H

- 5. DCM Conce ntrations 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 f or 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.

................................ ....................... 238Page 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

................................ ................................ ...... 277Page 12 of 279



### AUTHORS/ CO NTRIBUTORS/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 a nd 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 Yv ette M. Selby

– Mohamadu, OPPT/ RAD

Acknowledgements

We acknowledge the contributions of Mary Dominiak (OPPT/ C hemical Control Division ; retired) in the development of the draft work plan risk assessment for DCM . In addition, we appreciate the assistance f rom 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, p ortions of this document were prepared for EPA by Abt Assoc iates, the Eastern Research Group (ERG), Inc., the Syracuse Research Corporation (SRC) and Versar

.Page 13 of 279

EPA Internal Peer Reviewers

Office of Ch emical Safety and Pollution Prevention Anjali Lamba, OPPT/ RA D Brad Goodwin, AAAS, OPPT/CCD

Office of Chil dren’s Health Protection Brenda Foos and Lindsay McCormick

Office of Research and Development Paul S chlosser ORD/NCEA

External Peer Review EPA/OPPT released peer review plan in August of 2012 and draft risk assessment and charge questions for peer revie w 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 in fluential 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 pane l 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

.P age 14 of 279



## GLOSSARY OF TERMS AND ABBREVIATIONS

μg Microgram(s) μg/m 3 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 Disco mfort /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 Bioconcent ration factor BMD Benchmark dose BMD 10 Benchmark dose at 10% response BMDL Benchmark dose, lower confidence limit(s) BMDL 10 Benchmark dose, lower confidence limit(s) at 10% response BMDS Benchmark Dose Software BMR Benchmark response BOD Biochem ical oxygen demand BW Body weight C Contaminant concentration

° C D egree Celsius C ROH Concentration in the rest of the house Cal EPA California Environmental Protection Agency CASRN Chemical a bstracts s ervice r egistry n umber CBI Confidential bu siness 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)

c m 2 Square centi meter(s)

cm 3 Cubic centi meter( s) CNS Central nervous system CO Carbon monoxide CO 2 Carbon dioxide COHb CarboxyhemoglobinP age 15 of 279

CPSC Consumer Product Safety Commission CYP C ytochrome P450 CYP2E1 Cytochrome P450, family 2, subfamily E, polypeptide 1 DART/ETIC Developmental and Reprod uctive 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 EC 50 E ffective concentration necessary to produce a 50% response EC i,i+1 Exposure concentration over the time interval i to i+1 EC scenario1 Exp osure concentration for scenario 1 EC scenario 2→4 Exposure concentration for scenario 2, 3 or 4 EC scenario 2→16 Exposure concentration for scenario 2 through 16 ECG Electrocardiogram ED Exposure duration EETD Economics, Exposure and Technology Division EF Exposure frequency EFH Expo sure 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 F ahrenheit FACE Fatality Assessm ent and Control Evaluation FDA Food and Drug Administration ft Foot/feet ft 2 Square foot/feet ft 3 Cubic foot/feet FTIR Fourier transform infrared
g Gram(s) g/cm 2 Gram(s) per square centimeter g/cm 3 Grams(s) per cubic centimeter GENE

- TOX Genetic Toxicology Data Bank g/ft 2 , g/sq ft Grams(s) per square foot g/L Gram(s) per liter GLP Good Laboratory PracticesP age 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

- transfera se GST

- T1 GST

- theta1

- 1 GWP Global warming potential HEC Human equivalent concentration HEC 99 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 hazar d value HFC

- 32 Hydrofluorocarbon

- 32 HHE Health hazard evaluation HQ Hazard quotient HPLC High

- perf ormance liquid chromatography hr(s) Hour(s ) HSDB Hazardous Substances Data Bank HSIA Halogenated Solvents Industry Alliance, Inc. HVAC Heating, ve ntilation, and air conditioning IDLH Immediately dangerous to life and h ealth IMIS Integrated Management Information Systems IPCC Intergovernmental Panel on Climate Change IRIS Integrated Risk Information System IRTA Institute for Research and Technic al Assistance IUR Inhalation unit risk IURR Inventory Update Reporting Rule K (upper

- case) Kelvin k (lower

- case) first

- order rate constant K oc Soil organic carbon partition coefficient K ow Octanol:water partition coefficient kPa kilopascal(s) L Liter (s) l b(s) Pound(s) LADC Lifetime average daily concentration LBL Lawrence Berkeley Laboratory LC 50 Median lethal concentration LOAEL Lowest

- observed

- adverse

- effect level LOEC Lowest

- observed

- effect concentration

m Meter(s)

m 2 Square me ter(s)

m 3 Cubic meter(s) M acute Scenario

- specific acute exposure modifier M chronic Scenario

- specific chronic exposure modifier

m 3 /hr Cubic meter(s) per hour MATC Maximum acceptable toxicant concentrationP age 17 of 279

MCCEM Multi

- Chamber Concentration and Expo sure Model MCL Maximum contaminant level
mg Milligram(s) mg/L Milligram(s) per liter mg/m 3 Milligram(s) per cubic meter min Minute(s) MITI Ministry of International Trade and Industry mM Millim olar mm Hg Millimeters of mercury mL M illiliter(s) MMWR Morbidity and Mortality Weekly Report MOE Margin of exposure MR Mass released MRI Midwest Research Institute MSDS Material s afety d ata s heet s MSU Michigan State University NAICS North American Industry Classification System NAS Na tional 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 p harmacokinetic PEL Permissible exposure l imit 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 ActP age 18 of 279

REL Reference e xposure l evel RfC Reference concentration RIA Regulatory impact a nalysis ROH Rest of the house RTECS Registry of Toxic Effects of Chemical Substances SCG T he 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

- t erm e xposure l imit sq ft Square foot (feet)
t Time TLV Threshold l imit v alue TOXLINE Toxicology Literature Online TRI Toxics Release Inventory TSCA Toxic Substances Control Act TSCATS Toxic Substance Control Act Test Submission Database TWA Time

- weighted av erage UF Uncertainty factor UF A Interspecies uncertainty factor UF D Database uncertainty factor UF H Intraspecies uncertainty factor UF L LOAEL

- to

- NOAEL uncertainty factor UF total 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)P age 19 of 279



## EXECUTIVE SUMMARY

As a part of t he 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 . Th e Agency is perform ing risk assessments on chemicals in the work plan. I f an assessment identifies unacceptable risks to humans or the environ ment , EPA will pursue risk management

. M ethylene chloride (also called dichloromethane or DCM) was assessed as part of th e 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 identifie s 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 id entifi es 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 characterize s human health risks from inhalation exposures to DCM for the pain t 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 assump tions 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.htmlP age 20 of 279

through the skin. However, EPA has neither the data nor the methodology to estimate DCM dermal exposure. B ased 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 asse ssment 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 aqu atic 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 co ntamination is likely low

. In fact, DCM has been detected in drinking wat er, 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 regul atory 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
pregnan t 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, E PA/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) w ho are in a nearby area during product application

.

In either o ccupational or consumer setting
, EPA/OPPT assume s that direct contact or close proximity to the use would likely provide the highest exposures to DCM ( i.e., for a consumer or commercial appl ication with substantial fre quency 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), year s of exposure (working lifetime), and respirator use and effectiveness (assigned protection factors) were used to develop a variety of hypothetical occupational scenarios.P age 21 of 279

Acute risks were estimated from the 8

- h our DCM air concentrations reported in the occupational monitoring data. Chronic risks were based on non

- cancer and cancer i nhalation 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 develop ed 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 Estimate s Used in the Risk Assessment

Based on Monitoring Data

Industry Range for acute

8

- hr concentration : Scenario 1→4 (mg/m 3 ) ADC range :

Non

- Cancer Effects Following Chronic Exposure

Scenario s 1→16 (mg/m 3 ) LADC range :

Cancer Effects Following Chronic Exposure

Scenario s 1→16 (mg/m 3 ) L OW

- EN D
ESTIMATE H IGH

- END

ESTIMATE L OW

- END

ESTIMATE H IGH

- END

ESTIMATE L OW

- END

ESTIMATE H IGH

- 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 0.0 05 513 0.0 03 293 Art Restoration and Conservation 0.04 2 0.0 03 0.5 0.00 2 0.3

Aircraft Paint Stripping 1.7 3,802 0. 1 868 0. 06 496 Graffiti Removal 0.4 1,188 0.0 2 271 0. 01 155 Non

- Specific Workplace Settings

– Immersion Stripping of Wood 0.7 7,000 0. 04 1,598 0.0 2 913

No n

- 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/m 3 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 mode ling approach was selectedP age 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 con ducted in the U.S. and Europe. The literature search for this assessment did not identify any published exposure information for exposures to other househ old members (i.e., bystanders ). Of the available chamber studies, only one U.S. study provided sufficient informa tion 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 rat e 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 expo sure scenarios. T he primary distinct ions 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 excha nge 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 a re considered central tende ncy 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 comb inations 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 s cenario 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 . E stimated exposure levels for users of DCM

- based paint strippers are higher than those reported for the bystander in the ROH. Th e estimated exposure levels to bystanders in the bathroom scenario is in the same range as the exposures to bystanders in the wor kshop scenarios.

Characterization of Hazards and Risks to Human Health

DCM’s Carcinogenic Hazards and Risks:

DCM i s 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 m g/ m 3 ) 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 )

.P age 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 bas ed 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 stu dies ( EPA, 2011c )

.

DCM ’s Non

- Carcino genic 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 car bon 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 carboxyhe moglobin (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

- respon se 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

- h r SMAC POD was not available for the risk calculations. Although AEGLs are intended for emergency response act ivities, 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/m 3 (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 HEC 99 the concentration at which the re 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 w ell

- 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 )

.P age 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 whet her 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 resp iratory 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 prima rily 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 assumpti ons 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 ident ified 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

- e stimation 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 toxicit y, 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 :

 O ver 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 a re indirectly exposed.

 No data were available to estimate the number of consumers and residential bystanders exposed to DCM during the use of paint strippers.P age 25 of 279

Cancer Risks Associated With Chronic Exposures to DCM :

 There are cancer risk concerns for worker s 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 ris ks 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 b ystanders) using DCM

- based paint strippers in relevant industries, with the exception of the art renovation and conservation industry

.

 N on

- cancer risks occur for most workers (including bystanders) handling DCM

- based paint strippers with or without respira tory protection for v arious 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 scen arios, 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.

 N on

- cancer risks are not reported when workers reduce the ir exposure to DCM

- based strippers by taki ng 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 faciliti es 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 i n 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 n o 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 appl ying the product or staying in the residence after com pletion of the stripping task. These concerns are also present for residential bystanders in someP age 26 of 279

scenarios when exposure conditions are at the highest in the rest of the house after completing the pain t 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 build s up in the body over time.P age 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

. Th e Agency is p erform ing risk assessments on chemicals in the work plan. I f 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 che micals for further assessment 3 . The criteria focused on chemicals that meet one or more of the following factors: (1) p otentially of concern to children’s health (for example, because of reprodu ctive or developmental effects); (2)

n eurot oxic effects; (3) p ersistent, b ioaccumulative, and toxic (PBT); (3) probable or known carcinogens; (4) used in children’s products; or (5) d etected in biomonitoring programs

. Using this methodology , EPA identified a TSCA Work Plan of chemicals as candidates for risk

assessme nt 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 assistan ce to other Federal , State and L ocal agencies as well as to members of the general public who are interest ed in the chemical risks of DCM

. The risk assessment may also help those interested in reducing risk s 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, asse ssments 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.go v/oppt/existingchemicals/pubs/workplans.html

3 http://www.epa.gov/oppt/existingchemicals/pubs/wpmethods.pdfP age 28 of 279



### 1.2 BACKGROUND

1.2.1 Rationale for Selecting DCM for Risk Assessment

DCM was identified f or assessment based on high human health hazards and exposure potential

. The high human health hazard ranking wa s assigned for potential cancer risks (i.e., likely human carcinogen ) and acute 4 and chronic 5 non

- cancer effects

. DCM is a liquid VOC and its hi gh vapor pressure leads to rapid evaporation, which may pose an inhalation hazard for humans. The high exposure potential ranking wa s assigned because DCM is widely used with industrial, commercial and consumer user applications and at a relatively high pe rcent content particularly in paint stripping products

. DCM is ubiquitously present in the environment with levels detected in drinking water, indoor environments, amb ient 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; re frigerant; 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 Report ing (C DR) 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

Severa l 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 e xposure by the oral, dermal, or inha lation route for 24 hours or less ( EPA, 2011b )

. 5 Chronic exposure is defined as r epeated 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 )

.P age 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 Ca lifornia 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 informa tion 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 tox ic ( i.e., non

acute) hazardous waste under the Resource Conservation and Recovery Act (RCRA) (Code U080) ( EPA, 2012c ) . DCM is also listed on the T oxics 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, 2 011e )

. 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 Drink ing 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 bri ef description of actions in Canada and Europe.P age 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. U ses other than paint stripping are not covered in the risk assessment because EPA/OPPT deci ded 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 u se 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 i dentified ( 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 expert ise 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 recogniz es 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. B ased on the physical

- chemical properties of DCM and the scenarios described in this a ssessment, 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 size s 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 s exes [ > 16 years (yrs) and older]
, although exposures to younger individuals may be possible in occupational settings.P age 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 str ipping. 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 stri pping and removal applications (automotive, furniture, marine, wall paint, similar coating removal).

Pharmaceuticals N/A b Industrial 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/A b Industrial workers No

– Industrial use s ettings 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/A b Industrial workers No

– Industrial use settings which are generally believed to be better controlled and

monitored.

Notes:

a For the purposes of this asses sment, consumers are defined as non

- commercial/non

- industrial use rs 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 p ercent of DCM content is expected to be at or near 100 percent.P age 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
preg nant 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, adu lts, 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 t h e acute and chronic human hea lth 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 significa ntly build up in the body between exposure events. DCM’s plasma half

- life is estimated to be 40 minutes after inhalation e xposure ( 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 cl ear 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 s oil, migrate to groundwater. This substance has been shown to biodegrade over a range of rates and environmental conditions and is considered to be moderately persisten t in the environment. Measured bioconcentration factors for DCM suggest its bioconcentra tion 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 Chemical s ( 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.P age 33 of 279



## 2 SOURCES AND FATE

Chapter 2 discusses the physical and chemical propert ies 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 struct ure 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 chlorofo rm

- 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/cm 3 at 20°C). DCM is used as a substitut e for other solvents becau se it is non

- flammable and non

- explosive. DCM also is not readily oxidizable ( ECB, 2000 ; Lide, 2001 ; O'Neil, 2001 )

. Table 2

- 1 shows the common physical

chemical properties of DCM.

Table 2

- 1 . Physical

- Chemical Properties of DCM a Molecular formula CH 2 Cl 2 Molecular weight 84.93 Physica l 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 K OW 5.3 ("slow stirring" method); 5.9 at 25°C (measured; OECD 117 b ) Water solubility 13.7 g/L at 20 °C D ensity 1.33 g/cm 3 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 Liq uid Chromatography ( HPLC ) MethodP age 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 i n 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; tabl et 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 an d 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 approv ed 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 du e 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 199 7;

 warning labeling requirements required by CPSC on all products containin g 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 requir ing 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 mid

1980s to approximately 1 81 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 th ree 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 D CM 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 non

confidential 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 perc ent of theP age 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 equipme nt 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

co mmercial 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 in creasing 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 adhesive s 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 adhes ives 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

- 22 e

 Fluorocarbon production accoun ts 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)P age 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 Uses a Minor Uses a Overall Benefits

 Paint removal

 Formulated products

 Adhesives

 Aerosol propella nt

 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 solven t for oils, waxes, fats, spices, and hops

 Tablet coating for pharmaceuticals  Low flammability b

 Non

- corrosive to many substrates b

 Strong solvency properties b

 No flash point under normal use conditions and can be used to reduce the flammability of other sub stances c

 Lower costs

Sources : a Dow (1999) ; EPA (2013) ; HSIA (20 08) ; IAQUK (2014)

b Mannsville (1999)

c HSIA (2010)

As recently as the 1980s, approximately 50 percent of the total DCM market wa s 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 manufacture r s ma y 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

a pplication 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 r esulted in adhesive use not being selected as a focal point for this assessment.P age 37 of 279

Table 2

- 4

. Major Uses of DCM in the U.S. Major Uses Percent of DCM Consumed in E nd Products Adhesives 37 Paint stripping 25 Pharmaceuticals 10 Metal cleaning 7 Chemical processing 7 Aerosols 5 Polyurethane foam blowing 5 Miscellaneous 4 Source s : 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 thinners a

 Paint removers and strippers b  Varnish removers b

 Graffiti removers b Aerosol applications  Aerosol paints c

 Automotive products c

 Spray shoe polish a  Rust removers a

 Primers a

Cleaners/protectors  Water repellant/protectors a

 Spot removers a

 Wood floor and panel cleaners a

 Specialized electronic cleaners (for TV, VCR, razor, etc. ) a  Wood stains a

 Transmission cleaners a

 Battery terminal protecto r a

 Brake quieter/cleaner a

 Gasket removers a Adhesives  Contact cement a

 Super glues a

 Spray adhesives a  Adhesive removers (general purpose, tile and wallpaper) a

Miscellaneous  Silicone lubricants (excluding automotive) a

 Outdoor water repellan ts a  Gasket removers a

Sources : a NIH (2005)

b DHHS (2012)

c Mannsville (1999)

The 2012 CDR data indicated that DCM is used in the f ollowing 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

c ontaining DCM, in concentrations ranging from one to 100 percent. The products are dividedP age 38 of 279

almost evenly between aerosol and liquid formulations (with one in granular form) ( DHHS, 2012 )

.
DCM uses addressed by other agen cies ( 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 wide st 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 app lication 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 pa int 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 ex tent of DCM use in paint stripping. In 2008, EPA estimated that a total of 39,000 establishments perform ed surface coating operations, including paint stripping, motor vehicle, mobile equipment, and miscellaneous activities. Specifically, EPA estimated tha t about 3,000 of these facilities were paint stripping shops. Of these 3,000 facilities, 2,000 facilities used paint strippers containing ≤ 2,00 0 lbs of DCM, while 1,000 facilities used products containing > 2
, 000 lbs of the chemical ( EPA, 2008 )

.



### 2.3 SUMMAR Y 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 c oncern.

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 (GW P) 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 persisten t in the environment. Measured bioconcentration factors for DCM

s uggest its bioconcentration potential is low. Appendix E has additional information about the environmental fate of DCM.P age 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 appr oach 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 inc lude 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 possibili ty 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 depen d 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 refe rs 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. F urther characterization to determine which factors best distinguish small shops for all the various industries that perform pa int stripp ing 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 ).P age 40 of 279

The following industries were identified:

 Professional contractors;

 Bat htub refinishing;

 Automotive refinishing;

 Furniture refinishing;

 Art restoration and conservation;

 Aircraft paint stripping;

 Ship paint stripping; and

 Graffiti removal

By i dentif ying these industries, EPA/ OPPT identifi ed corresponding worker subpopulation s 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 work place
exposures. Section 3.1.1.2 and Appendix F provide the estimated number of w orkers 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 an d 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 pain t 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 50 th and 9 5 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)

serve d as substitutes for 50 th percentil es, and high ends of ranges serve d as substitutes for 95 th percentiles.

Data sources often did not indicate whether monitored exposure concentrations were for occupational users or bystanders. Therefore, EPA/OPPT assumed that these exposure concentration s 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 ob tained 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 t o stripping with DCM

containing products. R efer to Appendix G for a detailed discussion of the OSHA IMIS dat a.P age 41 of 279

W orkplace exposure scenarios evaluated in this assessment : Workers performing DCM

- based paint stripping might or might not use a respirator and may be exposed to DCM at different exposure frequencies (days per year) or working years. Thus, EPA /OPPT assessed acute risks for 4 occupational scenarios and chronic risks for 16 occupational scenarios based on 8

- hr time

weighted average (TWA) exposure co ncentrations 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 combina tion 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 Occ upational Exposure Scenarios for the Use of DCM

- Based Paint

Strippers Acute Scenario Respirator APF a 8

- hr TWA Concentration Multiplier 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 Respira tor 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 appli ed 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) o f 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 chroni c 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.P age 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 wo rkers 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, h igh 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 25 0/ 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 an d 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, midpoint s 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 respi rator 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).P age 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 pro tection factors
, and different exposure freq uencies and working years).

Approach for calculating a cute and chronic workplace exposure s : 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 chr onic, 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 value s 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 sce nario used an EF of 250 days/y r and a WY of 2 0 yrs, or an EF of 125 days/y r 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/m 3 reported for the various relevant industries. EPA/OPPT assumed that s ome 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 t he 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/m 3 ) for

scenario 1 C = contaminant concentration in air for relevant industry ( central tendency,

low

- or high

- end 8

- hr TWA in mg/m 3 from Appendix G , Table G

- 2 or G

- 5);P age 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/m 3 ) for acute scenarios 2, 3, or 4; EC scenario 1 = single (acute) exposure concen tration for relevant industry (8

- hr TWA in mg/m 3 from Appendix G , Table G

- 2 or G

- 5); M acute = Scenario

- specific acute exp osure multiplier (unit less) for relevant industry (s ee Table 3

- 1 )

Acute exposure estimates for scenario 1 are presented in Table 3

- 3 . Acute exposure estimates for scenarios 2 through 4 were integrated into the risk calculations by applying the scenario

specific multipliers . Thus, separate tables listing the acute exposure estimates for scenarios 2 through 4 are not provided in this section, but are available in a supplemental Excel spreadsheet documenting the risk calculations for this assessment ( DCM Exposure and Risk Esti mates_0 811 14.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 T WA air concentration in mg/m 3 reported for the various relevant industries ( Appendix G , Table G

- 5 ). EPA/OPPT assumed that the worker would be doing paint stripping activities during the entire 8

- hr work shift on a daily basis. Equation 3

- 3 was used to esti mate 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/m 3 ) for Scenario 1 = ADC for chronic n on

cancer risks or LADC for chronic cancer risks for Scenario 1; C = contaminant concentration in air for relevant industry ( central tendency,

low

- or high

- end 8

- hr TWA in mg/m 3 from Appendix G , Table G

- 2); ED = exposure duration (hrs/day) = 8 hrs/day; EF = exposure frequency (days/y r) = 250 days/y r for high

- end of range

for both ADC and LADC calculations ;P age 45 of 279

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

for both ADC and LADC calc ulations ; and AT = averaging time (years × 365 days/years × 24 hrs/day ) = 40 y rs for high

end of range for ADC calculations ; 70 y rs 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/m 3 ) for chronic scenarios 2 through 16 EC scenario 1 = chronic exposure concentration (ADC or LADC) for relevant industry, chronic scenario 1 (in mg/m 3 from Table 3

- 3 ); M chronic = scenario

- speci fic ADC/LADC chronic multiplier for relevant industry (see Table 3

- 2 )

N on

- cancer and cancer exposure estimates (i.e., ADC and LADC, resp ectively) for scenario 1 are presented in Table 3

- 3 . The estimate s 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 ar e available in a supplemental Excel spreadsheet documenting the risk calculations for this assessment ( DCM Exposure and Risk Estimates_0 811 14.xlsx ).

Numbers of exposed workers and shop sizes: Knowing the sizes of exposed populations provides perspective o n the prevalence of the health effects. Thus, EPA/OPPT estimated the current total number of workers in the potentially exposed populations.

EPA/OPPT found li mited data on numbers of workers exposed to DCM in shops that use DCM

based paint strippers. EP A/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 Operation s at Area Sources proposed rule ( EPA, 2007 )

.

Based on the NESHAP d ata 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 (“occu pational 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 expose d inP age 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 estima tes 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 contract ors (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 ai rcraft 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 apply ing multipliers to Scenario 1. Separate tables listing the acute and chronic exposure estima tes ar e not provided in this section, but can be found in the supplemental Excel spreadsheet

- DCM Exposure and Risk Estimates_0 811 14.xlsx

. Also, Table ES

- 1 provides a summary of the ranges of acute, ADC and LADC estimates for the various occupational scen arios.P age 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 Concent ration (mg/m 3 ) a CHRONIC EXPOSURE ESTIMATES USED IN THE NON

- CANCER RISK

ESTIMATES ADC (mg/m 3 ) b CHRONIC EXPOSURE ESTIMATES USED IN THE CANCER RISK ESTIMATES LADC (mg/m 3 ) b
Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low
Professional C ontractors 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 Re moval 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 4.6P age 48 of 279 Table 3

- 3. DCM Acute and Chronic Exposure Concentrations (ADCs and LA DCs) for Workers

– Scenario 1

–

Highest Exposed Scenario Group

Industry / Activity Time

Range of Studies ACUTE EXPOSURE ESTIMATES

Single 8

- hr Concentration (mg/m 3 ) a CHRONIC EXPOSURE ESTIMATES USED IN THE NON

- CANCER RISK

ESTIMATES ADC (mg/m 3 ) b CHRONIC EXPO SURE ESTIMATES USED IN THE CANCER RISK ESTIMATES LADC (mg/m 3 ) 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: Sourc es 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/m 3 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 95 th percentiles of the calculated acute single 8

- hr concentrations and the calculated ADCs and LADCs.

-- Indicates no d ata found.P age 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 value s established by O SHA, NIOSH , and ACGIH. Appendix F presents a dditional 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 s hort

- t erm e xposure l imit (STEL), adding an A ction L evel, and removing the ceiling limit ( OSHA, 1997a )

. See Appendix G, section G

- 2

- 3, for more details.

Table 3

- 4

. Occupational Exposure Limits for DCM a

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/m 3 per ppm ( NIOSH, 2011b )

. d IDLH = Immediately dangerous to life and h ealth

. IDLH values are based on effects that might occur from a 30

- minute exposure

. e REL = Recommended Exposure Limit

. T he REL notati on “ Ca ” is for a potential occupational carcinogen . T he NIOSH Pocket Guide website has detailed policy recommendations for chemicals with “ Ca ” notations ( NIOSH, 2011a )

. f TL V = Threshold l imit v alueP age 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 mo deling 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 mode ling 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 con ducted in the U.S. and Europe. The literature search for this assessment did not identify any published exposure information for exposures to other househ old members (i.e., bystanders). Of the available chamber studies, only one U.S. study provided sufficient informa tion for the exposure modeling ( EPA, 1994a )

.



### 3.2.2 Overview of the M CCEM

The MCCEM is an exposure model that estimates airborne concentrations of chemicals released from products in residential settings or other indoor environments ( EPA, 2 010a ) . 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 dat a 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 use s a two

- zone representation of a house to calcu late acute air concentrations of DCM for consumers and bystanders for various exposure scenarios. Zone 1 represent s the area where the consumer was using the product, whereas Zone 2 represent s the rest of the house (ROH). Zone 2 was used for modeling passi ve exposure to house residents (bystanders), such as children, adults, pregnant women and the elderly ( EPA, 2010a ) . The model assumes complete mixing in each zone.P age 51 of 279

The MCCEM us es 3 zones to model t he bathtub “source cloud” scenario. In this scenario, Zone 1 represent s the arbitrary volume close to the tub. Zone 2 represent s 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 repres ented 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 polluta nt 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 exchang e 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 oc cupant 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 instanta neous 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 concentrati ons 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 fo r 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 p aint 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 exp osure ( DiVincenzo et al., 1972 ) . Moreover, EPA/OPPT assumed th at 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.P age 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 ( 201 2 ) 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 prod u ct 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 informat ion 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 )

. D ata 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 exper imental 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/chambe r test studies above is provided in Appendix H, section H

- 5

.P age 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 pro ducts 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 conside r these differences between brush

on and spray

- on products.

3.2.3.3 Amount Applie d to the Surface (Product Mass)

The product application mass (grams of product) was d etermined for each of the cases examined using application rates ( in g/ft 2 ) calculated from the EP A (1994a) chamber tests and the surface areas of objects (in ft 2 ) to be stripped.

