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# H

H Cl Cl United States Office of Chemical Environmental Protection Safety and Pollution Agency Prevention



# TSCA Workplan Chemical Risk Assessment for Methylene Chloride:

Paint Stripping Use CASRN: 75

- 09

- 2

December 2012

NOTICE

This document is an External Review Draft . This information is distributed solely for the purpose of pre

- dissemination peer review under applicable information quality guidelines. It has not been formally disseminated by EPA. It does not represent and should not be construed to represent any Agency determination or policy. It is being circulated for review of its technical accuracy and science poli cy implications.

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### Table of Contents

**TABLE OF CONTENTS**

................................ ................................ ................................ ...................... 2

LIST OF TABLES

................................ ................................ ................................ ................................ .. 4

LIST OF FIGURES

................................ ................................ ................................ ................................ . 6 **AUTHORS / CONTRIBUTO RS / REVIEWERS** 

................................ ................................ .................. 8

GLOSSARY OF TERMS AN D ABBREVIATIONS

................................ ................................ ....................... 9

EXECUTIVE SUMMARY

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

CHAPTER 1: BACKGROU ND AND SCOPE

................................ ................................ ........................... 15

I NTRODUCTION

................................ ................................ ................................ ................................ ............................. 15 S COPE OF THE A SSESSMENT

................................ ................................ ................................ ................................ ............ 16
CHAPTER 2: SOURCES AND ENVIRONMENTAL FA TE

................................ ................................ .......... 18

INTRODUCTIO N

................................ ................................ ................................ ................................ ........................ 18 2.1. PHYSICAL AND C HEMICAL P ROPERTIES OF DCM

................................ ................................ ................................ ........ 18 2.2. PRODUCTION AND U SES

................................ ................................ ................................ ................................ ...... 19 2.2.1. Market Trends

................................ ................................ ................................ ................................ ....... 19 2.2.4. Consumer Uses

................................ ................................ ................................ ................................ ...... 22 2.2.4. Paint Stripping Applications

................................ ................................ ................................ .................. 23 2.3. E NVIRONMENTAL F ATE

................................ ................................ ................................ ................................ ............ 24 2.4. C ONCLUSIONS OF E NVIRONMENTAL F ATE

................................ ................................ ................................ ................... 25
CHAPTER 3: HUMAN HE ALTH RISK ASSESSMENT

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

INTRODUCTION

................................ ................................ ................................ ................................ ........................ 27 3.1. H UMAN E XPOSURE A SSESSMENT

................................ ................................ ................................ .............................. 27 3.1.1. Occupational Exposures

................................ ................................ ................................ ........................ 27 3.1.2. Residential/Consumer Exposures

................................ ................................ ................................ .......... 33 3.1.3. Consumer Exposure Modeling

................................ ................................ ................................ .............. 33 3.1.4. Inhalation Exposure Assessment

................................ ................................ ................................ ........... 35 3.1.5. Exposure Scenarios and Model Inputs

................................ ................................ ................................ .. 40 3.1.6. Summary of Model Outputs and Exposure Calculations.

................................ ................................ ...... 44 3.2. H UMAN H EALTH A SSESSMENT : H AZARD I DENTIFICATION AND D OSE

- R ESPONSE

................................ ................................ 46 3.2.1. Toxicokinetics and Biomonitoring

................................ ................................ ................................ ......... 46 3.2.2. Acute Hazard

................................ ................................ ................................ ................................ ......... 47 3.2.3. Chronic Hazard

................................ ................................ ................................ ................................ ...... 48 3.3. H UMAN H EALTH A SSESSMENT : D OSE

- R ESPONSE

................................ ................................ ................................ ......... 49 3.4. HUMAN H EALTH R ISK C HARACTERIZATION

................................ ................................ ................................ ................ 54 3.4.1. Risk Estimation Approach for Acute and Repeated Exposures

................................ .............................. 54 3.4.2. Risk Estimation Approach for Acute Exposures

................................ ................................ ..................... 54 3 .4.3. Risk Estimation Approach for Repeated Exposures

................................ ................................ ............... 56 3.4.4. Risk Estimates for Non

- Cancer Acute Inhalation Exposures in a Resi dential Setting

............................ 57 3.4.5. Occupational Risk Estimates for Chronic Inhalation

................................ ................................ .............. 64 3.5. D ISCUSSION OF K EY S OURCES OF U NCERTAINTY AND D ATA L IMITATIONS

................................ ................................ .......... 65 3.5.1. Key Uncertainties and Data Limitations for Occupational Exposure Estimates

................................ ..... 65 3.5 .2. Key Uncertainties and Data Limitations for Consumer Exposure Estimates

................................ ......... 66 3.5.3. Uncertainties in the Hazard and Risk A ssessment

................................ ................................ ................. 67 3.5.4. Conclusions of Uncertainties and Limitations

................................ ................................ ....................... 69 3.6. R ISK C HARACTERIZATION C ONCLUSIONS

................................ ................................ ................................ ..................... 69
REFERENCES

................................ ................................ ................................ ................................ .... 71

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

APPENDIX A: SUMMARY OF ENVIRONMENTAL EFF ECTS

- AQUATIC TOXICITY

................................ ..... 88

APPENDIX B: INVENTO RY UPDATE REPORTING RULE DATA FOR DCM

................................ ............... 90

APPENDIX C: HOUSEHO LD PRODUCTS DATA FOR DCM

................................ ................................ ..... 91

APPENDIX D : PAINT STRIPPING P ROCESSES AND ASSOCIA TED WORKER ACTIVITIE S, AND FACILITY AND POPULATION DATA AND INFORMATION

................................ ................................ ........................... 93

APPENDIX E: OCC UPATIONAL EXPOSURE L ITERATURE DATA

................................ ........................... 103

APPENDIX F: RESIDEN TIAL/CONSUMER EXPOSU RE ASSESSMENT

................................ ................... 120

F

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

................................ ................................ . 120 F

- 2. Sensitivity Analysis for Inhalation Scenarios

................................ ................................ ............................ 125 F

- 3. Inhalation Exposure Scenario Inputs

................................ ................................ ................................ ........ 126 F.4. Inhalati on Model Outputs and Exposure Calculations

................................ ................................ ............. 132 F.5. MCCEM Inhalation Modeling Scenario Summaries

................................ ................................ .................. 139
APPENDIX G: HUMAN H EALTH TOXICITY SUMMA RY

................................ ................................ ...... 160

APPENDIX H: HUMAN H EALTH DOSE

- RESPONSE ASSESSMENT

................................ ....................... 163

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### List of Tables

Table 1

- 1. Primary Uses of DCM and Selection Criteria.

................................ ................................ ............ 17

Table 2

- 1. Physical

- Chemical Properties of DCM. a

................................ ................................ ..................... 18

Table 2

- 2. DCM Market Trends by Use.

................................ ................................ ................................ ..... 20

Table 2

- 3. Major and Minor Uses of DCM.

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

Table 2

- 4. Major Uses of DCM in 2007 in the US.

................................ ................................ ...................... 22

Table 2

- 5. Consumer Uses of DCM.

................................ ................................ ................................ ........... 22

Table 2

- 6. Environmental Fate Characteristics of DCM, Dichloromethane. 1

................................ ............. 26

Table 3

- 1. Regulatory and Recommended Exposure Limits.

................................ ................................ ..... 28

Table 3

- 2. 2007 NAICS Codes Identified that Include Paint Stripping Activities.

................................ ....... 28

Table 3

- 3. Summary of Ranges of DCM Exposure Concentrations and Calculated ADCs and LADCs for Workers.

................................ ................................ ................................ ................................ . 30

Table 3

- 4. Summary of Number of Workers Exposed or Monitored and Total Number of Employees in the Monitored Facility Cited in the References Used for Each Industry.

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

Table 3

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

....................... 40

Table 3

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

............. 42

Table 3

- 7. Summary of Modeled DCM Concentrations to Which Consumer Users and Non

- Users are Exposed, by Scenario.

................................ ................................ ................................ ............ 45

Table 3

- 8. Worker Inhalation Health Effect Reference Values Used in the Risk Assessment. a

................. 51

Table 3

- 9 . Toxicological Endpoints and Approaches for Assessing Risks to DCM

- Based Paint Strippers.

. 56

Table 3

- 10. MOEs for CNS Effects following Acute Exposure Scenarios for Consumer/Residential Users and Non

- Users of DCM

- Based Paint Strippers.

................................ ................................ ...... 57

Table 3

- 11. Acut e HQs for Residential Users and Non

- Users of DCM

- based Paint Strippers.

................... 59

Table 3

- 12. Occupational Risks for Repeated Exposures to DCM from Paint Stripping Activities.

............ 64

Table B

- 1. Manufacturing and Importing Company and Site Information for DCM.

................................ . 90

Table C

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

.................. 91

Table D

- 1. 2007 US Economic Census Data for Painting and Wall Covering and Flooring Contractors.

... 98

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- 2. 2007 US Economic Census Data for Automotive Body, Paint, and Interior Repair and Maintenance.

................................ ................................ ................................ ......................... 98

Table D

- 3. 2007 US Economic Census Data for Reupholstery and Furniture Repair.

................................ 99

Table D

- 4. Estimated Annual DCM Based Stripper Usage in California.

................................ .................. 100

Table D

- 5. 2007 US Economic Census Data for Industry Sectors that May Engage in Art Restoration and Conservation Activities.

................................ ................................ ................................ ........ 100

Table D

- 6. 2007 US Economic Census Data for Aircraft Manufacturing.

................................ ................. 101

Table D

- 7. 2007 US Economic Census Data for Ship Building and Re pairing.

................................ .......... 102

Table E

- 1. Summary by Industry and Job Category of OSHA IMIS Data for DCM from 1992 to 2012.

.... 106

Table E

- 2. Summary of Personal and Area Concentrations in a Furniture Refinishing Shop that Uses a Pump and Brush Stripping Technique Measured Befor e Engineering Controls were Added.

................................ ................................ ................................ ................................ .............. 113

Table E

- 3. 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 t o the Stripping Booth.

................................ ................................ ................................ ............. 114

Table E

- 4. Summary of Personal and Area Concentrations in a Furniture Refinishing Shop that Uses a Pum p and Brush Stripping Technique Measured After Engineering Controls were Added to the Stripping Booth and Wash Booth.

................................ ................................ ................. 115

Table F

- 1 . US EPA (1994b) Study: Products Emissions Fit to Exponential Profile.

................................ ... 120

Table F

- 2. Fitted Parameters to the US EPA (1994b) Stu dy Results for the Two DCM

- Containing Paint Strippers.

................................ ................................ ................................ .............................. 123

Table F

- 3. Time Schedule for Brush

- on Application to Chest Surface: Four Segments with Repeat Application.

................................ ................................ ................................ .......................... 128

Table F

- 4. DCM Mass Released, by A pplication Target and Method.

................................ ...................... 129

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### List of Figures

Figure 2

- 1. Chemical Structure of Methylene Chloride.

................................ ................................ ............ 18

Figure 3

- 1. Time

- varying User Personal Concentration and Maximum TWA Values for Selected Averaging Times.

................................ ................................ ................................ ................................ ..... 37

Figure 3

- 2. Time

- varying Non

- user Personal Concentration and Maximum TWA Values for Selected Averaging Times.

................................ ................................ ................................ .................... 37

Figure 3

- 3. Model Sensitivity Results (Percent Change from Base

- case Response) for Peak One

- hr TWA for User and Non

- user.

................................ ................................ ................................ ........... 39

Figure 3

- 4. Model Sensitivity Results (Percent Change from Base

- case Response) for 24

- hr TWA for User and Non

- user.

................................ ................................ ................................ ......................... 39

Figure 3

- 5. Comparison of Acute Toxicity Values and User Exposures during Brush Application in a Residential Workshop.

................................ ................................ ................................ ........... 60

Figure 3

- 6. Comparison of Acute Toxicity Values and User Exposures during Spray Application in a Residential Workshop.

................................ ................................ ................................ ........... 62

Figure 3

- 7. Comparison of Acute Toxicity Values and Zone

- Specific DCM Concentrations for Brush Application in Residential Workshop or Bathroom.

................................ .............................. 62

Figure 3

- 8. Comparison of Acute Toxicity Values and Zone

- Specific DCM Concentrations for Spray Application in Residential Workshop.

................................ ................................ .................... 63

Figure D

- 1. Typical Flow Tray for Applying Stripper to Furniture.

................................ ............................. 95

Figure D

- 1. Typical Water Wash Booth Used to Wash Stripper and Coating Residue from Furniture.

..... 96

Figure D

- 2. Example Diagram of a Dipping Tank for Furniture Stripping.

................................ .................. 96

Figure F

- 1. Model Fit to MRI (US EPA, 1994b) Data for BIX Spray

- On (Spray Application).

..................... 122

Figure F

- 2. Model Fit to MRI (US EPA, 1994b) Data for Strypeeze (Brush Application).

......................... 123

Figure F

- 3. Theoretical Cumulative Mass of DCM Released fo r BIX Spray

- On Stripper.

.......................... 124

Figure F

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

............................... 124

Figure F

- 5. Zone Volumes and Airflow Rates for Workshop Scenarios.

................................ .................. 130

Figure F

- 6. Zone Volumes and Airflow Rates for Bathroom Scenario.

................................ .................... 131

Figure F

- 7. Example of the Personal Concentration Calculation as Defined in Equation F

- 9.

................. 133

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- 8. Modeled DCM Concentrations for Scenarios 1 and 4, Stripper Application in Workshop using Central Parameter Values.

................................ ................................ ................................ ... 135

Figure F

- 9. Modeled DCM Concentrations for Scenarios 2 and 5, Stripper Application in Workshop using Parameter Values selected for Upper

- end User’s Exposure.

................................ ............... 136

Figure F

- 10 . Modeled DCM Concentrations for Scenarios 3 and 6, Stripper Application in Workshop using Parameter Values Selected for Upper

- End

- user’s and Non

- user’s Exposure.

............ 137

Figure F

- 11. Modeled DCM Concentrations for Scenario 7, Brush Application in Bathroom (Simulation).

................................ ................................ ................................ ................................ .............. 138

Figure H

- 1. Illustration of the Different AEGL Threshold Levels.

................................ ............................. 164

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### Authors / Contributors / Reviewers

The report was developed by the Office of Pollution Prevention and Toxics (OPPT), Office of Chemical Safety and Pollution Prevention (OCSPP). The 2012 workplan risk assessments were prepared based on existing data and any additional information received up to June 1 5, 2012.

Assessment Team Lead: Scott P rothero, OPPT/EETD Team: Kent Anapolle , OPPT/EETD Judith Brown, OPPT/EETD Iris Camacho , OPPT/RAD Mary Dominiak , OPPT/CCD ( retired ) Conrad Flessner , OPPT/EETD Amuel Kennedy, OPPT/RAD Doyoung Lee , OPPT/EETD Andy Mamantov , OPPT/EETD Justin Roberts, OPPT/EETD

Portions of this document were developed with support from :

Contractor name (contract number) Task Abt Associates (EP

- W

- 08

- 010) Production and Uses Eastern Research Group (EP

- W

- 10

- 014) Releases Versar (EP

- W

- 10

- 005) Fate, Modeling, Monitoring SRC, Inc. ( EP

- W

- 09

- 027) Technical Editing

Internal Peer Review ers H. Kay Austin , OPPT/EETD Stan Barone Jr., OPPT/RAD Todd Stedeford , OPPT/RAD

External Peer Review

- A peer review panel is being arranged for this influential workplan assessment product based upon need and following Agency peer review guidance. The format will be a teleconference of an ad hoc panel meeting consisting of independent experts.