EPA (1994a) reported the most c omplete air monitoring data for the consumer use of paint strippers containing DCM 7 . The study documented chamber experiments for five pai nt 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 descriptio ns of the study design and the results to determine product application rates ( i.e., in g/ft 2 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 u sed 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 v alues. 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/ft 2 and ~68 g/ft 2 for a brush

- on and spray

- on application, respectivel y. These application rates are similar to those recommended by Savogran (i.e., 42 to 83 g/ft 2 based on a nominal density of 1.1 g/cm 3 ) 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 (E FH) ( EPA, 2011a ) . The CPSC (1992) survey reported the following central (near the median) and upper

end estimates for the amount of paint stripper product used pe r event:

7 Appendix H discusses other studies that were reviewed, but were not used to estimat e 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/P age 54 of 279

 50 th percentile value of 32 ounces or 1,000 g for the central

- tendency surface area of 10 ft 2

. The median value is also supported by Riley et al. (2001) 9 ;

 ~80 th percentile value of 80 ounces or 2,500 g for the upper

- end surface area of 25 ft 2

.
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 ft 2 , w hile 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 ft 2

. The model used median product masses of 900 and 680 g for the brush

- on and spray

- on scenarios, respectively. Upper

end product masses for th e 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 bat hroom scenario. The lower mass value was derived from the largest application amount identified in the NIOSH report ( CDC, 2012 )

. A surface area of 36 ft 2 was calculated for a bathtub, resulting in an application rate of 13.25 g/ft 2

.

3.2.3.4 Stripping Sequence

The stripping sequence was based in part on product label instructions, which for some DCM

containing products ( i.e. , Klean Strip® products) indicate that no mor e than 9 ft 2 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

- f t 2 coffee table: Surface area was divided into 2 application segments of 5 ft 2 each with repeat applica tion for a total of 4 segments;

 25

- ft 2 chest: Surface area was divided into 4 application segments of 6.25 ft 2 each with repeat application f or a total of 8 segments;

 36

- ft 2 bathtub: Surface area was divided into 4 application segments of 9 ft 2 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 appli cation, (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 describe s the detailed stripping sequen ce for the bru sh

- 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 Append ix H for more information on this study.P age 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 (disc ussed 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 applica tion. The corresponding 90 th 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 ab out the zone volume s , 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 m 3 ) was the central value listed in the 2011 EFH ( EPA, 2011a ) . The volume assigned to the in

- house workshop area was 54 m 3 , whic h is similar to the value reported in Riley et al. (2001) for the mean volume of the room u sed for paint stripping (51 m 3 ). The volume for the ROH (438 m 3 ) is determined by subtraction (492 m 3

- 54 m 3 ). For the bathtub scenario, the bathroom volume was set at 9 m 3 for 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 10 th p ercentile values reported by the 2011 EFH ( EPA, 2011a ) and represented the indoor

- outdoor airflow rate for t he 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 u se ( CPSC, 1992 ; EPA, 1987 ; Pollack

- Nelson, 1995 ; Riley et al., 2001 ) . T he indoor

- outdoor airflow rate assigned to the workshop (68 m 3 /hr) was obtained by multiplying the room volume of 54 m 3 by the 90 th percentile of the air

- exchange

- rate distribution from th e EFH (1.26 hr; EPA, 2011a ) , as it was thought to be a reasonable repres entation of the open

- window case.P age 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 b y ( 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 o f 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 in door

- 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 L ocations of Ex posed Individuals

The model places the user in the work area fo r stripper application and scra ping, 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 combin ations of input parameters generate s 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 ofP age 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 i n 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 expo sure 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 ba se case for the sensitivity analysis was formed as follows:

 House volume of 492 m 3 (corresponds to a 36 ft × 30 ft, two

- story house with 8

- ft ceiling);

 Workshop (area of product use) volume of 54 m 3 (corresponds to a 20 ft × 12 ft room with 8

- ft ceiling) a nd an indoor

- outdoor airflow rate of 68 m 3 /hr (expected value for a room with multiple open windows);

 Airflow rate of 197 m 3 /hr for the ROH, assuming windows closed, corresponding to an air exchange rate of 0.45 ACH;

 Brush

- on application with a target surf ace area of 10 ft 2 ;

 Applied product mass of 900 g (90 g/ft 2 ) 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 sc raping 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, accor ding 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)P age 58 of 279

in addition to the 24

- hr TWA value. All the exposure durations were reported in t he 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 Av eraging 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/m 3

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/m 3

Time, hours Non-user Exposure Concentration 10-min max 30-min max 1-hr max 4-hr maxP age 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 Sce narios)

.
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 perc ent 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) f or 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 bystanderP age 60 of 279

Figure 3

- 4

. Model Sensitivity Results: Percent Change from Base

- case Response for 24

- hr

TWA for User and Residentia l 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 thi s 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 frac tion 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 t he 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.P age 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 Characterization a 1 Brush

- on Workshop Central tendency 2 Brush

- on Workshop User Upper

- end 3 Brush

- on Works hop 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 sensiti ve 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 Des criptions and Parameters

Scenario ID Conc. Characte

rization DCM Released

Stripping Method Room of Use House User Location During Wait Period b By

stander Location Weight Fraction Surface

Area Treated a , ft 2 Application

Rate, g/ft 2 Release

Fraction Vo lume,

m 3 Ventilation/ACH ,

1/hr Volume,

m 3 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

- ft 2 segments with repeat application) and eight
segme nts for chest of drawers ( i.e. , four 6.25

- ft 2 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 (pro fessional judgment, 90 th percentile) 492

(central) 0.45

(central) ROH

ROH (entire time) 2 Upper

- end for user c

0.88

(upper

end) Workshop

3 Upper

- end

for user and bystander c 25 chest of drawers (upper

end) 0.18 (low

end) ROHP age 62 of 279 Table 3

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

Scenario ID Conc. Characte

rization DCM Released

Stripping Method Room of Use House User Location During Wait Period b By

stander Location Weight Fraction Surface

Area Treated a , ft 2 Application

Rate, g/ft 2 Release

Fraction Volume,

m 3 Ventilation/ACH ,

1/hr Volume,

m 3 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

- ft 2 segments with repeat application) and eight segments for chest of drawers ( i.e. , four 6.25

- ft 2 segments with repeat application)

 1

- minute application, 15

- minute wait, and 4

- minute scrape per segment

 No overlapping activities

 Scrapings remov ed from house after last scraping 54 (central) Open windows/

1.26

(pro fessional judgment, 90 th percentile) 492

(central) 0.45

(central) ROH

ROH (entire time) 5 Upper

- end for user c

0.87

(upper

end) Workshop

6 Upper

- end

for user and bystander c 25 chest of drawers (upper

end) 0.18 (low

end) ROHP age 63 of 279 Table 3

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

Scenario ID Conc. Characte

rization DCM Released

Stripping Method Room of Use House User Locatio n During Wait Period b By

stander Location Weight Fraction Surface

Area Treated a , ft 2 Application

Rate, g/ft 2 Release

Fraction Volume,

m 3 Ventilation/ACH ,

1/hr Volume,

m 3 ROH ACH, hr

- 1

Brush

- on Exposure Scenario in Bathroom

7 Simulation for bystan der
exposure 0.88

(upper

end) 36

bathtub (upper

end) 13.25 0.33  Eight segments ( i.e. , four 9 ft 2 segments with repeat application)

 3

- minute application, 15

- minute wait, and 6

- minute scrape per segment

 No overlapping activities

 Scrapings removed from house after last scraping 9 (low

end) d Window closed,

no exhaust fan/ 0.18 e (low

- end) 492

(central) 0.18

(low

end) ROH ROH (entire time)

Notes:

a The surface area values were selected so that the calculated amount of product applied ( in g rams ) corresponds approximately to the CPSC (1992) survey results for amount of paint stripper used (50 th percentile value of 32 ounces or 1,000 g for the central surface area of 10 ft 2 and ~80 t h percentile value of 80 ounces or 2,500 g for the upper

end surface area of 25 ft 2 ).
b For all scenarios, the user is in the treatment room during the application and scraping times and in ROH after the last scra ping.

c Changes in both chemical mass a nd ACH parameters are more influential than changes in only user location from workshop to the rest of the house. Consequentl y, the user concentrations for Scenarios 3 and 6 are higher than those for Scenarios 2 and 5, respectively.
d 1 m 3 for the vic inity of the tub (source cloud) and 8 m 3 for the rest of the bathroom.

e Because the user is working in the semi

- enclosed work area (bathtub) for an extended period, a third zone (“source cloud”) was created within the bathroom to represe nt the DCM conc entrations in the vicinity of the tub; this is a virtual zone, with no physical boundaries. The airflow rate between the clou d and the rest of the bathroom was based on work by Matthews et al. (1989) (for more informati on, see discussion in Appendix H, H .3. Inhalation Exposure Scenario Inputs (Airflow Rates and Volumes).

Abbreviations: ROH= room of use; ACH= air exchange ra teP age 6 4 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 includi ng 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 values 10 are exposure values expected to be near the average or median for the range of exposure values . On the other hand, upper

– end values 11 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 repor ted 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 est imate 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 vent ilation, 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 (1992 b) exposure assessment guidelines, “ I ndividual 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 p ersons 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 call ed “bounding.” Conceptually, the high end of the distribution means above the 90 th percentile of the population distribution, but not higher than the individual in the population who has the highest exposure. ” For this assessment, scenarios labeled “ uppe r

- end” were modeled by selecting low

- and high

- end values for sensitive parameters. An “upper

end” exposure estimate is above central tendency and may include the high end of the exposure distribution.P age 65 of 279



### 3.2.5 Consumer Model Results

Table 3

- 7 provides the scenario

- specific DCM air concentrations for the consumer user of DCM

containi ng 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 eac h 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 rat io of user to bystander maximum one

minute concentration is ~5:1 for scenario 1, whereas the ratio is ~1.5:1 for the 24

- hr user and bystander TWA values.

Appendix H provides additional information on various aspects of the model output, such as the foll owing:

 Mathematical descriptio n 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 , Comp arison 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 )P age 66 of 279

Table 3

- 7

. Modeled DCM Air Concentrations to Which Consumer Users and Residential Bystanders are Exposed

Scenario Individual a Maximum Values for Averaging Period, mg/m 3 (ppm)

1 Minute 10

Minutes 30

Minutes 1 Hour 4 Hours 8 Hours 24 Hours
1. Brush applic ation 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) 90 0 (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) 5 2 (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) 32 0 (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 assu med 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 Scenario s 3 and 6 are higher than those for Scenarios 2 and 5, respectively.P age 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 wor k plan risk assessment for DCM is primarily based on the peer

- reviewed hazard and dose

- response information 12 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 All owable 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 M ethylene C hloride 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

- respons e 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. P rimary, peer

- reviewed literature identified through September 2011 was systematically rev iewed 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 us es the hazard values (i.e., point s of de parture) 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.P age 68 of 279

Spacecraft Maximum Allowable Concentrations for Space Station Contaminants ( NRC, 1992 ) and California’s Air To xics 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), S MAC (section I

- 3) and the C alifornia 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 assessmen ts 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 Fo llowing 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 m g/m 3 ; assuming a 70

- y ear 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 continuo us 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 dose

response data for liver and lung cancer in mice ( EPA, 2011c )

. Moreover, the weight of evidence from multiple in vivo and in vitro studies supported the mutagenicity of DCM and the key role of glutathione S

- transferase ( GST ) metabolism and the formation of DNA

- re active 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 co ntaining 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 excee ding the point of departure (BMDL 10 = 7,700 mg/m 3 or 2,200 ppm ), because above this level the fitted dose

- response model does not characterize what is known about the carcinogenicity of DCM

.P age 69 of 279

These methods were published with the caveat that extrapolation of lifetim e theoretical excess cancer risks to single exposures has great uncertainties.

As NRC (2001) explains, “ There are no adopted state or fed eral 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

- te rm 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 m olecular, 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 dat e, 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 establi shed 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/m 3 (4.8 ppm) for chronic DCM inhalation exposures ( EPA, 2011c )

. The hazard value was estimated by PBPK modeli ng and expressed as the 1 st percentile of the distribution of human equivalent concentrations (HEC) i.e. the HEC 99 the concentration at which there is 99% likelihood an individual would have an internal dose less than or equal to the internal dose of hazar d was used to protect toxicokinetically sensitive individuals

. EPA/OPP T 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 r eport ed 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 dose 14 estimation

. The DCM IRIS ass essment chose the 1 st percentile HEC i.e. the HEC 99 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/m 3 as the point of departure (POD) 15 for the non

- ca ncer dose

- response assessment because it would protect toxicokinetically sensitive individuals

. Appendix J contains more information on how the non

cancer PBPK

- derived HEC was developed

.

14 The benchmark dose (BMD) is a dose or concentration that produc es 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 extrapolatio n. A POD is used to mark the beginning of extrapolation to determine risk associated with lower environmentally relevant human exposures ( EPA, 2011b )

.P age 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 inhalati on 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, MOE 16 ) 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 characterizatio n.

A total UF of 1 0 was used as the benchmark MOE and was allocated as follows:

 i nterspecies UF (UF A ) of 3 to account for toxicodynamic differences between animals and humans
,
 i ntraspecies UF (UF H ) of 3 to account for toxicodynamic differences within huma ns

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 UF s for interspecies and intraspecies uncertainty set by the IRIS
program. Refer to section 3.4 for more information about the MOE calculations.P age 71 of 279

Table 3

- 8 . Cancer and Non

- Cancer Hazard Values Used in the Risk Evaluation of Chronic Exposures to Worker s Using DCM

Based Paint Strippers

Effects Category Target

Organ/ System Species Route of

Exposure and Exposure Concentrations 1 Duration POD Type Effect Uncertainty Factors (UFs) for Benchmark MOE 2 Hazard Value

Used in Chronic Risk Assessment Additional

Information 3 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 BMD 10 and BMDL 10 = 913.9 and 544.4 mg DCM metabolized via GST pathway/liter tissue/day, respectively

Male lung tumors: Mouse internal BMD 10 and BMDL 10 = 61.7 and 48.6 mg DCM metabolized via GST pathway/liter tissue/day, respectively Liver and lung
tumors Not

a pplicable Inhalation

Unit Risk (IUR) : 4 x 10

- 5 per ppm (1 x 10

- 5 per

m g/m 3 ) Internal dose

BMDL 10 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 BMDL 10 =

531.82 mg DCM metabolized via cytochrome P450 (CYP) pathway/liter liver tissue/ day Hepatic

effects (vacuol ation) UF A = 3;

UF H =3; Total UF=1 0 1 st percentile

human equivalent concentratio n (HEC) i.e. the HEC 99 : 17.2 mg/m 3 (4.8 ppm) Allometric

scaling and probabilistic modeling were used to calculate the hazard value (i.e., HEC 99 ) fr om the rat internal BMDL 10 . Nitschke

et al. (1988a)

Notes:

1 Airborne concentration conversion factor for DCM is 3.47 mg/m 3 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 (UF A ) and intraspecies (UF H ) unc ertainty factors

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

. 3 for further information see Appendix JP age 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, n on

- 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 evaluate d 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 )

. Alth ough AEGLs are intended for emergency response activities, the AEGL PODs were used in this assessment to evaluate acute risks associated with discomfort/ non

- disabling (AEGL

- 1) and incapacitating (AEGL

- 2) effects following DCM exposure from the use of paint strippers.

EPA/OPPT assumed that consumers would not generally perform paint stripping jobs on a regular basis in their residences allowing sufficient time between exposures to clear DCM and its metabolites from the body. This assumption was supported by DCM’s short plasma half

- life (~40 min) ( DiVincenzo et al., 1972 )

. Evaluation of acute risks in occupational scenarios is appropriate based on the assumption that some workers could be rotating tasks and not necessarily using DCM

- based paint strippers on a daily basis. This type of exposure would allow the worker to clear DCM and its metabolites before the next encounter with the DCM

containing paint stripper.

The consumer exposure modeling indicated that virtually all of the DCM release occurs within 2 hrs after product application for both spray and brush p aint str ippers. 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 t o 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) ap plicable to 1

- hr exposures for consumer scenarios

.
In contrast, f or occup ational scenarios, the Ca lifornia REL POD w as time scaled to 8 hrs to compare the hazard value to the 8

- hr air concentration estimated from the monitoring data. This assumed that the worker would be performing paint stripping activities during the entire 8

- hr work shift. The 8

- hr AEGL

- 2 was used to evaluate whether the 8

- hr occupational exposures estimates exceeded the threshold for disability. However, comparisons of consumer exposure estimates with AEGLs incorporated AEGL PODs for shorter or longer time durations (i.e., 10

- min, 30

- min, 4

- hr and 8

- hr) in addition to the 1

- hr POD to evaluate a wider concentration

time response

. Sections 3.3.1.3.1 ( SMACs ), 3.3.1.3.2 ( AEGLs ), and 3.3.1.3.3 ( California’s Acute REL ) summarize the approach and methodology used in the acute inhalation risk assessment. Appendix K provides additional information about the definitions of the SMAC, AEGL and the California acute REL values and how their respective PODs were derived

.P age 73 of 279

3.3.1.3.1 SMACs
SMACs are developed by the U.S. National Academies ( NAS ) to provide g uidance 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 ex posed ( e.g., children, adults, the elderly)

.

The DCM acute risk assessment used the acute POD of 350 mg/m 3 (100 ppm) supporting the derivation of the 1

- hr SMAC

. The POD was considered the NOAEL 17 for central nervous system (CNS) effects associated with t he 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 ( CO 2 ) . 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 DC M 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 estim ates. 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 (che st 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

e t 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 levelP age 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 D CM

- 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 h uman data were us ed to support the 1

- h r 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 He alth 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 hr s) in a human population, including sensitive subgroups, expo sed on an intermittent basis ( OEHHA, 1999 )

.
As an alternative approach to estimate acute inhalation risks, t his assessment also considered the POD of 8 40 mg/m 3 ( 240 ppm) supporting the derivation of the 1

- hr acute REL

. The POD was considered the L OAEL 18 for subtle imp airment of the nervous system function in humans based

on human volunteers exposed to 195 ppm DCM (696 mg/m 3 ) for 1.5 hr s ( Putz et al., 1979 )

. The 1.5

- hr exposure concentration was the n time

- scaled to obtain the 1

- or 8

- hrs POD s of 840 mg/m 3 (240 ppm) and 290 mg/m 3 (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 knowledg e of what would be considered a NOAEL COHB level based on the

e xtensive CO database ( NRC, 1996 )

.

E PA/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 UF 19 of 6 ( OEHHA, 2008 )

.
Appendix K contains more information on the deriva tion 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.P age 75 of 279

3.3.1.3.3 AEGLs

AEGLs are emergency response values designed for once

- in

- a

- lifetime ex posures to airborne chemicals. AEGL values are threshold levels develo ped 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 susceptib le 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 )

.

R ecent 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

- d isabling 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 c omparisons 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 Appendi x 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 fo rmation in the blood ( NRC, 2008 )

. Taking this into consideration, PBPK modeling was used to calculate AEGL PODs based on DCM concentrations in brain and pe ak COHb in blood

. CNS effects dr o ve 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 afte r 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 satu rable 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

.P age 76 of 279

Table 3

- 9 . Non

- Cancer Hazard Values Used in the Risk Evaluation of Acute Exposures to Worker s and Consumer s Us ing DCM

- Based

Paint Strippers

Reference Value Target

Organ/ System Species Route of

Exposure and Ex posure Concen

trations 1 Duration POD Type Effect Hazard Value U sed 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/m 3 )

supported by various human studies CNS depression

related to formation of 3% COHb in blood 100 ppm

( 350 mg/m 3 ) UFs were not

applied to the 1

- hr SMAC. However, EPA/OPPT applied a UF H =10 in the acute risk
assessment to account f or human variability. NOAELs for CNS

depression have not been reported for DCM exposures. A linear regression analysis estimated the DCM concentration (350 mg/m 3 ) that produces ~3 percent COHb concentration in blood (NOAEL) NRC

(1996
, 200 8)

California Acute REL Central

Nervous System Human Inhalation

195 ppm (696 mg/m 3 ) 90 min

(1.5 hrs) LOAEL = 195 ppm

(696 mg/m 3 ) at 90 minutes ( Putz et al.
, 1979 ) or 240 ppm (840 mg/m 3 ) when time adj usted to a 60

- min exposure Impaired

performance on dual

- task and auditory vigilance tests in humans 1

- hr REL POD=

240 ppm (840 mg/m 3 )

8

- hr REL POD= 80 ppm (290 mg/m 3 ) UF H =10;

UF L =6; Total UF=60 ten Berge equation

(C n xt = k, n = 2) was used for time adjust ment from 90 to 60 min or 480 min (8 hrs). OEHHA

(2008)

AEGL

- 1 (threshold for discomfort/

non disabling 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/m 3 ) equivalent to a brain concentration of 0.063 mM. No effect level

for light

headedness, difficulties in enunciation 10

- min =

870 ppm (3,000 mg/m 3 )

4

UF H = 3

Total UF = 3 PBPK model was

used. Time scaling was based on maximum DCM
concentra tion in human brain. AEGL PODs for 4

- and 8

- hr were not calculated since they would be above the corresponding AEGL

2 values. NAC

(2008) 30

- min = 690 ppm (2,400 mg/m 3 )

4
1

- hr = 600 ppm (2,130 mg/m 3 )

4P age 77 of 279

Table 3

- 9 . Non

- Cancer Hazard Values Used in the Risk Evaluation of Acute Exposures to Worker s and Consumer s Us ing DCM

- Based

Paint Strippers

Reference Value Target

Organ/ System Species Route of

Exposure and Ex posure Concen

trations 1 Duration POD Type Effect Hazard Value U sed in Acute Risk Assessment Uncertainty

Factors (UFs) for Benchmark MOE 2,3 Additional

Information Reference

A EGL

- 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, 11 7 or 253 ppm (0, 420, or 900 mg/m 3 ) 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% C OHb 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/m 3 ) 6 30

- min= 1,200 ppm (4,200 mg/m 3 ) 6 1

- hr= 560 ppm (2,000 mg/m 3 ) 7 4

- hr= 100
ppm (350 mg/m 3 ) 7 8

- hr= 60 ppm (210 mg/m 3 ) 7 UF H = 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 concentrati on conversion factor for DCM is 3.47 mg/m 3 per ppm NIOSH (2011b)

2 Margin of Exposure (MOE) = (Non

- cancer hazard value, POD) ÷ (Human Exposure). The benchmark MOE is used to interpret the MO Es and consists of UF s

. 3 UF H =intraspecies UF; UF L =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 for mation of COHb determined the AEGL values for longer exposure durations. This is consi stent 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 satura ble around 500 ppm ( NAC, 2008 )

. 6 AEGL derivations were driven by CNS effects.

7 AEGL derivations were driven by COHb formation.P age 78 of 279



### 3.3.2 Human Health Hazard Summary

The information prese nted 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 . Thu s, 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 absorbe d through inhalation exposure. The pulmonary uptake o f 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 rat e is generally achieved within 2 hrs f or 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 b ody, 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 CO 2 , and saturation occurs at very low concentrations of a few hundred ppm. The second pathway yields formald ehyde and formic acid, and saturation occurs at very high concentrations (>10,000 ppm).

Acute toxic effects ( i.e. , CNS depression) may persist for h ou r s 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 h ou r s 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 mater nal 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 )

.P age 79 of 279

Blood concentrations of DCM were below the level of detection in 1,165 individuals who partic ipated in the recent National Health and Nutrition Examination Survey (NHANES) 2003 to 2004 subsample of the U

. S

. population ( CDC, 2009 ) . DCM w as 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 impairm ent 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 ) . I n some cases, high COHb levels (i.e., up to 40 percent) are measur ed 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 d epressant 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 a s 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 human s ( EPA, 2011c )

.

N eurological evaluations in animals during and after acute inhalation exposure to DCM ( i.e., >200 to 1000 ppm for 1 to 8 hr s ) have resulted in CNS depressant effect s 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, 194 4 ; Heppel et al., 1944 ; Kjellstrand et al., 1985 ; Weinstein et al., 1972 ) , impairment o f learning and memory ( Alexeeff and Kilgore, 1983 ) , an d changes in responses to sensory stimuli ( Rebert et al., 1989 )
, were reported from acute and short

- term DCM exp osure. Evidence of a localizedP age 80 of 279

immunosuppressive effect in the lung resulting from inhalat ion 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 F ollowing 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 neur ological symptoms among workers with average exposures of 75 to 100 ppm ( Cherry et al., 1981 ) . L ong

- term effects on some neurological measures ( i.e. , possible detriments in attent ion and reaction time in complex tasks) have been observed in retired workers whose past chronic exposures were in the 100 to 200 ppm range ( Lash et al., 1991 )

. These studies are limited by the relatively small sample sizes and their low power for detection of statistically significant results ( EPA, 2011c )

.
Following repeated inhalation exposure to DCM, the liver is the most sensitive target for non

cancer toxicity i n rats and mice. Lifetime exposure was associated with hepatocyte vacuolation and necrosis in F344 rats exposed to 1,000 ppm for 6 hr s/day ( Mennear et al., 1988 ; NTP, 1986 ) , hepatocyte vacuolation in Sprague

- Dawley rats exposed to 500 ppm for 6 hr s/day ( Burek et al., 1984 ; Nitschke et al., 1988a ) , and hepatocyte degeneration in B6C3F 1 mice exposed to 2,000 ppm for 6 hr s/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 B6C3F 1 mice at 2,000 ppm, testicular atrophy in B6C3F 1 m ice at 4,000 ppm, and ovarian atrophy in B6C3F 1 mice at 2,000 ppm ( EPA, 2011c )

.
Lung toxicity has also been reported in rodents exposed to DCM. In a 13

- week e xposure 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
per formance 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 weigh t 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., 198 0 ; Hardin and Manson, 1980 )

.

T hough 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 dat a identif ied changes in behavior habituation ( Bornschein et al., 1980 ) and increases in COHb ( Schwetz et al., 1975 ) following DCM e xposure ( EPA, 2011c )

. ( Bornschein et al., 1980 )P age 81 of 279

study obs erved 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 D CM

. The potential for developmental n eurotoxicity occurring at low exposures to DCM represents a data gap ( EPA, 2011c )

.

Th e 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 s ystem ( Barone et al., 2000 ; Rice and Barone, 2000 )

.

3.3.2.3.2 Carcinogenic Effects

EPA concluded that DCM is likely carc inogenic 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 increas ed 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

- induce d 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 B6C 3F1 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 hr s/day, 5 days/week for 2 years ( Mennear et al., 1988 ; NTP, 1986 ) . B rain 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 signifi cant trends in animal bioassays ( Sills et al., 1999 )

. Please refer to Chapter 4 and 5 of the DCM IRIS assessment for detailed information about the epidemiological and animal studies evaluated in the cancer

assessment, a s 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

- p athway metabolites ( EPA, 2011c )

.P age 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 bypro duct 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 sign ificant 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 thet a

- 1 and CYP2E1 ( Garte and Crosti, 1999 )

.
Hemoglobin in the fetus has a higher affinity for CO than does adult hemogl obin. 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 C hronic 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.P age 83 of 279

Table 3

- 10 . Summary of Inhalation Hazard Infor mation 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 pp m (1 x 10

- 5 per m g/m 3 ) Liver and lung
tumors Not applicable

1 st percentile human equivalent concentration (HEC) i.e. the HEC 99 : 17.2 mg/m 3 (4.8 ppm) Liver effects Total UF=10

ACUTE EXPOSURE 1

- hr SMAC POD= 100 ppm ( 350 mg/m 3 ) C entral 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/m 3 )

8

- hr California REL POD=80 ppm (290 mg/m 3 ) (for occupational scenarios) I mpairment of the CNS Total UF=60

AEGL

- 1 POD (threshold for d isc omfort /non

- disabling effects)

10

- min= 870 ppm (3,000 mg/m 3 ) 30

- min= 690 ppm (2,400 mg/m 3 ) 1

- hr= 600 ppm (2,130 mg/m 3 ) CNS effects (light headedness, difficulty in enunciation) Total UF=3

AEGL

- 2 POD (threshold for disability ) 10

- min= 1,700 ppm (6,000 mg/m 3 ) 6 30

- min= 1,200 ppm (4,200 mg/m 3 ) 6
1

- hr= 560 ppm (2,000 mg/m 3 ) 7 4

- hr= 100 ppm (350 mg/m 3 ) 7 8

- hr= 60 ppm (210 mg/m 3 ) 7 CNS effects for 10

- and 30

- min AEGL

- 2 PODs

COHb formation for 1

- , 4

- and 8

- hr AEGL

- 2 PODs Total UF=1P age 84 of 279



### 3.4 HUMAN HEALTH RISK CHARACTE RIZATION

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 assessm ent.

DCM is likely to be carcinogenic to humans. The cancer risk assessment uses the IUR derived in the 2011 DCM IRIS assessment based on liver and lung tumors in rodents . The weight

- of

evidence analysis for the cancer endpoint was sufficient to conclude that DCM

- induced tumor development operates through a mutagenic mode of action ( EPA, 2011c )

.P age 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 chron ic 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 OCCUPAT I ONAL USE RESIDENTIAL USE

Population of Interest and Exposure Scenario: Users Adult s 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 (>1 6 years old)

indirectly exposed to DCM while being in the same building during product use. I ndividuals of any age indirect ly exposed to DCM while being in the rest of the house during product use.

Health Effects of Concern, Concentration and Time Duratio n 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/m 3 8

- hr AEGL

- 2 POD = 210 mg/m 3 Hazard Values (PODs) for Residential Scenarios: 1

- hr SMAC POD= 350 mg/m 3 1

- hr California REL POD= 840 mg/m 3 10

- min AEGL

- 1 POD= 3,000 mg/m 3 30

- min AEGL

- 1 POD = 2,400 mg/m 3 1

- hr AEGL

- 1 POD = 2,130 mg/m 3 10

- min AEGL

- 2 POD = 6,000 mg/m 3
30

- min AEGL

- 2 POD = 4,200 mg/m 3
1

- hr AEGL

- 2 POD = 2,000 mg/m 3
4

- hr AEGL

- 2 POD = 350 mg/m 3 8

- hr AEGL

- 2 POD = 210 mg/m 3

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 DCM

based paint strippers.

3 AEGL

- 1 POD for 8

- hr is not available since the DCM AEGL technical support doc ument did not derive AEGL

- 1 values for 8

- hrs.P age 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 OCCUPAT I ONAL 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 H azard Value (PODs) for Non

- Cancer Effects (liver effects) :

1 st percentile human equivalent concentration (HEC) i.e. the HEC 99 :

17.2 mg/m 3 (4.8 ppm) H azard Value (PODs) for Cancer Effects (liver and lung tumor

s) :

Inhalation Unit Risk (IUR) : 4 x 10

- 5 per ppm (1 x 10

- 5 per m g/m 3 )

Uncertainty Factors (UF) used in Non

- Cancer Margin of Exposure (MOE) calculations UF for the HEC 99 = 10

UF is not applied for the cancer risk calculations.

Notes:

1 It is ass umed no substantial buildup of DCM in the body between exposure events due to DCM’s short biological half

- life (~40 min).

2 EPA/OPPT believes that the users of these products are generally adults, but younger individuals may be users of DCM

based paint st rippers.

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 t han users, especially when they are further away from the source of exposure.P age 87 of 279

Acute or chronic MOEs (MOE acute or MOE chronic ) were used in this assessment to esti mate non

cancer risks (Table 3

- 13 ).

Table 3

- 13

. Margin of Exp osure (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 = Margi n 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. A cute concentrat ions as expressed as 8

- hr TWA DCM air concentrations were used for acute risks.

Study

- specific UFs were identified for e ach hazard value (i.e., POD)

. These UFs accounted for (1) the variation in susceptibility among the members of the hum an population (i.e., inter

individual or intraspecies variability); (2) the uncertainty in extrapolating animal data to humans (i.e., interspecies uncertainty); and (3) the uncertainty in extrapolating from a LOAEL rather than from a NOAEL

.

The total UF f or 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 wa s less than the benchmark MOE (i.e. the total UF). On the othe r 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 r isks for r epeated exposures to DCM were estimate d 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 i n ppm) from occupational exposure assessment Inhalation unit risk 4 x 10
- 5 per ppm (1 x 10

- 5 per m g/ m 3 ) ( EPA, 2011c )P age 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 occupation al 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

- respo nse 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 as sessment. As discussed in section 3.3.1.3.3, AEGL PODs for the respective tiers (d iscomfort /non

- disabling effects = AEGL

- 1 threshold; disability = AEGL

- 2 threshold; and death = AEGL

- 3 threshold) are selected to represent an estimated point of transition be tween 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 )

. Alth ough 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 threshold s 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 CN S 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 e xposed to DCM , irrespective of the type of product used (i.e., brush

- on vs. spray

on paint stripper ) (Table 3

- 15)

.
Consumers using DCM

- base d 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 b ystanders (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 refini shing project. It was included in the assessment to estimate the DCM air concentrations toP age 89 of 279

residential occupants outside the use zone (i.e., bystanders) under conditions of high product use in the ro om 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

- dis abling (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 Stripp ers :

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/m 3 ) Margin of Exposure (MOE)

1

- hr SMAC POD
Total UF o r 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

- en d 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 paramete r 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 3.9P age 90 of 279

Table 3

- 16

. Acute Risk Estimates for Residential Exposures to DCM

- Based Paint Stripp ers: 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/m 3 Margin of Exposure (MOE)

10

- min 3 0

- 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/m 3 ) 30

- min

(2,400 mg/m 3 ) 1

- hr

(2,130 mg/m 3 ) 10

- min

(6,000 mg/m 3 ) 30

- min

(4,200 mg/m 3 ) 1

- hr

(2,000 mg/m 3 ) 4

- hr

(350 mg/m 3 ) 8

- hr

( 210 mg/m 3 ) 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,

u pper

- 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 76 0 560 400 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 1.4P age 91 of 279

Table 3

- 16

. Acute Risk Estimates for Residential Exposures to DCM

- Based Paint Stripp ers: 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/m 3 Margin of Exposure (MOE)

10

- min 3 0

- 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/m 3 ) 30

- min

(2,400 mg/m 3 ) 1

- hr

(2,130 mg/m 3 ) 10

- min

(6,000 mg/m 3 ) 30

- min

(4,200 mg/m 3 ) 1

- hr

(2,000 mg/m 3 ) 4

- hr

(350 mg/m 3 ) 8

- hr

( 210 mg/m 3 ) 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, simulatio n 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 1.4P age 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 relevan t 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 concentr ations . No risks were found for workers hand l ing DCM

- based strippers in the art restoration and conservation industry (Table 3

- 17)

.

Workers hand l ing DCM

- containing paint strippers with no respirator showed risks for incapacitating effects (AEGL

- 2) when em ployed in all of the relevant industries, except the art restoration and conservation industry (Table 3

- 17). These risks were present with either central tendency or high

- end DCM air concentrations of DCM.

Workers employed in industries with high exposure to DCM [i.e., professional contractors, furniture refinishing, aircraft paint stripping, and immersion stripping of wood (non

- specific workplace settings)] typically showed risks for incapacitating (AEGL

- 2) effects when using APF 10 respirators (Scenario 2) during high exposure conditions. The use of APF 25 respirators (Scenario 3) was not protective for workers employed in the immersion stripping of wood (non

specific workplace settings when DCM air concentrations were as high as 7,000 mg/m 3

.P age 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
Profe ssional Contractors Acute 8

- hr concentration (mg/m 3 ) Acute MOE (8hr

- REL POD=290 mg/m 3 ) Total UF or Benchmark MOE=60 Acute MOE (8hr

- AEGL

- 2 POD=210 mg/m 3 ) 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 3 0 1 5 10 242 4 7 175

Automotive Refinishing Acute 8

- hr concentration (mg/m 3 ) Acute MOE (8hr

- REL POD=290 mg/m 3 ) Total UF or Benchmark MOE=60 Acute MOE (8hr

- AEGL

- 2 POD=210 mg/m 3 ) Total UF or Benchmark MOE=1

Mean High Midpoint Low M ean 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

Sc enario 4 (Respirator, APF 50) 5 8 5 2 57 35 57 161 42 25 42 11 7

Furniture Refinishing Acute 8

- hr concentration (mg/m 3 ) Acute MOE (8hr

- REL POD=290 mg/m 3 ) Total UF or Benchmark MOE=60 Acute MOE (8hr

- AEGL

- 2 POD=210 mg/m 3 ) Total UF or Be nchmark MOE=1
Mean High Midpoint Low Mean High Midpoint Low Mean High Midpoint Low Scenario 1 (No respirator, APF=0) 499 2,24 5 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 2625P age 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/m 3 ) Acute MOE (8hr

- REL POD=290 mg/m 3 ) Total UF or Benchmark MOE=60 Acute MOE (8hr

- AEGL

- 2 POD=210 mg/m 3 ) 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

Sc enario 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/m 3 ) Acute MOE (8hr

- REL POD=290 mg/m 3 ) Total UF or Benchmark MOE=60 Acute MOE (8hr

- AEGL

- 2 PO D=210 mg/m 3 ) 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

Sc enario 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 1 22

Graffitti Removal Acute 8

- hr concentration (mg/m 3 ) Acute MOE (8hr

- REL POD=290 mg/m 3 ) Total UF or Benchmark MOE=60 Acute M OE (8hr

- AEGL

- 2 POD=210 mg/m 3 ) 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 1,18 8 603 18 1 0.2 0.5 16 0.8 0.2 0.4 12

Scenario 2 (Respirator, APF 10) 26 118. 8 6 0.3 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 583P age 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/m 3 ) Acute MOE (8hr

- REL POD=290 mg/m 3 ) Total UF or Benchmark MOE=60 Acute MOE (8hr

- AEGL

- 2 POD=210 mg/m 3 ) 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

- Specif ic Workplace Settings

- Immersion Stripping of Wood and Metal Acute 8

- hr concentration (mg/m 3 ) Acute MOE (8hr

- REL POD=290 mg/m 3 ) Total UF or Benchmark MOE=60 Acute MOE (8hr

- AEGL

- 2 POD=210 mg/m 3 ) 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

S cenario 4 (Respirator, APF 50) 20 17 13 14 18 23 10 13 17

Non

- Specific Workplace Settings

- Unknown Acute 8

- hr concentration (mg/m 3 ) Acute MOE (8hr

- REL POD=290 mg/m 3 ) Total UF or Benchmark MOE=60 Acute MOE (8hr

- AEGL

- 2 POD=210 mg/m 3 ) 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 37P age 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 e xposures 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 estimat e (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. Nev ertheless, 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

- 6 for determining the acceptability of the cancer risk in a population. S ince 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 developi ng 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 s trippers. Selected scenarios ranging from the highest exposure

scena rio (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_0 811 14.xlsx

.
Workers showed excess cancer risks for all of the industries evaluated when working with DCM

based paint strippe rs 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

- 6 target level.P age 97 of 279

On the other ha nd, 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 pai nt 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 Profe ssional Contractors LADC (mg/m 3 )

** LADCs for scenarios 2 to 16 have been adjusted with the multiplier Excess Cancer Risk (Inhalation Unit Risk = 1x10 - 5 per mg/m 3 ) 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 1.9 E

- 05 9.9E

- 06 3.9E

- 07P age 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/m 3 )

** LADCs for scenarios 2 to 16 have been adjusted with the multiplier Excess Cancer Risk (Inhalation Unit Risk = 1x10 - 5 per mg/m 3 ) 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/m 3 )

** LADCs for scenarios 2 to 16 have been adjusted with the multiplier Excess Cancer Risk ( Inhalation Unit Risk = 1x10 - 5 per m g/m 3 ) 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 ra nges 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

- 08P age 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 (m g/m 3 )

** LADCs for scenarios 2 to 16 have been adjusted with the multiplier Excess Cancer Risk (Inhalation Unit Risk = 1 x10 - 5 per mg/m 3 ) 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

Ta ble 3

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

Lowest Exposure Highest Exposure Graffiti Removal LADC (mg/m 3 ) ** LADCs for scenarios 2 to 16 have been adjusted with the multiplier Excess Cancer Risk (Inhalation Unit Risk = 1x10 - 5 per mg/m 3 ) Mean High Midpoint Low Mean High Midpo int 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

- 07P age 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
- I mmersion Stripping of Wood LADC (mg/m 3 ) ** LADCs for scenarios 2 to 16 have been adjusted with the multiplier Excess Cancer Risk (Inhalation Unit Risk = 1x10 - 5 per mg/m 3 )

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

- 07P age 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/m 3 )

** LADCs for scenarios 2 to 16 have been adjusted with the multiplier Excess Cancer Risk (Inhalation Unit Risk = 1x10 - 5 per mg/m 3 )

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

- Spec ific Workplace Settings

— Unknown

(Scenarios 1, 3, 15 and 16)

Lowest Exposure Highest Exposure Non
- Specific

Workplace Settings
- Unknown LADC (mg/m 3 )

** LADCs for scenarios 2 to 16 have been adjusted with the multiplier Excess Cancer Risk (Inhalation Unit Risk = 1x10 - 5 per mg/m 3 )

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 4.7 E

- 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

- 06P age 102 of 279

Table 3

- 26

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

and 16)

Lo west Exposure Highest Exposure Art Restoration and Conservation LADC (mg/m 3 ) ** LADCs for scenarios 2 to 16 have been adjusted with the multiplier Excess Cancer Risk (Inhalation Unit Risk = 1x10 - 5 per mg/m 3 ) Mean High Midpoint Low Mean High Midpoint Low Scenario 1 [No respirator, high ends of ranges for exposure frequency (EF) and working yea rs (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 l iver 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 1 st percentile HEC i.e. the HEC 99 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

- ca ncer MOE estimates calculated for workers of different industries handling DCM

- based paint s trippers on a repeated basis

. S elected s cenarios ranging from the highest exposure scenario (i.e., no respiratory protection and high end values for EF and WY─i.e., Scenario 1) to the lowest exposure scenario (e.g., respiratory protection APF 50 and midpoints for EF and WY─ Scenario 16) were included in the tables. Calculations of non

cancer risk s for the full set of industries and scenarios are provided in the supplemental Excel spreadsheet, DCM Exposure and Risk Estimates_0 811 14.xlsx

.

Most w orkers using DCM

- based paint strippers showed non

- cancer risks for liver effects
, with the exception of w orkers employed in the art renovation and conservation industry ( Table 3

- 30 )

. For instance , r isk concerns for liver effects were reported for most workers handling DCM

-P age 103 of 279

based paint strippers

. These risk findings were reported with or without respiratory pro tection 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.

N on

- 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 respi rator), (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/m 3 ) ** ADCs for scenarios 2 to 16 have been adjusted with the multiplier Chronic MOE (24 hr HEC 99 = 17.2 mg/m 3 ) Total UF or Benchmark MOE= 1 0 High Midpoint Low High Midpoint Low Scenario 1 [No respirator, h igh 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.P age 104 of 279

Table 3

- 28 . Occupational Non

- Cancer Risks for Auto motive Refinishing Following Chronic

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

Lowest Exposure Highest Exposure Automotive

Refinishing ADC (mg/m 3 )

** ADCs for scen arios 2 to 16 have been adjusted with the multiplier Chronic MOE (24hr HEC 99 = 17.2 mg/m 3 ) Total UF or Benchmark MOE= 1 0 Mean High Midpoint Low Mean High Midpoint Low Scenario 1 [No respirator, high ends of ranges for exposure frequency (EF) and wor king 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 Chroni c

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

Lowest Exposure Highest Exposure Furniture

Refinishing ADC (mg/m 3 )

** ADCs for scenarios 2 to 16 have been adjusted wit h the multiplier Chronic MOE (24hr HEC 99 = 17.2 mg/m 3 ) Total UF or Benchmark MOE= 1 0 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 3822P age 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/m 3 ) ** ADCs for scenarios 2 to 16 have been adjusted with the multiplier Chronic MOE (24hr HEC 99 = 17.2 mg /m 3 ) 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) 0.0 2 860

Sc enario 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 belo w 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/m 3 )

** ADCs for scenarios 2 to 16 have been adjusted with the multiplier Chronic MOE (24hr HEC 99 = 17.2 mg/m 3 ) Total UF or Benchmark MOE= 1 0 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 172P age 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/m 3 ) ** ADCs for s cenarios 2 to 16 have been adjusted with the multiplier Chronic MOE (24 hr HEC 99 = 17.2 mg/m 3 ) Total UF or Benchmark MOE= 1 0 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

Sc enario 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/m 3 ) ** ADCs for scenarios 2 to 16 have been adjusted with the multiplier Chronic MOE (24hr HEC 99 = 17.2 mg/m 3 ) Total UF or Benchmark MOE=10

High Midpoint Low High Midpoint Low Scenario 1 [No respirat or, 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 an d 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 430P age 107 of 279

Table 3

- 34 . Occupational Non

- Cancer Risks for Non

- Specific Workplace Settings ( Immersion

Stripping of Wood and Met al ) 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/m 3 )

** ADCs for scenarios 2 to 16 have been adjusted with the multiplier Chronic MOE (24hr HEC 99 = 17.2 mg/m 3 ) Total UF or Benchmark MOE= 1 0

High Midpoint Low High Midpoint Low Scenario 1 [No respirator, high ends of ranges for
exposur e 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 (Respirat or 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 )

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

Lowest Exposure Highest Exposure Non
- Specific

Workplace Settings
- Unknown ADC (mg/m 3 )

** ADCs for scenario s 2 to 16 have been adjusted with the multiplier Chronic MOE (24hr HEC 99 = 17.2 mg/m 3 ) Total UF or Benchmark MOE= 1 0

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 53P age 108 of 2 79



### 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
requ ired to derive non

- cancer risk estimates associated with acute and chronic exposures to DCM

. In addition, c ancer risks were estimated for occupational scenarios and expressed as lifetime risks, meaning the risk of developing cancer as a result of the occup ational exposure over a normal lifetime of 70 yrs. Lifetime cancer risks from DCM exposure were compared to benchmark cancer risks ranging from 10

- 6 to 10

- 4

.
Many of the occupational scenarios exceeded the target cancer risks of 10

- 6 , 10

- 5 and 10

- 4 when workers employed at various industries handled DCM

- paint strippers for 250 days/year for 40 years with no respiratory protection. Adequate respiratory protection and reduced exposure conditions (e.g., exposure to 125 day/year for 20 years) resulted in red uced 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, M OEs 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 effe cts 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 strip pers 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) i n 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 show ed 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.,P age 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 ris ks 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 afte r
com pletion 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, t here were concerns for incapacitating eff ects (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 als o observed for workers wearing respirators (i.e., APF 10 or APF 25) while performing paint stripping activities in industries wi th high DCM air concentrations [i.e., professional contractors, furniture refinishing, aircraft paint stripping, and immersion s tripping 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

- dis abling (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 strip ping task. However, residential bystanders did not report risk concerns for AEGL

- 1 and AEGL

- 2 effects.P age 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 assessmen t. 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 ava ilable 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 confidenc e 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 Uncertain ties in the Occupational Exposure Estimates

U ncertainties 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 50 th and 95 th percentiles for each population. In the absence of percentile data, the air concentration means and midpoints (means are pr eferred over midpoints) of the data sets served as substitutes for 50 th percentiles of the actual distributions, whereas high ends of ranges served as substitutes for 95 th percentiles of the actual distributions.

However, these substitutes are highly unc ertain and are weak substitutes for the ideal percentiles. For instance, in the few cases where enough data were found to determine statistical means and 95 th percentile s ( Appendix G , Table G

- 2 ), the associated substitutes (i.e., midpoints and high ends of ranges) were shown to overestimate expos ures, 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 t he 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 hypoth etical 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, aP age 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 DCM

based strippers only and does not include exposures to DCM from other sources. Evaluation of other DCM uses did not fall within the scope of this assessment.

2. Population Exposed: The estimates of numbers of exposed workers are uncertain. The
most unce rtain 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 num bers 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 inc ludes 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 unc ertainty. 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 mo deled 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 identif ied in ( Brown, 2012 ) . However, these valu es 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 )

.P age 112 of 279

The confidence level is similarly high for the amount of product applied and application rates, wi th 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 80 th percentile value, which should tend to reduce the total exposure estimate.

For the stripp ing 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 retar dant 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 paramete r 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 descripto rs, 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 bathtu b refinishing . Given the model’s sensitivity of concentrations in the ROH to room

- of

- use air exchange and interzonal air flow, there is uncertainty a bout 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.P age 113 of 279



### 3.5.3 Uncertainties in the Hazard and D ose - R esponse Assessments

3.5.3.1 Uncertainties in the Cancer Haz ard/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. F or 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 associatio n between occupational exposure to DCM and increased risk form so me 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 t he IUR. Th e major uncertainties are briefly listed and summarized in Table 3

- 3 6 from information discussed in the DCM IRIS assessment ( EPA, 2011c )

. Note that the information in Table 3

- 3 6 was extracted from Table 5

- 26 in the DCM IRIS assessment, which covered uncertainties for both oral and i nhalation cancer values. Table 3

- 3 6 is only summarizing uncertainties for the cancer IUR. Please refer to the DCM IRIS asses sment 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 inhal ation 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 coul d change the recommended cancer risk values.) Liver and lung were selected as the target organs. Cancer risk values were considered for mammary gland tumors. P otential brain cancer risk and hematopoietic cancer risk were identified as data
gaps. The eviden ce 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

.P age 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.) I nhalation data was used to deriv e IUR. Uncertainty is lower when deriving cancer IUR from inhalation exposure data rather than using route

- to

- route extrapolation from oral data.

Selection of dose metric (Selection of dose metric could change the recommended cancer risk values.) Tissue

- specific GST

metabolism was used as dose metric. Cancer risk estimates based on alternative (whole

- body) metrics also examined. The c ontribution of CYP pathway to cancer risk is unknown, but strong evidence of GST role in carcinogenesis supports focus on this pathway. Values based on tissue

- specific GST metabolism recommended based on evidence of site locality of effects. Dose

- response modeling (Human risk values could increase or decrease, depending on fits of alternative models) The multistage dose

resp onse 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 l inear extrapolat ion of risk in low

dose region. PBPK model incorporates the metabolic shift and expected nonlinearity (GST dose attenuation) in th e exposure

- dose relationship across exposure levels. DCM’s mutagenic mode of action is supported by i n vivo and in vitro studies, resulting in support for the l inear low

- dose extrapolation approach used in the inhalation cancer assessment. Interspecies ex trapolation of dosimetry and risk (Alternative values for PBPK model parameters and cross

species scaling factor could increase or decrease human cancer risk values.) PBPK model and allometric scaling factor were used for the primary dose metric

. Use of ro dent 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 m etabolic 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 variab ility 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 Hazar d/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 m ay respond differentlyP age 115 of 279

to DCM exposure in terms of dose, magnitude o f response, or different response. Thus, the MOEs presented for the acute occupational and consumer exposure scenarios may under

- or
over estimate risk to younger age groups for this endpoi nt.

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 a dditional studies are published. These uncertainties are minimized in the SMAC POD by co nsidering multiple human observations report ing 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 combinat ion 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 (C n *t=k) 20 and PBPK modeling, respectively, to adjust the experimental exposure duration to the desired acute e xposure duration relevant for risk assessment purposes. It is possible that the time extrapolation approach may not accurately represent the concentration

- time

response relationship of DCM.

3.5.3.2.2 Uncertainties in the Chronic Hazard/Dose

- Response Assessments

Th ere 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 iden tified 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 , the re is a paucity of data on chronic neurological impacts, especially developmental neurotoxicity. Likewise, there is limited informat i on about immunotoxicity following chronic exposure to DCM. E xisting 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 h uman 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 B erge equation ( C n * T = k, n = 2) , C = concentration of the chemical of interest, n=chemica l

- specific exponent, t=time, and k=constant (NRC, 2001).P age 116 of 279

The dose metric used in the models is the rate of metabolism to a putative toxic metabolite rather than its concentration expresse d as the average or area under the concentratio n curve of the metabolite. The selected dose

- metric fails to account for rod ent

- 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 res earch question represents a data gap, and the DCM IRIS assessment did not address this uncertainty
qu antitatively 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 pharm acokinetic differences. The model and resulting distributions considered the known differences in human physiology and metabolic capability with regard to DCM dosime try. The first percentile value of the distributions of HECs served as the non

- cancer POD t o protect toxicoki netically sensitive individuals

. The model did not address toxicodynamic diff erences 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 dep endent 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 (UF A ): The UF A accounts for the uncertainties in extrapolating from rodents to humans. In the absence of data, the default UF A 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 exposur e to DCM) , t he 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 ad dress interspecies toxicodynamic differences, the total UF A of 3 was retained ( EPA, 2011c )

.

2. Inter

- individual variation (UF H ): The UF H accounts for the variation in sensitivity within the human population. In the absence of data, the default UF H of 10 is adopted which breaksP age 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 UF H 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 toxi codynamics variability ( EPA, 2011c )

.
In the absence of PBPK modeling, a UF H of 10 was retained for the SMAC and the Califo rnia 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 UF H of 3 and 1 were used for the AEGL

- 1 and

- 2 PODs, respectively. Since susceptibility for gross CNS

depressing effects do not vary by more than a factor of 2

- to 3

- fold in humans, a UF H of 3 was applied for the AEGL

- 1 POD ( NAC, 2008 )

. On the other hand, a UF H 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 inconsis tent 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), w hich is also protective for other h uman subpopulations ( NRC, 2008 , 2010 )

.

3. LOAEL

- to

- NOAEL extrapolation (UF L ): The UF L accounts for the uncertainty in extrapolating from a LOAEL to a NOAEL. A value of 10 is the standard default UF L 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 UF L of 6 to the California acute REL POD to generate a NOAEL ( OEHHA, 2008 ) , but the basis for the valu e selection was not explained. EPA/OPPT retained the UF L of 6 as part of the compos ite 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. A lso, 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 hypotheti cal 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

.P age 118 of 279

Re garding 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 sele cted 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 cum ulative 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 t o other availabl e 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 )

.P age 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 assessmen t 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 occupationa l scenarios exceed at least one of the target cancer risks of 10

- 4

, 10

- 5 and 10

- 6

.

 The greatest cancer risk s occur for workers handling DCM

- based paint strippers with no respiratory protection for an extended period of time.

Non

- Cancer Risks Associated W ith 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.

 N on

- cancer risks occur for most worker s 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 pro tection 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 r isks for neurological effects for most workers using DCM

- based paint strippers . These risks are apparent i n 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 areP age 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 inca pacitating 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.

 A pplication of DCM

- based paint strippers in a bathroom generate s unsafe exposure conditions for the user of the product , but not residential bystanders

. DCM concentrations may reac h 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 inter nal dose build s up in the body over time.P age 121 of 279



## 4 References

ACGIH (American Conference of Governmental Industrial Hygienists). 2001. Documentation of the Threshold Limit Values and Biological Exposure Indices for Dichloromethane

. Cincinnat i, OH. (as cited in EPA, 2011c).

Alexander, H. C., W. M. McCarty, and E. A. Bartlett. 1978. Toxicity of Perchloroethylene, Trichloroethylene, 1,1,1

- Trichloroethane, and Methylene Chloride to Fathead Minnows

. Bulletin of Environmental Contamination and Tox icology, 20(3), 344

- 352.

Alexeeff, G. V., and W. W. Kilgore. 1983. Learning Impairment in Mice Following Acute Exposure to Dichloromethane and Carbon Tetrachloride . Journal of Toxicology and Environmental Health, 11(4

- 6), 569

- 581. (as cited in EPA, 2011c)

.
Allred, E. N., E. R. Bleecker, B. R. Chaitman, T. E. Dahms, S. O. Gottlieb, J. D. Hackney, D. Hayes, M. Pagano, R. H. Selvester, S. M. Walden, and J. Warren. 1989a. Acute Effects of Carbon Monoxide Exposure on Individuals with Coronary Artery Disease . R esearch Report No. 25. Health Effects Institute, Cambridge, MA. (as cited in NRC, 2010).

Allred, E. N., E. R. Bleecker, B. R. Chaitman, T. E. Dahms, S. O. Gottlieb, J. D. Hackney, M. Pagano, R. H. Selvester, S. M. Walden, and J. Warren. 1989b. Short

- Term Effects of Carbon Monoxide Exposure on the Exercise Performance of Subjects with Coronary Artery Disease . The New England Journal of Medicine, 321(23), 1426

- 1432. (as cited in NRC, 2010).

Allred, E. N., E. R. Bleecker, B. R. Chaitman, T. E. Dahms, S. O. G ottlieb, J. D. Hackney, M. Pagano, R. H. Selvester, S. M. Walden, and J. Warren. 1991. Effects of Carbon Monoxide on Myocardial Ischemia . Environmental Health Perspectives, 91, 89

- 132. (as cited in NRC, 2010).

Andersen, M. E., H. J. Clewell, 3rd, M. L. Ga rgas, M. G. MacNaughton, R. H. Reitz, R. J. Nolan, and M. J. McKenna. 1991. Physiologically Based Pharmacokinetic Modeling with Dichloromethane, Its Metabolite, Carbon Monoxide, and Blood Carboxyhemoglobin in Rats and Humans . Toxicology and Applied Pharmac ology, 108(1), 14

- 27. (as cited in NAC, 2008 and NRC, 1996).