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### Glossary of Terms and Abbreviations

μg Microgram(s) μg/m 3 

### Microgram(s) per cubic meter °C Degrees Celsius °F Degrees Fahrenheit ACGIH American Conference of Governmental Industrial Hygienists ACH Air c hanges per hour ADC Average daily concentration AEGL Acute E xposure G uideline L evel AEGL

- 1 Discomfort threshold AEGL

- 2 Disability threshold AEGL

- 3 Death threshold
atm atmosphere(s) ATSDR Agency for Toxic Substances and Disease Registry BAF Bioaccumulation Factor BCF Bioconcentration Factor BMD Benchmark d ose BMDL 10 

### Lower 95 percent confidence limit of the 10 percent BMD BMDS Benchmark Dose Software BMR Benchmark r esponse BW Body weight Cal EPA California Environmental Protection Agency CASRN Chemical Abstract s Service Registry Number CBI Confidential business information CDC Center s for Disease Control and Prevention CHO Chinese hamster ovary CNS Central n ervous s ystem CO Carbon monoxide CO 2 

### Carbon dioxide COHb Carboxyhemoglobin CPSC Consumer Product Safety Commission CYP2E1 Cytochrome P450, family 2, subfamily E, polypeptide 1 DCM Dichloromethane DEM Department of Environmental Management DIY D o

- it

- yourself DNA Deoxyribonucleic acid DNA SSB Single stranded DNA

- binding protein DOSH Division of Occupation Safety and Health EC European Commission ECG Elec trocardiogram EFH Exposure Factors Handbook EPA Environmental Protection Agency EU European Union

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### FACE Fatality Assessment and Control Evaluation ft Foot/feet ft 2 

### Square feet FTIR Fourier transform infrared
g G ram (s) g/cm 2 

### G ram(s) per square centimeter g/cm 3 

### Grams(s) per cubic centimeter g/ft 2 

### , g/sq ft Grams(s) per square foot g/L Gram ( s ) per liter g/min ute Grams(s) per minute g/mol Gram (s) per mole GST Glutathione S

- transferase GWP Global warming potential HEC Human equivalent concentration HFC

- 32 Hydro fluorocarbon

- 32 HQ Hazard quotient hr Hour HVAC H eating, ventilation, and air conditioning K oc 

### Soil Organic Carbon Partition Coefficient IDLH Immediately D angerous to L ife and H ealth IMIS Integrated Management Information Systems IPCC Intergovernmental Panel on Climate Change IRIS Integrated Risk Information System IRTA Institute for Research and Technical Assistance IUR Inhalation Unit Risk IURR Inventory Update Reporting Rule L Liter(s) Lb(s) Pound(s) LADC Lifetime average daily concentration LC 50 

### Median l ethal c oncentration LOAEC Lowest

- o bserved

- a dverse

- e ffect c oncentration LOAEL Lowest

- observed

- adverse

- effect level LOEC Lowest

- observed

- effect concentration MATC Maximum acceptable toxicant concentration MCCEM Multi

- Chamber Concentration and Exposu re Model
mg Milligram (s) mg/L Milligram(s) per liter mg/m 3 

### Milligram ( s ) per cubic meter min M inute (s) mM Milli

- Molar MMWR Morbidity and Mortality Weekly Report MOE Margin of e xposure MRI Midwest Research Institute MSDS Material S afety D ata S heet

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### MSU Michigan State University NAICS North American Industry Classification System NAS National Academy of Sciences NESHAP National Emission Standards for Hazardous Air Pollutants NHANES National Health and Nutrition Examination Survey NIH National Institutes o f Health NIOSH National Institute for Occupational Safety and Health 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 PBPK Physiol ogically Based Pharmacokinetic PEL Permissible E xposure L imit POD Point of departure
ppm Parts per million REL Reference E xposure L evel RfC Reference concentration RIA Regulatory Impact Analysis ROH Rest of the house SIC Standard Industry Classification SMAC Spacecraft m aximum a llowable c oncentration SNAP Significant New Alternatives Policy STEL Short

- T erm E xposure L imit TLV Threshold L imit V alue TRI Toxics Release Inventory TSCA Toxic Substances Control Act TWA Time

- weighted average UF Uncertainty factor UF A 

### Interspecies uncertainty factor UF D 

### Database deficiency uncertainty factor UF H 

### Intraspecies uncertainty factor UF L 

### LOAEL

- to

- NOAEL uncertainty factor UF total 

### Total uncertainty factor UK United Kingdom US United States VOC Volatile organic compound
wt W eight

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### Executive Summary

Methylene chloride (dichloromethane, DCM) was assessed as part of the United States (US) Environmental Protection Agency’s (EPA) Existing Chemicals Management Program. EPA reviewed readily available information on DCM including us es, physical

- chemistry, fate, exposures, and associated hazards to humans and the environment.

DCM was identified because it ranked high for hazard ( i.e. , a probable human carcinogen) and high for exposure potential because it is widely used in consumer products. It has been detected in drinking water, indoor environments, ambient air, groundwater and soil, and because of these reported releases to the environment
, and it was ranked high.

DCM is volatile and does not significantly partition to solid p hases. Therefore, releases of DCM to the environment are likely to evaporate to the atmosphere, or if released to soil, migrate to groundwater. DCM has been shown to biodegrade over a range of rates and environmental conditions and in the environment, it is moderately persistence. Measured bioconcentration factors for DCM suggest its bioconcentration potential is low. This assessment did not evaluate risks to the environment because DCM possesses moderate persistence, low bioaccumulation potential, and low hazard to aquatic organisms.

DCM is a quick acting and inexpensive solvent with a wide range of industrial, commercial, and consumer use applications such as adhesives, paint stripping, pharmaceuticals, metal cleaning, chemical processing, and aerosols. However, it is mainly used as a solvent, and is the primary ingredient in many paint stripping products.

US demand for DCM in 2006 was estimated at 185 million pounds ( lbs ) with a projected demand of 181 million lbs for 2010. The 2006 Inventory Update Reporting Rule (IURR) indicate s that 100 million to 500 million lbs of the chemical is produced or imported (estimated 20 million lbs ) into the US. There are only three DCM production facilities in operation in the US.

EPA assumed that direct contact or close proximity to the use ( i. e., for a consumer or commercial application with substantial frequency or duration of exposure) would likely provide the highest exposures to DCM paint strippers. In either occupational or consumer settings, there may be significant inhalation exposure d uring the use of these products. In addition to product users, there also may be non

- users or bystanders who may not come in direct contact with the product, but may be exposed indirectly while in a nearby area during product application.

Using this rationale
, EPA’s assessment focused on estimating risk(s) due to consumer and occupational use of paint strippers containing DCM. In the residential/ consumer scenarios indirect exposures to children, who could be in the vicinity of the paint strippers wi th inadequate ventilation, were also assessed. Due to DCM’s high volatility, the assessment covered exposure scenarios via inhalation and did not address dermal exposures because this route of exposure is not expected to be as significant as compared to i nhalation

.

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### For worker exposures, this assessment relied upon published exposure concentration data. Exposure data were found for paint stripping applications in six industry segments. While data were found to estimate worker exposures, EPA did not con sider the available data robust enough to develop statistical distributions of exposure for workers. Therefore, each of the exposure estimates is a snapshot of the particular uses that are cited.

EPA focused this assessment on exposures to workers empl oyed by “small commercial shops.” For this assessment, EPA considered a small shop as one that employs less than 10 workers ( i.e., the remaining facilities were considered large facilities or un assigned and were not considered in this assessment).

Publis hed monitoring data for non

- occupational inhalation exposures ( i.e. , consumer do

- it

yourself [DIY]) were limited to that from several experiments conducted in the US and Europe. No published exposure information was found for exposures to other household members ( i.e.,

non

- users). Of the available studies, only one US study provided sufficient information to estimate consumer DCM inhalation exposures. EPA used its Multi

- Chamber Concentration and Exposure Model (MCCEM), to estimate DCM concentrations (e.g
., in the room of use and the rest of the house; ROH), as well as to calculate potential user and non

- user exposure concentrations.

Cancer risks were calculated for chronic worker exposure scenarios only. Cancer incidence risks were calculated by multiply ing the chronic exposure estimates by the EPA cancer inhalation unit risk (IUR) value. Margins of exposure (MOE) indicate that there are occupational non

cancer risks of concern associated with exposures to DCM

- based paint strippers in the industries EPA assessed : professional contractors, aircraft paint stripping, workplace settings doing immersion stripping of wood, and wood and metal paint stripping. The data showed that the Occupational Safety and Health Administration (OSHA) Permissible Exposur e Limit (PEL) and Short

- Term Exposure Limit (STEL) were exceeded under some circumstances. The representativeness of the available exposure data to the broader worker populations that are exposed to DCM during its use in various paint stripping applicatio ns cannot be determined due to data and information limitations and uncertainties.

EPA’s assessment also found a potential risk of concern to people in residential environments where DCM vapors are released during brush

- on or spray

- on applications of DCM

- based paint strippers. Th ese findings are based on workplace air monitoring data and a modeling

- based approach employed to estimate acute inhalation exposures to residential users and non

- users.

The inhalation exposure assessment is composed of modeled exposure scenarios for which the inputs are based on experimental data, survey information, and a number of assumptions with varying degrees of uncertainty. The results are characterized as either plausible estimates of individual exposure, i.e. , central t endency, or possibly greater than the distribution of actual
exposures, i.e. , bounding. The extent of the identified uncertainties for estimating occupational

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### or residential exposures is not known and could result in either larger or smaller exposure esti mates under real world conditions.

There is general confidence in the characterization of the hazard database for acute and chronic effects used for the points of departure. However there is residual uncertainty in domains of the hazard characterization for some outcomes. These uncertainties are drawn from concern for potential developmental neurotoxicity and immunological effects which are supported by the modes of action affecting the nervous system resulting in CNS depression and COHb buildup and indi cations from acute inhalation study, specifically immunosuppressive effects that may be relevant for infectious diseases spread through inhalation.

In conclusion, the following consumer and worker exposure scenarios resulted in exposures that were of potential concern for non

- cancer risks for DCM paint stripping uses :

 Acute potential risks of concerns ( i.e., neurotoxicity, generally an order of magnitude below acceptable margins of exposure) for consumers and bystanders for most scenarios

.

 Chronic potential risks of concern ( i.e., liver toxicity, below acceptable margin of exposure) and cancer ( i.e., liver and lung, 1 x 10 - 3 

### to 1 x 10 - 6 

### with most above 1 x 10 - 4 

### ) potential risks of concerns for workers in almost all uses identified

.

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## Chapter 1: Background and Scope

I NTRODUCTION



### M ethylene c hloride ( i.e., dichloromethane ; DCM)
, was identified for assessment as part of the United States (US) Environmental Protection Agency’s (EPA ) Existing Chemicals Management Program. EPA reviewed readily available information on DCM including: uses, physical

chemistry, fate, exposure potential
, and associated hazards to humans and the environment.

DCM is a volatile, colorless liquid with a ch loroform

- like, sweet odor (OSHA, 2010). It has a low boiling point and is moderately water soluble

. DCM is used as a substitution for other solvents because it is non

- flammable and non

- explosive . Because DCM is volatile , it does not significantly partition to solid phases. Therefore, releases of DCM to the environment are likely to evaporate to the atmosphere, or if released to soil, migrate to groundwater. This substance has been shown to biodegrade over a range of rates a nd environmental conditions and is considered to be moderately persistence in the environment. Measured bioconcentration factors for DCM suggest its bioconcentration potential is low.

DCM has been the subject of regulations by such organizations as the EPA, the Occupational Safety and Health Administration (OSHA), the Consumer Product Safety Commission (CPSC), and the European Commission (EC). This chemical is listed as a toxic ( i.e., non

- acute) hazardous waste under the Resource Conservation and Recov ery Act (RCRA) (Code U080) and is listed on the Toxics Release Inventory (TRI) pursuant to section 313 of the Emergency Planning and Community Right

- to

- Know Act (EPCRA). CPSC issued a statement of policy (CPSC, 1987) regarding its decision to require labe ling of consumer products that contain DCM. 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. In 1997, OSHA lowered its permissible exp osure limit (PEL) for DCM f rom 500 parts per million (ppm) to 25 ppm (OSHA, 1997). 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; US EPA, 2008), 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. The NESHAP also implemented manag ement practices that minimize DCM emissions. In addition, the European Commission (EC) amended its Registration, Evaluation, Authorization, and Restriction of Chemical substances to incorporate restrictions for use of DCM in paint strippers (EC, 2010). T he chemical is banned from: (1) placement on the market in a new product for consumers/professionals by December 2010, (2) placement on the market in any product for consumers/professionals by December 2011, and (3) use by professionals by June 2012, unle ss the professionals are appropriately trained and licensed.

DCM was identified because it ranked high for hazard ( i.e. , a probable human carcinogen and
acute non

- cancer hazard ), and it ranked high for exposure potential because it is widely used in

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### consumer products. DCM has been detected in drinking water, indoor environments, ambient air, groundwater and soil, and reported releases to the environment are high (US EPA, 2012c)

.

S COPE OF THE 

### A SSESSMENT



### This assessment focused on the use of DCM

- based paint strippers. EPA assumed that direct contact or close proximity to the use ( i.e., for a consumer or commercial application with substantial frequency or duration of exposure) would likely provide the highest exposures to NMP paint strippers. In either occupational or consumer settings, there may be significant inhalation exposure during the use of these products. In addition to product users, there also may be non

- users or bystanders who may not come in direct contact with the product, but may be exposed indirectly while in a nearby area during product application.

EPA’s assessment focused on estimating the quantitative risk(s) due to occupational and residential use of paint strippers containing DCM. Occupational exposures include possible direct exposures to workers who may use these products at work, in training, or other situations. In the residential/consumer scenarios indirect exposures to individuals , who could be in the vicinity of the paint strippers with inadequate ventilation, also were assessed. Th ese type s of exposure scenario s for small commercial shop workers and consumers (including “DIYs”) are addressed in this assessment.

EPA understands that exposures that result from large

- scale industrial oper ations are generally monitored and well controlled. I n small commercial or consumer settings , users may not adhere to the same types of controls. Thus, large

- scale manufacturing exposure scenarios are not addressed in this risk assessment. EPA focused t his assessment on exposures to workers employed by “small commercial shops.” For the purpose of this assessment, EPA considered a small shop as one that employs less than 10 workers ( i.e., the remaining facilities were considered large facilities or were unassigned and were not considered in this assessment). Due to its high volatility, dermal exposure is of less concern to EPA than other routes of exposure. Its rapid evaporation suggests that the most likely route of exposure is via inhalation; therefore, the risk assessment focused on inhalation exposures to commercial workers and consumers

. EPA focused the assessment on DCM use in paint stripping. Other uses beyond paint stripping

were not covered in the risk assessment. Table 1

- 1 shows the primary uses of DCM and the rationale for their inclusion or exclusion for this risk assessment. Narrowing of the scope required exc lusion of some uses based on comparative judgments on potential exposure ( e.g. , percent content relative to potential exposure) among the primary uses identified.

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- 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 “ DIYs ”); industrial workers No

– Relatively narrower range of removal applications and likely lower exposure levels compared to paint stripping. Information indicates that many of the adhesive uses are in adhesive removers.
Paint s tripping 25

- 100 Small commercial shop workers, consumers (including “ DIYs ”); industrial workers Yes

– Relatively high percent content range, broad range of stripping and removal applications (automotive, furniture, marine, wall paint, similar coating removal).
Pharmaceuticals N/A b Industrial workers No

– Industrial use settings which are generally beli eved to be better controlled and monitored

. Metal c leaning 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 p rocessing N/A b Industrial workers No

– I ndustrial use settings which are generally believed to be better controlled and monitored

. Aerosols (propellant use) <25 Small commercial shop workers, consumers (including “ DIY s ”); industrial workers No

– Relatively low percent content range, small market percentage (5 percent ), and likely lower exposure levels compared to paint stripping.

Polyurethane f oam N/A b Industrial workers No

– I ndustrial use settings which are generally believed to be better controlled and monitored

.

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

- commercial/non

- industrial users of products containing DCM. Commercial workers are defined as persons employed in a commercial enterprise providing salable goods or services. Examples of a commercial enterprise include
, but are not limited to
, commercial and residential cleaning services, painting companies, carpet installers, commercial and residential r epair and refurbishing companies, and automotive painting and repair shops.

a For these industrial applications, the percent of DCM content is expected to be at or near 100 percent.



### E cological impacts of DCM also were considered , but were ruled out, during EPA’s problem formulat ion and scoping process. The aquatic toxicity of DCM for fish, aquatic invertebrates, and aquatic plants is low based on the Office of Pollution Prevention and Toxics ( OPPT ) criteria described in the TSCA Work Plan Chemicals M ethods Document ( US EPA, 2012b , 1992b ) and the Classification Criteria for Environmental Toxicity and Fate of Industrial Chemical s ( US EPA, 1992b )

. Appendix A contains a summ ary of the aquatic toxicity studies considered in the evaluation of environmental hazards of DCM. Because of its low hazard observed in aquatic toxicity studies, EPA did not evaluate risks to the environment from DCM.

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## Chapter 2: Sources and Environmental Fate

INTRODUCTION

To assess the environmental risks of dichloromethane (DCM), a firm understanding of the physical and chemical properties, sources related to production and uses, and fate in the environment is important. These topics are i ntroduced in Chapter 2 and discussed in relation to the risk characterization in Chapter 3.