Anderson, E. W., R. J. Andelman, J. M. Strauch, N. J. Fortuin, and J. H. Knelson. 1973. Effect of Low

- Level Carbon Monoxide Exposure on Onset and Duration of Angina Pectoris. A Study in Ten Pati ents with Ischemic Heart Disease . Annals of Internal Medicine, 79(1), 46

- 50. (as cited in NRC, 2010).P age 122 of 279

Anundi, H., S. Langworth, G. Johanson, M. L. Lind, B. Akesson, L. Friis, N. Itkes, E. Soderman, B. A. Jonsson, and C. Edling. 2000. Air and Biological Mo nitoring of Solvent Exposure During Graffiti Removal . Int Arch Occup Environ Health, 73(8), 561

- 569.

Anundi, H., M. L. Lind, L. Friis, N. Itkes, S. Langworth, and C. Edling. 1993. High Exposures to Organic Solvents among Graffiti Removers . Int Arch Occup Environ Health, 65(4), 247

- 251.

Aranyi, C., W. J. O'Shea, J. A. Graham, and F. J. Miller. 1986. The Effects of Inhalation of Organic Chemical Air Contaminants on Murine Lung Host Defenses . Fundamental and Applied Toxicology, 6(4), 713

- 720. (as cited in EP A, 2011c).

Aronow, W. S., C. N. Harris, M. W. Isbell, S. N. Rokaw, and B. Imparato. 1972. Effect of Freeway Travel on Angina Pectoris . Annals of Internal Medicine, 77(5), 669

- 676. (as cited in NRC, 2010).

Ash, M., and I. Ash. 2009. Methylene Chloride. In Specialty Chemicals Monographs (pp. 1361). Synapse Information Resources, Inc., Endicott, NY.

ASTM (ASTM International). 1997. Standard Practice for Estimation of Short

- Term Inhalation Exposure to Volatile Organic Chemicals Emitted from Bedding Sets . Des ignation: D 6178

- 97 (Reapproved 2008). West Conshohocken, PA.

Astrand, I., P. Ovrum, and A. Carlsson. 1975. Exposure to Methylene Chloride. I. Its Concentration in Alveolar Air and Blood During Rest and Exercise and Its Metabolism

. Scandinavian Journal o f Work, Environment & Health, 1(2), 78

- 94. (as cited in NRC, 1996).

ATSDR (Agency for Toxic Substances and Disease Registry). 1990. Methylene Chloride Toxicity. Case Studies in Environmental Medicine . PB 85

- 241529. U.S. Department of Health and Human Serv ices, Atlanta, GA. (as cited in ATSDR, 2000).

ATSDR (Agency for Toxic Substances and Disease Registry). 2000. Toxicological Profile for Methylene Chloride . Division of Toxicology/Toxicology Information Branch, Atlanta, GA. http://www.atsdr.cdc.gov/toxprofiles/tp14.pdf

. ATSDR (Agency for Toxic Substances and Disease Registry, U.S. Department of Health and Human Services). 2010. Addendum to the Toxicological Profile for Methylene Chloride

. Divisi on of Toxicology and Environmental Medicine, Atlanta, GA. http://www.atsdr.cdc.gov/toxprofiles/methylene_chloride_addendum.pdf

.
Barone, S., Jr., K. P. Das, T. L. Lassiter , and L. D. White. 2000. Vulnerable Processes of Nervous System Development: A Review of Markers and Methods . Neurotoxicology, 21(1

- 2), 15

- 36.P age 123 of 279

Barry, K. H., Y. Zhang, Q. Lan, S. H. Zahm, T. R. Holford, B. Leaderer, P. Boyle, H. D. Hosgood, 3rd, S. Chanock , M. Yeager, N. Rothman, and T. Zheng. 2011. Genetic Variation in Metabolic Genes, Occupational Solvent Exposure, and Risk of Non

- Hodgkin Lymphoma

. American Journal of Epidemiology, 173(4), 404

- 413. (as cited in EPA, 2011c).

Bornschein, R. L., L. Hastings , and J. M. Manson. 1980. Behavioral Toxicity in the Offspring of Rats Following Maternal Exposure to Dichloromethane . Toxicology and Applied Pharmacology, 52(1), 29

- 37. (as cited in EPA, 2011c).

Bos, P. M., M. J. Zeilmaker, and J. C. van Eijkeren. 2006. Application of Physiologically Based Pharmacokinetic Modeling in Setting Acute Exposure Guideline Levels for Methylene Chloride . Toxicological Sciences, 91(2), 576

- 585. (as cited in EPA, 2011c).

Brown, J. (U.S. Environmental Protection Agency). Formulatio ns Spreadsheet File . Personal communication with: Conrad, F. (U.S. Environmental Protection Agency, Washington, DC), June 2012.

Buccafusco, R. J., S. J. Ells, and G. A. LeBlanc. 1981. Acute Toxicology of Priority Pollutants to Bluegill (Lepomis Macrochiru s) . Bulletin of Environmental Contamination and Toxicology, 26(4), 446

- 452.

Burek, J. D., K. D. Nitschke, T. J. Bell, D. L. Wackerle, R. C. Childs, J. E. Beyer, D. A. Dittenber, L. W. Rampy, and M. J. McKenna. 1984. Methylene Chloride: A Two

- Year Inhalati on Toxicity and Oncogenicity Study in Rats and Hamsters . Fundamental and Applied Toxicology, 4(1), 30

- 47.

Cal EPA (California Environmental Protection Agency). 2000. Public Health Goals for Chemicals in Drinking Water. Dichloromethane (Methylene Chloride, DCM) . Office of Environmental Health Hazard Assessment, Sacramento, CA. http://oehha.ca.gov/water/phg/pdf/dcm.pdf

.
Carlsson, A., and M. Hultengren. 1975. Exposure to Methylene Chloride. Metabolism of 14c

Labelled Methylene Chloride in Rat . Scandinavian Journal of Work, Environment & Health, 1(2), 104

- 108. (as cited in ATSDR, 2000).

CDC (Centers for Disease Control and Prevention). 2009. Fourth National Report on Human Exposure to Environmental Che micals . Department of Health and Human Services, Atlanta, GA. http://www.cdc.gov/exposurereport/pdf/FourthReport.pdf

. CDC (Centers for Disease Control and Prevention). 2012. Tub Refini sher Died Due to Methylene Chloride Overexposure While Stripping a Bathtub . Michigan case report: 10MI013. Atlanta, GA. http://www.cdc.gov/niosh/face/stateface/mi/10MI013.html

.P age 124 of 279

CDHS/E PA (California Department of Health Services/U.S. Environmental Protection Agency). 2006. Assessment, Development and Demonstration of Alternatives for Five Emerging Solvents . Prepared by the Institute for Research and Technical Assistance for the Californ ia Department of Health Services and U.S. Environmental Protection Agency. www.cdph.ca.gov/programs/hesis/Documents/emergingsolvents.pdf

.
Chen, Q., and W. Xu. 1998. A Zer o

- Equation Turbulence Model for Indoor Airflow Simulation

. Energy and Buildings, 28(2), 137

- 144.

Cheng, K. C., V. Acevedo

- Bolton, R. T. Jiang, N. E. Klepeis, W. R. Ott, O. B. Fringer, and L. M. Hildemann. 2011. Modeling Exposure Close to Air Pollution Sou rces in Naturally Ventilated Residences: Association of Turbulent Diffusion Coefficient with Air Change Rate . Environ Sci Technol, 45(9), 4016

- 4022.

Cherrie, J. W. 1999. The Effect of Room Size and General Ventilation on the Relationship between near and Far

- Field Concentrations . Appl Occup Environ Hyg, 14(8), 539

- 546.

Cherry, N., H. Venables, and H. A. Waldron. 1983. The Acute Behavioural Effects of Solvent Exposure . The Journal of the Society of Occupational Medicine, 33(1), 13

- 18. (as cited in EPA, 201 1c).

Cherry, N., H. Venables, H. A. Waldron, and G. G. Wells. 1981. Some Observations on Workers Exposed to Methylene Chloride . British Journal of Industrial Medicine, 38(4), 351

- 355. (as cited in EPA, 2011c).

Chester, D., K. D. Rosenman, G. R. Grimes, K . Fagan, and D. N. Castillo. 2012. Fatal Exposure to Methylene Chloride among Bathtub Refinishers

- United States, 2000

– 2011 . Morbidity and Mortality Weekly Report, 61(7), 119

- 122.

CPSC (U.S. Consumer Product Safety Commission). 1987. Statement of Policy f or Methylene Chloride . Washington, DC. http://www.cpsc.gov/en/newsroom/news

releases/1987/statement

- of

- policy

- for

- methylene

- chloride/ (Accessed J une 19, 2014).

CPSC (U.S. Consumer Product Safety Commission). 1992. Methylene Chloride Consumer Products Use Survey Findings . Prepared by L. Boast from Abt Associates, Inc., for the U.S. Consumer Product Safety Commission, Bethesda, MD.

DHHS (Department of Health and Human Services). 2012. Household Products Database

. Bethesda, MD. http://householdproducts.nlm.nih.gov/ (accessed in June 2014).

Dill, D. C., P. G. Murphy, and M. A. Mayes. 1987. Toxicit y of Methylene Chloride to Life Stages of the Fathead Minnow, Pimephales Promelas Rafinesque . Bulletin of Environmental Contamination and Toxicology, 39(5), 869

- 876.P age 125 of 279

Dilling, W. L., N. B. Tefertiller, and G. J. Kallos. 1975. Evaporation Rates and Reactivi ties of Methylene Chloride, Chloroform, 1,1,1

- Trichloroethane, Trichloroethylene, Tetrachloroethylene, and Other Chlorinated Compounds in Dilute Aqueous Solutions

. Environ Sci Technol, 9(9), 833

- 838.

DiVincenzo, G. D., and C. J. Kaplan. 1981. Uptake, Meta bolism, and Elimination of Methylene Chloride Vapor by Humans . Toxicology and Applied Pharmacology, 59(1), 130

- 140. (as cited in NAC, 2008 and NRC, 1996).

DiVincenzo, G. D., F. J. Yanno, and B. D. Astill. 1972. Human and Canine Exposures to Methylene Chlo ride Vapor . American Industrial Hygiene Association Journal, 33(3), 125

- 135. (as cited in ATSDR, 2000 and NAC, 2008).

Dow. 1999. Alternatives to Chlorinated Solvents . Dow Newsletter, 3(4), 1

- 4.

DTSC (California Department of Toxic Control Substances). 20 10. Chemical Lists . Sacramento, CA. https://dtsc.ca.gov/SCP/ChemList.cfm (accessed on July 9, 2014).

DuPont (DuPont Chemical Company). 1982. Inhalation Approximate Lethal Concentration of Methylene Chloride with Cover Letter Dated 081092 . Study conducted by Haskell Laboratories,(July 23, 1982), Newark, DE. Doc #88

- 920009163. (as cited in NAC, 2008).

EC (European Commision). 1999. Methylene Chloride: Advantages and Drawbacks of Possible Market Restrictions in the EU. STB

- 99

- 53 Final. Brussels, Belgium.

EC (European Commission). 2004. Effectiveness of Vapour Retardants in Reducing Risks to Human Health from Paint Strippers Containing Dichloromethane . Brussels, Belgium.

EC (European Commission). 2010. Commission Regulation (EU) No 276/2010 of 31 March 2010 Amending Regulation (EC) No 1907/2006 of the European Parliament and of the Council on the Registration, Evaluation, Authorisation and Restriction of Chemicals (Reach) as Regards Annex Xvii (Dichloromethane, Lamp Oils and Grill Lighter Fluids and Organosta nnic Compounds) . Official Journal of the European Union. http://eur

lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:086:0007:0012:en:PDF

. ECB (Europe an Chemicals Bureau). 2000. IUCLID Dataset for Dichloromethane . European Chemical Substances Information System, Joint Research Centre, Institute for Health and Consumer Protection, European Chemicals Bureau, Helsinki, Finland.

ECHA (European Chemicals Ag ency). 2011. Proposal for Identification of a Substance as a Category 1a or 1b CMR, PBT, vPvB or a Substance of an Equivalent Level of Concern: Annex Xv Dossier: Identification of 1

- Methyl

- 2

- Pyrrolidone as SVHC . Helsinki, Finland.P age 126 of 279

Enander, R. T., H. J. Co hen, D. M. Gute, L. C. Brown, A. M. Desmaris, and R. Missaghian. 2004. Lead and Methylene Chloride Exposures among Automotive Repair Technicians . Journal of occupational and environmental hygiene, 1(2), 119

- 125.

Environment Canada. 2003a. Code of Practice for the Reduction of Dichloromethane Emissions from the Use of Paint Strippers in Commercial Furniture Refinishing and Other Stripping Applications . EPS 1/CC/4. June 2003, Ottawa, Canada. http://www.ec.gc.ca/lcpe

cepa/default.asp?lang=En&n=B7812356

- 1

.

Environment Canada. 2003b. Notice Requiring the Preparation and Implementation of Pollution Prevention Plans in Respect of Dichloromethane, November 29, 2003 . Ottawa, Canada. http://www.ec.gc.ca/planp2

- p2plan/default.asp?lang=En&n=540C2673

- 1

. EPA (US Environmental Protection Agency). 1978. In

- Depth Studies on Health and Environmental Impacts of Sele cted Water Pollutants . Duluth, MN.

EPA (US Environmental Protection Agency). 1980. Acquisition and Chemical Analysis of Mother’s Milk for Selected Toxic Substances . EPA 560/13

- 80

- 029 Office of Pesticides and Toxic Substances, Washington, DC. (as cited in ATSDR, 2000).

EPA (US Environmental Protection Agency). 1986a. Guidelines for Mutagenicity Risk Assessment . EPA/630/R

- 98/003. Risk Assessment Forum, Washington, DC. http://www.epa.gov/iris/backgrd.html

. (as cited in EPA, 2011c).

EPA (US Environmental Agency). 1986b. Guidelines for the Health Risk Assessment of Chemical Mixtures . EPA/630/R

- 98/002. Risk Assessment Forum, Washington, DC. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=22567 . (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 1987. Household Solvent Products: A National Usage Survey . Office of Toxic Substances, Washington, DC.

EPA (US Environment al Protection Agency). 1988. Recommendations for and Documentation of Biological Values for Use in Risk Assessment . EPA/600/6

- 87/008. Office of Research and Development, Cincinnati, OH. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=34855 . (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 1991. Guidelines for Developmental Toxicity Risk Assessment . EPA/600/FR

- 91/001. Risk Assessment Forum, Washington, DC. http://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=4560 . (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 1992a. Classification Criteria for Environmental Toxicity and Fate of Industrial Chemical . Office of Pollution Prevention and Toxics, Washington, DC.P age 127 of 279

EPA (US Environmental Protection Agency). 1992b. Guidelines for Exposure Assessment

. EPA/600/Z

- 92

- 001. Risk Assessment Forum, Washington, DC. http://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=429103

. EPA (US Enviornmental Protection Agency). 1993a. Draft Guidance on LADDs and APDRs . Office of Pollution Prevention and T oxics, Washington, DC.

EPA (US Environmental Protection Agency). 1993b. Locating and Estimating Air Emissions from Sources of Methylene Chloride . EPA

- 454/R

- 93

- 006. Office of Air Quality Planning and Standards, Research Triangle Park, NC.

EPA (US Environm ental Protection Agency). 1994a. Consumer Exposure to Paint Stripper Solvents . Office of Pollution Prevention and Toxics, Washington, DC.

EPA (US Environmental Protection Agency). 1994b. Interim Policy for Particle Size and Limit Concentration Issues in I nhalation Toxicity Studies . Office of Pesticide Products, Washington, DC. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=186068 . (as cited in EPA, 2011c).

EPA (US Environmenta l Protection Agency). 1994c. Methods for Derivation of Inhalation Reference Concentrations and Application of Inhalation Dosimetry . EPA/600/8

- 90/066F. Office of Research and Development, Research Triangle Park, NC. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=71993 . (as cited in EPA, 2011c).

EPA (US Enviornmental Protection Agency). 1994d. OPPT Chemical Fact Sheet. Chemicals in the Environment: Methylene Chloride (Dichlorometh ane) (CAS No. 75

- 09

- 2) . EPA 749

- F

- 94

- 018. Office of Pollution Prevention and Toxics, Washington, DC. www.epa.gov/chemfact/f_dcm.txt

. EPA (US Environmental Protection Agency). 1995a. Estimation of Distr ibutions for Residential Air Exchange Rates . Office of Pollution Prevention and Toxics, Washington, DC. http://nepis.epa.gov/Exe/ZyNET.exe/910063GS.TXT?ZyActionD=ZyDocument&Client=EP A&Index=1995+Thru+1999&Docs=&Query=&Time=&EndTime=&SearchM ethod=1&Toc Restrict=n&Toc=&TocEntry=&QField=&QFieldYear=&QFieldMonth=&QFieldDay=&IntQFi eldOp=0&ExtQFieldOp=0&XmlQuery=&File=D%3A%5Czyfiles%5CIndex%20Data%5C95th ru99%5CTxt%5C00000025%5C910063GS.txt&User=ANONYMOUS&Password=anonymo us&SortMethod=h%7C

- &MaximumD ocuments=1&FuzzyDegree=0&ImageQuality=r75g8/r75g8/x150y150g16/i4 25&Display=p%7Cf&DefSeekPage=x&SearchBack=ZyActionL&Back

. EPA (U S Environmental Protection Agency). 1995b. The Use of the Benchmark Dose Approach in Health Risk Assessment . EPA/630/R

- 94/007. Risk Assessment Forum, Washington, DC.P age 128 of 279

http://www.epa.gov/raf/publications/useof

- bda

- healthrisk.htm . (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 1996a. C onsumer/Small Shop Paint Stripping Use Cluster. Draft Risk Assessment Report: Engineering Assessment . Chemical Engineering Branch, Economics, Exposure and Technology Division, Washington, DC.

EPA (US Environmental Protection Agency). 1996b. Guidelines for Reproductive Toxicity Risk Assessment . EPA/630/R

- 96/009. Risk Assessment Forum, Washington, DC. http://www.epa.gov/raf/publications/pdfs/REPRO51.PDF . (as cited in EPA, 2011c).

EPA (US E nvironmental Protection Agency). 1997. Use of Small Chamber Data to Estimate and Model Chemical Emissions from Latex and Alkyd Paints . Prepared by GEOMET Technologies, Inc., under EPA contract# 68

- D3

- 0013 for the Office of Pollution Prevention and Toxics, Washington, DC.

EPA (U S Environmental Protection Agency). 1998a. Guidelines for Neurotoxicity Risk Assessment . EPA/630/R

- 95/001F. Risk Assessment Forum, Washington, DC. http://www.epa.go v/raf/publications/pdfs/NEUROTOX.PDF . (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 1998b. Methods for Exposure

- Response Analysis for Acute Inhalation Exposure to Chemicals (External Review Draft) . EPA/600/R

- 98/051. Office of Resear ch and Development, Washington, DC.

EPA (US Environmental Protection Agency). 1999. Category for Persistent, Bioacculative, and Toxic New Chemical Substances . 64 Federal Register 213 (November 4, 1999), pp. 60194

- 60204.

EPA (US Environmental Protection A gency). 2000a. Air Quality Criteria for Carbon Monoxide

. EPA 600/P

- 99/001F. Office of Research and Development, Washington, DC. http://www.epa.gov/NCEA/pdfs/coaqcd.pdf . (as cited in NRC, 2010).

EPA ( US Environmental Protection Agency). 2000b. Benchmark Dose Technical Guidance Document [External Review Draft] . EPA/630/R

- 00/001. Risk Assessment Forum, Washington, DC. http:// www.epa.gov/raf/publications/benchmark

- dose

- doc

- draft.htm

. (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 2000c. Science Policy Council Handbook: Risk Characterization . EPA/100/B

- 00/002. Office of Science Policy, Washington, DC. http://www.epa.gov/osa/spc/pdfs/rchandbk.pdf . (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 2000d. Supplementary Guidance for Conducting Health Risk Assessment of Chemical Mixt ures . EPA/630/R

- 00/002. Risk AssessmentP age 129 of 279

Forum, Washington, DC. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=20533

. (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 2001. Risk Assessment Guidance for Superfund: Volume 3

- Part a, Process for Conducting Probabilistic Risk Assessment . EPA/540

- R

- 02

- 002. Office of Emergency and Remedial Response, Washington, DC. http://www.epa.gov/oswer/riskassessment/rags3adt/

. EPA (US Environmental Protection Agency). 2002. A Review of the Reference Dose and Reference Concentration Processes . EPA/630/P

- 02/002F. Risk Assessment Forum, Washington, DC. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=51717 . (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 2003. Source Ranking Database, Volume 1: Guide and Documentation . O ffice of Pollution Prevention and Toxics, Washington, DC. http://www.epa.gov/oppt/exposure/pubs/srd.htm

. EPA (US Environmental Protection Agency). 2005a. Guidelines for Carcinogen Risk Assessme nt

. EPA/630/P

- 03/001F. Risk Assessment Forum, Washington, DC. http://www.epa.gov/cancerguidelines/ . (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 2005b. Supplemental Guidance for A ssessing Susceptibility from Early

- Life Exposure to Carcinogens . EPA/630/R

- 03/003F. Risk Assessment Forum, Washington, DC. http://www.epa.gov/cancerguidelines/guideline s

carcinogen

- supplement.htm . (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 2006a. A Framework for Assessing Health Risk of Environmental Exposures to Children . EPA/600/R

- 05/093F. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=158363 . (as cited in EPA, 2011c).

EPA (US Environmental Protection Agency). 2006b. Peer Review Handbook (3rd Edition)

. EPA/100/B

- 06/002. Science Policy Council, Washington, DC. http://www.epa.gov/peerreview/pdfs/peer_review_handbook_2006.pdf . (as cited in EP A, 2011c).

EPA (US Enviornmental Protection Agency). 2006c. Proposed Test Rule for Certain Chemicals on the ATSDR/EPA CERCLA Priority List of Hazardous Substances . 71 Federal Register 203 (October 20, 2006), pp. 61926

- 61944.

EPA (US Environmental Protect ion Agency). 2007. Technical Support Document for Proposed Rule: National Emission Standards for Hazardous Air Pollutants: Paint Stripping Operations at Area Sources . OAQPS/Sector Policies and Programs Division, ResearchP age 130 of 279

Triangle Park, NC. http://www.regulations.gov/#!documentDetail;D=EPA

- HQ

- OAR

- 2005

- 0526

- 0159

. EPA (US Environmental Protection Agency). 2008. National Emission Standards for Hazardous Air Pollutants: Paint Stripping and Miscellaneous Surface Coating Operations at Area Sources . 73 Federal Register 6 (January 9, 2008), pp. 1738

- 1768.

EPA (US Environmental Protection Agency). 2009. Risk Assessment Guidance for Superfund. Volume I: Human Health Evaluatio n Manual (Part F, Supplemental Guidance for Inhalation Risk Assessment) . EPA

- 540

- R

- 070

- 002. Office of Superfund Remediation and Technology Innovation, Washington, DC.

w ww.epa.gov/oswer/riskassessment/ragsf/pdf/partf_200901_final.pdf

. EPA (US Environmental Protection Agency). 2010a. Multi

- Chamber Concentration and Exposure Model (MCCEM) Version 1.2 . Washington, DC. http://www.epa.gov/oppt/exposure/pubs/mccem.htm (accessed on October 31, 2012).

EPA (US Environmental Protection Agency). 2010b. National Primary Drinking Water Regulations . 40 CFR 141.61, Washington, DC. http://www.gpo.gov/fdsys/pkg/CFR

- 2010

- title40

- vol1/content

- detail.html

. EPA (US Environmental Protection Agency). 2011a. Exposure Factors Handbook . EPA/600R

090052F. National Center for Environmental Assessmen t, Office of Research and Development, Washington, DC. http://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=236252

. EPA (US Environmental Protection Agency). 2011b. Integrated Ris k Information System (IRIS) Glossary . National Center for Environmental Assessment, Office of Research and Development, Washington, DC. http://ofmpub.epa.gov/sor_internet/registry/termreg/searchandretrieve/glossariesand keywordlists/search.do?details=&glossaryName=IRIS%20Glossary (accessed on March 1, 2014).

EPA (US Environmental Protection Agency). 2011c. Toxicological Review of Dichloromethane (Methylene Chloride; CAS No. 75

- 09

- 2) . EPA/635/R

- 10/003F. Integrated Risk Information System, Office of Research and Development, Washington, DC. ht tp://www.epa.gov/iris/toxreviews/0070tr.pdf

. EPA (US Environmental Protection Agency). 2011d. TRI.Net . Washington, DC. http://www.epa.gov/tri/tridotnet/index.html (accessed on August 15, 2012).

EPA (US Environmental Protection Agency). 2011e. TSCA Inventory Update Modifications; Chemical Data Reporting . 76 Federal Register 158, pp. 50816

- 50879.P age 131 of 279

EPA (US Environmental Protection Agency). 2012a. Benchmark Dose Technical Guidance

. EPA/100/R

- 12/001. Risk Assessment Forum, Washington, DC. http://www.epa.gov/raf/publications/pdfs/benchmark_dose_guidance.pdf

. EPA (US Environmental Protection Agency). 2012b. Estimation Programs Interface SuiteTM for Microsoft® Windows, V4.10 . Office of Pollution Prevention and Toxics, Washington, DC. http://www.epa.gov/opptintr/exposure/pubs/episuitedl.htm (accessed on March 19, 2012).

EPA (US Environmental Protection Agency). 2012c. Identification and Listing of Hazardous Waste . 40 CFR 261, Washington, DC. http://www.gpo.gov/fdsys/pkg/CFR

- 2012

- title40

- vol27/xml/CFR

- 2012

- title40

- vol27

- part261.xml#seqnum261.30

. EPA (US Environmental Protection Agency). 2012d. TSCA Work Plan Chemicals: Methods Document . Office of Pollution Prevention and Toxics, Washington, DC. www.epa.gov/oppt/existingchemicals/pubs/wpmethods.pdf

. EPA (US Environmental Protection Agency). 2013. 2012 Chemical Data Report (CDR)

. Washington, DC. http://www.epa.gov/tri/index.htm (accessed in June 2014).

EPA (US Environmental Protection Agency). 2014. Toxic Chemical Release Reporting: Community Right

- to

- Know . 40 CFR 372.65, Washington, DC. http://www.ecfr.gov/cgi

bin/text

- idx?c=ecfr&tpl=/ecfrbrowse/Title40/40cfr372_main_02.tpl

.
Estill, C. F., and A. B. Spencer. 1996. Case Study: Control of Methylene Chlorid e Exposures During Furniture Stripping . Am Ind Hyg Assoc J, 57(1), 43

- 49.

EU (European Commission). 2007. Impact Assessment of Potential Restrictions on the Marketing and Use of Dichloromethane in Paint Strippers. Revised Final Report

- Annexes

. Directorate

- General Enterprise and Industry. http://ec.europa.eu/enterprise/sectors/chemicals/files/markrestr/j549_dcm_annex_en. pdf

. FDA (U.S. Food and Drug Admini stration). 1989. Use of Methylene Chloride as an Ingredient of Cosmetic Products . Washington, DC. http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSear ch.cfm?fr=700.19

.
Fisher, J., D. Mahle, L. Bankston, R. Greene, and J. Gearhart. 1997. Lactational Transfer of Volatile Chemicals in Breast Milk . American Industrial Hygiene Association Journal, 58(6), 425

- 431. (as cited in ATSDR, 2000).

Forster, P., V. Ramaswamy, P. Artaxo, T. Berntsen, R. Betts, D.W. Fahey, J. Haywood, J. Lean, D.C. Lowe, G. Myhre, J. Nganga, R. Prinn, G. Raga, M. Schulz and R. Van Dorland. 2007. Changes in Atmospheric Constituents and in Radiative Forcing. In Solomon, S., D. Qin, M.P age 132 of 279

M anning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller, Climate Change 2007: The Physical Science Basis . Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Pres s, Cambridge, United Kingdom and New York, NY, USA. http://www.ipcc.ch/pdf/assessment

- report/ar4/wg1/ar4_wg1_full_report.pdf

.
Frey, H. C., and S. R. Patil. 2002. Iden tification and Review of Sensitivity Analysis Methods . Risk analysis : an official publication of the Society for Risk Analysis, 22(3), 553

- 578.

Furtaw, E. J., Jr., M. D. Pandian, D. R. Nelson, and J. V. Behar. 1996. Modeling Indoor Air Concentrations nea r Emission Sources in Imperfectly Mixed Rooms . J Air Waste Manag Assoc, 46(9), 861

- 868.

Gamberale, F., G. Annwall, and M. Hultengren. 1975. Exposure to Methylene Chloride: Psychological Functions . Scandinavian Journal of Work, Environment & Health, 1(2), 95

- 103. (as cited in EPA, 2011c and NAC, 2008).

Garte, S., and F. Crosti. 1999. A Nomenclature System for Metabolic Gene Polymorphisms . IARC Scientific Publications(148), 5

- 12. (as cited in ATSDR, 2000).

Geiger, D. L., S. H. Poirier, L. T. Brooke, and D. J. Call. 1986. Acute Toxicities of Organic Chemicals to Fathead Minnows (Pimephales Promelas) . Superior, WI: Center for Lake Superior Environmental Studies, University of Wisconsin.

Gold, L. S., P. A. Stewart, K. Milliken, M. Purdue, R. Severson, N. Seix as, A. Blair, P. Hartge, S. Davis, and A. J. De Roos. 2011. The Relationship between Multiple Myeloma and Occupational Exposure to Six Chlorinated Solvents . Occupational and Environmental Medicine, 68(6), 391

- 399. (as cited in EPA, 2011c).

Grevenkamp, A. 2007. Overexposure and Control of Methylene Chloride in a Furniture Stripping Operation . Journal of occupational and environmental hygiene, 4(5), D39

- D41.

Hall, R. M., K. F. Martinez, and P. A. Jensen. 1995. Control of Methylene Chloride

— Furniture Strippi ng Dip Tank . Applied Occupational and Environmental Hygiene, 10(3), 188

- 195.

Hardin, B. D., and J. M. Manson. 1980. Absence of Dichloromethane Teratogenicity with Inhalation Exposure in Rats . Toxicology and Applied Pharmacology, 52(1), 22

- 28. (as cited in EPA, 2011c).

Hearne, F. T., and J. W. Pifer. 1999. Mortality Study of Two Overlapping Cohorts of Photographic Film Base Manufacturing Employees Exposed to Methylene Chloride . Journal of occupational and environmental medicine / American College of Occupa tional and Environmental Medicine, 41(12), 1154

- 1169. (as cited in EPA, 2011c).P age 133 of 279

Heineman, E. F., P. Cocco, M. R. Gomez, M. Dosemeci, P. A. Stewart, R. B. Hayes, S. H. Zahm, T. L. Thomas, and A. Blair. 1994. Occupational Exposure to Chlorinated Aliphatic H ydrocarbons and Risk of Astrocytic Brain Cancer . American Journal of Industrial Medicine, 26(2), 155

- 169. (as cited in EPA, 2011c).

Heitmuller, P. T., T. A. Hollister, and P. R. Parrish. 1981. Acute Toxicity of 54 Industrial Chemicals to Sheepshead Minnow s (Cyprinodon Variegatus) . Bulletin of Environmental Contamination and Toxicology, 27(5), 596

- 604.

Heppel, L. A., and P. A. Neal. 1944. Toxicology of Dichloromethane (Methylene Chloride): Its Effect Upon Running Activity in the Male Rat . Journal of Indust rial Hygiene and Toxicology, 26(1), 17

- 21. (as cited in EPA, 2011c).

Heppel, L. A., P. A. Neal, T. L. Perrin, M. L. Orr, and V. T. Porterfield. 1944. Toxicology of Dichloromethane (Methylene Chloride): Studies on Effects of Daily Inhalation . Journal of In dustrial Hygiene and Toxicology, 26, 8

- 16. (as cited in EPA, 2011c).

HSDB (Hazardous Substances Data Bank). 2012. Dichloromethane . National Library of Medicine, Bethesda, MD. http://toxnet.nlm.ni h.gov/newtoxnet/hsdb.htm (accessed on March 19, 2012).

HSE (Health and Safety Executive). 2001. Health Risks During Furniture Stripping Using Dichloromethane (DCM) . Woodworking Sheet No 19 (Revised). United Kingdom. www.hse.gov.uk/pubns/wis19.pdf

. HSIA (Halogenated Solvents Industry Alliance, Inc.). 2008. White Paper on Methylene Chloride

. Arlington, VA.

HSIA (Halogenated Solvents Industry Alliance, Inc.). 2010. Dichloromethane (Methylene Chloride)

. Arlington, VA.

IAQUK (Indoor Air Quality UK). 2014. IAQUK Resources: Methylene Chloride . Somerset, UK. http://www.iaquk.org.uk/ResourcesMethylene.html (accessed on July 29, 2014).

IARC (Inte rnational Agency for Research on Cancer). 1999. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans: Dichloromethane, Volume 71 . World Health Organization, Lyon, France. http://monographs.iarc.fr/ENG/Monographs/vol71/mono71

- 10.pdf

. IARC (International Agency for Research on Cancer). 2010. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans: Occupational Exposure as a Painter, Volume 98 . World Health Org anization, Lyon, France. http://monographs.iarc.fr/ENG/Monographs/vol98/mono98

- 6.pdf

.P age 134 of 279

ICIS. 2007. Chemical Profile for Methylene Chloride . ICIS Chemical Business Americas, April 2

- 8, 2007.

Kjellstrand, P., B. Holmquist, I. Jonsson, S. Romare, and L. Mansson. 1985. Effects of Organic Solvents on Motor Activity in Mice . Toxicology, 35(1), 35

- 46. (as cited in EPA, 2011c).

Kleinman, M. T., D. M. Davidson, R. B. Vandagriff, V. J. Caio zzo, and J. L. Whittenberger. 1989. Effects of Short

- Term Exposure to Carbon Monoxide in Subjects with Coronary Artery Disease . Archives of Environmental Health, 44(6), 361

- 369. (as cited in NRC, 2010).

Kleinman, M. T., D. A. Leaf, E. Kelly, V. Caiozzo, K . Osann, and T. O'Niell. 1998. Urban Angina in the Mountains: Effects of Carbon Monoxide and Mild Hypoxemia on Subjects with Chronic Stable Angina . Archives of Environmental Health, 53(6), 388

- 397. (as cited in NRC, 2010).

Kühn, R., M. Pattard, K.

- D. Pern ak, and A. Winter. 1989. Results of the Harmful Effects of Selected Water Pollutants (Anilines, Phenols, Aliphatic Compounds) to Daphnia Magna

. Water Research, 23(4), 495

- 499.

Lanes, S. F., A. Cohen, K. J. Rothman, N. A. Dreyer, and K. J. Soden. 1990. Mor tality of Cellulose Fiber Production Workers . Scandinavian Journal of Work, Environment & Health, 16(4), 247

- 251. (as cited in EPA, 2011c).

Lanes, S. F., K. J. Rothman, N. A. Dreyer, and K. J. Soden. 1993. Mortality Update of Cellulose Fiber Production Wo rkers . Scandinavian Journal of Work, Environment & Health, 19(6), 426

- 428. (as cited in EPA, 2011c).

Lash, A. A., C. E. Becker, Y. So, and M. Shore. 1991. Neurotoxic Effects of Methylene Chloride: Are They Long Lasting in Humans? British Journal of Indust rial Medicine, 48(6), 418

- 426. (as cited in EPA, 2011c).

LBL (Lawrence Berkeley Laboratory). 1986. Source Characterization and Personal Exposure to Methylene Chloride from Consumer Products . Report Number LBL

- 20227. Indoor Environment Program, Applied Sci ence Division, Berkeley, CA.

LBL (Lawrence Berkeley Laboratory). 1987. Exposure to Methylene Chloride from Controlled Use of a Paint Remover in Residences . Report Number LBL

- 23078. Indoor Environment Program, Applied Science Division, Berkeley, CA.

LeBla nc, G. A. 1980. Acute Toxicity of Priority Pollutants to Water Flea (Daphnia Magna)

. Bulletin of Environmental Contamination and Toxicology, 24(5), 684

- 691.

Lide, D. R. 2001. Physical Constants of Organic Compounds. In CRC Handbook of Chemistry and Physic s, 82nd Edition (pp. 3

- 206). Taylor and Francis, Boca Raton, FL.P age 135 of 279

Lofgren, D. J., C. K. Reeb

- Whitaker, and D. Adams. 2010. Surveillance of Washington OSHA Exposure Data to Identify Uncharacterized or Emerging Occupational Health Hazards

. Journal of occupat ional and environmental hygiene, 7(7), 375

- 388.

Mannsville (Mannsville Chemical Products Corp). 1999. Chemical Products Synopsis. Methylene Chloride . Adams, NY. http://mannsvillechemical.com/synopsis/

.
Matthews, T. G., C. V. Thompson, D. L. Wilson, A. R. Hawthorne, and D. T. Mage. 1989. Air Velocities inside Domestic Environments: An Important Parameter in the Study of Indoor Air Quality and Climate . Environment International, 15(1

– 6), 545

- 550.

McCa mmon, C. S., R. A. Glaser, V. E. Wells, F. C. Phipps, and W. E. Halperin. 1991. Exposure of Workers Engaged in Furniture Stripping to Methylene Chloride as Determined by Environmental and Biological Monitoring . Applied Occupational and Environmental Hygien e, 6(5), 371

- 379.

MDH (Minnesota Department of Health). 2013. Chemicals of High Concern List (July 1, 2013) . St. Paul, MN. http://www.health.state.mn. us/divs/eh/hazardous/topics/toxfreekids/chclist/mdhchc2 013.pdf (accessed on July 9, 2014).

Mennear, J. H., E. E. McConnell, J. E. Huff, R. A. Renne, and E. Giddens. 1988. Inhalation Toxicity and Carcinogenesis Studies of Methylene Chloride (Dichlorometha ne) in F344/N Rats and B6C3F1 Mice . Annals of the New York Academy of Sciences, 534, 343

- 351. (as cited in EPA, 2011c).

Merlin, G., H. Thiebaud, G. Blake, S. Sembiring, and J. Alary. 1992. Mesocosms' and Microcosms' Utilization for Ecotoxicity Evaluation of Dichloromethane, a Chlorinated Solvent

. Chemosphere, 24(1), 37

- 50.

Miligi, L., A. S. Costantini, A. Benvenuti, D. Kriebel, V. Bolejack, R. Tumino, V. Ramazzotti, S. Rodella, E. Stagnaro, P. Crosignani, D. Amadori, D. Mirabelli, L. Sommani, I. Belletti, L. Troschel, L. Romeo, G. Miceli, G. A. Tozzi, I. Mendico, and P. Vineis. 2006. Occupational Exposure to Solvents and the Risk of Lymphomas . Epidemiology (Cambridge, Mass.), 17(5), 552

- 561. (as cited in EPA, 2011c).

MSU/MIFACE (Michigan State University/ Michigan Fatality Assessment and Control Evaluation). 2011. Tub Refinisher Died Due to Methylene Chloride Overexposure While Stripping a Bathtub . MIFACE investigation report #10MI013. East Lansing, MI. http://www.oem.msu.edu/MiFace/10MI013Report.pdfP age 136 of 279

Musy, M., E. Wurtz, and J. M. Nataf. 1999. An Intermediate Model to Predict Thermal Comfort and Air Quality in a Building . Proceedings of the 8th International Conference on Indoor Air Quality and Climate, Vol. 1, pp. 685, Edinburgh, Scotland.

NAC (National Advisory Committee). 2008. Interim Acute Exposure Guideline Levels (AEGL) for Methylene Chloride . Washington, DC. http://www.epa.gov/oppt/aegl/pubs/methylene_chloride_interim_dec_2008_v1.pdf

.
NCA (National Coffee Association). 1983. 24

- Month Oncogenicity Study of Methylene Chloride in Mice: Final Report . Study conducted by Hazleton Laboratories, Vienna, VA. Doc #45

- 8303005. (as cited in EPA, 2011c).

NIH (National Institutes of Health). 2005. Substance Profiles for Dichloromethane . Bethesda, MD.

NIOSH (National Institute for Occupational Safety and Health). 1977. Health Hazard Evaluation Determination R eport 75

- 195

- 396. United Airlines Maintenance Base San Francisco International Airport Burlingame, California . U.S. Department of Health, Education and Welfare, Cincinnati, OH. www.ntis.g ov/search/product.aspx?ABBR=PB273779

. NIOSH (National Institute for Occupational Safety and Health). 1990. Walk

- Though Survey Report: Control of Methylene Chloride in Furniture Stripping at Colonial Furniture Stripping . ECTB number: 170

- 14a. U.S. Departm ent of Health and Human Services, Cincinnati, OH. www.cdc.gov/niosh/surveyreports/pdfs/170

- 14a.pdf

. NIOSH (National Institute for Occupational Safety and Health). 1991. In

- Depth Surve y Report. The Control of Methylene Chloride in Furniture Stripping at Association for Retarded Citizens . ECTB number: 170

- 18a. Division of Physical Sciences and Engineering, Cincinnati, OH. http://www.cdc.gov/niosh/surveyreports/pdfs/170

- 18a.pdf

. NIOSH (National Institute for Occupational Safety and Health). 1993. Health Hazard Evaluation. Ackerman and Sons, Littleton, Colorado . Report No. 92

- 0360. Cincinnati, Ohio. www.cdc.gov/niosh/hhe/reports/pdfs/1992

- 0360

- 2372.pdf

. NIOSH (National Institute for Occupational Safety and Health). 2011a. NIOSH Pocket Guide to Chemical Hazards: Introduction . Atlanta, GA. http://www.cdc.gov/niosh/npg/pgintrod.html (accesed on July 20, 2012).

NIOSH (National Institute for Occupational Safety and Health). 2011b. NIOSH Pocket Guide to Chemical Hazards: Methylene Chloride

. http://www.cdc.gov/niosh/npg/npgd0414.html (accessed on July 20, 2012).P age 137 of 279

NITE (National Institute of Technology and Evaluation). 2002. Biodegradation and Bioaccumulation of the Existing Chemical Su bstances under the Chemical Substances Control Law . Japan.

Nitschke, K. D., J. D. Burek, T. J. Bell, R. J. Kociba, L. W. Rampy, and M. J. McKenna. 1988a. Methylene Chloride: A 2

- Year Inhalation Toxicity and Oncogenicity Study in Rats

. Fundamental and appl ied toxicology : official journal of the Society of Toxicology, 11(1), 48

- 59. (as cited in EPA 2011b).

Nitschke, K. D., D. L. Eisenbrandt, L. G. Lomax, and K. S. Rao. 1988b. Methylene Chloride: Two

Generation Inhalation Reproductive Study in Rats . Fundame ntal and applied toxicology : official journal of the Society of Toxicology, 11(1), 60

- 67. (as cited in EPA 2011b).

NRC (National Research Council). 1983. Risk Assessment in the Federal Government: Managing the Process . National Academy Press, Washington, DC. http://www.nap.edu/openbook.php?record_id=366&page=R1 . (as cited in EPA, 2011c).

NRC (National Research Council). 1992. Guidelines for Developing Spacecraft Maximum Allowable Conce ntrations for Space Station Contaminants National Academy Press, Washington, DC.

NRC (National Research Council). 1996. Spacecraft Maximum Allowable Concentration for Selected Airborne Contaminants: Methylene Chloride (Volume 2) . National Academy Press, W ashington, DC. http://www.nap.edu/catalog.php?record_id=5170

. NRC (National Research Council). 2001. Standing Operating Procedures for Developing Acute Exposure Guideline Levels for Hazardous C hemicals . National Academy Press, Washington DC. http://www.epa.gov/oppt/aegl/pubs/sop.pdf

. NRC (National Research Council). 2008. Spacecraft Maximum Allowable Concentration for Selected Airborne C ontaminants: Methylene Chloride (Volume 5) . National Academy Press, Washington, DC. http://www.nap.edu/catalog.php?record_id=12529

. NRC (National Research Council). 2010. Final Acute Exposure Guideline Levels for Carbon Monoxide . Volume 8. National Academy Press, Washington, DC. http://www.nap.edu/catalog.php?record_id=12770

. NTP (National Toxicolgy Program). 1986. Toxicology and C arcinogenesis Studies of Dichloromethane (Methylene Chloride) (CAS No. 75

- 09

- 2) in F344/N Rats and B6C3F1 Mice (Inhalation Studies) . Report No. 306. U.S. Department of Health and Human Services, Research Triangle Park, NC. (as cited in EPA, 2011c).

O'Neil , M. J. 2001. Methylene Chloride. In The Merck Index: An Encyclopedia of Chemicals, Drugs and Biologicals (13th ed., pp. 1082). Merck & Co., Inc, Whitehouse Station, NJ.P age 138 of 279

OECD (Organization for Economic Co

- operation and Development). 2010. Emission Scenari o Document on Coating Application Via Spray Painting in the Automotive Refinishing Industry (Draft Final) . OECD Environmental health and safety publications. Series on emission scenario documents, Paris, France.

OECD (Organization for Economic Co

- operatio n and Development). 2011. SIDS Initial Assessment Profile for Methylene Chloride . CoCAM 1, October 10

- 12, 2011, Paris, France.

OEHHA (Office of Environmental Health Hazard Assessment). 1999. Air Toxics Hot Spots Program Risk Assessment Guidelines. Part I: The Determination of Acute Reference Exposure Levels for Airborne Toxicants . State of California Environmental Protection Agency, Sacramento, CA. http://oehha.ca.gov/air/pdf/acuterel.pdf

. OEHHA (Of fice of Environmental Health Hazard Assessment). 2001. Methylene Chloride: Prioritization of Toxic Air Contamination

- Children’s Environmental Health Protection Act

. State of California Environmental Protection Agency, Sacramento, CA. http://oehha.ca.gov/air/toxic_contaminants/pdf_zip/methylene%20chloride_final.pdf

. OEHHA (Office of Environmental Health Hazard Assessment). 2008. Acute Reference Exposure Level ( REL) and Toxicity Summary for Methylene Chloride . State of California Environmental Protection Agency, Sacramento, CA. http://oehha.ca.gov/air/hot_spots/2008/AppendixD 2_final.pdf#page=187

. OEHHA (Office of Environmental Health Hazard Assessment). 2014a. Chemicals Biomonitored in California . State of California Environmental Protection Agency, Sacramento, CA. http://www.biomonitoring.ca.gov/chemicals/chemicals

- biomonitored

- california (accessed on July 9, 2014).

OEHHA (Office of Environmental Health Hazard Assessment). 2014b. Chemicals Known to the State to Cause Cancer or Reprod uctive Toxicity (May 2, 2014) . State of California Environmental Protection Agency, Sacramento, CA. http://oehha.ca.gov/prop65/prop65_list/files/P65single050214.pdf

.
OSHA (Oc cupational Safety and Health Administration). 1997a. Intro to 29 CFR Parts 1010, 1915 and 1926; Occupational Exposure to Methylene Chloride . 29 CFR 1910, 1915, 1926, Washington, DC. https:// www.osha.gov/pls/oshaweb/owadisp.show_document?p_table=PREAMBLES&p _id=998

. OSHA (Occupational Safety and Health Administration). 1997b. Substance Safety Data Sheet and Technical Guidance for Methylene Chloride . 29 CFR 1910.1 052 App. A, Washington, DC.P age 139 of 279

https:// www.osha.gov/pls/oshaweb/owadisp.show_document?p_table=STANDARDS&p _id=10095

. OSHA (Occupational Safety & Health Administ ration). 2010. Regulatory Review of 29 CFR 1910.1052: Methylene Chloride . Directorate of Evaluation and Analysis, Washington, DC.

OSHA (Occupational Safety and Health Administration). 2012a. Integrated Management Information System (IMIS): Methylene Chlor ide (CASRN 75

- 09

- 2) . Washington, DC.

OSHA (Occupational Safety and Health Administration). 2012b. Methylene Chloride

- Safety and Health Topics . Washington, DC. http://www.osha.gov/SLTC/methylenec hloride/ (accessed on August 15, 2012).

Pauli, R. 1996. Alternative Processes to Methylene Chloride . National Metal Finishing Resource Center, Fairfield, CA. http://www.nmfrc.org/pdf/pf0697b.htm

.

Pell izzari, E. D., T. D. Hartwell, B. S. Harris, 3rd, R. D. Waddell, D. A. Whitaker, and M. D. Erickson. 1982. Purgeable Organic Compounds in Mother's Milk . Bulletin of Environmental Contamination and Toxicology, 28(3), 322

- 328. (as cited in ATSDR, 2000).

Pet erson, J. E. 1978. Modeling the Uptake, Metabolism and Excretion of Dichloromethane by Man . American Industrial Hygiene Association Journal, 39(1), 41

- 47. (as cited in NAC, 2008 and NRC, 1996).

Pollack

- Nelson, C. 1995. Analysis of Methylene Chloride Produ ct Labelling . Ergonomics, 38(11), 2176

- 2187.

Putz, V. R., B. L. Johnson, and J. V. Setzer. 1979. A Comparative Study of the Effects of Carbon Monoxide and Methylene Chloride on Human Performance . Journal of Environmental Pathology and Toxicology, 2(5), 97

- 112. (as cited in NRC, 1996; OEHHA, 2008; and EPA, 2011c).

Raje, R., M. Basso, T. Tolen, and M. Greening. 1988. Evaluation of in Vivo Mutagenicity of Low

Dose Methylene Chloride in Mice . International Journal of Toxicology, 7, 699

- 703. (as cited in EPA, 2011c).

Ratney, R. S., D. H. Wegman, and H. B. Elkins. 1974. In Vivo Conversion of Methylene Chloride to Carbon Monoxide . Archives of Environmental Health, 28(4), 223

- 226. (as cited in NRC, 1996).

Rebert, C. S., M. J. Matteucci, and G. T. Pryor. 1989. Ac ute Effects of Inhaled Dichloromethane on the Eeg and Sensory

- Evoked Potentials of Fischer

- 344 Rats . Pharmacology, Biochemistry and Behavior, 34(3), 619

- 629. (as cited in EPA, 2011c).P age 140 of 279

Rice, D., and S. Barone, Jr. 2000. Critical Periods of Vulnerability fo r the Developing Nervous System: Evidence from Humans and Animal Models . Environ Health Perspect, 108 Suppl 3, 511

- 533.

RIDEM (Rhode Island Department of Environmental Management). 2011. Environmental/Occupational Health Complicance Certification Program. Certification Workbook for Auto Body Repair Facilities . Office of Customer and Technical Assistance, Providence, RI. http://www.dem.ri.gov

.
Riley, D. M., B. Fischhoff, M. J. Small, and P. Fischbeck. 2001. Evaluating the Effectivenes of Risk

Reduction Strategies for Consumer Chemical Products . Risk Analysis, 21(2), 357

- 369.

Riley, E. C., D. W. Fassett, and W. L. Sutton. 1966. Methylene Chloride Vapor in Expired Air of Human Subjects . American Industrial Hygiene Associ ation Journal, 27(4), 341

- 348. (as cited in NAC, 2008).

Roederer, G. 1990. Testung Wassergefaehrdender Stoffe Als Grundlage Fuer Wasserqualitaetsstandards . Fraunhofer

- Institutfuer Umweltchemie und Oekotoxikologie, 5948 Schmallenberg, UFOPLAN

- Nr. 116 08 07 1/01.

Schwetz, B. A., K. J. Leong, and P. J. Gehring. 1975. The Effect of Maternally Inhaled Trichloroethylene, Perchloroethylene, Methyl Chloroform, and Methylene Chloride on Embryonal and Fetal Development in Mice and Rats . Toxicology and Applied Pharma cology, 32(1), 84

- 96. (as cited in EPA, 2011c).

Seidler, A., M. Mohner, J. Berger, B. Mester, E. Deeg, G. Elsner, A. Nieters, and N. Becker. 2007. Solvent Exposure and Malignant Lymphoma: A Population

- Based Case

- Control Study in Germany . Journal of occupa tional medicine and toxicology (London, England), 2, pp. 2. (as cited in EPA, 2011c).

Serota, D. G., A. K. Thakur, B. M. Ulland, J. C. Kirschman, N. M. Brown, R. H. Coots, and K. Morgareidge. 1986. A Two

- Year Drinking

- Water Study of Dichloromethane in Rod ents. Ii. Mice . Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association, 24(9), 959

- 963. (as cited in EPA, 2011c).

Sheps, D. S., K. F. Adams, Jr., P. A. Bromberg, G. M. Goldstein, J. J. O'Neil, D. Horstman, and G. Koch. 1987. Lack of Effect of Low Levels of Carboxyhemoglobin on Cardiovascular Function in Patients with Ischemic Heart Disease . Archives of Environmental Health, 42(2), 108

- 116. (as cited in NRC, 2010).

Sills, R. C., J. R. Ha iley, J. Neal, G. A. Boorman, J. K. Haseman, and R. L. Melnick. 1999. Examination of Low

- Incidence Brain Tumor Responses in F344 Rats Following Chemical Exposures in National Toxicology Program Carcinogenicity Studies . Toxicologic Pathology, 27(5), 589

- 599 . (as cited in EPA, 2011c).P age 141 of 279

Smithsonian (Smithsonian Museum Conservation Institute). 2012a. Does My Painting Need to Be Cleaned . Suitland, MD. http://si.edu/mci/english/le arn_more/taking_care/painting_clean.html (accessed on July 20, 2012).

Smithsonian (Smithsonian Museum Conservation Institute). 2012b. What Does It Mean to Have a Painting Restored and How Do I Pick a Conservator . Suitland, MD. http://si.edu/mci/english/learn_more/taking_care/conservation_meaning.html (accessed on July 20, 2012).

SRC (Syracuse Research Corporation). 1978. Results of Continuous Exposure of Fathead Mi nnow Embryo to 21 Priority Pollutants . OTS#0511060. Doc#40

- 7848049.

SRRP (Source Reduction Research Partnership). 1992. Source Reduction and Recycling of Halogenated Solvents in the Adhesives Industry . Prepared by Jacobs Engineering Group, Pasadena, CA.

Stewart, R. D., T. N. Fisher, M. J. Hosko, J. E. Peterson, E. D. Baretta, and H. C. Dodd. 1972. Experimental Human Exposure to Methylene Chloride . Archives of Environmental Health, 25(5), 342

- 348. (as cited in NAC, 2008 and NRC, 1996).

Stewart, R. D., C. L. Hake, and A. Wu. 1976. Use of Breath Analysis to Monitor Methylene Chloride Exposure . Scandinavian Journal of Work, Environment & Health, 2(2), 57

- 70. (as cited in NAC, 2008).

Tabak, H. H., S. A. Quave, C. I. Mashni, and E. F. Barth. 1981. Biodegradabi lity Studies with Organic Priority Pollutant Compounds . Journal of the Water Pollution Control Federation, 53(10), 1503

- 1518.

Tomenson, J. A. 2011. Update of a Cohort Mortality Study of Workers Exposed to Methylene Chloride Employed at a Plant Producing C ellulose Triacetate Film Base . Int Arch Occup Environ Health, 84(8), 889

- 897. (as cited in EPA, 2011c).

USDOC (U.S. Department of Commerce). 2007a. American Factfinder: 2007 Economic Census

. U.S. Census Bureau, Washington, DC. http://factfinder2.census.gov/faces/nav/jsf/pages/programs.xhtml?program=econ (accessed in August 2012).

USDOC (U.S. Department of Commerce). 2007b. North American Industry Classification S ystem (NAICS): 2007 NAICS Index File . U.S. Census Bureau, Washington, DC. http://www.census.gov/cgi

- bin/sssd/naics/naicsrch?chart=2007 (accessed on August 9, 2012).P age 142 of 279

van Veen, M. P., F. Fortezza, E. Spaans, and T. T. Mensinga. 2002. Non

- Professional Paint Stripping, Model Prediction and Experimental Validation of Indoor Dichloromethane Levels . Indoor Air, 12(2), 92

- 97.

Vincent, R., P. Poirot, I. Subra, B. Rieger, and A. Cicolella. 1994. Occupational Exposure to Organic Solvents During Paint Stripping and Painting Operations in the Aeronautical Industry . Int Arch Occup Environ Health, 65(6), 377

- 380.

von Bringmann, G., and F. Meinck. 1964. Wassertoxikologische Beurteilung Von Indus trieabwassern . Gesundheits

- Ingenieur, 85, 229

- 260.