2.1

. PHYSICAL AND 

### C HEMICAL 

### P ROPERTIES OF 

### DCM

The chemical structure for DCM is shown in Figure 2

- 1.

Figure 2

- 1. Chemical Structure of Methylene Chloride

. 

### DCM is a volatile (vapor pressure = 351.8 Torr at 25 °C), colorless liquid with a chloroform

- like, sweet odor (OSHA, 2010). DCM is low boiling (39.8 °C ) and 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 substitution for other solvents because it is non

- flammable and non

- explosive. DCM a lso is not readily oxidizable (CRC, 2001; IUCLID, 2000; Merck, 2001). Table 2

- 1 shows common physical

- chemical properties for DCM.

Table 2

- 1

. Physical

- Chemical Properties of DCM

. a
Molecular formula CH 2 Cl 2 Molecular weight 84.93 Physical form Colorless liquid; sweet, pleasant odor resembling chloroform Melting point

- 95 °C Boiling point 39.7 °C Vapor pressure 351.8 mmHg at 

### 25 °C Log K OW 5.3 ("slow stirring" method); 5.9 @ 25 °C (measured; OECD 117) Water solubility 13.7 g/L at 20 °C Density 1.33 g/cm 3 at 20 °C Flash point none

a IUCLID, 2000 H

H Cl Cl

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### 2.2

. PRODUCTION AND 

### U SES



### DCM is mainly used as a solvent, usually at concentrations ranging from 20 to 90 percent, and is the primary ingredient in many paint stripping products ( Mannsville, 1999 )

. It is a quick acting and inexpensive solvent with a wide range of industrial, commercial, and consumer uses, which include : solvent for vapor degreasing; paint/varnish removers; e lectronics; resin cleaners; adhesives; tablet coatings; process solvent for cellulose acetate; butyl rubber; cleaning solvent; plastics processing; blowing agent in polyurethane foams; propellant for paint aerosols; refrigerant; heat

- transfer fluid; extrac tion solvent for industrial applications and food; color diluents for foods; and food packaging adhesives ( Ash, 2009 )

. It also has several minor uses, especially as an extraction solvent for spice oleoresins and hops, and for the removal of caffeine from coffee. It is approved as an extraction solvent for these uses by the Food and Drug Administration, although most decaf feinators no longer use DCM due to concerns over residuals ( ATSDR, 2000 )

.

2.2.1. M ARKET 

### T RENDS


### Use of DCM as a solvent in a number of sectors has been declining steadily since the mid

- 19 80s due to increasing government regulation ( i.e., both federal and state), and environmental, consumer, and worker exposure concerns ( ICIS, 2007 ; US EPA, 2006b , 1994a , 1991 ) . These regulations include: a lower Occupational Safety and Health Administration’s (OSH A’s) Permissible Exposure Limit (PEL) in 1997,; CPSC required warning labels on all products containing more than 1 percent of DCM in 1988; NIOSH listed DCM as a potential carcinogen; and new OSHA standards required facilities using DCM to use vapor contro l equipment by 2000 (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 US ( Cal EPA, 2000 )

. Currently, there are only two manufacturers in the US with a total of three plants in operation. DCM use has declined in several areas in recent years for various reasons, including the OSHA’s reduction in the PEL in 1997 ( US EPA, 2010b ) . 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).

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- 2

. DCM Market Trends by Use.

DCM Use Use Trend Background
Paint stripper Decreasing • OSHA’s 1997 reduced PEL for paint removal in furniture refinishing operations resulted in new equipment costs (especially for small shops), which led to a reduction of DCM use as a paint stripper a

• Consumer Product Safety Commission (CPSC) warning labels on consumer DIY products has also resulted in less furniture refinishing use a

• The aircraft industry has replaced DCM paint stripping on commercial and military planes with non

- chemical stripping processes because new technology in chemical processing has resulted in less of a need for DCM a

• Use of substitutes like high

- boiling ketones, glycol ethers, and N

- methylpyrrolidone (NMP) has been increasing b

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 a
Foam adhesives Decreasing • EPA’s 2007 Flexible Polyurethane Foam Production and Fabrication National Emission Standards for Hazardous Air Pollutants (NESHAP) required a reduction in use of DCM a

• Lower OSHA PEL has steered many foam manufacturers into using non

- DCM adhesives due to the cost of compliance with the PEL a Feedstock in production of refrigerant HFC

- 32 Increasing • Expected to grow because HFC

- 32 is an EPA Significant New Alternatives Policy (SNAP) replacement chemical for HFC

22 a

• Fluorocarbon production accounts for less than 10 percent of DCM use a

Sources : a US EPA (2010b )

. b Mannsville (1999 )

.


### US consumption of DCM declined from a high of approximately 540 million lbs in the mid

- 1980s to approximately 160 million lbs currently ( US EPA, 2010b )

. US demand for DCM in 2006 was estimated at 185 million lbs by industry sources with a projected demand of 181 million lbs for 2010 ( ICIS , 2007 ; HSIA, 2008 )

. The 2006 non

- confidential business information (CBI) I nventory Update Reporting Rule (IURR) indicates that 100 million to 500 million lbs of the chemical is produced or imported into the US ( US EPA, 2006a )

. DCM imports were estimated at 20 million lbs in 2006 ( ICIS, 2007 ) , so the producti on volume of DCM makes up 80 to 96 percent of the market share depending on the high or low estimates of total production and imports

. Only The Dow Chemical Company ( one facility) and Occidental Chemical Corporation ( i.e., two

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### facilities) manufacture DCM in the US

. Between these two companies, there are only three DCM production facilities remaining in operation in the US ( US EPA, 2010b )

. In terms of environmental releases, according to data from the EPA’s 2010 Toxics Release Inventory (TRI), 292 facilities reported a total of 4.8 million lbs of on

- and off

- site disposal or other releases of DCM ( US EPA, 2011a )

.

Table 2

- 3 pre sents 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 propellant

• Metal cleaner and degreaser

• Chemical processor for polycarbonate resins and cellulose triacetate (photographic film)

• Flexible polyurethane foam manufacturing

• Feedstock in the production of the refrigerant
, hydrofluorocarbon

- 32 ( HFC

- 32) • Extraction solvent for oils, waxes, fats, spices, and hops

• Tablet coating for

pharmaceuticals • Low 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 flammabi lity of other substances c

• Does not contribute significantly to atmospheric pollution through the formation of smog, to depletion of the ozone layer, or to global warming c

• Lower costs

Sources : a HSIA (2008 ); US EPA (2006a ); Dow (1999 ); ( Aerias, 2012 )

. b Mannsville (1999 )

. c HSIA (2010 )

. 

### As recently as the 1980s, approximately 50 percent of the total DCM market was made up of paint stripping products (Mannsville, 1999). Industry sources stated 40 percent of the domestic DCM market was made up of paint strippers in 2006 (HSIA, 2008). However, the most recent industry figures indicate paint stripping products now only make up 2 5 percent of the domestic market for DCM (Table 2

- 4 ). These figures coupled with an overall decline in the demand for DCM suggest manufactures may be substituting other solvents for DCM in their paint stripping products. Because the data are too recent , EP A cannot determine at this point if this is a real trend

. The estimates for DCM use in 2007 are shown in Table 2

- 4

. The percentages of DCM use by application type are based on production volume for use in domestic products.

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- 4

. Major Uses of DCM in 2007 in the US

. Major Uses Percent of DCM Consumed in 2007 in End Products
Adhesives 37
Paint s tripping 25
Pharmaceuticals 10
Metal c leaning 7
Chemical p rocessing 7
Aerosols 5 Polyurethane foam blowing 5
Miscellaneous 4

Source : ICIS (2007 )

.



### 2.2.4. C ONSUMER 

### U SES



### DCM has a number of TSCA consumer uses. The 2006 IUR R data indicated that DCM is used in the following commercial/consumer use categories: paints and coatings, adhesives and sealants, and “other” ( US EPA, 2006a ) ( Appendix B )

. The National Institutes of Health ( NIH ) Household Products Database currently lists 49 products containing DCM, in concentrations ranging from one to 100 percent. The products are divided almost evenly between aerosol and liquid form ulations (with one in granular form ) ( NIH, 2012 )

. DCM uses addressed by other agencies ( i.e., non TSCA regulations) have changed over time. O nce an ingredient in aerosol cosmetic products, such as hairsprays
, in concentrations ranging from 10 to 25 percent , DCM was banned as an ingredient from all cosmetic products in 1989 ( FDA, 1989 )

. It no longer is used in hair sprays or cosmetic products ( Cal EPA, 2000 )

. Table 2

- 5 presents the major consumer uses of DCM.

Table 2

- 5

. Consumer Uses of DCM

. Consumer Uses

Paint s trippers • Paint thinners a

• Paint removers and strippers b

• Varnish removers b

• Graffiti removers b

Aerosol a pplications • Aerosol paints c

• Automotive products c

• Spray shoe polish a

• Rust removers a

• Primers a Cleaners/ p rotectors • Water repellant/protectors a

• Spot removers a

• Wood floor and panel cleaners a

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- 5

. Consumer Uses of DCM

. Consumer Uses

• Specialized electronic cleaners (for TV, VCR, razor, etc. ) a

• Wood stains a

• Transmission cleaners a

• Battery terminal protector 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 repellants a

• Gasket removers a

• Herbicides b

Sources : a NIH (2005 )

. b NIH (201 2 )

. c Mannsville (1999 )

.



### 2.2.4. P AINT 

### S TRIPPING 

### A PPLICATIONS



### DCM is considered the best chemical stripper that is effective on the widest range of cured coatings from the widest variety of substrates ( Mannsville, 1999 )

. The major applications for DCM

- based paint strippers include use on Original Equipment Manufacturing (OEM), field maintenance stripping, and home improvement and repair. Most of these users purchase paint stripper from a formulator who mixes the DCM with other chemicals to achieve the desired product ( SRRP, 1992 )

. For industrial use, paint strippers are typically 70 to 90 percent DCM by weight. Household paint strippers for consumer use are typically 60 to 80 percent ( US EPA, 1993; see also: Appendix C )

.

Several studies have been conducted to evaluate the extent of DCM use in paint stripping. In 2008 , EPA estimated that a total of 39,000 establishments perform surface coating operations, including paint stripping, motor vehicle, mobile equipment, and misc ellaneous activities. Specifically, EPA estimated that about 3,000 of these facilities were paint stripping shops. Of these 3,000 facilities, 2,000 used paint strippers containing ≤ 2,00 0 lb s of DCM, while 1,000 facilities used products containing > 2000 lb s of the chemical ( US EPA, 2010b )

.

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### 2.3

. E NVIRONMENTAL 

### F ATE



### The environmental fate of a compound is important to understanding potential exposures to its specific environmental media ( e.g. , water, sediment, soil, plants) and impact on target organisms of concern. Releases of DCM to soil can volatilize from soil surfaces or migrate through soil and contaminate groundwater.

DCM has high mobility in soil. It is not readily biodegradable, but biodegrades at varying rates under both aerobic and anaerobic conditions. The rate of hydrolysis is negligible. The high vapor pressure and Henry’s Law constant, 2.19 × 10 - 3 

### atm

- m 3 

### /mole, indicate DCM has a tendency to partition to the atmosphere. DCM is not expected to undergo photooxidation in the atmosphere and is considered moderately persistent and has low bioaccumulati on potential (OECD SIAP 2011, National Institute of Technology and Evaluation, 2002, EPA, 2012; Federal Register. 1999). Due to its volatility, DCM enters the atmosphere where it reacts slowly enough to undergo atmospheric transport and act as a greenhouse gas. DCM has been reported to the Intergovernmental Panel on Climate Change (IPCC) as a global warming potential (GWP) chemical with a value of 8.7 ( i.e., or approximately 8.7 times more heat absorptive than carbon dioxide (CO 2 

### )) GWP (IPCC Fourth Assessment Report, 2007). This section summarizes current knowledge of the transport, persistence, bioaccumulation, and bioconc entration of DCM in the environment including biological and abiotic reactions and environmental distribution.

Fate in Air. If released to the atmosphere, DCM is expected to exist solely in the vapor

- phase based on its vapor pressure. Vapor

- phase DCM is degraded slowly in air by reaction with photochemically produced hydroxyl radicals. The half

- life of this reaction is approximately 107 days. Thus, it is con sidered persistent in the atmosphere and subject to transport.

Fate in Water. When released to water, DCM is not expected to adsorb to suspended solids and sediment in the water column based upon its soil organic carbon partition coefficient ( K oc ) 

### value. The rate of volatilization is expected to be high based on a Henry’s Law constant of 2.19

× 10 - 3 

### atm

- m 3 

### /mole. 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 under environmental conditions is expected to be negligible. The hydrolysis half

- life reported at neutral pH, is approximately 18 m onths at 25 o 

### C (Dilling et al . 1975). Biodegradation is expected to occur slowly under aerobic conditions, but 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 isolate d from an anaerobic aquifer as inoculum (Hazardous Substance Databank (HSDB, 2012). A half

- life of 108 days was observed for DCM in contaminated groundwater under methanogenic conditions ( HSDB, 2012). Bioconcentration factor ( BCF ) values ranging from 2.0 to 5.4 were measured for DCM in carp over a 6 week incubation period at an initial concentration of 0.25 mg/L ( National Institute of Technology and Evaluation 2002 ).

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### BCF values of <6.4 to 40.0 were observed when the concentration was 0.025 mg/L. Based on the BCF study, DCM is not expected to bioconcentrate significantly in aquatic organisms.

Fate in Soil/Sediment. Based on its low soil organic carbon partitioning coefficient (K oc 

### ) of 25, DCM is likely to possess high mobility in soils and may be expected to leach from soils into groundwater (ATSDR 2000). DCM present at 100 mg/L achieved 13 percent of its theoretical biochemical oxygen demand (BOD) using an activated sludge inoculum at 30 mg/L and the modified MITI ( i.e., Ministry of International Trade and Industry) test (OECD 301C) over the course of a 4 week incubation period and is not readily biodegradable ( National Institute of Technology and Evaluation
, 2002 ). DCM was shown to degrade under aerobic conditions in
st atic culture screening studies that used domestic wastewater amended with yeast as inoculum (Tabak et al . 1981). Complete loss of DCM was observed within 7 days in the static culture tests; however, up to 25% of the loss could have arisen from volatilizat ion. These studies suggest that given its low affinity for soil and potential to grade somewhat slowly, DCM will be mobile in soils and persist long enough to migrate to groundwater.

Bioconcentration and Persistence

. Bioconcentration and persistence are qualitatively characterized according to the criteria set forth in EPA’s TSCA New Chemical Premanufacture Notification Program (PMN) (Federal Register (FR)
, 1999). Though biodegradation tests of this substance found it not readily biodegradable, there is evidence to support that metabolism occurs under both aerobic and anaerobic conditions

. Measured BCF values, indicate that DCM does not bioconcentrate.

2.4. C ONCLUSIONS OF 

### E NVIRONMENTAL 

### F ATE



### DCM is volatil e 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. It has been shown to biodegrade over a range of rates and condi tions and is considered to be moderately persistence in the environment. Measured bioconcentration factors for DCM suggest its bioconcentration potential is low. Table 2

- 6 provides a summary of the environmental fate information for DCM.

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- 6. Env ironmental Fate Characteristics of DCM, Dichloromethane. 1
Property Value

CASRN 79

- 09

- 2 Photodegradation Half

- life 107 days (measured) 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 (measured) 3

Fugacity (Level III Model) 3 Air (%) Water (%) Soil (%) Sediment (%) 43.8 45.0 11.0

0.1
Persistence 4 M oderate
Bioaccumulation 4 L ow

1 OECD SIAP. 2011. OECD HPV Chemicals Programme. Dichloromethane. Available online at http://webnet.oecd.org/hpv/ui/SponsoredChemicals.aspx as of March 19, 2012.
2 NITE (National Institute of Technology and Evaluation). 2002. Biodegradation and Bioaccumulation of the Existing Chemical Substances under the Chemical Substances Control Law. Available online from: http://www.safe.nite.go.jp/english/kizon/KIZON_start_hazkizon.html as of March 19, 2012.
3 U.S. EPA. 2012. Estimation Programs Interface SuiteTM for Microsoft® Windows, v4.10. U.S. Environmental Pro tection Agency, Washington, DC, USA. Available online at http://www.epa.gov/opptintr/exposure/pubs/episuitedl.htm as of March 19, 2012.
4 Federal Register. 1999. Category for Persis tent, Bioaccumulative, and Toxic New Chemical Substances. Federal Register 64, Number 213 (November 4, 1999) pp. 60194

– 60204.

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## Chapter 3: Human Health Risk Assessment

INTRODUCTION

EPA reviewed readily available information on the chemistry, uses, sources, fate, exposure and hazard of DCM to humans and the environment. The review of this information helped focus the scope of this risk assessment. This chapter has five major sections: ( 1 ) Human Exposure Assessment, (2) Hazard Identification and Dose

- Response Assessment, (3) Human Health Characterization, and (4) Discussion of Key Sources of Uncertainty and Data Limitations

.


## 3.1

. H UMAN 

## E XPOSURE 

## A SSESSMENT



### This assessment focused on the use of DCM

- based paint strippers. EPA assumed that direct contact or close proximity to the use ( i.e., for a consumer or commercial application with substantial frequency or duration of exposure) would likely provide the highest exposures to DCM paint strippers. In either occupational or consumer settings, ther e may be inhalation exposure during the product use. In addition to product users, there also may be non

- users or bystanders who may not come in direct contact with the product, but may be exposed indirectly while in a nearby area during product applicati on.

For quantifying risks, estimates were provided for inhalation exposures to workers and residential consum ers who use DCM

- based paint strippers, and for inhalation exposures to residential non

- users, who may be indirectly exposed.

3.1.1. O CCUPATIONAL 

### E XPOSURES



### This section summarizes the available information on occupational exposure monitoring data and regulatory and non

- regulatory occupational exposure limits to DCM for the primary industries where DCM is used in paint stripping applicat ions.

Recommended worker exposure limits have been established for DCM. A summary of the values established by OSHA, the National Institute for Occupational Safety and Health (NIOSH), and the American Conference of Governmental Industrial Hygienists (A CGIH) is provided in Table 3

- 1 . Additional background on processes, respiratory protection, and facilities and worker populations are presented in Appendix D . OSHA amended the regulatory occupational exposure limits for DCM effective April 10, 1997. The amendments included reducing the PEL, reducing and changing the averaging time of the Short

- Term Exposure Limit (STEL), adding an action level, and removing the ceiling limit ( OSHA, 1997a ) . The pre

- 1997 limits are included here to provide context when analyzing exposure data measured on or before 1997. W orkplaces may consider these levels when instituting respiratory protections

.

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- 1 . Regulatory and Recommended Exposure Limits.
Source Limit Type Exposure Limit OSHA PEL (1997 and forward) PEL (8

- hr TWA) 25 ppm 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 a IDLH 2,300 ppm
REL Ca
ACGIH TLV 8

- hr TWA 50 ppm

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

- minute exposure; REL notation Ca is for a potential occupational carcinogen, and the NIOSH Pocket Guide website has detailed policy recommendations for chemicals with Ca notations ( NIOSH, 2011b )

. IDLH = Immediately Dangerous to Life and Health; TLV = Threshold Limit Value; TWA = time

- weighted average Source: OSHA (1997a )

. 

### Because a variety of industries include paint stripping among their business activities, an effort was made to determine and characterize these industries, especially for the “small commercial shops” of interest to EPA. The terms for commercial, industrial, and small ( i.e., in terms of employees per employer) often are difficult to distinguish, particularly as related to exposure data . EPA reviewed the published literature and e valuat ed the 2007 North American Industry Classification System (NAICS) codes to determine industries that likely included paint stripping activities presented in Table 3

- 2

.

Table 3

- 2 . 2007 NAICS Codes Identified that Include Paint Stripping Activities.

2007 NAICS a 2007 NAICS Title Rationale for Inclusion of NAICS with Paint Stripping Activities
238320 Painting and wall covering contractors US Census reports an index entry of “Paint and wallpaper stripping” ( US Census, 2007a )

. 238330 Flooring contractors US Census reports index entries of “Floor laying, scraping, finishing, and refinishing” and “Resurfacing hardwood flooring” ( US Census, 2007a )

. NIOSH (1993 ) cites the paint stripping of flooring by a wood flooring and restoration
company ( NIOSH, 1993 )

. 811121 Automotive body, paint, and inter ior 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 US Census reports index entries of “Furniture refinishing

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. 711510 Independent artists, writers, and performers US Census reports index entries of “Painting restorers, independent” and “Conservators ( i.e. , art, artifact restorers), independent” ( US Census, 2007a ) . Research has shown art conservation to use paint strippers based on DCM or, preferably, NMP ( Wollbrinck, 1993 )

. 712110 Museums Research has shown art con servation to use paint strippers based on DCM or, preferably, NMP ( Wollbrinck, 1993 )

. 336411 Aircraft manufacturing US Census reports an index entry of “Aircraft rebuilding ( i.e. , restoration to original design specifications)” ( US Census, 2007a ) . Paint removal during the restoration process may use DCM

- or NMP

- based paint strippers.
336611 Ship building and repairing US Census NAICS definition includes shipyards involved in the construction of ships as well a s “their repair and conversion and alteration” ( US Census, 2007a ) . Any paint removal activities during repair, conversion, and alteration may use DCM

- or NMP

- based paint strippers.

a NAICS codes were identified by performing general internet searches to identify workplace

- related activities that involve paint stripping, and searching the US Census 2007 NAICS website for keywords related to paint stripping, including those determined from the general i nternet search, such as “refinish,” “stripping,” “paint,” “restorer,” and “conservator” ( US Census, 2007a )

. 

### Published monitoring studies were used to estimate occupational exposures to DCM. Additionally, inhalation exposure data from OSHA and state health inspections were obtained from the OSHA ’s Integrated Management Information System (IMIS) database. Appendix H presents a detailed discussion of these data. These studies formed the basis from which EPA calculated Average Daily Concentrations ( ADCs ) and lifetime average daily concentrations (LADCs) from eight

- hr time

- weighted average (TWA) exposures, using Equation 3

- 1 ( Eq; US EPA, 2009 ) to assess the risks to workers from these exposures. The ADC or LADC is equivalent to EC in the equation below with the substitution of the appro p ri ate AT value.

Eq. (3

- 1)

where: AD C = exposure concentration (mg/m 3 ); C = contaminant concentration in air (mg/m 3 ); ED = exposure duration ( hr s/day; default: 8); EF = exposure frequency (days/year; default: 250); WY= working years per lifetime (years; ADC and LADC: 40 years); and AT= averaging time (lifetime in years × 365 days/years × 24 hr s/day; ADC: 40 years; LADC: 70 years, which is used to match the years used to calculate EPA’s cancer inhalation unit risk [IUR]).

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### A summary of the identified exposure concentrations and the calculated ADCs and LADCs for several of the exposed populations are provided in Table 3

- 3

. In comparison to more detailed literature sources
, OSHA IMIS data were not included in this summary except where noted because of the high degree of uncertainty and questionable relevancy of these data to paint stripping with DCM

- containing products. EPA determined that the av ailable datasets were not amenable to developing statistical distributions of all exposures in the specified industries. Therefore, each of the exposure estimates represents a snapshot of the particular cases studied and may not be representative of the b roader worker populations that are exposed to DCM during its use in various paint stripping applications. Despite these limitations, these data show that the OSHA PEL and STEL are exceeded under some circumstances.

Table 3

- 3 . Summary of Ranges of DCM Ex posure Concentrations and Calculated ADCs and LADCs for Workers.

Industry Number of Studies Time Range of Studies Range of Task

Based, Short

- Term, or Peak Exposure

Concentrations (mg/m 3 ) a Range of 8

- hr TWA Exposure Concentrations (mg/m 3 ) b ADC (mg/m 3 ) c LADC (mg/m 3 ) c

Professional
contractors 4 1990

- 1998 130

- 14,100 (37

- 4,063 ppm) – – –

1 1981

– 60

- 2,980 (17

- 859 ppm) 14

- 680 7.8

- 390

Bathtub refinishing 1 2003

- 2008 6,940

- 7,565 (2,000

- 2,180 ppm) – – –

Automotive refinishing 1 2004 250

– 416 (72

- 120 ppm) – – –

1 2004

– 90

- 416 (26

- 120 ppm) 21

- 95 12

- 54

Furniture refinishing 5 1990

- 2007 24

- 3,814 (7

- 1,099 ppm) – – –

4 1991

- 2007

– 2.4

- 1,270 (0.7

- 366 ppm) 0.55

- 290 0.32

- 170

Art restoration and conservation d 1 2005

– 2 (0.58 ppm) 0.46 0.26

Aircraft paint stripping 4 1977

- pre

1999 38

- 5,400 (11

- 1,556 ppm) – – –

4 1994

- 2002

– 86

- 3,802 (25

- 1,096 ppm) 20

- 870 11

- 500

Ship paint stripping 1 1980 215 (62 ppm) – – –

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- 3 . Summary of Ranges of DCM Ex posure Concentrations and Calculated ADCs and LADCs for Workers.

Industry Number of Studies Time Range of Studies Range of Task

Based, Short

- Term, or Peak Exposure

Concentrations (mg/m 3 ) a Range of 8

- hr TWA Exposure Concentrations (mg/m 3 ) b ADC (mg/m 3 ) c LADC (mg/m 3 ) c

Unspecified workplace setting: immersion stripping of wood Unknown 1980

- 1994

– 35

- 7,000 (10

- 2,017 ppm) 8.0

- 1,600 4.6

- 910

Unspecified workplace setting: wood and metal paint stripping 1 1980

– 633

- 1,017 (182

- 293 ppm) 150

- 230 83

- 130

a These exposures include task

- based exposures averaged over a time period of <8 hr s, short

- term ( i.e. , STEL) exposures, and peak exposures. b These exposures include 8

- hr TWA exposures that were either directly measured or calculated from shorter time frame exposures by the study authors.

c Calculated Average Daily Concentration (ADC) and Lifetime

- Average Daily Concentrations (LADC) are only calculated from 8

- hr TWA exposures; see Equation 3

- 1. d The data point provided for this industry was obtained from OSHA IMIS. No other literature data were obtained. Note: Airborne concentration conversion factor for DCM is 3.47 mg/m 3 per ppm ( NIOSH, 2011a )

.

-- indicates no data found.



### The data presented in Table 3

- 3 were obtained from the cited studies in Table 3

- 4 , which summarizes the number of workers monitored or exposed in the respective studies and the total number of employees at the facility.

Table 3

- 4 . Summary of Number of Workers Exposed or Monitored and Total Number of Employees in the Monitored Facility Cited in the References Used for Each Industry.

Industry Reference * Number of Workers Exposed or Monitored Total Number of Employees in Facility
Professional contractors TNO (1999 ) Unknown a Unknown US EPA (1994b ) N/A N/A Bathtub refinishing b CDC (2012b
, a ); MSU/MIFACE (2011 ) 1 1

Lo fgren et al. (2010 ) 1 Unknown Automotive refinishing Enander et al. (2004 ) 1 14 Furniture refinishing NIOSH (1992 ) 5 Unknown Grevenkamp (2007 ) 1 18

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- 4 . Summary of Number of Workers Exposed or Monitored and Total Number of Employees in the Monitored Facility Cited in the References Used for Each Industry.

Industry Reference * Number of Workers Exposed or Monitored Total Number of Employees in Facility
McCammon et al. (1991 ) 14 c Unknown NIOSH (1991 ) 1 Unknown NIOSH (1990 ) 1 1 TNO (1999 ) Unknown Unknown
Art restoration and conservation OSHA (2012 ) 1 Unknown

Aircraft paint stripping IARC (2010 ); TNO (1999 ); EU (2007a ); Vincent et al. (1994 ) Unknown Unknown

Ship paint stripping IARC (2010 ) 8 Unknown Unspecified workplace setting TNO (1999 ) Unknown Unknown

*Study details are provided in Appendix E

. a Unknown ( i.e. , not specified in the reference). b For bathtub refinishing, "facility" refers to the job site where the refinisher was working at the time of the monitoring or at the time the fatality occurred.

c For this particular study, a total of 14 workers were monitored over a total of five furniture stripping shops, which averages to 2.8 workers monitored per facility.



### Using the limited information identified , EPA could not estimate the current total number of workers in the potentially exposed populations. Knowing the sizes of exposed populations provides perspective on how prevalent the effects may be

. By way of comparison
, more recent OSHA data on the num bers of facilities and workers in the wood furniture stripping industry indicate that the current total number of workers exposed to DCM appear fewer than the 7,872 estimated in the mid

- 1990s ( Appendix D ).

When identifying “small commercial shops,” the a vailable data provide information that may allow some generalizations about the relative sizes of facilities/shops that fit this category. EPA combined the facility and population data from Appendix D and the average number of employees per facility to generall y categorize the industries included in this assessment into the following classifications:

• Small shops could generally be expected to include (< 10 workers) professional contractors ( i.e., including bathtub refinishers), automotive refinishers, f urniture refinishers, and independent art restorers;

• Larger facilities (> 10 workers) could generally be expected to include facilities that strip paint from aircraft and ships; and

• The exposures labeled Unspecified Workplace Setting cannot be classified into either small shop or larger facilities.

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### Because these size distinctions are simple generalizations that may not be entirely applicable to the exposure data in the industry categories identified, the exposure estimates from all of the industries were considered in the risk characterization presented lat er in this chapter.

3.1.2. R ESIDENTIAL 

### / C ONSUMER 

### E XPOSURES



### DCM was selected for further assessment based on its high hazard ( i.e., due to liver toxicity and cancer risks ) and it s numerous uses in consumer products, EPA assessed the exposure route with the greatest potential for consumer exposure to DCM. This section provides estimates of inhalation exposure s for residential users and other residential occupants (bystanders) during the use of paint

- stripper products containing DCM. I n the absence of sufficient measured data on consumer exposures, i nhalation exposures were calculated for current use patterns using a model

- based approach. Specifically, the EPA’s Multi

- Chamber Concentration and Exposure Model (MCCEM) was utilized to predict airborne con centrations of DCM in various consumer

use scenarios ( US EPA, 2010a )

.

3.1.3. C ONSUMER 

### E XPOSURE 

### M ODELING


### Input Parameters. The parameters needed to support EPA’s modeling effort to estimate consumer inhalation exposure and the input values used for different exposure scenarios and their rationale are described in this section.

The MCCEM model requires input of several chemical

- specific parameters. EPA identified published dat a for current product characteristics, use patterns, exposure factors, and air concentrations to develop appropriate scenarios and for modeling inpu t parameters . A limited number of relevant sources were identified ; however, the majority of these were ove r a decade old. All sources were compared to quality criteria, e.g. , currency, scope, accuracy/reliability, transparency, clarity
, and completeness of the information provided.

EPA used published values for DCM

- containing products currently available for consumer purchase ( Brown, 2012 ) to determine reasonable percentage of DCM in products and product densities. Other resources providing information on product characteristics included: (1) the NIH ’s Household Products Database; (2) MSDSs; and
, (3) Product Labels and Technical Data Sheets. I nformation was collected from available p roduct l abels or Technical Data Sheets for approximately half of the products listed in Brown (2012 )

. EPA identified published air monitoring data from the consumer use(s) of DCM paint strippers from t wo comprehensive US experimental studies

. O ne study was conducted by the US EPA (1994b ) and the other was conducted by the Consumer Product Safety Commission (CPSC) in 1986 (as cited in US EPA, 1996 ; Riley et al. , 2000 )

. Both studies were over 15 years old ; the usefulness of the CPSC study was limited because the original source was not available for quality criteria evaluation . Limited results and experimental parameters were obtained from the CPSC study
, US EPA (1996 ) , a nd Riley et al. (2000 )

.

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### EPA also reviewed a European Commission (EC, 2004) study that described chamber
exper iments performed in the EU in 2003. A standard scenario was monitored and other scenarios reported in this study that estimated changes in air concentration based on variations in surface area, ventilation, surface orientation, exposure duration, and product amount; only air concentrations for the standard scenario were measured. However, this study had several limi tations to its utility for the current assessment including: (1) too little information to confirm model parameters, study design, or results; (2) lack of information on
, study design of and product formulation or percent D CM in the test products ; (3) the presence of vapor retardants, which not typical in US products ; (4) th e ventilation rate was high for indoor rooms unless mechanical ventilation is used ( e.g. , a fan venting directly outdoors) ; and, (5) differences in typical US room size ( i.e., US r oom sizes may be larger).

Exposure factor information was identified from a variety of sources, including the Exposure Factors Handbook (EFH; EPA, 2011c) which provides recent information on generic exposure factors ( e.g., body weights, body part surface areas, house volumes, and house ventilation
rates ) as well as for specific use of paint strippers ( i.e. , use amounts, frequencies, durations as presented in Westat (1987) and Abt (1992)).