Wang, R., Y. Zhang, Q. Lan, T. R. Holford, B. Leaderer, S. H. Zahm, P. Boyle, M. Dosemeci, N. Rothman, Y. Zhu, Q. Qin, and T. Zheng. 2009. Occupational Exposure to Solvents and Risk of Non

- Hodgkin Lymphom a in Connecticut Women . American Journal of Epidemiology, 169(2), 176

- 185. (as cited in EPA, 2011c).

Weinstein, R. S., D. D. Boyd, and K. C. Back. 1972. Effects of Continuous Inhalation of Dichloromethane in the Mouse: Morphologic and Functional Observati ons . Toxicology and Applied Pharmacology, 23(4), 660

- 679. (as cited in EPA, 2011c).

Winneke, G. 1974. Behavioral Effects of Methylene Chloride and Carbon Monoxide as Assessed by Sensory and Psychomotor Performance. In Xintaras, C., B. L. Johnson , and I. de Groot, Behavioral Toxicology: Early Detection of Occupational Hazards (pp. 130

- 144 ). U.S. Department of Health, Education and Welfare Washington, DC. (as cited in EPA, 2011c and NAC, 2008).

WM Barr (W.M. Barr and Company). 2008. Material Safety Data S heet: Klean

- Strip Color Change Stripper . Memphis, TN. http://www.wmbarr.com/ProductFiles/GKCC00326.pdf

. WM Barr (W.M. Barr and Company). 2009a. Material Safety Data Sheet. Klean Strip Aircra ft Remover . Memphis, TN. http://www.wmbarr.com/ProductFiles/3404.11.pdf

. WM Barr (W.M. Barr and Company). 2009b. Material Safety Data Sheet. Klean Strip Klean Kutter . Memphis, TN. http://www.wmbarr.com/ProductFiles/130%20(Klean%20Kutter).pdf

. WM Barr (W.M. Barr and Company). 2010a. Material Safety Data Sheet. Klean

- Strip Naked Gun Spray Gun Paint Remover . Memphis, TN

. WM Barr (W.M. Barr and Company). 2010b. Material Safety Data Sheet. Klean

- Strip Peeler

. Memphis, TN. http://www.wmbarr.com/ProductFiles/KS%20Peeler%20(A223.2)%207

- 23

- 10.pdf

.P age 143 of 279

WM Barr (W.M. Barr and Company). 2011a. Material Safety Data Sheet. Klean

- Strip Premium Sprayable Stripper . Memphis, TN. http://www.wmbarr.com/ProductFiles/MSWRPTM.pdf

. WM Barr (W.M. Barr and Company). 2011b. Material Safety Data Sheet. Klean

- Strip Strip X Stripper . Memphis, TN.

WM Barr (W.M. Barr and Company). 2011c. Material Safety Data Sheet. Klean Strip Adhesive Remover/Klean Strip Premium Stripper . Memphis, TN. http://www.wmbarr.com/ProductFiles/KS%20Adhesive%20Remover%20(4015

- 26)%205

- 17

- 11.pdf

. WM Barr (W.M. Barr and Company). 2012. Material Safety Data Sheet. Premium Stripper

. Memphis, TN. http://www.wmbarr.com/ProductFiles/KS%20Premium%20Stripper%203%2028%20201 2.pdf

.
Wollbrinck, T. 1993. The Composition of Proprietary Paint Strippers . Journal of the Amercian Institute for Conservation, 32(1), Article 5 (pp. 43

- 57).

Wong, K. L. 1990. Carbon Monoxide. In Spacecraft Maximum Allowable Concentrations for Selected Airborne Contaminants (Vol. 1, pp. 61

- 90). National Academy Press, Washingto n, D.C. (as cited in NRC 1996).

WSDE (Washington State Department of Ecology). 2013. Chemicals of High Concern to Children

. Lacey, WA. http://www.ecy.wa.gov/programs/swfa/cspa/chcc.html ( accessed on July 9, 2014).

Xu, J. Q., K. D. Kochanek, S. L. Murphy, and B. Tejada

- Vera. 2010. Deaths: Final Data for 2007

. National Center for Health Statistics, Hyattsville, MD. http:/ /www.cdc.gov/nchs/data/nvsr/nvsr58/nvsr58_19.pdf . (as cited in EPA, 2011a).P age 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 Protectio n 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 Conservatio n and Recovery Act ( RCRA) (Code U080) ( EPA, 2012c ) , and DCM is listed on the Toxics Release Inventory (TRI) pursuant to section 313 of the Emergen cy Planning and Community Right

- to

Know Act (EPCRA) ( EPA, 2014 ) . DCM is also listed on the TSCA Inventory of Chemical Substances and is subject to reporting under the TSCA Chemical Data Reporting (CDR) rule ( EPA, 2011e )

. EPA’s Office of Air Quality Planning and Standards issued a final rule in January 2008, under the National Emission Standards for Hazardous Air Pollutants (NESHAP) that established national emission standards for using DCM to remove dried paint ( i.e., including, but not limited to: paint, en amel, 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 produc ts 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 hair spray

. 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 to ok steps to reduce the DCM expo sure in occupational settings. OSHA lowered the permissible exposure limit (PEL) for DCM from 500 parts per million (ppm) to 25 ppm ( OSHA, 1997a , 1997b )

.P age 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 h arm ( OEHHA, 2014b ) . In addition, California lists DCM as a designated chemical for bio monitoring ( 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 Enviro nmental Protection Act, 1999 (CEPA 1999) requiring the preparation and implementation of pollution prevention plans for DCM ( Environment Can ada, 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 cleani ng; and adhesive formulations.

Also in 2003, Environment Canada published a Code of Practice for the r eduction of d ichloromethane e missions from the u se of p aint s trippers in c ommercial f urniture r efinishing and o ther s tripping a pplications ( Environment Canada, 2003a )

. The Code of Practice was developed by a multi

- stakeholder t echnical w orking c ommittee, which consisted of industry representatives (i.e., furniture strippers, auto body shops, paint stripper formulators, solvent recovery firms), government personnel, and environmental non

- gov ernmental 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 eq uipment. 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 equipmen t, and adequate informati on and training fo r 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 ) ”P age 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 Chemical s ( 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 fl ow

- through conditions for 96 hrs. A 96

- h r LC 50 of 99 mg/L was reported ( Alexander et al., 1978 )

.
Fathead minnows ( P. promelas ) were exposed to unspecified measured concentrations of DCM under fl ow

- through conditions for 96 hrs. A 96

- h r LC 50 of 193 mg/L was reported ( Alexander et al., 1978 )

. Fathead minnows ( P. promelas ) were exposed to unspecified nominal concentrations of DCM

un der static conditions for 96 hrs. A 96

- h r LC 50 of 310 mg/L was reported ( Alexan der et al., 1978 )

.
Fathead minnows ( P. promelas ) were exposed to unspecified measured concentrations of DCM under flow

- th rough conditions for 96 hours. A 96

- h r LC 50 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

- th rough conditions for 96 hrs. A 96

- h r LC 50 of 502 mg/L was re ported ( Dill et al., 1987 )

. Sheepshead minnows ( Cyprinodon variegates ) were exposed to unspecified nomin al concentrations of DCM under s tatic conditions for 96 hrs. A 96

- h r LC 50 of 330 mg/L was reported ( Heitmuller et al., 1981 )

.
Zebrafish ( Danio re r io ) were exposed to unspecified concentrations of DCM under unspec ified conditions for 96 hrs. The 96

- h r LC 50 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 hr s. A 96

- hr LC 50 of 220 mg/L was reported ( Buccafusco et al., 1981 )

.P age 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 o f DCM under flow

- t hrough conditions for 28 days. The 28

- day lowest

- observed

effect concentration (LOEC) ranged between 82.5 and 142 mg/L and a maximum acceptable toxicant concentration (MATC) of 108 mg/L was reported ( Dill et al., 1987 )

.



### B

- 3 Acute Toxicity to Aquatic Invertebrates

Water fleas ( Daphnia magna ) were exposed to unspecified nominal concentrations of D CM under static conditions for 48 hr s. A 48

- hr EC 50 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 hr s. A 48

- hr EC 50 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 hr s. A 48

- hr EC 50 of 220 mg/L was reported ( LeBlanc, 1980 )

.

O possum shrimp ( Americamysis bahia ) were exposed to unspecified nominal concentrations of DCM under static conditions for 96 hr s. A 96 hr EC 50 of 256 mg/L was reported ( SRC, 1978 )

.



### B

- 4 Toxicity to Aquatic Plants

Green algae ( Pseudokirchneriella subcapitat a ) were exposed to unspecified nominal concentrations of DCM under static conditions for 96 hr s. A 96

- hr EC 50 of 500 mg/L was reported ( EPA, 1978 )

. Diatoms ( Skeletomema costatum ) were exposed to unspecified nominal concentrations of DCM under static conditions for 96 hr s. A 96

- hr EC 50 of 662 mg/L was r eported ( SRC, 1978 )

. Green algae ( Scenedesmus subspicatus ) were exposed to unspecified nominal concentrations of DCM under static conditions for 96 hr s. A 96

- hr EC 50 of 1,000 mg/L was reported ( Merlin et al., 1992 )

.P age 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 Occi dental Chemical Corporation ( EPA, 2013 ) . There were also s ome 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 ( E PA, 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 rea sonably 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 o r 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

- inc orporation into formulation, mixture, or reaction product

Table B

- 2. Summary of Industrial DCM Uses from 2012 CDRP age 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 formulat ion 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 produc tion 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 liste d 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 Kno wn or Reasonably Ascertainable Automotive Care Products Both No Metal Products not covered elsewhere Commercial No
Paints and Coatings Both NoP age 150 of 279



## Appendix D H OUSEHOLD PRODUCTS DATA FOR DCM

EPA/OPPT searched the National Institute of Health (NIH) Household Databas e, which links over 13,000 consumer brands to health effects reported in Mate rial Safety Data Sheets (MSDS) ( DHHS, 2012 ) . The database also allows scientists and consumers to research products based on chemical ingredient s. 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 Jun e 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 Cleaner

08/01/2002

- old product Auto products Liquid 60

- 7 0
Sprayway Industrial Gasket Remover No. 719 Auto products Aerosol 70

- 80 Gunk Carb Medic Carburetor and Choke Cleaner

04/07/2010 Auto 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 C hoke and Valve Cleaner

old product Auto 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 Pa int 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 Gra de Lubricant Home maintenance Aerosol 32P age 15 1 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 Jun e 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 a nd 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 Purp ose 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 Sup erStrip 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 mainten ance 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 Aer osol 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, Aeroso l 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) Pesticide s 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 conten t. 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. S avogran 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)P age 152 of 279



## Appendix E ENVIRONMENTAL FATE OF DCM

Knowledge of the environmental fate (transport and trans formation) 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 Hen ry’s Law constant, 2.19 × 10

- 3 atm

- m 3 /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 wa rming potential (GWP) chemical with a value of 8.7 [ i.e., or approximately 8.7 times more heat absorptive than carbon dioxide (CO 2 ) ] GWP ( Forster, 2007 )

.

Table E

- 1 provides a summary of the environm ental fate information for DCM. Th e section s below summarize current knowledge of the transport, persistence, bioaccumulation, and bioconcentration of DCM in the environment includin g biological and abiotic reactions and environmental distribution.P age 153 of 279

Table E

- 1

. Environmental Fate Charact eristics of DCM 1

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 K oc 1.4 (estimated) 3 Fugacity (Level III Model) 3 Air (%) Water (%) Soil (%) Sediment (%) 43.8

45.0 11.0 0.1 Persistence 4 Moderate Bioaccumulation 4 Low 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 produ ced 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 (K oc ) 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

- m 3 /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 o C ( 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 o C ( 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 meth anogenic conditions ( HSDB, 2012 )

.P age 154 of 279



### E

- 3 Fate in Soil/Sediment

Based on its low soil organic carbon partitioning coefficient (K oc =25 ), DCM is likely to possess high mobility in soils and may be expected to leach from soi ls 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 d emand (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 biodegradabl e ( NITE, 2002 )

.
DCM was shown to degrade under aerobic conditions in static culture screening studies that used domestic wastewater amende d with yeast as inoculum ( Tabak et al., 1981 ) . Complete loss of DCM was observed within 7 days in the static culture tests

. H owever, up to 25% of the loss could have arisen from volatilization. Taken together, t hese studies suggest that DCM is mobile in soils and persist s long enough to migrate to groundwater given its low affinity for soil and potential to de grade somewhat slowly.



### E

- 4 B ioconcentration 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 init ial concentration of 0.25 mg/L ( NITE, 2002 ) . BCF values of <6.4 to 40.0 were observed when the concentration was 0.0 25 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 FACIL I TY AND POPULATION INFORMATION

A ppendix F presents information about indus tries 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

B ecause 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

s hops” of interest to EPA/OPPT. Note that the terms for commerci al, 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 indu stries 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 In clusion 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 f looring 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, ind ependent” and “Conservators ( i.e. , art, artifact restorers), independent” ( USDOC, 2007b )

. Research h as shown art conservation to use paint strippers based on DCM or NMP ( Wollbrinck, 1993 )

. 7 12110 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 In clusion 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 invol ved 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 pai nt 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 s tripping 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 Contra ctors

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 co mmonly 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 sur faces using a hand

- held brush. Strippers used in these applications oft en have a high viscosity since they can be applied to vertical surfaces. After application, the stripper is allowed to s et and soften the old coating. Once the stripper has finished setting, the old coating is removed from the surface by scraping and brush ing. 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 complete d on an incremental basis with treatment for one section of wall or flooring being completed before moving to the next sectionPage 157 of 279

( CDHS/EPA, 2006 ; EC, 1999 ; EU, 2007 ; NIOSH, 1993 )

. Professional contractors can use portable local exhaust ventilation machines to increase venti lation in the vicinity of the paint stripping ( EU, 2007 )

.

Professi onal 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, t he 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

– R eupholstery 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
pr ofessional contractor

- type work differs from furniture refinishing, which typically entails the refinishing of customer furniture at fixed furniture refinishing facilities.

B athtub refinishing or reglazing can involve a worker pouring and brushing strippe r 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 )

. H owever, multiple health case studies have reported the use of aircraft and marine coating remover in bathtu b refinishing/reglazing ( CDC, 2012 )

.



### F

- 2

- 2 Graffiti Removal

Unlike fixed facility operations, g raffiti removal is expected to employ similar job

- site characteristi c s 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 sprayi ng and wiping or brushing the solvent on the surface, the surface is then washed with heated (70 o C) wash water using a high

- pressure spray.

The observed work was performed in train depots and underground stations and included confined spaces, suc h as el evators and train cars. The study authors noted poor venti lation 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 compa nies 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 sub sequent to the o riginal 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;

 Sol vent wipe

- down;

 Topcoat (basecoat color and clearcoat) mixing;

 Spray application of topcoat; and

 Curing.

As stated in OECD (2010) , t he surface preparation step of the refinishing process involves

“ removing residual wax, grease, or other contaminants from the surface to be painted, to

ensur e 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 b een roughened through sanding. Alternatively, the previous coating may be removed using a mechanical method (e.g., sanding ) or a paint

removing solvent. After the coating is roughened or remov ed, 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 contai ning the stripper, brushing or spraying the stripper onto the furniture surface, or m anually 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 a s 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 t o apply the stripper to parts. The flow tray is a sloped, shallow tank w ith 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 brush ed 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 surfa ce. Wash water is collected and either recycled or disposed of as waste. After washing, thePage 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 coat ing ( 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 (2 006) . 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 furn iture 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

FurniturePage 160 of 279 Sourc e: CDHS/EPA (2006)

Source: HSE (2001)Page 161 of 279



### F

- 2

- 5 Art Restoration and Conservation

Art restorati on and conservation can include the care and maintenance of paintings to reverse negative effects o f 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

o riginal paint layer that is being conserved. Products marketed for use in this field that do n o t 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 certai n 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 an d 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 p aint 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. A ir

- 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 s trippers. Eight of the 10 MSDS recommended a NIOSH

- approved, self

- contained breathing apparatus or air

- supplied respirator if respi ratory p rotection is required. One MSDS recommended NIOSH

- approvedPage 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 furt her 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

- base d 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 expose d 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 P otentially 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 s ites 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, respectiv ely).
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 li terature 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 stri pping 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 tha t emit less than 10 tons/y r of DCM, and major sources were defined as f acilities that emit at le ast 10 tons/y r 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 o f 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 facil ities (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 esti mated 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 Typ e 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 busi nesses.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 fo r 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 4 9,085
Source: USDOC (2007a)

The Census data d id not include hours worked for construction industry sect ors nor data about bathtub refinishers/reglazers or graffiti removal. Also, there were no data about t he number of painting and wall covering contractors and flooring contractors who use DCM

- based paint strippers, the number of jobs per year a contractor u ses 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 pote ntially 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 indica ted 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 o f 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 p er 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 perform ed 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 t his 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 A utomotive body, paint,

and interior repair and maintenance 35,581 223,942

Source: USDOC (2007a)

The Ce nsus data indicated an average of approximately 6 employees per facility ( USDOC, 2007a )

. A 2003 Rhode Island study observ ed 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 b ody 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 o f 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 exp osed 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 s tudy 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

. Econom ic 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 identifi ed among the exposure studies. Of these 10 shops, only one was confirmed to have grea ter than 10 total employees (this shop ha d 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, 1 990 , 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 OSH A Methylene Chloride Standard. In the RIA, OSHA estimat ed 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 repa ir facilities decrease d 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 tha t use DCM in the present day ( OSHA, 2010 )

. EPA/OPPT did not have information about t he 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 expose d 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 unknow n the representativeness of the distribution of facility annual use rate of stripper across the entire U

. S.

CDHS/EPA (2006) identifies the faci lities that use >200 gallons/y r of stripper as larger f acilities that purchase stripper in drum quantities from suppliers. The firms that use <200 gallons/y r of stripper likely use hand stripping and purchase their stripper from hardware and home improvement stores ( CDH S/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 5 96 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 gi ves 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

. 200 7 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 varie ty of professions, including independent art restorers and independent conservators. According to the U.S. Census Bureau, t he majority of the professions listed within this NAICS code are not expected to engage in paint stripping. Furthermore, the extent t hat art restorers and conservators engage in paint stripping is unknown particularly for the use of DCM

- based paint strippers.

Similarly, it is unknown the number of museums within NAICS code 712110 that use DCM

based paint strippers. Therefore, the num ber 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, a verage 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 h rs 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 h rs per day

. The calculations also assumed 250 worker days per y r when estimating the average worker hours per day

. The estimates of worker days per yr and worker h rs per day were within 10 percent of the EPA /O PPTs’ New Chemicals Progra m default values of 250 days/y r 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 liter ature. 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 mainten ance activities ( NIOSH, 1977 )

. Similarly, a 1994 French study of an aeronautical workshop monitored 30 painters, although the total number of employees was not identi fi ed ( 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 N AICS 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

manufact

uring 254 81,456 157 ,589 242 7.74

Source: USDOC (2007a)

In the 1996 RIA, OSHA estimated 300 establishments engaged in paint stripping of aircraft s 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 20 07 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). I t is unknown if these data are representative of the number of e stablishments and workers that use DCM in the present day ( OSHA, 2010 )

.Page 169 of 279

EPA/OPPT did not have information about t he current number of aircraft manufacturing establishments that use DCM

- based pain t strippers and the number of employees within an establishment exposed to DCM

- based paint stripper s . Therefore, the number of establishments and employees from the U

. S

. Census are possibly overestimates of the number of establishments and employees potent ially 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 Cens us ( USDOC, 2007a )

. The table also estimates the average worker days per year and average worker hours per day. These para meters were estimated from the production workers hours and the average number of production workers. The calculations for the average worker da ys per year assumed 8 worker h rs per day. The calculations als o assumed 250 worker days per y r when e stimating t he average worker h rs per day. The estimates of worker days per
y r and worker hours per day were within 10 percent of the EPA/OPPTs’ New Chemicals Progra m default values of 250 days/y r and 8 hr/day, respectively ( EPA, 1993a )

.

The Census data also indicate d an average of approximately 100 p roduction 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

20 07 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 t h e 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:

 I nhalation exposure monitoring data of DCM during paint stripping, specifica lly 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 o f 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

are a samples.

 Description of processes and worker activities used to perform paint stripping

 Description of engineering controls and personal protective equipm ent used during paint stripping

 Estimates of number of workers exposed to DCM during paint strippi ng 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 t hat 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 i n 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 d id not require these types of data;

 Recreated exposure conditions from case studies: Monitoring data were preferred to

rec reated 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 c onditions 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 menti on 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 d etailed 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 d efined 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 followin g targeted NIOSH online resources.

 NIOSH Workplace Survey Reports: http://www.cdc.gov/niosh/surveyreports/

 NIOSH Health Hazard Evaluations (HHEs): http://www2 a.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 pe er reviews o f 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 an d 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, t he data point me t the data need of personal, inhalation monitor ing 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 in clude the following acceptance specifications:

 The information or data are from a
peer

- reviewed, government, or industry

specific source.

 The source is published.

 The author is engaged in a relevant field such that competent knowledge is expected (i.e., th e 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 follow ing sources:

U S or o t her g ov er n m ent p ub lication.

Sources by a n ac a demic resear c h e r where:

 Publication is i n pee r

- r e view e d j ou rnal;

or

 Pres e n ted at a technical conf e rence; or

 S o urce has d o c u m ented q u ali f ications or

cre d e n tials to disc u ss p artic u lar to p ic.

Sources by a n ind u st ry ex p ert o r t r a d e g r ou p where:

 Pres e n ted at a technical conf e rence

w h ere t h e informati o n is sub j ect to revi e w by o t h e r i nd u stry e xp e rts; or

 S o urce has d o c u m ented q u ali f ications or

cre d e n tials to disc u ss p artic u lar to p ic; or

 Source r e pres e n ts a large por t ion of the i n d u stry o f i n terest.

Unbiased The information is not biased towards a

particular product or outcome.  Objective of the infor m ation i s clear.

 M et h o do l ogy i s des i gn e d t o a n sw e r a specific qu e stion.

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 i ndustry 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.

Ap plicability 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 Approac h 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, w ith 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

 Graf fiti removal

By i dentif ying 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 w orker exposures.



### G

- 2

- 2 Estimation of Potential Workplace Exposures for DCM

- Based Paint

Strippers

G

- 2

- 2

- 1 Workplace E xposures B ased on M

onitoring D ata

EPA /OPPT used air concentration data and estimates found in literature sources to serve as exposure concentrations for o ccupational 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 p aint 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 info rmation about shop size de te rmination, see section 3.1.1.2 and Appendix F

.Page 175 of 279

EPA/OPPT did not find enough monitoring data to determine complete stat istical distributions of actual exposure concentrations for the exposed populations. Ideally, EPA/OPPT would like to know 50 th and 95 th percentiles for each population. The air concentration means and midpoints (means are preferred over midpoints) serve d a s substitutes for 50 th percentiles, and high ends of ranges serve d as substitutes for 95 th percentiles.

In compiling the results from the individual literature sources into the results summary for this risk assessment, EPA/OPPT classified exposure durati ons 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 fo r 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 exposu re.

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) inhalati on exposures for DCM found in IMIS may or may not be caused by DCM

- based strippers; and (2) data from literature were deemed adequate to estimate exposures from DCM

- based strippers. In this assessment, the IMIS data were useful for examining the impact of the OSHA PEL update in 1997 on exposures in the industries that are most likely to employ DCM

- based strippers ( see section G

3

- 10 ).

Table G

- 2 presents a summary of the exposure data collected for each industry. The risk characterization of occupational ex posures 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 Chroni c Exposure Concentrations for Non

Cancer and Cancer Risks and Non

- 8 hr Air Concentration Data from the Literature

Industry / Activity 8

- hr TWA (mg/m 3 ) a STEL, Peak, Short

- Tasked Based, and Unknown (mg/m 3 ) b Data Source for 8

- hr TWA and short

term values Number of Studies Time

Range of Studies Number

of Sites Total Number of

Measurements c Mean High Midpoint d Low Mean High Mid

point 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 Conservation f 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 Chroni c Exposure Concentrations for Non

Cancer and Cancer Risks and Non

- 8 hr Air Concentration Data from the Literature

Industry / Activity 8

- hr TWA (mg/m 3 ) a STEL, Peak, Short

- Tasked Based, and Unknown (mg/m 3 ) b Data Source for 8

- hr TWA and short

term values Number of Studies Time

Range of Studies Number

of Sites Total Number of

Measurements c Mean High Midpoint d Low Mean High Mid

point 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)

No n - 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 (S TEL/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 Chroni c Exposure Concentrations for Non

Cancer and Cancer Risks and Non

- 8 hr Air Concentration Data from the Literature

Industry / Activity 8

- hr TWA (mg/m 3 ) a STEL, Peak, Short

- Tasked Based, and Unknown (mg/m 3 ) b Data Source for 8

- hr TWA and short

term values Number of Studies Time

Range of Studies Number

of Sites Total Number of

Measurements c Mean High Midpoint d Low Mean High Mid

point 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) exposu res by the study authors; area samples and modeling results are not included. Airborne concentration conversion factor for DCM is 3.47 m g/m 3 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 A ppendix 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 95 th percentile of the collected 8

- hr TWA exposure concentrations for this industry.
f The data point provided for this industr y 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 midpoint s. Unk

- UnknownPage 179 of 279

G

- 2

- 2

- 2 Workplace E xposure 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 fr equencies (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 t he acute scenarios, EPA/OPPT defined 4 scenarios to reflect a combi nation 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 Exposu re 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, t hese multipliers a re 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 combina tion 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 w orking 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 Scenari os 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 lifet ime average daily concent rations (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 i nformation 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 o verall prevalence of the use of respirators to reduce DCM exposures. While it wasPage 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 hig h 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/OPP T evaluated occupational risks by developing hypothetical scenarios under varying exposure conditions (i.e., different respiratory pro tection factors , exposure frequencies and working years).

Approach for calculating a cute and chronic workplace exposure s : 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 Scenario s 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 whe n 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 singl e (acute) exposure concentration was set to the 8

- hour time

- weighted average (TWA) air concentration in mg/m 3 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 singl e (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/m 3 ) for

scenario 1 ; C = contaminant concentration in air for relevant industry ( central tendency,

low

- or high

- end 8

- hr TWA in mg/m 3 from 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/m 3 ) for acute scenarios 2 through 4 ; E C scenario 1 = single (acute) exposure concentration for rele vant industry ( 8

- hr TWA in mg/m 3 from Table G

- 2 or G

- 5 ); M a cute = Scenario

- specific acute exposure multiplier (unitless) for relevant industry (see Table G

- 3 )

.

Acute exposure estimates for scenario 1 are presented in Table G

- 5. Acute exposure estimates for scenarios 2 through 4 were integrated into the risk calculations by applying the scenario

specific multipliers. Thus, separate tables listing the acute exposure estimates for scenarios 2 through 4 are not provided in this section , but are available in a supplemental Excel spreadsheet documenting the risk calculations for this assessment ( DCM Exposure and Risk Estimates_0 8 1114.xlsx )

.

Chronic occ upational exposure estimates The worker exposure estimates for the non

- cancer and cancer risk calculations were estimated

as a verage d aily c oncentrations (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/m 3 reported for the various relevant industries (Table G

- 5 ). EPA/OPPT assumed that the worker would be doing paint stripping activities dur ing the entire 8

- hr work shift on a daily basis. E quation 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/m 3 ) for Scenari o 1 = ADC for chronic non

cancer risks or LADC for chronic cancer risks for Scenario 1 ; C = contaminant concentration in air for relevant industry ( low

- or high

- end

8

- hr TWA in mg/m 3 from Table G

- 2 ); ED = exposure duration (h rs/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 ; andPage 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 inhalatio n 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 c hron i c (Equation G

- 4 )

where: EC scenario 2 → 16 = exposure concentration for chronic exposure concentration (ADC or LADC) to DCM (mg/m 3 ) for chronic s cenarios 2 through 16 EC scenario 1 = chronic exposure concentration (ADC or LADC) for relevant industry, chronic scenario 1 ( in mg/m 3 from Table G

- 5 ); M c hronic = scenario

- specific ADC/LADC chronic m ultipl ier for relevant industry (see Table G

- 4 )

N on

- 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 t hrough 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 a re not provided in this section, but are available in a su pplemental Excel spreadsheet documenting the risk calculations for this assessment ( DCM Exposure and Risk Estimates_0 811 14.xlsx ).Page 184 of 279

Table G

- 5 . DCM Acute and Chronic Exposure Concentrations (ADCs and LADCs) for Workers

– Scenar io 1

- Highest Exposed

Scenario Group

Industry / Activity Time Range

of Studies ACUTE EXPOSURE ESTIMATES

Single 8

- hr Concentration (mg/m 3 ) a CHRONIC EXPOSURE ESTIMATES USED IN THE NON

- CANCER RISK ESTIMATES [ ADC (mg/m 3 ) b ] CHRONIC EXPOSURE ESTIMATES USED IN THE CANCER RISK ESTIMATES [ LADC (mg/m 3 ) 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 19 77

- 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

- 19 94

-- 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

– Scenar io 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 f rom 8

- hr TWA exposures; see Equation 3

- 1 or F

- 1. Airborne concentration conversion factor for DCM is 3.47 mg/m 3 per ppm ( NIOSH, 2011b )

. b Calculated ADCs and LADCs are only calculated from 8

- hr TWA exposur es; see Equation 3

- 3 or F

- 3.

c The values in parentheses are the 95 th 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 n on

- 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 oc cupational exposure values established. Appendix F presents a dditional background on processes, respiratory protection, facilities and worker populations.