EPA utilized some information on paint stripper use patters by Rile y (2001). This study provides relevant data on paint strippers and is the most current use

- pattern survey available for paint strippers. This single

- site survey was not specific to the use of DCM paint strippers, was based on a small sample size (n=20), and utilized participant recall of product

- use behavior. Other information, not specific to paint strippers but used to identify input parameters for the inhalation modeling, such as interzonal air flows and air exchange
, rates, was obtained from published sources including EPA (1995b) and Matthews et al . (1989)

. Rationale for a Modeling

- Based Approach

. Complete air monitoring data for the consumer use of paint strippers containing DCM are only available from EPA (1994b). In that study, chamber experiments were conducted for five paint stripping products, including two paint

- stripping products containing DCM. T he 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. It is unclear why US EPA (1996 ) doesn’t discuss a third product in the study that also contained DCM; however, DCM was not listed as an ingredient , nor were air monitoring results provided for the product. An advantage of this study is that it used US products and provided sufficient descriptions of the study design and results. However, the experimental data cannot be used directly to assess resi dential 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 ) do not reflect the range of possible residential values. Additionally, the experimen ts were conducted in a one

- room chamber and, thus, do not provide concentrations for areas of the house other than the treatment room. The study was useful, however, in determining product application rates ( i.e., in g/ft 2 

### and g/min) and in estimating the fraction of applied chemical mass that ultimately was released to the indoor air, as described in more detail in Appendix F , F

- 1.

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### Estimation of Emission Profiles for Paint Removers/Strippers

. EPA identified other air monitoring studies for consumer paint strippers using DCM

- containing products, including the previously described European Commission (EC) study ( EC, 2004 ) and a study conducted in the Netherlands by van Veen et al. (2002 ) . The EC (2004 ) study is the most current experimental study conducted for paint strippers. However, one of its main limitations was the failure to provide the raw data in the report. Thus, t he 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 US. The van Veen et al

. (2002 ) study provided useful information related to this task; however, the study was conducted on a small scale and, as with the EC (2004 ) study, the exposure scenario assessed did not represent well use patterns in the US.

3.1. 4

. I NHALATION 

### E XPOSURE 

### A SSESSMENT


### Methodolog y. Inhalation exposure to DCM emitted during paint stripper application and associated scraping was modeled using the MCCEM which is ideally suited to this application

. It provides for modeling of “incremental source” emissions, whe reby a product is applied at a constant rate and the emission rate of the chemical in each instantaneously applied segment is assumed to decline exponentially over time. Depending on the type of applied product, either one or two exponential expressions m ay be needed to characterize the declining emission rate. From an analysis of chamber tests conducted in US EPA (1994b ) (see Appendix F , F

- 1. Estimation of Emission Profiles for Paint Removers/Strippers ), it was determined that a single

exponential expression was appropriate for paint strippers with DCM as a primary ingredient.

The selection of exposure scenarios for the inhalation exposure assessment was guided in part by the outcome of a sensitivity analysis to determine which parameters used in the model have the most influence over the results of the ass essment. Changing those values for various combinations of parameters will generate a wide range of plausible exposure scenarios and can increase the level of confidence in the model results. The methods for and results of this analysis are described imm ediately below.

Sensitivity Analysis

. The types of factors that can be varied in MCCEM include the following:

• The configuration of the structure (residence in this case) being modeled, including the number of zones, volume of each zone, airflow rates bet ween each zone and outdoors, 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: (1) the user(s)

— the individual(s) applying the product, and (2) the non

- user(s)

— other i ndividual(s) present in the house who are not involved in the paint

- stripping activity and, by assumption, are located in a house zone other than the one in which the paint

- stripping activity is taking place.

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### The sensitivity analysis was conducted using a n 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. Next, the inputs are varied

— one at a time

— and the model response ( i.e., average or peak concentrations to which individuals are exposed) is noted. The “i ndex of sensitivity ” is the magnitude of change in model response, typically expressed as a percent change from that of the base case. Details on this approach are in Appendix F, F

- 2. Sensitivity Analysis for Inhalation Scenarios

.
The time required to apply and scrape the p aint stripper, including the wait time between applying and scraping, is about an hr , according to Abt (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 include the maximum or peak TWA concentrations for certain averaging periods ( i.e., one, 10 , and 30 minutes and one, four, and eight hr s) in addition to the 24

- hr TWA value. T ime

- varying concentrations that the user and

non

- user could be exposed to are shown in Figures 3

- 1 and 3

- 2 along with the maximum TWA values and the corresponding time pe riods for selected averaging times. All the exposure
measures as described were included for the formal model runs ; but only the maximum one

- hr and the 24

- hr TWA were used for the sensitivity analysis.

The base case for the sensitivity analysis was forme d using central values for the various inputs, 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) and 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 surface 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 ; and
,
• User located in workshop during application and scraping periods but in ROH during wait periods between applying/scraping and after completion of all applying/scraping.

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- 1 . Time

- varying User Personal Concentration and Maximum TWA Values for Selected Averaging Times.

Figure 3

- 2 . Time

- varying Non

- user Personal Concentration and Maximum TWA Values for Selected Averaging Times.

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### The sensitivity results for two exposure measures
, peak one

- hr TWA and 24

- hr TWA are displayed in Figur es 3

- 3 and 3

- 4 , respectively. For both measures, and for both the user and the

non

- user, the change in model output for changing chemical mass is 75 percent, indicative of a linear and proportional response. For the user, the model response is highly sen sitive to location during the wait period between applying and scraping ( i.e., user stays in workshop vs. moves to ROH). The model response is somewhat sensitive to the ROH air exchange rate with outdoors (ROH ACH) for the non

- user , but not for the user. As a result of the sensitivity analysis, EPA determined that the chosen modeling scenarios should include some variations in each of these three factors to address greater model sensitivity.

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Page 39 Figure 3

- 3

. Model Sensitivity Resul ts (Percent Change from Base

- case Response) for Peak One

- hr TWA for User and Non

- user.

Figure 3

- 4 . Model Sensitivity Results (Percent Change from Base

- case Response) for 24

- hr TWA for User and Non

- user.

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### 3.1. 5

. E XPOSURE 

### S CENARIOS AND 

### M ODEL 

### I NPUTS


### Exposure Scenarios

. Seven exposure scenarios were developed for the assessment, as summarized in Table 3

- 5 . The following factors were considered in developing the scenarios:

• The type of application ( i.e. , brush

- on or spray

- on), weight fraction of applied product, application rate, surface area of object to be stripped, and emission rate of the chemical concern, which can affect the amount of DCM that ultimately is released to the indoor environment;

• The location where the product is applied, which relates to exposure factors such as the room volume and its air exchange rate with outdoors;

• The house volume and air exchange rate, for reasons similar to those for the product use location; and
,
• Precautionary behaviors such as opening windows in the appl ication 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.

Table 3

- 5 . Consumer Exposure Scenarios for the DCM Inhalation Exp osure 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 Workshop Non

- user upper

- end

4 Spray

- on Workshop Central tendency

5 Spray

- on Workshop User upper

- end

6 Spray

- on Workshop Non

- user upper

- end

7 Brush

- on Bathroom Non

- user upper

- end

a Conditions obtained by varying the most sensitive parameters: DCM mass emitted; user location during the effect or wait period; and the rest of the house (ROH) air exchange rate with outdoors.



### The primary distinctions among the seven scenarios ( guided by the sensitivity analysis ) were: type of application ( i.e. , brush vs. spray) ; location of product application ( i.e. , workshop for most scenarios, bathroom for one scenario) ; and values used for other inputs including the DCM mass emitted, the user’s location during the effect or wait period, and the air exchange rate of the rest of the house ( ROH) with outdoors. Of the scenarios listed in Table 3

- 5 , two are considered central tendency 1 

### for both the user and the non

- user, two were developed to

1 As noted in Section 2.3.1 (Individua l Risk) of the US EPA (1992a ) 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.

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### estimate upper

- end concentrations for the user, and two were developed to estimate upper

en d 2 

### concentrations primarily for the non

- user. Central

- tendency values are exposure values expected to be near the average or median for the range of exposure values; upper

– end values are plausible exposure values from the upper half of the range of expect ed exposure amounts. These descriptive exposure estimates are generally required for risk assessments.

The seventh s cenario EPA used was a simulation of actual reported conditions from a Centers for Disease Control and Prevention (CDC)/NIOSH occupational exposure case for a DCM paint stripper used on a bathtub ( CDC, 2012a , b ) . This scenario represents high product use in a confined ( i.e. , closed, poorly ventilated) space. The selected parameter values for this scenario ( e.g. , large surface area, small room size, minimal ventilation, upper

- end weight fraction
, and low ROH ventilation ) would increase concentrations and e xposures so that the combinations of parameter values would be expected to result in upper

- end to bounding 4 

### concentrations for the user and non

- user. The purpose of including this latter scenario in this assessment was to estimate the DCM concentrations to residential occupants outside the use zone.

Further details of the exposure scenario inputs are discussed in Appendix F, F

- 3 in the section

on Inhalation Exposure Scenario Inputs

. Summary of Exposure Scenarios and Model Inputs

. The exposure scenario inputs included : amount of DCM release, stripping method, room of use volume and ventilation characteristics, house volume and ventilation characteristics, the user location during the wait period, and non

user location. The inputs for all seven scenarios are summarized in Table 3

- 6 , from which the major and subtle differences among the seven scenarios are shown. For example, Scenarios 2 and 3
, and their spray

- application counterparts, Scenarios 5 and 6
, are targeted toward estimation of upper

- end exposur es for the user and non

- user, respectively, by changing the application amount, the location of the user, and the airflows.

2 As also noted in Section 2.3.1 of the above

- cited guidelines, “ a high end exposure estimate is a plausible estimate of the individual exposure for those persons at the upper end of an exposure distribution. The intent of this de signation is to convey an estimate of exposures in the upper range of the distribution, but to avoid estimates that are beyond the true distribution. Conceptually, the high end of the distribution means above the 90 th percentile of the population distribu tion, but not higher than the individual in the population who has the highest exposure.” For this assessment, scenarios labeled “ upper

- end” were modeled by selecting low

- and high

- end values for sensitive parameters. An “upper

- end” exposure estimate is above central tendency and may include the high end of the exposure distribution.

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- 6

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

Scen ario ID Characteriz ation DCM Released Stripping Method Room of Use House User Location During Wait

Period b Non

- User 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 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 segments 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

a fter 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 0.88 (upper

end) Workshop

3 Upper

- end for non

user 25 chest of drawers (upper

- end) 0.18 (low

- end) ROH

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 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) 5 Upper

- end for user 0.87 (upper

end) Workshop

6 Upper

- end for non

user 25 chest of drawers (upper

- end) 0.18 (low

- end) ROH

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- 6

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

Scen ario ID Characteriz ation DCM Released Stripping Method Room of Use House User Location During Wait

Period b Non

- User 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 non

user 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) c Window closed, no exhaust fan/ 0.18 d (low

- end) 492 (central) 0.18 (low

- end) ROH ROH (entire time)

a The surface area values were selected so that the calculated amount of product applied (g) corresponds approximately to the Abt (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 th 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 s craping.

c 1 m 3 for the vicinity of the tub (source cloud) and 8 m 3 for the rest of the bathroom. d Because the user is working in close proximity to the target (bathtub) for an extended period, a third zone (“source cloud”) was created within the bathroom to represent the DCM concentrations in the vicinity of the tub; this is a virtual zone, with no physical boundaries. The airflow rate between the cloud and the rest of the bathroom was based on work by Matthews et al. (198 9 ) (for more information, see discussion in Appendix F, F

- 3. Inhalation Exposure Scenario Inputs (Airflow Rates and Volumes).

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### 3.1. 6

. S UMMARY OF 

### M ODEL 

### O UTPUTS AND 

### E XPOSURE 

### C ALCULATIONS


### . To account for an individual’s location at specific times, MCCEM outputs a detailed time series of zone

- specific ( e.g. , house, workshop, and bathroom) and personal concentrations. This output is in the form of instantaneous values at the end of consecutive one

- minute time intervals for the entire duration of the model run ( i.e., 24 hr s in this case). A more detailed, mathematical description of the calculations is provided in Appendix F, F

- 3. Inhalation Model Outputs and Exposure Calculations

.
Table 3

- 7 provides a summary of DCM exposure concentrations for the consumer user and non

user of DCM

- containing paint strippers. These concentrations were calculated by computing running averages and selecting the maximum of these averages. For example, for the one

- hr averaging period, the one

- hr average concentration was calculated for each one

- minute start time during the 24

- hr period ( e.g. , zero to 60, one to 61, and etc. ), for which the maximum of these averages is reported in Table 3

- 7

. As the averaging tim e increases, the user to non

- user exposure ratio decreases. For Scenario 1, for example, the ratio of user to non

- user maximum

one

- minute concentration is ~5:1, as compared to a ratio of ~1.5:1 for the 24

- hr user and non

user TWA values.

Appendix F, F

- 5. MCCEM Inhalation Modeling Scenario Summaries provides s cenario summaries for each of the modeled scenarios, including both model inputs and results.

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- 7. Summary of Modeled DCM Concentrations to Which Consumer Users and No n - Users are Exposed, by Scenario.

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 application in workshop, central parameter values User 630 (180) 380 (110) 270 (78) 220 (64) 120 (35) 69 (20) 23 (6.7)

Non

- user 130 (38) 130 (38) 130 (37) 120 (36) 82 (24) 49 (14) 17 (4.8) 2. Brush application in workshop, upper

- end values User 1,300 (370) 1,300 (360) 1,100 (330) 1,100 (300) 420 (120) 220 (64) 75 (22)

Non

- user 220 (63) 220 (63) 220 (62) 210 (59) 140 (39) 82 (24) 28 (8.0) 3. Brush application in workshop, upper

- end values User 1,800 (520) 1,200 (340) 900 (260) 760 (220) 560 (160) 400 (120) 160 (45)

Non

- user 470 (140) 470 (140) 470 (140) 460 (130) 380 (110) 290 (83) 120 (34) 4. Spray application in workshop, central parameter values User 1,500 (430) 780 (220) 600 (170) 490 (140) 270 (77) 150 (44) 52 (15)

Non

- user 300 (87) 300 (87) 300 (86) 280 (82) 190 (54) 110 (32) 38 (11) 5. Spray application in workshop, upper

- end values User 2,000 (570) 1,900 (550) 1,800 (510) 1,600 (460) 620 (180) 330 (96) 110 (32)

Non

- user 330 (95) 330 (95) 320 (93) 310 (89) 200 (59) 120 (35) 42 (12) 6. Spray application in workshop, upper

- end values User 2,800 (810) 1,600 (470) 1,300 (360) 1,100 (320) 810 (230) 580 (170) 230 (66)

Non

- user 710 (210) 710 (210) 710 (200) 700 (200) 580 (170) 430 (120) 180 (51) 7. Brush application in bathroom, simulation User 2,700 (770) 1,500 (440) 940 (270) 840 (240) 560 (160) 350 (100) 140 (40)

Non

- user 220 (64) 220 (64) 220 (64) 220 (63) 190 (54) 150 (43) 70 (20)

a Non

- user assumed to be in ROH.

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### 3.2

. H UMAN 

### H EALTH 

### A SSESSMENT 

### : H AZARD 

### I DENTIFICATION AND 

### D OSE 

### - R ESPONSE


### The hazard summary information used in this assessment was based on the EPA’s Toxicological Review of Methylene Chloride [i.e., Integrated Risk Information System (IRIS) assessment; ( US EPA, 2011b ) ], the Acute Exposure Guideline Levels (AEGL) technical support document ( US EPA, 2008 ) , the Agency for Toxic Substances and Disease Registry’s ( ATSDR’s) Toxicological Profile for Methylene Chloride ( ATSDR, 2000 , 2010 ) , and the Technical Support Document Supporting the California’s Acute Reference Exposure Level (REL) for DCM ( OEHHA, 2008 )

. Additional information is provided in Appendix G.

3.2.1. T OXICOKINETICS AND 

### B IOMONITORING



### DCM is rapidly absorbed through inhalation exposure. The pulmonary uptake of DCM ranges roughly from 40 to 60 percent ( Gamberale et al. , 1975 ; Stewart et al. , 1976 ; Andersen et al.
, 1991 ; as cited in US EPA, 2008 ) , but may be up to 70 percent during the first minutes of
exposure ( Riley et al. , 1966 ; as cited in US EPA, 2008 ) . The uptake decreases with exposure duration and concentration ( Stewart et al. , 1976 ; Peterson, 1978 ; as cited in US EPA, 2008 ) , and

a steady

- state absorption rate is generally achieved within two hr s of exposure s up to 200 ppm ( DiVincenzo and Kaplan, 1981 ; DiVincenzo et al. , 1972 ; as cited in US EPA, 2008 )

. Results from studies of animals show that following absorption, DCM is rapidly distributed throughout the body
, primarily reaching the liver, brain, and subcutaneous adipose tissue ( Carlsson and Hultengren, 1975 ; US EPA, 2011b ; as cited in ATSDR, 2000 ) . DCM’s plasma half

life is estimated to be 40 minutes after inhalation exposure ( DiVincenzo et al. , 1972 ; as cited in ATSDR, 2000 )

. Metabolism occurs predominantly in the liver, although additional transformation occurs in the lungs and ki dneys ( ATSDR, 2000 )

. In the liver, metabolism of DCM involves two primary pathways. The first pathway produces carbon monoxide (CO) and carbon dioxide ( CO 2 

### ), and saturation occurs at very low concentrations of a few hundred ppms . The second pathway yields formaldehyde and formic acid, and saturation occurs at very high concentrations (>10,000 ppm).

Acute toxic effects ( i.e. , central nervous system [CNS] depression) may persist for hr s after cessation of exposure because of continued metabolism of DCM released from tissue storage ( ATSDR, 1990 ; as cited in ATSDR, 2000 ) . Car boxyhemoglobin (COHb) levels can continue to increase reaching peak levels as much as five to six hr 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 ; as cited in ATSDR, 2000 )

.

DCM has been detected in human breast milk ( Pellizzari et al. , 1982 ; US EPA, 1980 as cited in ATSDR, 2000 ) , so it is possible that infants could be exposed to DCM throu gh maternal exposures. However, physiologically based pharmacokinetic (PBPK) modeling suggests that

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### lactating females who breast feed their infants will not deliver DCM in quantities significant enough to be harmful ( Fisher et al. , 1997 ; as cited in ATSDR, 2000 ) . Blood concentrations of DCM were below the level of detection in 1,165 individuals who participated in the recent National Health and Nutrition Examination Survey (NHANES) 2003 to 2004 subsample of the US population ( CDC, 2009 ) . DCM was present in the urine of workers employed at a pharmaceutical factory. Urine levels appear to be nearly eliminated during the overnight period after exposure has occurred ( HSDB, 2012 ) . Human health effects associated with exposure to low environmental levels of DCM or low levels detected in biomonitoring studies are unknown ( CDC, 2009 )

.

3.2.2. A CUTE 

### H AZARD


### Acute inhalation exposure of humans to DCM has been associated with decreased oxygen availability from COHb formation and with neurological impairment from the interaction of DCM with membranes in the nervous system ( Bos et al.
, 2006 ; ACGIH, 2001 ; ATSDR, 2000 ; Cherry et al. , 1983 ; Putz et al. , 1979 ; Gamberale et al. , 1975 ; Winneke, 1974 ; as cited in US EPA, 2011b ) . Acute lethality in humans following inhalation exposure is related to Central Nervous System ( CNS ) depress ant effects. These effects include loss of consciousness and respiratory depression, resulting in irreversible coma, hypoxia, and eventual death ( US EPA, 2008 ) . The organ most often affected in exposures to high levels of DCM is the brain, followed by the lungs and heart. 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 ( US EPA, 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 ( US EPA, 2008 ) . Also in nonfatal cases, the adverse effect s most frequently described are CNS

- related only; in a few cases, cardiotoxic effects ( i.e., evidenced by electrocardiogram [ECG] changes) were reported. Effects on lung, liver, or kidney have been reported as primary signs of DCM toxicity ( US EPA, 2008 ) . It is noted that in some cases, high COHb levels (i.e., up to 40 percent) are measured without serious complaints. The reported COHb levels could not b e linked to effects in a dose

related way in any of these cases ( US EPA, 2008 )

.

Acute expos ure to human s results in acute neurobehavioral deficits measu red 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 hr s of exposure ( Bos et al
., 2006; ACGIH, 2001; ATSDR, 2000; Cherry et al ., 1983; Putz et al ., 1979; Gamberale et al ., 1975; Winneke, 1974
, as cited in US EPA, 2011b ).

Neurological evaluations in animals during and after acute inhalation exposure to DCM ( i.e., >200 to 1000 pp m for 1 to 8 hr s ) have resulted in CNS depressant effects with decreased motor activity, impaired memory, and changes in responses to sensory stimuli. Neurobehavioral, neurophysiological, and neurochemical/neuropathological studies have been used to charac terize the effects of DCM on the CNS ( US EPA, 2011b )

.

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### There are multiple lines of evidence demonstrating that DCM exposure ( i.e., orally or via inhalation) in adult animals results in measured changes in excitatory and in hi bitory neurotransmitters, such as glutamate and acetylcholine and the inhibitory neurotransmitter, GABA. Additionally, dopamine and serotonin levels, which are associated with addiction and mood, were measured. Other parameters that wer e measured included DNA/protein content and changes in the cerebellum and hippocampus. Measurement of neurochemical changes provides mechanistic information, and neurobehavioral and neurophysiological effects can be correlated to these results.

T hough fe w developmental effects were observed at high exposures to DCM ( Bornschein et al
., 1980; Schwetz et al ., 1975), there are no studies that have adequately evaluated neurobehavioral and neurochemical changes resulting from gestational DCM exposure. The available data identify changes in behavior habituation at 4,500 ppm (Bornschein et al ., 1980) and increases in COHb at 1,250 ppm (Schwetz et al ., 1975). The behavioral changes observed at 4,500 ppm indicate developmental neurotoxic effects; this is the only dose group used in the Bornschein et al . (1980) study. No other neurological endpoints have been evaluated in the available developmental studies of DCM

. Th e significance of this data gap also is supported by evidence from adult neurotoxic ity testing indicating that acute/short term exposures can affect neurotransmission and neurotransmitters levels

. These effects on neurotransmitters levels
, while transient
, may have qualitatively different outcomes if they occur during development of the nervous system when neurotransmitters serve a critical role in patterning the nervous system (for review B arone et al

. , 2000 ). The potential for developmental neurotoxicity occurring at lower exposures to DCM represents a very important data gap.

3.2.3. C HRONIC 

### H AZARD


### Relatively little is known about the long

- term neurological effects of chronic low level DCM exposures in humans, although there are studies that provide some evidence of an increased prevalence of neurological symptoms among workers with a verage exposures of 75 to 100 ppm ( Cherry et al. , 1981 ; as cited in US EPA, 2011b ) . L ong

- term effects on some neurological measures ( i.e. , possible detriments in attention and reaction time in complex tasks) have been observed in retired workers whose past chronic exposures were in the 100 to 200 ppm rang e ( Lash et al. , 1991 ; as cited in US EPA, 2011b ) . These studies are limited by the relatively small sample sizes and their low power for detection of statistically significant results.

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

cancer toxicity in rats and mice. Lifetime exposure was associated with hepatocyte vacuolation and necrosis in F344 rats exposed to 1,000 ppm for six hr s/day ( Mennear et al. , 1988 ; NTP, 1986 ; as cited in US EPA, 2011b ) , hepatocyte vacuolation in Sprague

- Dawley rats exposed to 500 ppm for six hr s/day ( Nitschke et al. , 1988a ; Burek et al. , 1984 as cited in US EPA, 2011b )
, and hepatocyte degeneration in B6C3F 1 

### mice exposed to 2,000 ppm for six hr s/day ( i.e., lower concentrations were not tested in mice) ( Mennear et al. , 1988 ; NTP, 1986 ; as cited in US EPA, 2011b ) . Other effects observed include renal tubular degeneration in F344 rats and B6C3F 1

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### mice at 2,00 0 ppm, testicular atrophy in B6C3F 1 

### mice at 4,000 ppm, and ovarian atrophy in B6C3F 1 

### mice at 2,000 ppm.

DCM was determined as “likely to be carcinogenic in humans” under the Guidelines for Carcinogen Risk Assessment ( US EPA, 2005 ; as cited in US EPA, 2011b ) . Results from two

- year bioassays provide adequate evidence of the carcinogenicity of DCM and data to describe dose

response relationships in mice and rats exposed by inhalation. Oral exposure to DCM produced statistically significant increases in hepatocellular adenomas and ca rcinomas in male B6C3F1 mice ( Serota et al. , 1986 ; Hazleton Laboratories, 1983 ; as cited in US EPA, 2011b ) . Inhalation exposure to concentrations of 2,000 or 4,000 ppm DCM produced increased incidences of lung and liver tumors in male and female B6C3F1 mice ( Maronpot et al. , 1995 ; Foley et al. , 1993 ; Kari e t al. , 1993 ; Mennear et al. , 1988 ; NTP, 1986 ; as cited in US EPA, 2011b ) . Significantly increased incidences of benign mammary tumors (adenomas or fibroadenomas) were observed in male and female F344/N rats exposed by inhalation to 2,000 or 4,000 ppm ( NTP, 1986 ; Mennear et al. , 1988 ; as cited in US EPA, 2011b )

.

The information on the Mode of Action ( MOA ) for one of the most sensitive adverse effects for acute exposure to DCM indicates both time dependent changes in some neurological endpoints that track more closely with the blood levels of parent compound versus generation of carbon monoxide or as measured by COHb ( Putz et al. , 1979 ; 

### Winneke, 1981). The CNS depressant effects versus hypoxic response track with these two proximate toxicants (Winneke, 1981) and

are relevant to both acute adult and developmental neurotoxici ty. In the case of the MOA for chronic exposure
, it is less clear what mediates the non

- cancer effects with the exception of

some cancer s which have mutagenic mode of action (for review see US EPA, 2011b )

.

3.3

. H UMAN 

### H EALTH 

### A SSESSMENT 

### : D OSE 

### - R ESPONSE



### Non

- cancer and cancer dose

- response assessments have been conducted by various agencies (For details, see Appendix H)

. For the non

- cancer assessments, t he se values represent exposure levels that are either not expected to result in an appreciable adverse effect ( e.g. , CalEPA REL or EPA’s reference concentration [ RfC ] ) or may represent a threshold where exposures above the value are expected to result in specific effect s ( e.g. , EPA’s AEGL

- 2 for disability) or provide guidance on chemical exposures that ma y occur during normal operations ( i.e., of spacecraft ) as well as under some emergency situations ( e.g., NASA Spacecraft Maximum Allowable Concentrations ( SMACs ; See Table 3

- 8 ) ) ( NRC, 1996 )

. NAS developed the

one

- hr SMAC a s the concentration of DCM that will not compromise the performance of specific tasks by healthy astronauts during emergency conditions or cause serious or permanent toxic effects.

For the cancer assessments, the estimated values represent published upp er

- bound 3 

### excess cancer risk from continuous exposure to a chemical at a concentration of 1 μg/m 3 

### . For

3 A plausible upper limit to the true value of a quantity, usually not a true statistical confidence limit.

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### example, if a unit risk was 2 × 10 - 6 

### per μg/m 3



### , then two excess cancer cases (upper bound estimate) would be expected to develop per 1,000,000 people if exposed daily for a lifetime to 1 μg/m 3 

### of the chemical.

The assessments conducted by the US EPA, California’s Office of Environmental Health Hazard Asse ssment (OEHHA) derived a reference exposure limit (REL)
, NA S developed the one

- hr SMAC , and the National Advisory Committee on AEGLs ( i.e.., Acute Exposure Guideline Levels for emergency response

– Appendix F) were used to derive points of departure ( PODs ) for inhalation exposures of DCM associated with its use as a paint stripper in this assessment

. The se PODs represent the concentration levels from the principal studies where uncertainty factors ( UFs ) were applied to derive specific levels of exposure ( e .g. , Cal EPA’s REL = POD ÷ UFs). For the non

- cancer portion of this assessment, the composite UFs were used as the benchmark margin of e xposure ( MOE )

. EPA developed a list of the human health toxicity values and the dose

- response assessment information that were considered relevant for this analysis of acute and chronic exposure scenarios ( Table 3

- 8)

. More extensive s ummar ies of the hazard and dose

- response information used in this assessment are provided in Appendices E and F, respectively. These data were used in conjunction with the occupational exposure and consumer monitoring data discussed in the following sections to c haracterize the potential risks to workers and residential users of DCM

containing products.

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- 8

. Worker Inhalation Health Effect Reference Values Used in the Risk Assessment

. aNon-Cancer Acute Effects Reference Value Duration Reference Value b Health Effect (Key Study) POD UFs c Additional Information Reference

AEGL

- 3 Acute, 8 hr s 7,400 mg/m 3 Absence of central nervous system ( CNS )

- related mortality in rats ( Haskell Laboratory, 1982 )
, carbox y

hemoglobin ( COHb ) formation in humans ( NRC, 2010 ) DCM concentration in rat brain of 3.01 mM and maximum of 15 percent COHb formation in huma ns Total UF = 3 UF A = 1 UF H = 3 Time scaling based on maximum DCM concentration (10, 30, and 60 min utes and 4 hr s ) or on COHb formation (8

- hr exposure) US EPA (2008 ) Acute, 4 hr s 17,000 mg/m 3

Acute, 1 hr 24,000 mg/m 3 Acute, 30 min utes 30,000 mg/m 3

Acute, 10 min utes 42,000 mg/m 3

AEGL

- 2 d Acute, 8 hr s 210 mg/m 3 Absence of CNS effects in humans ( Winneke, 1974 ) , COHb formation in humans ( NRC, 2010 ) DCM concentration in human brain of 0.137 mM and maximum of 4 percent COHb formation Total UF = 1 U F H = 1 Time scaling based on maximum DCM concentration in human brain (10 and 30 min utes ) or on COHb formation (1

- , 4

- , and 8

- hr exposure) US EPA (2008 ) Acute, 4 hr s 350 mg/m 3 Acute, 1 hr 2 , 000 mg/m 3 Acute, 30 min utes 4,200 mg/m 3

Acute, 10 min utes 6,000 mg/m 3

AEGL

- 1 Acute, 4 and 8 hr s Not recommended Not recommended because the calculated values were at

or above the corresponding AEGL

- 2 values US EPA (2008 )

Acute, 1 hr 710 mg/m 3 Absence of slight CNS effects ( Stewart et al.
, 1972 ) DCM concentration in human brain of 0.063 mM corresponding to 514 p pm at 1

- hr exposure Total UF = 3 UF H = 3 Time scaling based on maximum DCM concentration in human brain using a physiologically based pharmacokinetic ( PBPK ) model Acute, 30 min utes 800 mg/m 3

Acute, 10 min utes 1,000 mg/m 3

a These interim AEGLs have been reviewed by the National Advisory Committee on AEGLs
, but have not been finalized by the National Academies. b Conversion factor: 1 mg/m 3 = 0.28 ppm.

c UF L = LOAEL

- to

- NOAEL UF ; UF A = interspecies UF ; UF H = intraspecies UF ; UF D = UF reflecting database deficiencies. d AEGL

- 2 values are thresholds for disability and are generally considered action levels for risk in emergency response situations. They are used for consumer and worker exposure to better characterize the risk picture.

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- 8

. Worker Inhalation Health Effect Reference Values Used in the Risk Assessment

.Non-Cancer Acute Effects Reference Value Duration Reference Value a Health Effect (Key Study) POD UF b Additional Information Reference
California REL Acute, 1 hr 14 mg/m 3 Impaired performance on dual

- task and auditory vigilance tests in humans ( Putz et al.
, 1979 ) LOAEL = 688 mg/m 3 at 90 minutes or 842 mg/m 3 when time adjusted to a 60

- minute exposure Total UF = 60 UF L = 6 UF H = 10 t en B erge equation (C n xt = k, n

= 2) was used for time adjustment from 90 to 60 min utes OEHHA (2008 )

SMAC Acute, 1 hr 350 mg/m 3 CNS depression based on human observations ( Putz et al. , 1979 ; DiVincenzo and Kaplan, 1981 ; Stewart et al.
, 1972 ; Peterson, 1978 ; Andersen et al. , 1991 ; Astrand et al. , 1975 ; Ratney et al. , 1974 ; as cited in NRC, 1996 ) NOAEL = 350 mg/m 3 for 1

- hr exposure to DCM UFs were not applied to 1

- hr SMAC value 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 for CNS effects related to COHb formation) NRC (1996
, 2008 )Non-CancerChronic Effects RfC Chronic 0.6 mg/m 3 Hepatic effects (hepatic vacuolation) in rats observed in 2

- year inhalation bioassay ( Nitschke et al. , 1988a ; as cited in US EPA, 2011b ) 1 st percentile HEC: 17.2 mg/m 3 Total UF = 30 UF A = 3 UF H = 3 UF D = 3 PBPK modeling was used in the RfC derivation US EPA (2011b )

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- 8

. Worker Inhalation Health Effect Reference Values Used in the Risk Assessment

. aon Reference

Value Duration Reference Value b Health Effect (Key Study) POD UFs c Additional Information ReferenceCancer ChronicEffects I UR Chronic 1 × 10 - 5 per mg/m 3 Liver and lung cancer in male B6C3F1 mice ( Mennear et al

. , 1988 ; NTP, 1986 ; as cited in US EPA, 2011b ) Mouse BMDL 10 combined with tissue

- specific GST

internal dose metric with allometric scaling Not applicabl

e Mutagenic mode of action ; PBPK modeling and a multistage model with linear extrapolation from the POD (BMDL 10 ) US EPA (2011b )

a Conversion factor: 1 mg/m 3 = 0.28 ppm. b UF L = LOAEL UF ; UF A = interspecies UF ; UF H = intraspecies UF ; UF D = database deficiency UF

.