OSHA ’s amended regulatory occupational exposure limits for DCM were effective April 10, 1 997. The amendments included reducing the permissible exposure limit ( PEL ) , reducing and changing the averaging time of the s hort

- t erm e xposure l imit (STEL), adding an A ction L evel, 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 va lues were compared to the air concentrations. Workplaces may consider these levels when instituting respiratory protections. Table G

- 6 also includes t he pre

- 1997 OSHA limits to provide context when analyzing exposure data measured on or before 1997.

Tab le 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/m 3 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 valuePage 187 of 279



### G

- 3 Summary o f Inhalation Monitoring Data

Data summaries from the literature search are presented below by sector. Inhalation exposure monitoring data of DCM during paint strippin g, specifically full

- shift 8

- h r TWA brea thing zone or personal samples , were used for risk analyses. Data m onitoring 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 fo r perspective and completeness
, but

were not use d 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 s amples.



### 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) p rogram, OSHA identified 10 other bathtub refinisher fatalities associated with DCM

based stripping agents that had been investigated in 9 states during 2000 to 2011. Each death occurred in a residential bathroom with inadequate ventilation. Protective equi pment, 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 death s 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 )

.

More over, 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 re finishing. 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 progr am 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/m 3 ) in the bathtub and 5,099 ppm to 8,499 ppm (17,694 to 29,492 mg/m 3 ) in the bathroom. The concen tration 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 ai rcraft 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/m 3 ) ( CDC, 2012 ) . Further details about the fatality case are available in the MMWR ( CDC, 2012 ) , the NIOSH FACE Program Michig an Case Report 10MI013 ( Chester et al., 2012 )
, and the Michigan S tate University (MSU)/FACE Report ( MSU/MIFACE, 2011 )

. The MSU/Michigan FACE reporte d 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 Occupati onal Safety and Health (DOSH). Although the exact date of the Washington DOSH inspection was not cited, the inspection occurred betwee n April 2003 and August 2008 ( Lofgren et al., 2010 )

.
During the inspection, a bathtub refinishing employee was monitored while stripping a residential bathtub with Kl een 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/m 3 ) and 2,000 ppm (6,940 mg/m 3 ) 23 . Two area samples were also taken and the DCM concentrations were 545 ppm (1,891 mg/m 3 ) and 314 ppm (1,090 mg/m 3 ). All of the samples significantly exceeded the OSHA 15

- minute TWA STEL of 125 ppm (434 mg/m 3 ), and the two breathing zone samples were close to the NIOSH IDLH value of 2,300 ppm (7,981 mg/m 3 ) ( 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 litera ture 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 stud ies,

23 The 15

- min DCM air concentrations of 6,940 mg/m 3 (2,000 ppm) and 7,565 mg/m 3 (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 c ontractors 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 con sumers 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 p aint 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/m 3 (10 ppm) to a few short

- term exposures of over 14,1 00 mg/m 3 (4,063 ppm) 24 . The majority of the exposures were below 1,770 mg/m 3 (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/m 3 (83.3 ppm), but the ventilation rate or air change rate was not specified. The peak exposure during application was 460 mg/m 3 (133 ppm). The peak exposure during
scrape

- off ranged from 710 to 1,410 mg/m 3 (205 to 406 ppm), and the observed maximum during th e study was 3,530 mg/m 3 (1,017 ppm). When no ventilation was used, the worst

case exposure exceeded 14,000 mg/m 3 (4,035 ppm). Based on the solvent manufacturer, 8

- hr TWA exposures under supplier

- recommended ventilation would be 187 to 226 mg/m 3 (54 to 65 p pm) ( EC, 1999 )

.

 A literature review conducted by the United Kingdom (UK) in 1998 identified 1

- hr TWA exposures of 840 to 2,765 mg/m 3 (240 to 790 ppm) in an unventilated room, and 129.5 to 948 mg/m 3 (37 to 270 ppm) with the door open ( EC, 1999 )

.

24 The short

- term exposure of over 14,100 mg/m 3 ( 4,063 ppm) was selected to represent the hig h 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 m g/m 3 (133 to 859 ppm) 25 in unventilated rooms and 60 to 400 mg /m 3 (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/m 3 (52 ppm), ranging from 21 to 318 mg/m 3 (6 to 92 ppm), was reported for “paint stripping at a block of flats” ( E U, 2007 )

.

 A case study of paint stripping in a building stairway reported an average personal DCM exposure of 86 mg/m 3 (25 ppm) ( EU, 2007 )

.

 Another case study observed an average personal DCM exposure of 710 mg/m 3 (205 ppm) while paint stripping a ceiling

. The DCM air concentration was measured during brush applicatio n and stripping over approximately 40 minutes ( EU, 2007 )

.

 A 2003 c ase study of the paint stripping of an external façade observed personal monitoring DCM concentrations with a maximum of 400 mg/m 3 (115 ppm) and a minimum of zero mg/m 3 26 . The average of all of the reported means was approximately 62 mg/m 3 (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 exch ange 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 wors t

case scenario ( EPA, 1994a )

.
During each experiment, the following samples were taken for the spray and brush applications : a personal breathing zone sample of the test subject using the paint stripper; two stationary air samples for the duration of the paint stripp ing task; and one stationary air sample

25 The DCM air concentrations of 60 mg/m 3 ( 17 ppm) and 2, 980 mg/m 3 (859 ppm) were selected to represent the low and high end s 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/ m 3 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 3,0 00 and 3,400 mg/m 3 (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/m 3 (836 to 1,037 ppm). The stationary, 8

- hr TWA concentration ranged from 1,700 to 2,000 mg /m 3 (490 to 576 ppm) ( EPA, 1994a )

.

 MRI reported breathing zone concentrations of 380 and 430 mg/m 3 (110 and 124 ppm) over sampling times of approximately 2 hours for the brush application. The stationary length

- of

task concentrations ranged from 300 to 490 mg/m 3 ( 86 to 141 ppm). The stationary, 8

- hr TWA concentration ranged from 230 to 270 mg/m 3 (66 to 78 ppm) ( EPA, 1994a )

.



### G

- 3

- 3 Graffiti Removal

Anundi et al. (1993) described a study of personal monitoring conducted on 12 worker s 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/m 3 ) was measured while the worker was wo rki ng in an elevator ( Anundi et al., 1993 ) . This observation illustrates how working in a confined space, with limited ventilation, can lead to high DCM
exposuresPage 192 of 279

Table G

- 7

. Summar y of DCM Personal Concentrations during Graffiti Removal Calculated 8

- hr TWA Concentrations (mg/m 3 ) (values in parentheses are in ppm) b 15

- min Sample Concentrations (mg/m 3 ) (values in parentheses are in ppm) b Arithmetic Mean 260 (75) d 1,117 (322) e Ge ometric 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/m 3 to units of ppm.

c EPA/OPPT calculated midpoint values from the high and low values reported by the study authors.
d The DCM air concentrations of 18 mg/m 3 , 260 mg/m 3 , 603 mg/m 3 , and 1,188 mg/m 3 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/m 3 , 1,117 mg/m 3 , 2,661 mg/m 3 , and 5,315 mg/m 3 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 f all. This worker engaged in paint stripping one to two times pe r week and 3 to 4 hrs per day. The spring 8

- hr TWA exposure was 26 ppm (90 mg/m 3 ) 28 and the fall 8

- hr TWA exposure was 120 ppm (416 mg/m 3 ). These exposures exceeded OSHA’s 8

- hr TWA action level (12.5 ppm or 43 mg/m 3 ) and PEL (25 ppm or 87 mg/m 3 ), 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/m 3 ) 29 , 93 ppm (323 mg/m 3 ), and

27 Repainting facilities are shops that specialize in repainting the entire surface of cars and small trucks.
28 The DCM air concentrat ions of 90 mg/m 3 and 416 mg/m 3 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 a nd 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/m 3 and 416 mg/m 3 were selected to represent the low and high ends of th e 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 stu dy authors.Page 193 of 279

120 ppm (416 mg/m 3 ), which had a mean value of 95 ppm (330 mg/m 3 ) and were all below the OSHA STEL (125 ppm or 434 mg/m 3 ) ( En ander 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 pa int 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 str ipping, 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 sam ples. For instance, the initial survey indicated that personal exposure concentrations associated with stripping activities ranged from 83 ppm (288 mg/m 3 ) to 523 ppm (1815 mg/m 3 ) over a range of sampling times with an average of 347 ppm (1,204 mg/m 3 ) (Tabl e 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/m 3 ) to 110 ppm (382 mg/m 3 ) over a range of sampling times with an average of 72 ppm (249 mg/m 3 ) (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 a dded to th e wash booth) (Table G

- 10) ( NIOSH, 1993 )

.
Personal samples were not taken during washing activities, and ar ea 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 ave rages of the individual samples and not the samples themselves, were below the pre

- 1997 OSHA PEL of 500 ppm (1,735 mg/m 3 ) but above the ACGIH Threshold Limit Value (TLV) of 50 ppm (174 mg/m 3 ). NIOSH noted that after the ventilation systems were installed, the 8

- hr TWA exposures were all below 50 ppm (174 mg/m 3 ) ( 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 aPage 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/m 3 ), which was a bove the OSHA PEL of 25 ppm (87 mg/m 3 ). OSHA also measured 7 STEL sampling results, which ranged from 153 ppm (531 mg/m 3 ) to 662 ppm (2,297 mg/m 3 ), with an average of 404 ppm (1,402 mg/m 3 ). These measurements were all above the OSHA STEL of 125 ppm (434 mg /m 3 ). 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 ( Grev enkamp, 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 Cont rols Added) a Personal Samples Area Samples

Activity Concentration

(mg/m 3 ) (values in parentheses are in ppm) b Sampling

Time (Minutes) Location Concentration (mg/m 3 ) (values in parentheses are in ppm) b Sampling

Time (Minutes)

Stripping large chest 1,4 37 (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 1,54 4 (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 strippe r 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/m 3

.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/m 3 ) (values in parentheses are in ppm) b Sampling

Time (Minutes) Location Concentration (mg/m 3 ) (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 bo oth (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/m 3

.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

T hird Survey (After Controls Added to Stripping Booth and Wash Booth) a Personal Samples Area Samples

Activity Concentration

(mg/m 3 ) (values in parentheses are in ppm) b Sampling

Time (Minutes) Location Concentration (mg/m 3 ) (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 dr esser 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 ND c 182

Above wash slu dge 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/m 3

.
c ND

– not detected at a limit of 0.01 mg per samplePage 198 of 279

OSHA followed

- up with the facility 10 months later and found the worker usin g 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/m 3 ), which was still above the OSHA PEL. OSHA also measured two STEL exposures of 330 ppm (1,145 mg/m 3 ) and 380 ppm (1,319 mg/m 3 ), which were still above the OSHA STEL ( Grevenkamp, 2007 )

.
The facility hired a consu ltant 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/m 3 ) and a STEL
expos ure of 1,072 ppm (3,720 mg/m 3 ). 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 advi ce on the exposures. Over these six visits, the consultant measured five 8

- hr TWA exposures ranging from 44 ppm (153 mg/m 3 ) to 647 ppm (2,245 mg/m 3 ) 30 with an average of 278 ppm (965 mg/m 3 ). The consultant also measured 12 STEL or task

- based samples (approximately 3 hrs), ranging from 298 pp m (1,034 mg/m 3 ) to 2,015 ppm (6,992 mg/m 3 ) 31 with an average of 926 ppm (3,213 mg/m 3 ) ( Grevenkamp, 2007 )

.
OSHA visited the facility again and measured an 8

- hr TWA exposure of 192 ppm (666 mg/m 3 ) and three STEL exposures ranging from 300 ppm (1,041 mg/m 3 ) to 811 ppm (2,814 mg/m 3 ) with an average of 481 ppm (1,669 mg/m 3 ). OSHA then recommended improved engineering controls consisting of a combination of a slotted back draft hood coupled with a down draft ventilation system. After the facility implemented these controls, OSHA measured an 8

- hr TWA exposure of 1.16 ppm (4 mg/m 3 ) 32 and a STEL exposure of 5.5 ppm (19 mg/m 3 ) 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 re quired 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 em ployed a total of 6 full

- time employees, including two co

owners. Two employees regularly stripped furniture on a daily basis while the other employees performed other refinishing operations. The facility used a dip tank for stripping, followed by a rinse, drying, and then applying the new finish. The stripping solutions were prepared by the facility and contained 60 to 80 percent DCM.

30 The DCM air concentrations of 2,245 mg/m 3 w as 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/m 3 w as selected to repres ent 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/m 3 w as selected to represent the low end of the range of 8

- hr TWA values for furnit ure refinishing in Table G

- 2 (Grevenkamp, 2007).
33 The DCM air concentrations of 19 mg/m 3 w as 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/m 3 ) without the ventilation system, which prompted the facility t o activate the existing ventilation system. The existing ventilation system reduced DCM levels to 230 ppm (798 mg/m 3 ). After completing the initial air sampling, NIOSH evaluated the existing ventilation system and recommended a new design. The facility ins talled 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 oper ations over a period of 3 days ( Hall et al., 1995 )

.

Table G

- 11 summarizes NIOSH’s per sonal 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 vent ilated. The NIOSH researchers felt that exposures could be reduced to meet the (at the time proposed) OSHA PEL of 25 ppm (87 mg/m 3 ) if the rinse area controls were improved ( Hall et al., 1995 )

. McCammon et al. (1991) described a N IOSH 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 refin ishing

.
Personal air sampling of these facilities reported TWA exposures to DCM ranging from 15 ppm (52 mg/m 3 ) to 366 ppm (1270 mg/m 3 ) over 5 to 8 hrs with an overall average of 133 ppm (462 mg/m 3 ). A shop where a single worker was monitored (who perform ed both stripping and washing) had a 4

- hr TWA exposure of 57 ppm (198 mg/m 3 ). The highest average exposures to DCM by job category were: 191 ppm (663 mg/m 3 ) for strippers; 145 ppm (503 mg/m 3 ) for washers; and 31 ppm (108 mg/m 3 ) for refinishers. These TWA e xposures were below the pre

1997 OSHA PEL of 500 ppm (1,735 mg/m 3 ). 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 wer e constant throughout the
year ( McCammon et al., 1991 )

.Page 200 of 279

Table G

- 11

. Summary of Worker E xposures to DCM During Furniture Paint Stripping using a

Dip Tank after Implementation of NIOSH

- Recommended Slotted Hood Ventilation System a

Number of Samples Sample Concentration

Ranges (mg/m 3 )

(values in parentheses are in ppm) b Total

Time Sampled (m in) Total

Time Sampled (hr) Personal TWA C oncentration (mg/m 3 ) 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/m 3

. 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 surv eys are described below.

 Furniture stripping workshop in Meadow Lands, Pennsylvania : The workshop used a flow

over tank with a solution recycling system to strip furnit ure. The furniture was placed in tank, covered with stripping solution, and then scrubb ed by a worker. During scrubbing, the worker alternate d 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 solutio n that contained 60 volume percent DCM ( Estill and Spencer, 1996 ; NIOSH, 1991 )

.
The workshop installed a ven tilation 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/m 3 ) to 1,152 ppm (3997 mg/m 3 ) 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 ppmPage 201 of 279

(1,735 mg/m 3 ). After completin g the air sampling, NIOSH made recommendations for improving the ventilation system ( Estill and Spencer, 1996 ; N IOSH, 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 d ay. The three daily average DCM exposures were 25 ppm (87 mg/m 3 ), 41 ppm (142 mg/m 3 ), and 22 ppm (76 mg/m 3 ), 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/m 3 ); 17 to 106 ppm (59 to 368 mg/m 3 ); and 6 to 32 ppm (21 to 111 mg/m 3 ), respectively. The corresponding calculated 8

- hr TWA exposures were 15, 29, and 13 ppm (52, 101, and 45 mg/m 3 ), respectively. The 9 individual measur ements taken over the 3 days and over the 3 different ventilation system configurations ranged from 7 to 59 ppm (24 to 205 mg/m 3 ) 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 o f 100 ppm (347 mg/m 3 ) and 77 ppm (267 mg/m 3 ) of the facility owner and the NIOSH employee, respectively. NIOSH observed three area concentrations of 20 ppm (69 mg/m 3 ) , 63 ppm (219 mg/m 3 ) , and 90 ppm (312 mg/m 3 ) . 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/m 3 ) ( 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 s olution

soaked furniture, but no other personal protective equipment was worn ( NIOSH, 1990 )

.

The EC (1999) report described a 1990 EPA source that cited exposure levels in furniture paint stripping ranging from 258 to 3,812 mg/m 3 (74 to 1,099 ppm) in the absenc e of adequat e 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/m 3 (144 ppm) and a 95 th

- percentile value of 1,266 mg/m 3 (365 ppm) (Table G

2)

.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 (Tabl e G

- 12). The data point was an 8

- hr TWA exposure of 2 mg/m 3 (0.58 ppm) and corresponded to the exposure of a manager ( OSHA, 2012a ) . This is the only value reported for art restora tion and conservation in Table G

- 4. The relevance of this exposure to DCM

- based paint stripping is

uncer tain 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/m 3 (23 to 274 ppm) wi th a mean of 379 mg/m 3 (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 sampl ing time of 267 minutes

. Personal air samples ranged from 38 34 to 2,820 mg/m 3 (11 to 813 ppm) with a mean of 795 mg/m 3 (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/m 3 ), with a mean of 62 ppm (215 mg/m 3 ). Peak levels wer e as high as 1,600 ppm (5,552 mg/m 3 ) ( EC, 1999 ; EU, 2007 )

. Vincent et al. (1994) observed the paint stripping of a Boeing 747 in an aerona utical 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/m 3 (86 ppm) to 1,888.9 mg/m 3 (544 ppm) over 3 8 data points with a mean of 783.4 mg/m 3 (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/m 3 (25 ppm) 35 to 1,239.5 mg/m 3 (357 ppm) with a mean of 382 mg/m 3 (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/m 3 (91 to 220 ppm) with a mean concentration of 464 mg/m 3 (134 ppm). The calculated 8

- hr TWA

34 The DCM air concentration of 38 mg/m 3 was selected to represent the low end of the range of short

- term and other non

- 8

- hr TWA values for air craft paint stripping in Table G

- 2 (NIOSH, 1977).
35 The DCM air concentration of 86 mg/m 3 was selected to represent the low end of the range of 8

- hr TWA values for air craft 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/m 3 (28 to 50 ppm) with a mean of 128.2 mg/m 3 (37 ppm) ( EU, 2007 ; IARC, 1999 ; Vincent et al., 1994 )

.
Norwegian studies from 2001 and 2002 found 8

- hr TWA exposures to DCM associated wit h paint removal of aircraft of 1,444, 2,319, and 3,802 mg/m 3 (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/m 3 (29 to 95 ppm) with a mean of 210 mg/m 3 (61 ppm). The same study also stated that peak exposures as high as 5,400 mg/m 3 (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 loc ations 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/m 3 (42, 22, 23, and 20 ppm) fo r the ground, nose, right wing, and left wing, respectively. The standard deviations of each average ranged from 40 to 111 mg/m 3 (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/m 3 (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 worke rs) was not provided in the identified references.

36 The DCM air concentration of 3,802 mg/m 3 was selected to represent the high end of the range of 8

- hr TWA values for aircraft paint stripping in Tab le G

- 2 (EU, 2007).
37 The DCM air concentration of 5,400 mg/m 3 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/m 3 (11 to 2,017 ppm) 38 with a mean of 700 mg/m 3 (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/m 3 (10 to 605 ppm) 39 and a mean of 350 to 420 mg/m 3 (101 to 121 ppm).

Moreover, the same 1998 UK report described in the EC (1999) docum ent reported DCM exposure data during the immersion stripping of metal. The exposures were characterized as less than 350 mg/m 3 (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/m 3 (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/m 3 (10 to 204 ppm) with an overall average of 324 mg/m 3 (93 ppm). Two maximums of 459 and 1,413 mg/m 3 (132 and 407 ppm) were also presented ( EU, 2007 )

.

The EU (2007) report discussed a 2004 report about DCM exposure monitoring data in Germany

assoc iated with both indoor and outdoor paint stripping in 1997. The 62 indoor measurements ranged from 294 to 3,035 mg/m 3 (85 to 875 ppm) 42 over unknown sampling times. The mean was 1,373 mg/m 3 (396 ppm) and the 95 th percentile was 2,457 mg/m 3 (708 ppm). The 37 outdoor measurements were only slightly lower with a range of 158 to 2,275 mg/m 3 (46 to 656 ppm) (the sampling times ranged from three to 295 minutes). The mean was 524 mg/m 3 (151 ppm) and the 95 th percentile was 1,339 mg/m 3 (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/m 3 (0.07 to 785 ppm) 43 . The arithmetic mean was 163 mg/m 3 (47 ppm),

38 The DCM air concentration of 7,000 mg/m 3 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/m 3 was selected to represent the low end of the range f or 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/m 3 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/m 3 were selected to represent the low and high ends of the

ran ge 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/m 3 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/m 3 was selected as the low end of the range of short

- term and other non

8

- hr TWA values for non

- specific workplace settings (unkno wn) in Table G

- 2 (EU, 2007).Page 205 of 279

the geometric mean was 17.2 mg/m 3 (5 ppm), the median was 17.5 mg/m 3 (5 ppm), and the 95 th percentile was 956 mg/m 3 (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 t he res pirator type. The 8

- hr TWA concentrations

were 285 mg/m 3 (82 ppm) 44 and 5 mg/m 3 (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 5 7. The second study was conducted in 1998 and measured 8

- hr TWA concentrations of 428 mg/m 3 (123 ppm) 39 and 2.2 mg/m 3 (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 measure ments obtained from OSHA IMIS for the industries of interest. Area measurements were excluded from this summary. Additionally, non

detect results were excluded from this summary. A non

- detect result is not meaningful for risk analyses as it could be the re sult 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 tempo ral 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/m 3 ).

For the industries that have data both before and after 1997 (aircraf t 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 90 th percentile of TWA exposures in ship and boat refinis hing increased by more than 100 percent from pre

- 1997 to post

- 1997.

44 The DCM air concentrations of 285 and 428 mg/m 3 w ere 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/OPP T 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 p roblems 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 in forming 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 STE L mg/m 3 ppm mg/m 3 ppm mg/m 3 ppm mg/m 3 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 Poi nts 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

-- -- Numb er of Data Points 11 5 8 NonePage 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 STE L mg/m 3 ppm mg/m 3 ppm mg/m 3 ppm mg/m 3 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 model ing 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

- vary ing 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. E C Chamber Study

— European Commission, ETVAREAD. Effectiveness of vapour retardants in reducing risks to human health from paint strippers containing dichloromethane ( EC, 2004 ) ;

3. van Veen Chamber Study

— van Veen, M.P., Fortezza, E.S. and Mensinga, T.T. Non

professional paint stripping and experimental validation of indoor dichloromethane levels

. Indoor Air, 12:92

- 97 ( van Veen et al., 2002 ) ;

4. Lawrence Berkley Laboratory ( LBL Chamber Study )

— Girman, J.R. and Hodgson, A. T. Source Characterization and Personal Exposure to Methylene Chloride from Consumer Products
, Lawrence Berkeley Laboratory, Report No. LBL

- 20227 ( LBL, 1986 )

.
Data from the MRI chamber study were used as the basis for developing emission profiles for the brush

- on and spray

- on applications evaluated in this assessment ( EPA, 1994a ) . The advantages of the MRI study include the following: (1) the chamber data were adequate to support the estimation effort; and (2) the products studied were considered to be the most representative of paint strippers available in the U.S. consumer prod uct 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) usePage 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 non

U.S. products. Moreover, the study had limitations similar to the EC study, although room volumes and ventilation rates were more in line with values that mig ht 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 study 45 . 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 section s 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 disc ussion 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 D CM content (% by weight). The DCM content (83

- 87%) was determined analytically by LBL ( LBL, 1986 )

. In the van Veen study, the DCM content was reported, but not its basis ( van Veen et al., 2002 )

. For the EC experiments, the DCM content was assumed to be 82.5% (midpoint of range for their “typical formulation”) ( EC, 2004 )

. For the MRI experiments, DCM contents of 16.8% for a brush

- on product and 85.0% for a spray

on product were assumed based on formulation data ( e.g., per MSDS ) near the time when these experiments were conducted ( EPA, 1994a )

.
The DCM mass emitted per experiment was estimated by two alternative methods:

1. Mass

- balance Calculation

– this method consisted of (a) using the starting and ending concentrations for successive brief ( ≤ 10

- minute) time intervals, together with knowledge of the airflow rate into and out of the chamber, to determine the mass emitted during each interval; and (b) summing these estimates to determine the total DCM mass emitted during the entire experiment.
2. Model Fit to Chamber Data

– this method consisted of (a) using nonlinear least squares (NLS) analysis to fit an incremental source model governed by a single exponential; and (b) calculating the mass emitted by integrating the fitted model over the duratio n 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:


### MR i, i+1 

### = (C i+1 

### - C i 

### )*V + Q*(  t )*(C i+1 

### + C i 

### )/2 ) (Equation H

- 1)

Where: 

### MR i, 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 i n the compartment, mg/m 3 compartment volume, m 3 compartment ventilation rate, m 3 /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 eac h 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 t he 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 = E 0 e − kt (Equation H

- 2) Where: E = emission rate, mg/hr E 0 = initial emission rate (the emission rate at t = 0), mg/hr k = first

- order rate constant, hr

- 1 t = time since application, hr

Integra ting Equation H

- 2 to infinity gives the mass released according to the exponential, as follows:
Mass Released (mg) = E 0 k (Equation H

- 3)

Or: E 0 = ( Mass Released ) ∗ k (Equation G

- 4)Page 212 of 279

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, 1 997 )
, respectively:

Single

- exponential representation

C ( t ) = E 0

V ∗ ( Q V − k ) ( e − kt

− e − Q V t ) (Equation H

- 5)

Where: C(t)= concentration, mg/m 3 V = chamber volume, m 3 Q = air flow rate in and out of the chamber, m 3 /hr

Doub le

- exponential representation

C ( t ) = E 01

V ∗ ( Q V − k 1 ) ( e − k 1 t

− e − Q V t ) + E 02 V ∗ ( Q V − k 2 ) ( e − k 2 t

− e − Q V t ) (Equation H

- 6)

Where: E 01 = initial emission rate for the first exponential, mg/hr E 02 = initial emission rate for the second exponential, mg/hr k 1 = first

- order rate constant for the first exponential, hr

- 1 k 2 = 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 exper iments 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

- in tegrated 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 s tudy teste d 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 bet ween successive applications. In each case, thePage 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 applicatio n 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 dat a 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 ex tracted, 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 1/8 th 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 an d the following relationship:

E 0 = ( 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 vis ual 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 b etter 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 re lated 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 ei ght exponentials are shown in the lower part of the figure, with the sum sho wn 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 C hamber Study for BIX Spray

- on Product

Figure H

- 2

. Model Fit to Data Extracted from MRI Chamber Study Report for Strypeeze Brush

on ProductPage 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 0.85 b 459.0 0.66 10.0
Stry peeze (Brush

- On) Run 7 724 0.168 c 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 perform ed by using the average concentration for each one

- minute interval. Then a mass

balance calculation was conducted for the test chamber, which accounted for the mass in the chamber and the mass that had been removed through ventilation. The estimated cumula tive 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 Sp ray - on Stripper

111 minutesPage 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 p roducts. 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 infer ence 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 MSDS a Strypeeze

2013 MSDS a LBL (1986),

Paint Remover (PR)

- A LBL (1986),
PR

- B
DCM >10% 25

- 30% 83.0% 86.6% Toluene >35% 15

- 20% Met hanol 25% 25

- 30% Present b Present b
Acetone <25% 15

- 20% Paraffin Wax <5% 0

- 5% Aliphatic Hydrocarbon 0

- 5%

-- Isopropanol 9.4% Xylenes Present b
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 minutesPage 217 of 279

The LBL and MRI studies used similar ventilation rates

— ~3.0 hr

- 1 and 0.6 hr

- 1 for LBL Experiments 2 and 5, respectively; and ~0.55 hr

- 1 for each of MR I 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 Br ush

- on Products Study and Expt/Run a Chamber Duration, min Applied Product

Mass, mg Applied DCM

Mass, mg % DCM

Released Vol, m 3 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 0.5 6 105 724,000 121,632 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 emission s:

 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 highe r 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 mi nimal impact on the DCM emission rate and total mass emitted. LBL Experiments 2 and 5 are very similar with the exce ption of the ventilation
rate. A greater fraction of the mass might be expected to be released in an environment with a higher ventilation r ate, 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 V een et al., 2002) and EC Chamber Study (EC, 2004)
EC (2004) and van Veen et al. (20 02) 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

- m 2 horizontal surface under a range of ventilation rates (0.26

- 0.73 hr

- 1 ). The substrate
mater ial 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 detector 46 ” 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, desc ribed 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 G as 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

Re leased Vol, m 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 va por

retarded, DCM

- containing paint strippers. TWA concentrations were reported for ten such products available on the European market, as shown in Figure H

- 6. Of these ten products, six were described as “fluid” and the remaining four as “paste.” The chamb er was a 15 m 3 room with a ventilation rate of 60 m 3 /hr (4 hr

- 1 ) for the standard

- condition studies. The substrate was a 1.0

- m 2 chipboard in a vertical orientation. The composition of specific products was not provided, but the study reported a DCM content ranging from 75 to 90% for the typical formulation of DCM

- containing paint strippers on the European market. A single application of the paint stripper lasting about 5 minutes was made to the entire substrate, with scraping occurring after a typical “effe cting” 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.