BMDL 10 = l ower 95 percent confidence limit of the 10 percent benchmark dose; GST = glutathione

- S

- transferase; HEC = human equivalent concentration; IUR = inhalation unit risk; LOAEL = lowest

- ob s erved

- adverse

- effect level; NOAEL = no

- observed

- adverse

- effect level; SMAC = s pacecraft maximum allowable concentration

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### 3.4

. HUMAN H EALTH 

### R ISK 

### C HARACTERIZATION



### 3.4.1. R ISK 

### E STIMATION 

### A PPROACH FOR 

### A CUTE AND 

### R EPEATED 

### E XPOSURES



### Non

- cancer risks were addressed by comparing consumer and worker exposures to levels of exposure that cause effects, or are thresholds for effects, in animals or humans as appropriate. The ratio of this comparison is an indicator of the concern level for these effects. All consumer and worker exposure scenarios resulted in exposures that were very close to, or exceeded, the threshold or effect levels for DCM. Cancer risks were calculated only for worker exposure. Cancer incidence risks were calculated by multiplying the exposure estimates by the EPA

determined cancer risk value. Cancer risks varied between levels of a few in a million to a few in a thousand. In 5 of the 7 worker exposure scenari os , the cancer risk was estimated to be more than one in a thousand.

To estimate non

- cancer acute and chronic risks, EPA calculates a margin of exposure ( MOE )
, which is the ratio of the one of the following, no

- observed

- adverse

- effect level [ NOAEL ]
, NOAE L HEC 

### , or lowest

- observed

- adverse

- effect level [ LOAEL ] or BMDL to the estimated exposure. This approach allows the reader to better understand the toxicological basis for the risks and the importance of the identified uncertainties and how they potentially affect EPA’s determination of risk. This MOE is compared to a level of concern , which is the same value as the total UF relevant to a particular toxicity study (Table 3

- 9 ). EPA’s level of concern for non

cancer effects depends on the specific scenarios assessed. MOEs that are lower than the level of concern are interpreted as potential human health risks, but do not necessarily mean that these health effects will occur. MOEs exceeding the level of concern ( i.e., total UF (UF Total 

### ) ) are interp reted as a negligible concern for adverse human health effects . Typically, the larger the MOE, the more unlikely it is that a non

- cancer adverse effect would occur.

3.4.2. R ISK 

### E STIMATION 

### A PPROACH FOR 

### A CUTE 

### E XPOSURES



### EPA chose to use the CalEPA’s REL for DCM as the basis for its acute POD to address noncancer consumer exposures. This REL was derived by applying a composite UF of 60 to a POD, based on impaired cognitive performance in acutely exposed humans ( Putz et al. , 1979 ) . EPA used this POD which was a LOAEL in a human study point of departure. This POD (688 mg/m 3 

### ) was for 90 minutes and was time adjusted to a 60

- minute using a ten Berge equation (C n 

### xt = k, n = 2) resulting in POD of 842 mg/m 3 

### . The benchmark MOE for the acute inhalation is ≥ 60 where no adverse effects would be expected. This MOE of 60 is made up of a factor of 6 accounting f or a LOAEL to NOAEL extrapolation and factor of 10 accounting for human variability

.
In addition, EPA assessed acute risks by calculating hazard quotients (HQ acute 

### ). Air concentrations of DCM may reach dangerous levels in enclosed environments when indiv iduals are using DCM

- based paint strippers for a single daily use. Thus, air concentration thresholds for disability ( i.e., typically notes for an AEGL

- 2) are compared with the estimated inhalation

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### exposure s for residential users 4 

### and other non

- user residential occupants ( e.g. , children). This risk assessment presents the AEGL derivations with their POD and UFs as a point of comparison to other hazard estimates used in the MOE appro a ches

. AEGLs represent threshold exposure limits for the general pub lic, including infants and children as well as other individuals who may be sensitive or susceptible. They are applicable for once

in

- a

- lifetime acute exposures ( i.e. , ≤24 hr s) to airborne concentrations of highly toxic chemicals typically occurring durin g emergency response situations. AEGL values are developed for three different health effect end point tiers ( i.e., discomfort = AEGL

- 1 threshold; disability = AEGL

- 2 threshold; and death = AEGL

- 3 threshold) at different durations of exposure ( i.e., 10 mi nutes; 30 minutes; one hr ; four hr s; and eight hr s).

For this a ssessment , the one

- hr AEGL

- 2 value provides a useful comparison between the threshold concentration for disability ( i.e. , AEGL

- 2) and air concentrations ( i.e. , measured or modeled) of DCM exposures to residential users and residential non

- users or bystanders (Appendix F) . Exposure levels that are estimated to be less than the one

- hr AEGL

- 2 ( i.e. , HQ <1) are not likely to be associated with DCM

- induced incapacitating effects. Howeve r, EPA expects that e xposure to levels greater than the one

- hr AEGL

- 2 ( i.e. , HQ >1) are dangerous for human health.

MOE and HQ values give some indication of the degree of risk but alone cannot give an understanding of the exposure paradigm and how it relates to the endpoints used in the risk characterization. A more complete characterization is presented in Figures 3

- 5 to 3

- 8. Figures 3

- 5 and 3

- 6 present exposures to the user for brush and spray applications respectively and their relation to the endpoints used in the risk characterization. In Figure 3

- 5 the “ spikes ” of exposure returning to a baseline in Scenarios 1, 3 and 7 represent the user applying DCM by brush in the workshop and leaving the workshop area to move to the rest of the house (ROH) while the DCM is working. The next spike is when the user returns to the workshop, removes the paint and appl ies another coat of DCM. Scenario 2 lacks the pointed spikes of exposure because it reflects the user stay ing in the workshop during the entire paint stripping process. Figure 3

- 6 tells a similar story for user exposure during spray application.

The concentrations of DCM in the workshop and the ROH are presented in Figures 3

- 7 and 3

- 8 for brush and spray application s respectively and their relation to the endpoints used in the risk characterization. The concentration of DCM in the ROH is also the exposure the non

- user or bystander experiences

.

4 A user is defined as an individual(s) applying the product such as a DIY homeowner or a professional contractor. Other residential occupants are defined as other individual(s) present in the house who are not involved in the paint

- stripping activity and are located in a house zone other than the one in which the paint

- stripping activity is taking place (see Exposure section).

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### 3.4. 3

. R ISK 

### E STIMATION 

### A PPROACH FOR 

### R EPEATED 

### E XPOSURES



### EPA chose to use the chronic POD from EPA’s DCM RfC as the basis for its non

- cancer occupational exposures. EPA’s chronic RfC for DCM was derived by applying a composite UF of 30 to a POD ; this is based on hepatic effects seen in a two

- year rat inhalation study ( US EPA 2011b ) . The benchmark MOE for the acute inhalation is ≥ 30 where no adverse effects would be expected. This MOE of 1 0 is made up of a factor of 3 accounting for interspecies extrapolation for pharmacodynamics and , a factor of 3 accounting for human variability (see uncertainty section).

L iver and lung cancer in male B6C3F1 mice ( Mennear et al. , 1988 ; NTP, 1986 as cited in US EPA, 2011b ) were identified as the basis for estimating chronic cancer risk for occupational scenarios. To estimate excess cancer risk from chronic worker exposures to DCM included in this assessment ( i.e., professional contractors, automotive and furniture refinishing, art restoration/conservation, aircraft paint stripping, and unspecified workplace setting involving immersion stripping of wood , and wood and metal paint stripping) , a cancer risk estimate was calculated. This value is a unitless 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) ( US EPA, 1989 )

. A summary of the toxicological endpoints and risk approaches used in EPA’s assessment of the hazard potential for DCM for paint stripping applications is provided in Table 3

- 9

.

Table 3

- 9 . Toxicological Endpoints and Approaches for Assessing Risks to DCM

- B ased Paint Strippers

. Exposure Scenario Concentration(s) and T ime D uration(s) U sed in

R isk A ssessment Level of

concern Toxicological Effect Risk Estimation Approach

Non

- Cancer Acute Inhalation Risks
Residential users a and non

- users b LOAEL = 842 mg/m 3 at 1 hr c from California’s acute REL dose

response assessment ( OEHHA, 2008 ) UF L = 6 UF H = 10 Total UF = 60 CNS effects MOE d

NOAEL = 350 mg/m 3 at 1 hr from SMAC’s dose

- response assessment ( NRC, 1996 , 2008 ) UF H = 10 Total UF = 10 CNS effects MOE

1

- hr AEGL

- 2 = 2,000 mg/m 3
4

- hr AEGL

- 2 = 350 mg/m 3
8

- hr AEGL

- 2 = 210 mg/m 3 from AEGL's dose

- response assessment ( US EPA, 2008 ) Hazard Quotient ( HQ ) e > 1 CNS effects HQ

Non

- Cancer Chronic Inhalation Risks
Small

- shop workers 1 st percentile HEC= 17.2 mg/m 3 (equivalent to a NOAEL) UF A = 3 UF H = 3 Liver toxicity MOE

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Page 57 from EPA RfC’s dose

- response assessment ( US EPA, 2011b ) Total UF= 1 0

Cancer Chronic Inhalation Risks
Chronic i nhalation,

s mall

- shop workers 1 × 10 - 5 per mg/m 3

EPA’s inhalation unit risk ( US EPA, 2011b ) 1 × 10 - 6 Liver and lung cancer Excess cancer risk f

a Users are assumed to be exposed to a 1

- hr single daily use. The peak

- TWA concentration for 1

- hr exposures are used in the risk analysis. b These individuals are not involved in the paint

- stripping activity and are located in a house zone other than the one in which the paint

- stripping activity is taking place. These individuals may be healthy adults , infants, children, pregnant women , or the elderly.

c Details about the health effects, PODs, UFs
, and key studies are described in Appendix F. d MOE = NOAEL, NOAEL HEC , LOAEL or BMDL (mg/m 3 ) ÷ Human Exposure Estimate (mg/m 3 ).

e HQ = Human Exposure Estimate (mg/m 3 ) ÷ 1

- hr AEGL

- 2 (mg/m 3 ). f Excess cancer risk = Human Exposure Estimate (mg/m 3 ) × IUR ( 1 × 10 - 5 per mg/m 3 ).



### 3.4. 4

. R ISK 

### E STIMATES FOR 

### N ON 

### - C ANCER 

### A CUTE 

### I NHALATION 

### E XPOSURES IN A 

### R ESIDENTIAL 

### S ETTING


### The potential risks of concern from acute DCM exposures indicate exceedances for both the MOE and HQ approaches. As presented in Table 3

- 1 0 , the acute MOEs ranged from 0.2 to 7, whereas the HQ acute 

### values for one , four , and eight hr s ranged from 0.1 to 0.8, 0.3 to 2.3, and 0.2 to 2.7, respectively (Table 3

- 1 1 ). All of these MOEs are significantly lower than the benchmark level of concern and are interpreted as potential human health risks of concern and in many cases represent exposures exceeding the PODs. Further, the HQ approach indicated the potential for incapacitating effects in some users ( i.e. , S cenarios 2, 3, 5, 6, and 7) and for

non

- users ( i.e. , S cenarios 3 and 6) exposed to DCM for four or eight hr s , but not for one

- hr
exposures , ( i.e., which is indicated by HQ>1 in bold)

. These results are presented graphically in Figures 3

- 5 to 3

- 8

.

Table 3

- 1 0 . MOEs for CNS Effects fo llowing Acute Exposure Scenarios for Consumer/ Residential Users and Non

- Users of DCM

- B ased Paint Strippers

.

Exposure Scenario Individual Maximum or P eak TWA C oncentration for 1

- hr E xposure a , mg/m 3 MOEs LOAEL=842 mg/m 3

Level of Concern MOE <60 NOAEL=350 mg/m 3 Level of Concern MOE <10 Scenario #1 Brush a pplication in

w orkshop,

c entral p arameter v alues User 220 4 2 Non

- u ser 120 7 3

Scenario #2 Brush a pplication in

w orkshop,

u pper

- e nd v alues for u ser User 1,100 0.8 0.3 Non

- u ser 210 4 2

Scenario #3 User 760 1 0.5

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w orkshop, u pper

- e nd v alues for u ser and n on

- u ser Non

- u ser 460 2 0.8

Scenario #4 Spray a pplication in

w orkshop, c entral p arameter v alues User 490 2 0.7 Non

- u ser 280 3 1

Scenario #5 Spray a pplication in

w orkshop, u pper

- e nd v alues for u ser User 1,600 0.5 0.2 Non

- u ser 310 3 1

Scenario #6 Spray a pplication in

w orkshop, u pper

- e nd v alues for u ser and n on

- u ser User 1,100 0.8 0.3 Non

- u ser 700 1 0.5

Scenario #7 Brush a pplication in b athroom, s imulation User 840 1 0.4 Non

- u ser 220 4 2



### All of the MOE and some of the HQ acute 

### risk estimates indicate a potential risk of concern to human health in residential environments where DCM vapors are released during brush

- on or spray

- on applications of DCM

- based paint strippers

.

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Page 59 Table 3

- 1 1 . Acute HQs for Residential Users and Non

- Users of DCM

- based Paint Strippers.

Exposure Scenario Individual Maximum or Peak TWA Concentration for 1

- hr Exposures a
,

mg/m 3 Maximum or Peak TWA Concentration for 4

- hr Exposures a
,

mg/m 3 Maximum or Peak TWA Concentration for 8

- hr Exposures a
, mg/m 3 Acute HQ

1

- Hr AEGL

- 2 = 2,000 mg/m 3 Level of Concern HQ >1 4

- Hr AEGL

- 2 = 350 mg/m 3 Level of Concern HQ >1 8

- Hr AEGL

- 2 = 210 mg/m 3 Level of Concern HQ >1 Scenario #1 Brush application in workshop, central parameter values User 220 120 69 0.11 0.34 0.33 Non

- user 120 82 49 0.060 0.23 0.23

Scenario #2 Brush application in workshop,
upper

- end values for user User 1,100 420 220 0.55 1.2 1.0 Non

- user 210 140 82 0.11 0.40 0.39

Scenario #3 Brush application in workshop, upper

- end values for user and non

- user User 760 560 400 0.38 1.6 1.9 Non

- user 460 380 290 0.23 1.1 1.4

Scenario #4 Spray application in workshop, central parameter values User 490 270 150 0.25 0.77 0.71 Non

- user 280 190 110 0.14 0.54 0.52

Scenario #5 Spray application in workshop, upper

- end values for user User 1,600 620 330 0.80 1.8 1.6 Non

- user 310 200 120 0.16 0.57 0.57

Scenario #6 Spray application in workshop, upper

- end values for user and non

- user User 1,100 810 580 0.55 2.3 2.8 Non

- user 700 580 430 0.35 1.7 2.0

Scenario #7 Brush application in bathroom, simulation User 840 560 350 0.42 1.6 1.7 Non

- user 220 190 150 0.11 0.54 0.71

a These are the user’s personal

- concentration results reported in the Exposure assessment and reflect temporary relocation of the user to Zone 2 rest of house ( i.e. , ROH) during wait times between applying and scrapping the DCM

- based paint stripper.