As suming 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 t ogether 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 e ven 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 ab ove 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 unde r 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 pa int

- 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 t o 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 sec tion 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
app roximately 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 t he 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 with in 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 d ue 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 E xperiment Applied Product Mass, mg DCM

Weight Fraction Applied

DCM Mass, mg Chamber DCM Mass Released at Duration NLS Fit b

Theor etical Mass Released Title a Duration,

min Volume,

m 3 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, 1994 a ) 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 theoret ical 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 a t 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 wou ld 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 dis cretely 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 wi th the change in location pattern from the base case.



### H

- 3 Inhalation Exposure Scenario Inputs

Method of Application. A review of product labels and technical data sheets indicates that paint stripping products can be applied using either brush

- on or spray

- on ( i.e. , aerosol or trigger

pump) application methods. In this assessment, exposures were assessed for both brush

- on and spray

- on products due to differences in chemical release characteristics, DCM weight fraction of products, application rates, and time req uired 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/ft 2 ) and the surface areas of objects to be stripped (ft 2 ). 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 t he large nationwide survey by CPSC (1992) , as reported in Table 17

- 20 of the Exposure Factor s 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 o f the nominal product density (~1.1 g/cm 3 ) (calculated from Brown, 2012) yielded a product mass on the order of 1,000 grams as a central estimate. An upper

- end application amount (~80 th 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 pr oduct used.Page 224 of 279

Median product masses of 900 and 680 g were input into the model for the brush

- on and spray

on scenarios, respectively. Upper

- end product masses for the brush

- on and spray

- on scenarios were 2,250 and 1700 g, respectively.

The bathroom sce nario 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 identifi ed in the NIOSH report ( CDC, 2012 )

.
The application amounts for Scenarios 1 through 6 were obtained by multiplying the application rates calculated from the MR I experiments ( EPA, 1994a ) and the surface area of objects to be treated. The calculated application rates were ~90 g/ft 2 for a brush

- on application of a DCM

containing product (722 g of product applied to 8 ft 2 ) and ~68 g/ft 2 for a spray

- on application of a DCM

- co ntaining product (540 g of product applied to 8 ft 2 ). These application rates were similar to those recommended on the Savogran Company website for paint strippers in general

— 1 gallon per 50 to 100 ft 2 (~42 to 83 g/ft 2 based on a nominal density of 1.1 g/c m 3 ) 47

.
The applied surface areas selected for central and upper

- end values were 10 and 25 ft 2 . 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 wi th surface areas close to the two specified surface areas (10 and 25 ft 2 ) were used in the exposure scenarios to reflect real

world situations. A coffee table with nominal dimensions of 4 ft × 2.5 ft for the top surface was selected for the central case (1 0 ft 2 ) 48 . A chest of drawers with nominal dimensions of 4 ft high by 2.5 ft wide by 1.5 ft deep 49 was selected for the upper

- end case (4 × 2.5 ft 2 for front + 2.5 × 1.5 ft 2 for top + 2 × 4 × 1.5 ft 2 for sides ≈ 25 ft 2 ). For the bathroom scenario, a bathtub s urface area of 36 ft 2 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 in formation for some DCM

- containing products ( i.e. , Klean Strip® products) indicate that no more than 9 ft 2 should be stripped at a time. Accordingly, the 10

- ft 2 surface for the coffee table was divided into two application segments of 5 ft 2 each. The 25

- ft 2 surface for the chest was divided into four application segments of 6.25 ft 2 each. The 36

- ft 2 surface for the bathtub was divided into four application segments of 9 ft 2 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=1093Page 225 of 279

instructions on the majority of product labels indicating that the stri pping 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 segmen t consisted of applying the product to the target surface followed by a wait period and then scraping the treated surface. The application and
scrape time s w ere deduced from the protocol descr iption 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 peri od 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 duratio ns 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 sa me 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 sequenc es 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 reporte d 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, 1 st time 0

- 2 2

- 17 17

- 21 Seco nd 1/4, 1 st time 21

- 23 23

- 38 38

- 42 Third 1/4, 1 st time 42

- 44 44

- 59 59

- 63 Fourth 1/4, 1 st time 63

- 65 65

- 80 80

- 84 First 1/4, 2 nd time 84

- 86 86

- 101 101

- 105 Second 1/4, 2 nd time 105

- 107 107

- 122 122

- 126 Third 1/4, 2 nd time 126

- 128 128

- 143 143

- 147 Fourth 1 /4, 2 nd 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 90 th 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 lis t, 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/ft 2 a Weight

Fraction b Release

Fraction DCM Mass

Released, g Coffee table (10 ft 2 ) 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 Ch est of drawers (25 ft 2 ) Brush

- on Spray

- on 90 68 0.88

0.87 0.33

0.66 653.4

976.1 Bathroom tub (36 ft 2 ) 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 fracti ons 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 u pper

- 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 ru ns (492 m 3 ) is the central value listed in the 2011 EFH ( EPA, 2011a )

. The volume assigned to the in

- house

wo rkshop area was 54 m 3 , corresponding to a 12 ft × 20 ft room with an 8

- ft ceiling (20 × 12 × 8 = 1,920 ft 3 or ~54 m 3 ). 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 m 3 ). The volume for the ROH ( 438 m 3 ) is determined by subtraction (492 m 3

- 54 m 3 ). For the b athtub scenario, the bathroom volume was set at 9 m 3 for consistency w ith 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 10 th 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 contribut e to upper

- end concentration estimates.

For the workshop, it was assumed that multiple windows were opened. T he indoor

- outdoor airflow rate assigned to this zone (68 m 3 /hr) was obtained by multiplying the room volume of 54 m 3 by the 90 th 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 da ta. 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 percen t 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 p aint 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 tha t 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 alg orithm, developed by EPA (1995a) : Q = (0.078 + 0.31*ACH) * house volume ( Equation H

- 10) where Q is the interzonal airflow rate, in m 3 /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 m 3 yields an estimated interzonal airflow rate of 107 m 3 /hr.

The algorithm was derived from empirical ventilation data collected in over 4,000 U.S. residences by the perfluorocarbon tr acer (PFT) technique ( EPA, 1995a ) . In the EP A (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 m 3 /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 liter ature. 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

v irtual compart ment around the source ( Cherrie, 1999 ) , rough partitioning ( Musy et al., 1999 )
, and a zero

- equation tu rbulence 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 th e virtual compartment has not b een discussed in the literature, Furtaw et al. (1996) successfully represented concentrations using a sphere around the source (with an unspecified Denotes air flow 1.6
m 3 /hr Rest of Bathroom (8 m 3 ) 35

m 3 /hr Rest of

House (483 m 3 )

“Source Cloud” (1 m 3 ) 86.9
m 3 /hr

80
m 3 /hrPage 230 of 279

volume). Thus, both the presence of higher concentrations nea r 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 heav ier

- 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 worksh op 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 wor ker’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 i n 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 a rea, 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 virt ual 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 m 3 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

Fig ure 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 h eating 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 dev eloped 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 (m 2 ). An assumed air velocity of 65 m/hr, representing the fa n

- off case, together with an assumed entry/exit surface area of 5 ft by 2 ft, 8 in (13.35 ft 2 or 1.24 m 2 ) resulted in an estimated airflow rate of 80 m 3 /hr between the source cloud and the rest of the bathroom. HVAC OFF and ON flows for Master BedroomPage 233 of 279

Locations of Exposed Individuals. Two locat ion 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 assume d 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 concentrati ons 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”). A lso, 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 a s going to the kitchen and making a sandwich or going outside to do yard work.

For the upper

- end Scenarios 2 and 5, it was assumed that the user would stay in the workshop, based on the fact that some people do not read/skim labels (~28 percent in 1990) ( Pollack

Nelson, 19 95 ) 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 im mediately 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 t he roo m 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 R OH 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 tim e. 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 coi ncides 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 differe nt 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 ca n 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 interv al, i to i +1 , for i = 0 to 1,440:

EC i
, i + 1 = [ ( C 1 , i + C 1 , i + 1 ) 2 ⁄ ]

∗ F

i
, i + 1 + [ ( C

ROH
, i + C

ROH
, i + 1 ) 2 ⁄ ]

∗ ( 1

− F

i
, i + 1 ) (Equation H

- 11)

where: EC

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

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

ROH,i+1 = the concentrations in the ROH zone at times i and i+1 , respectively F i,i+1 = the fraction of time spent in the use zone during the time interval i to i +1

These calculations, illustra ted in Figure H

- 11, were implemented in an Excel spreadsheet for each of the seven scenarios.

Figure H

- 11 . Example of the Exposure Concentration Calc ulation as Defined in Equation H

- 11Page 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
pe riod) 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

- 15 50 . 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 app lication) 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 non

user’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 bru sh 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 pro duct); 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 t he 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 m inor 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/m 3 , 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 2 79

r eflected 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 worksho p 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/m 3 for spray

- on vs

. 1,300 mg/m 3 for brush

- on) again had a ratio (1.54) that was similar to that for the applied mass.

Figure H

- 14 shows the zone and user exposure concentration results for Scenarios 3 and 6 (brush and spray application, respectively) for the workshop with p arameter 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 n on

- user was exposed (180 mg/m 3 for spray application

vs . 120 mg/m 3 for brush application). The more pronounced crossover of the Zone 1 and 2 concentration time series for these scenarios, shortly after the user finishes the last scraping, can be explained by the indoor

- outdoor air exchange rates: 1.26/hr for the workshop vs

. 0.18/hr for the 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.

Fi gure H

- 15 shows the air concentrations for the simulation scenario, namely the bathtub stripping activity with a modeled peak concentration of ~3,000 mg/m 3 . The saw

- tooth appearance of the concentration rise associated with the stripping activity

— particula rly 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 fa tality 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 pp m, 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 bathtu b 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 Concen trations for Scenarios 1 and 4, Stripper Application in Workshop using Central Parameter

ValuesPage 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 ExposurePage 240 of 279

Figure H

- 15 . Modeled DCM Concentrations for Scenario 7, Brush Application in Bathroom (Simulatio n)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 supp ort from the U.S. Consumer Product Safety Commission (CPSC).

The LBL (1987) study includes both monitored and modeled exposure results from consumer

use scenarios t hat 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/m 3 that were calculated for the EPA/OPPT assessment. With k nowledge 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/m 3 DCM.

LBL conducted a total of 21 experiments, so me 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 interi or door together with some form of ventilation, in accordance with both label instructions and predominant patterns of paint

- stripper use based on household surveys (s ection H

- 3, Airflow Rates and Volumes ).

For all 6 workshop cases in the EPA/OPPT assess ment, 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 prod uct 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 Estimat es

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 volu me and ventilation rate, the EPA/OPPT workshop cases (volume = 54 m 3 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 additio n 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 o f 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 rat e 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

Tabl e 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

Ra te for Work Area, ACH User

Location during Wait Period TWA Exposure during

Work Period, mg/m 3

User Non

- user OPPT Cases (modeled with door to room of application assumed to be open in all cases) Workshop (54 m 3 ) Brush

- Table 157.4 84 1.26 ROH 17 4 25 Workshop (54 m 3 ) Brush

- Table 261.4 84 1.26 Workshop 917 42 Workshop (54 m 3 ) Brush

- Chest 653.4 168 1.26 ROH 563 186 Workshop (54 m 3 ) Spray

- Table 359.0 80 1.26 ROH 383 55 Workshop (54 m 3 ) Spray

- Table 390.5 80 1.26 Workshop 1,418 5 9 Workshop (54 m 3 ) 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 m 3 ) Brush

- Panel 194.8 102 0.13 Bedroom 2,090

--- Bedroom (22.6 m 3 ) Brush

- Panel 223.4 89

-- - a Bedroom 771 143 Bedroom (22.6 m 3 ) Brush

- Panel 253.8 90 1.57 Bedroom 982

--- Dining R oo m (73.2 m 3 ) Brush

- Panel 231.4 88 0.23 Dining Room 574 67 Basement (60.7 m 3 ) Brush

- Panel 247.5 92 1.60 b Basement 818

---
Notes:

a Not measured but l ikely 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 compar able non

- user (bystander) exposures

Non

- user= Residential bystanderPage 244 of 279



### H

- 6 MCCEM Inhalation Modeling Scenario Summaries

Formula: CH 2 Cl 2 CAS Number: 75

- 09

- 2 Molecular Weight: 84.93 g/mol Density: 1.33 g/cm 2 (liquid) Appearance colorles s 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/m 3 Saturation Concentration: 463,862 ppm = 1,611,281 mg/m 3

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 m 3 ROH volume = 492

– 54 = 438 m 3 Airflows: Workshop

- outdoors 68 m 3 /h
ROH

- outdoors 197.1 m 3 /h (0.45 ACH) Workshop

- ROH 107 m 3 /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 f raction) × 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 ti me 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 minPage 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 Concentr ations (maximum values over first 24 hrs):

In mg/m 3 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 h r 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 bystanderPage 247 of 279

DCM Scenario 2. Coffee Table, Brush

- On, Workshop, User in Workshop during wait time, 0.45 ACH, 0.88 Weight Fraction

MCC EM Input Summary Application Method: Brush

- on Volumes: Workshop volume = 54 m 3 ROH volume = 492

– 54 = 438 m 3 Airflows: Workshop

- outdoors 68 m 3 /h
ROH

- outdoors 197.1 m 3 /h (0.45 ACH) Workshop

- ROH 107 m 3 /h

DCM Mass Released: Coffee table = 10 sq ft surfa ce 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 nee ded 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 mi n 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 (2 2 hrs, 36 minutes)Page 248 of 279

MCCEM Results Summary Exposure Concentrations (maximum values over first 24 hrs):

In mg/m 3 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 1 36.3 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 bystanderPage 250 of 279

DCM Scenario 3. Chest, Brush

- On, Works hop, User in ROH during wait time, 0.18 ACH, 0.88 Weight Fraction

MCCEM Input Summary Application Method: Brush

- on Volumes: Workshop volume = 54 m 3 ROH volume = 492

– 54 = 438 m 3 Airflows: Workshop

- outdoors 68 m 3 /h
ROH

- outdoors 78.8 m 3 /h (0.18

ACH)
Wor kshop

- ROH 65.8 m 3 /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 2 1

- 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 d uring 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/m 3 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

- u ser= Residential bystanderPage 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 m 3 ROH volume = 492

– 54 = 438 m 3 Airflows: Workshop

- outdoors 68 m 3 /h
ROH

- outdoors 197.1 m 3 /h (0.45 ACH) Workshop

- ROH 107 m 3 /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 a fter 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/m 3 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 bystanderPage 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 m 3 ROH volume = 492

– 54 = 438 m 3 Airflows: Workshop

- outdoors 68 m 3 /h
ROH

- outdoors 197.1 m 3 /h (0.45 ACH) Workshop

- ROH 107 m 3 /h

DCM Mass Released: Coffee table = 10 sq ft surface area Applied p roduct 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 in puts) 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

se cond 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 minut es)Page 257 of 279

MCCEM Results Summary Exposure Concentrations (maximum values over first 24 hrs):

In mg/m 3 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 bystanderPage 259 of 279

DCM Scenario 6. Chest, Spray

- On, Workshop, User in R OH during wait time, 0.18 ACH, 0.87 Weight Fraction

MCCEM Input Summary Application Method: Spray

- on Volumes: Workshop volume = 54 m 3 ROH volume = 492

– 54 = 438 m 3 Airflows: Workshop

- outdoors 68 m 3 /h
ROH

- outdoors 78.8 m 3 /h (0.18 ACH) Workshop

- ROH 65.8 m 3 /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 period s 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/m 3 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= Residen tial bystanderPage 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 m 3 Rest of Bathroom volume = 9

- 1 = 8 m 3 ROH volume = 492

– 9 = 483 m 3 Airflows: Source Cloud

- Bathroom 80 m 3 /h (0 to outdoors/ROH) Bathroom

- outdoors 1.6 m 3 /h
ROH

- outdoors 86.9 m 3 /h (0.18 ACH) Bathroom

- ROH 35 m 3 /h

DCM Mass Released: Tub = 36 sq ft surface area Applied product mass = 90 g/s q 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 minPage 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 Summa ry Exposure Concentrations (maximum values over first 24 hrs):

In mg/m 3 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 m in 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:Page 264 of 279 Non

- user= Residential bystanderPage 265 of 279



## Appendix I RISK ASSESSMENT GUIDELINES, LITERATURE

SEA RCH STRATEGY AND DATA QUALITY CR ITERIA USED IN THE HAZARD/DOSE

RESPONSE ASSESSMENTS OF METHYLENE CHLORIDE

EPA/ OPPT’s work plan risk assessment for dichloromethane ( DCM ; methylene chloride) is based on the peer

- reviewed hazard and dose

- response information published in the following repor ts:

 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
str ategy and data quality criteria used in these assessments.



### I

- 1 EPA/IRIS Toxicologica l Review

I

- 1

- 1 Risk Assessment Guidelines

The description below was extracted from the DCM IRIS assessment published in November 2011 ( E PA, 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 th e DCM IRIS assessment include the following:

1. Guidelines for the Health Risk Assessment of Chemical Mixtures ( EPA, 1986b ) ; 2. Guidelines for Mutagenic ity 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 Toxi city ( EPA, 1994b ) ; 6. Methods for Derivation of Inhalation Reference Concentrations and Application of Inhalation Dosimetry ( EPA, 1994c

) ; 7. Use of the Benchmark Dose Ap proach in Health Risk Assessment ( EPA, 1995b ) ;Page 266 of 279

8. Guidelines for Reproductive Toxicity Risk Assessment ( EPA, 1996b ) ; 9. Guidelines for Neurotoxi city 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 thi s 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 Toxicol ogy 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 Informat ion 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. Oth er 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 followin g study selection and data quality crit eria were used by the EPA ’s IRIS program when devel oping 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 c riteria 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 confo unding and effect modific ation (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 Cons iderations for Epidemiological StudiesPage 268 of 279

Figure I

- 2

. Study Quality Considerations for Animal StudiesPage 269 of 279



### I

- 2 Acute Exposure Guideline Levels (AEGLs)

AEGLs are emergency response guideline levels for on ce

- 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 Le vels for Hazardous Chemicals ( NRC, 2001 )

. Specifically, the AEGL SOP contains the following information supporting the derivations of AEGLs, including tho se for DCM ( NRC, 2001 ) :

 Empirical toxicologic al e ndpoi nts and methods for determining exposure concentrations used to derive AEGLs 1,2, and 3 ( Chapter 2.2 of the AEGL SOP ) ;

 Guidelines and c riteria for t he search strategy, evaluation, selection, and documentation of key data and supporting data u sed for the derivation of AEGL values ( Chapter 2.3 of the AEGL SOP ) ;

 Dosimetry corrections from animal to human e x posures ( Chapter 2.4 of the AEGL SOP )

 Guidelines and criteria for selection of uncertainty f actors to address the variability between animals and humans and w ithin the human p opulation ( Chapter 2.5 of the AEGL SOP ) ;

 Guidelines and criteria for time s calin g ( 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 Ma ximum 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 followi ng ( 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.Page 270 of 279



### I

- 4 California’s Ac ute 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 hr s) 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 )

.Page 271 of 279



## Appendix J SUMMARY OF THE DERIVATIONS OF THE EPA

IRIS CANCER INHALATION UNIT RISK AND NON

CANCER HUMAN EQ UIVALENT CONCENTRATION FOR CHRONIC EXPOSURES

The reader is referred to the DCM IRIS assessment for detailed explanations of the toxicological studies and the derivation approaches supporting the cancer inhalation unit risk and the non

cancer hazard value a ssociated 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 m g/m 3 ) 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 l ung. The selected internal dose

- metric w as 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, 2011 c )

.

2. Dose

- response modeling and extrapolation: The multistage dose

- response model (Benchmark Dose Software [BMDS] version 2.0) was used to fit the mouse live r tumor incidence and PBPK

- derived internal dose s and derive a mouse internal BMD 10 and BMDL 10 52

a ssociated with 10% extra risk ( EPA, 201 1c )

.

The mouse internal BMDL 10 (0.1/BMDL10) were used to derive inhalation risk factors for lung and liver tumors by linear extra polation. 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 (BMDL 10 = 7,700 mg/m 3 or 2,200 ppm ), because above this level the fitted dose

- response model better characterizes what is known about the carcinogenicity of di chloromethane.

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 )

. BMD 10 = benchmark dose at the 10% response BMDL 10 =lower confidence limit of the benchmark dose at the 10% responsePage 272 of 279

Figure J

- 1

. Process of deriving the DCM’s cancer inhalati on 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 tox ic metabolites. Currently, there are no data pertaining to the reactivity or clearance rat e 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 BMDL 10 was derived by applying a mouse:human dose

- rate scaling factor of 7 [i.e., (B ody Weight human/B ody Weight mouse) 0.25 = 7] to adjust the mouse

- based BMDL 10 values downward based on the potential slower clearance per volume tissue in th e human compared with the ( EPA, 2011c )

.
A linear extrapolation app roach using the internal human BMDL 10 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 inhal ation 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 d istribution of human internal doses lung, liver, or blood doses associated with chronic unit inhalation (1 μg/m 3 ) 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 resul ting from chronic, unit inhalation exposures of one μg/m 3 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 BMDL 10 is 1 × 10

- 8 per μg/m 3 ( 4 x 1 0

- 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 th e 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 estim ate the rat inter nal BMDL 10 for hepatic effects. In other words, the BMDL 10 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 respons e 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, t here were no additional data to suggest that the severity of the critical ef fect or the power of the study would warrant a lower BMR ( EPA, 2011c )

.

The rat internal BMDL 10 was allometrically adjusted b ecause 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 adjustmen t consisted of dividing the rat internal BMDL 10 by 4.09 [(BW human) /(BW rat ) 0.25 ≈ 4.09) ] 53 to obtain a human equivalent internal BMDL 10 of 130.03 mg DCM metabolized via CYP 54 pathway/litter liver tissue/day ( EPA, 2011c )

.

53 BW=body weight

54 CYP=cytochrome P450Page 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/m 3 ) associated with the internal BMDL 10 based on the responses in female Sprague

Dawley rats. Estimated HECs corresponding to the mean, 1 st , and 5 th percentiles of th e distribution were 48.5, 17.2 and 21.3 mg/m 3 , respec tively. The 1 st percentile of the distribution of HECs i.e. the HEC 99 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/m 3 , was chosen

as the point of dep arture ( 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 obse rved 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 275 of 279



## 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 Maxi mum 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 Ex posure Guideline Levels technical support document ( NAC, 2008 ) for detailed explanations of toxicological studies and derivation approaches for these values.



### K

- 1 Spac ecraft 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 i s the concentration of DCM which it is not expected to compromise the performance of specific tasks by healthy ast ronauts during emergency conditions or cause serio us 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 do se

- response evaluation leading to the selection of 100 ppm (350 mg/m 3 ) 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, wh ich 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 SMAC

s 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 methylenePage 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 methyle ne 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 f itted line through the origin. All the data in the above table [ table not inclu ded 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/m 3 ) was considered a NOAEL 56 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 inclu ded in the derivation of the 1

- hr SMAC value, which i s 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 a s 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 g aps 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 volunteer s (n = 12) exposed to 195 ppm DCM (696 mg/m 3 ) 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 appl ied to the LOAEL 57 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 (C n * T = k, n = 2) 58 resulting in

56 NOAEL= No

- observed

- adverse

- ef fect 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 B erge equation (C n * T = k, n = 2) , C = concentration of the chemical of interest, n=chemical

- specific

e xponent, t=time, and k=c onstant (NRC, 2001).Page 277 of 279

a 1

- hr acute REL of 4 ppm (14 mg/m 3 ). The rationale for the choice of n = 2 was not do cumented in the OEHHA document.



### K

- 3 Acute Exposure Level Guidelines (AEGL)

AEGLs represent threshold exposure limits for the general public, including infants and childr en as well as other individuals who ma y be sensitive or susceptible. They are applicable for once

in

- a

- lifetime acute exposures ( i.e. , ≤24 hrs) to ai rborne concentrations of toxic chemicals typically occurring during emergency response situations. AEGL val ues 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; 4 hrs; and 8 hr s). 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 carboxyhemoglobi n (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. Likew ise, it was expected that the toxicPage 278 of 279

endpoint of interest would change over an exposure range of 10 minutes to 8 hr s. The AEGL

values for the shorter exposure durations would be triggered by the CNS effects, whereas the formation of COHb would determine the AEGL values for longer exposure durations ( NAC, 2008 )

.
The following derivation summaries were extracted from the AEGL document for DCM ( NAC, 2008 )

.

AEGL

- 1 values
The AEGL

- 1 values were based on the observation in humans that exposure concentrations of 868 and 986 ppm (3,100 and 3,521 mg/m 3 ) may lea d to light

- headednes s 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/m 3 ). The concentration of 514 ppm was used as the P OD 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 expo sure to 514 ppm. Since susceptibility for gross CNS

depressing effects do not vary by more than a factor of two

- to three

- fold in humans, an intraspecies UF of three was applied, resulting in a maximum target concentration of DCM i n the human brain of 0.02 1 mM. The human PBPK model used this concentration to estimate the AEGL values for the different time durations ( i.e. , 10 minutes to 8 hr s). Because the calculated AEGL

- 1 values at 4

- and 8

- hrs (160 and 140 ppm, respectively) were at or above the
correspo nding 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 effects 59 during a DCM exposure to 751 ppm (2,682 mg/m 3 ) for 230 minutes ( Winneke, 1974 )

. A PBPK model estimated that 0.137 mM was the hum a n 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. , CN S effects and COHb formation). The lowest valu e 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 resul t 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. , corona ry 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 27 9 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/m 3 ) 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 estima ted for the formation of COHb formation, assuming a maximum COHb level of approximately 15 percent in humans ( NRC, 2010 )

. PB PK 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 i n 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, 2 008 )

. An intraspecies UF of 3 was applied since the susceptibility for CNS

depressing effects is not expected to vary by more than a factor of 2

- to 3

- fold in the human population ( NAC, 2008 )

. Application of an overall UF of 3 results in a maximum target DCM concentration in human brain of 1.0 mM. Similarly, an intraspecies factor of 3 was applied for the effects associated with COHb formation because the POD was supported by information on effects, such as myocardial infarction and stillbirths, reported in more susceptible subpopulations ( NRC, 2010 )

.