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- 5 . Comparison of Acute Toxicity Values and User Exposures during Brush Application in a Residential Workshop. 0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #2: Exposure Concentrations for User during Brush Application in Workshop,

Upper

- End Values for User

User Personal Concentration California acute REL

Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality)

0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #7: Exposure Concentrations for User during Brush Application in Bathroom, Simulation

User Personal Concentration California acute REL

Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality) 0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #1: Exposure Concentrations for User during Brush Application in Workshop, Central Parameter Values

User Personal Concentration California acute REL

Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality)

0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #3: Exposure Concentrations for User during Brush Application in Workshop, Upper

- End Values for User and Non

- User

User Personal Concentration California acute REL

Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality)

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Page 61 0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #5: Exposure Concentrations for User during Spray Application in Workshop, Upper

- End Values for User

User Personal Concentration California acute REL

Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality)

0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #6: Exposure Concentrations for User during Spray Application in Workshop, Upper

- End Values for User and Non

- User

User Personal Concentration California acute REL

Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality) 0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #4: Exposure Concentrations for User during Spray Application in Workshop, Central Parameter Values

User Personal Concentration California acute REL

Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality)

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- 6

. Comparison of Acute Toxicity Values and User Exposures during Spray Application in a Residential Workshop.

Figure 3

- 7 . Comparison of Acute Toxicity Values and Zone

- Specific DCM Concentrations for Brush Application in Residential Workshop or Bathroom. 0.01 0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #2: Zone

- Specific Concentrations during Brush Application in Workshop, Upper

- End Values for User Zone 1 (Workshop)
Zone 2 (ROH)

California acute REL
Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality)

0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #7: Zone

- Specific Concentrations during Brush Application in Bathroom, Simulation Zone 1 (Source Cloud)
Zone 2 (Bathroom)
Zone 3 (ROH)

California acute REL
Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality) 0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #1: Zone

- Specific Concentrations during Brush Application in Workshop, Central Parameter Values Zone 1 (Workshop)
Zone 2 (ROH)

California acute REL
Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality)

0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #3: Zone

- Specific Concentrations during Brush Application in Workshop, Upper

- End Values for User and Non

- User Zone 1 (Workshop)
Zone 2 (ROH)

California acute REL
Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality)

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- 8 . Comparison of Acute Toxicity Values and Zone

- Specific DCM Concentrations for Spray Application in Residential Workshop. 0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #5: Zone

- Specific Concentrations during Spray Application in Workshop, Upper

- End Values for User Zone 1 (Workshop)
Zone 2 (ROH)

California acute REL
Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality)

0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #6: Zone

- Specific Concentrations during Spray Application in Workshop, Upper

- End Values for User and Non

- User Zone 1 (Workshop)
Zone 2 (ROH)

California acute REL
Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality) 0.01

0.1

1 10 100 1000 10000 100000

0 1 2 3 4 5 6 7 8DCM Concentration (mg/m3)

Time (Hours) Scenario #4: Zone

- Specific Concentrations during Spray Application in Workshop, Central Parameter Values Zone 1 (Workshop)
Zone 2 (ROH)

California acute REL
Adjusted SMAC

AEGL

- 1 (Detectability)

AEGL

- 2 (Disability)

AEGL

- 3 (Lethality)

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### 3.4. 5

. O CCUPATIONAL 

### R ISK 

### E STIMATES FOR 

### C HRONIC 

### I NHALATION


### For occupational chro nic inhalation concerns, t he MOEs calculated for small

- shop workers handling DCM

- based pai nt strippers are shown in Table 3

- 1 2

. For t he risk calculations , EPA

assume d that the worker is exposed for eight hr s/day, 250 days/y ea r , for a working lifetime of 40 y ea rs. The ranges of MOEs for the different industries indicate potential risks of concern ( i.e. , the industry based MOE were below the benchmark MOE 1 0) with two exception s, the lower end exposures for furniture refinishing and the art restoration industry ha d a low concern for non

- cancer risks based on an MOE of 31 and 38 , respectively

.

Table 3

- 1 2 . Occupational Risks for Repeated Exposures to DCM from Paint Stripping Activities

.

Industry Range of 8

- hr TWA Exposures (mg/m 3 ) a ADC (mg/m 3 ) b LADC (mg/m 3 ) b Range of Chronic MOEs c NOAEL = 17.2 mg/m 3

Level of Concern MOE < 1 0 Range of Inhalation Cancer Risks

Professional

c ontractors 60

- 2,980 14

- 680 7.8

- 390 1

- 0.03 e 8 × 10 - 5

- 4 × 10 - 3

Automotive

r efinishing 90

- 416 21

- 95 12

- 54 0.8

- 0.18 1 × 10 - 4

- 5 × 10 - 4

Furniture

r efinishing 2.4

- 1,270 0.55

- 290 0.32

- 170 31

- 0.059 3 × 10 - 6 f

- 2 × 10 - 3

Art r estoration and c onservation d 2 0.46 0.26 37 3 × 10 - 6 f

Aircraft p aint

s tripping 86

- 3,802 20

- 870 11

- 500 0.86

- 0.020 1 × 10 - 4

- 5 × 10 - 3

Unspecified

w orkplace s etting: i mmersion

s tripping of w ood 35

- 7,000 8.0

- 1,600 4.6

- 910 2.2

- 0.011 5 × 10 - 5

- 9 × 10 - 3

Unspecified

w orkplace s etting:

w ood and m etal p aint s tripping 633

- 1,017 150

- 230 83

- 130 0.12

- 0.074 8 × 10 - 4

- 1 × 10 - 3

a These exposures include 8

- hr TWA exposures that were either directly measured or calculated from shorter time frame exposures by the study authors. b ADC s and LADC s are calculated from 8

- hr TWA exposures reported in the exposure assessment (Section 3 , Table 3

- 3 ). Conservative exposure assumptions are used in the ADC and LADC calculations: 8 hr s/ day, 250 days / year for 40 years.

c MOEs are calculated by dividing the POD for chro n ic liver toxicity ( US EPA, 2011b ) (17.2 mg/m 3 or HEC ) by the ADCs. There is a risk concern when MOE < UF Total = 30. d The data point provided for this industry was obtained from OSHA IMIS. No other literature data were obtained.

e Bolded values indicate that the MOE or excess cancer risks were exceeded. f Italicized values indicate a marginal concern for excess cancer risk.

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## 3.5

. D ISCUSSION OF 

## K EY 

## S OURCES OF 

## U NCERTAINTY AND 

## D ATA 

## L IMITATIONS



### This section contains discussion of key uncertainties and data limitation s for three main topics of the assessment:

• Occupational Exposure Estimates,

• Consumer Exposure Estimates, and

• Toxicity and Risk Assessment.

**3.5.1.** K EY 

### U NCERTAINTIES AND 

### D ATA 

### L IMITATIONS FOR 

### O CCUPATIONAL 

### E XPOSURE 

### E STIMATE S


### The principal limitation of the worker exposure data is the uncertainty in the representativeness of the data. EPA reviewed a number of published exposure studies with inherent data limitations including: number of facilities, job sites, or residences; most often
, limited number of sites investigated. This reduced information sampling pool introduces uncertainty and precludes EPA from asc ertaining whether the observed data are fairly representative of the broad array of possible sites at all geographic locations across the US and for all workers within the particular end

- use application. The level of exposure to DCM during stripping processes depends highly on the use of adequate engineering controls ( i.e. , general and local exhaust ventilation systems ) and work practices as seen by the range of exposure data ( TNO, 1999 )

. Therefore, these differences can limit the representativeness of any one site with regards to all sites within the specific end

- use application

. As a result of these uncertainties
, th e actual exposure distributions are unknown; the assumed central tendency and high

- end exposures may , or may no t , fall within the range of exposures estimated for this assessment.

An additional data limitation for occupation exposure estimation is the age of the identified exposure studies. Most of the exposure studies were conducted in the 1990 s, with some pre

dating the 1990 s; some studies were more recent. Some references have discussed a trend to reduce the use of DCM in paint stripping products ( i.e., OSHA promulgated new exposure limits for DCM in 1997 )

. T hese factors can limit the representativeness of 1 990 and older data with regards to present day workplace conditions and exposures. As a result of these uncertainties , it is not known
, but it is possible
, that actual exposure distributions could be declining during the monitoring period considered in th is assessment.

The OSHA IMIS data have the same data limitations as discussed above for the published occupational exposure studies. IMIS data also have additional data limitations to consider. Whereas most exposure studies provide information on the in vestigated site, engineering controls, and working activities, this is not the case for IMIS data

. The IMIS data include only a brief description of the monitored worker activity , but do not provide information on whether the activity involved chemical paint stripping ( i.e., particularly using DCM )

. Therefore, the relevance of IMIS data to exposures that occur from DCM

- based paint stripping is uncertain ; EPA cannot draw conclusions about worker exposures within the art restoration and conservation uses based upon the IMIS data . As a result, central tendency and high

- end

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Page 66 

### exposures may be above or below the estimated exposure s for these industries in this
assessment

. Lack of certainty in the identity of activities that are sources of exposures of DCM can make risk determinations more difficult

. DCM can be used in both paint strippers and paints and coatings. This leads to a recognized uncertainty when evaluating data for certain industries. When evaluating OSHA IMIS data or other release and exposure information, unless the worker activity or release source specifically cites paint stripping activities, it is not known whether reported data are representative of paint stripping activities or might also include other activities such as surface coating. The same uncertainty holds for data for painting and wall covering contracting (NAICS 2383 20), flooring contracting (NAICS 2383 30), automotive body, paint, and interior repair and maintenance (N AICS 8 1112 1), and reupholstery and furniture repair (NAICS 8 1142 0) industries . T hese industries are expected to conduct both paint stripping and surface coating activities ; the extent of use for DCM

- containing paints and coatings in these industries is un known. It also should be noted that exposures also may be overestimated if DCM sources other than paint stripping products were present ( i.e., and not accounted for) during air monitoring.

A ssumed values for s everal parameters use d in the equation to estimate ADCs and LADCs introduce additional uncertainties. Exposure frequencies are assumed to be 250 days / year (every work day) and the number of working years per lifetime is assumed as 40 years, which seems likely to be a high

- end estimate. As a result of these uncertainties
, some exposures in this assessment will be overestimated for workers who are not exposed each work day or for their full working career.

3.5.2. K EY 

### U NCERTAINTIES AND 

### D ATA 

### L IMITATION S FOR 

### C ONSUMER 

### E XPOSURE 

### E STIMATES



### The inhalation exposure assessment is composed of modeled exposure scenarios for which the inputs are based on experimental data, survey information
, and a number of assumptions with varying degrees of uncertainty. The results are characterized as either plausible estimates of individual exposure, i.e. , central tendency, or possibly greater than the distribution of actual
exposures, i.e. , bounding.

The extent of the uncertainties identified below is not known, so the 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 avai lable consumer products, as identified in Brown (2012 )

. However, these values were not weighted by percent market share. Similarly, there is a high degree of confidence in the values chosen to represent the house volume and air exchange rate, as they are based on scientifically defensible data cited in the EPA’s Exposure Fac tors Handbook ( EFH ) ( US EPA, 2011c )

. The confidence level is similarly high for the amount of product applied and application rates, with data ties to surveys cited in the EFH as well as experiments conducted by US EPA (1994b )

. For the stripping sequence , the wait

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### time per segment has a high level of confidence because the time is based on what is shown on current product labels. The appli cation and scraping times have a slightly lower confidence level because they are based on the US EPA (1994b ) study, which only included a limited number of experiments

. High

- quality US EPA (1994b ) 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 F, F

- 1. Estimation of Emis s ion Profiles for Paint Removers/Strippers ), but the re were only a few cases on which the estimates were based.

Given the potential variability across paint stripping scenarios for estimating consumer exposure , not only for airflow rates but also for factors such as amount of product used, 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. Therefore, in this case , the general term “upper

- end”

— instead of more definitive descriptors,
e.g. , high

- end

— was used to characterize plausible exposure values greater than central tendency; the more definitive descriptors would imply an inappr opriate level of accuracy.

T he bathtub stripping scenario is an occupational exposure for the user that was modeled to estimate potential exposures for residential non

- users occupying the rest of the house (ROH) during bathtub refinishing in the home . Gi ven the model’s sensitivity of concentrations in the ROH to room

- of

- use ACH and interzonal air flow, there is uncertainty about the likelihood that a

non

- user would be exposed to this scenario’s ROH concentrations ; thus
, EPA characterized the

non

- user exposures as upper

- end to bounding.

3.5.3. U NCERTAINTIES IN THE 

### H AZARD AND 

### R ISK 

### A SSESSMENT


### The human health risk assessment is based on toxicity values that considered human and animal data in their derivations.

Single occupational exposure scenario risk s were assessed by comparing the exposures to the California REL, National Research Council ( NRC ) Spacecraft Maximum Allowable Concentration ( SMAC )
, and AEGL

- 2 levels. The California REL was the most conservative acute p oint of departure estimate for non

- cancer effects because it assessed a level that would not cause effects in the general population as opposed to the SMACs that assess risk to healthy adults working in a very specif i c occupational context of operating a spacecraft

.

T he absence of data o n susceptible populations and the NOAEL, EPA used default or modified default values to calculate acceptable MOE values. N eurotoxicity in adults was the endpoint used to derive the POD ; it is possible that younger ages may respond differently (in terms of dose, magnitude or response, or different response). Thus, the MOEs presented for acute consumer exposure scenarios in Tab le 3

- 10 may under

- estimate risk to younger age groups for this endpoint.

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### T he chro nic non

- cancer risk for exposure scenarios were assessed using the POD 

### from the US EPA (2011b ) IRIS 

### derivation of an inhalation RfC value. A n acceptable MOE was informed by the
uncerta in ty analysis developed for the IRIS assessment.

The inhalation database for DCM includes several well

- conducted chronic inhalation studies. In these chronic exposure studies, the liver was identified as the most sensitive noncancer target organ in rats (Nitschke et al ., 1988a; NTP, 1986; Burek et al ., 1984). The critical effect of hep atocyte vacuolation was corroborated in the principal study (Nitschke et al ., 1988a) and in a supporting study (Burek et al ., 1984), both of which identified 500 ppm as the lowest inhalation LOAEL for noncancer liver lesions.

Uncertainty in extrapolating from laboratory animals to humans (UF A 

### ) wa s reduced because EPA used PBPK model ing to extrapolate internal doses from rats to humans ; thus, reduc ing toxicokinetic uncertainty in extrapolati o n from the rat liver lesion data

. However , this use of PBPK modeling does not account for the possibility that humans may be more sensitive than
rats to DCM due to toxicodynamic differences. An UF of 3 to account for this toxicodynamic uncertainty was employed in the MOE

. Uncertainty about vari a bility in the average humans to more sensitive humans (UF H 

### ) is accounted for partially in t he probabilistic human PBPK model used in this assessment because it incorporates the best available information about variability in toxicokinetic disposition of d ichloromethane in humans
, but does not account for humans who may be sensitive due to toxicodynamic factors. Thus, an UF of 3 was employed in the MOE to account for possible such differences in sensitive humans.

Uncertainty in extrapolating from LOAELs t o NOAELs (UF L 

### ) was not employed in the MOE because BMD modeling was used to determine the POD, and this factor was addressed as one of the considerations in selecting the bench mark response ( BMR ) . The BMR was selected based on the assumption that it represents a minimum biologically significant change.

There is an additional potential concern for immunological effects as suggested by a single acute inhalation study, specifically immunosuppressiv e effects that may be relevant for infectious diseases spread through inhalation.

The POD is based on results from a chronic

- duration inhalation toxicity study such that no UF is
necessary. T he uncertainties associated with th is derivation of the choice of this POD for chronic noncancer outcomes and the cancer assessment are discussed more extensively in the US EPA (2011b ) document. I t is interesting to note that the calculated MOE values are often one to two orders of magnitude below the acceptable benchmark MOE

.

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### 3.5.4. C ONCLUSIONS OF 

### U NCERTAINTIES AND 

### L IMITATIONS



### EPA reviewed a number of published exposure studies with inherent data limitations including: number of facilities, job sites, or residences; most often, only a single site was investigated. This limited sampling pool introduces uncertainty and precludes EPA from ascertaining wh ether the observed data are fairly representative of the broad array of possible sites at all geographic locations across the US and all workers within the particular end

- use application. The level of exposure to DCM during stripping processes depends hig hly on the use of adequate engineering controls ( i.e. , general and local exhaust ventilation systems) and work practices as seen by the range of exposure data ( TNO, 1999 ) . Therefore, these differences can limit the representativeness of any one site with regards to all sites within the specific end

- use application. The result of these uncertainties is that actual exposure distributions are unknown; central tendency and h igh

- end exposures may, or may not, fall within the range of exposures estimated for this assessment. It also should be noted that exposures may be overestimated if DCM sources other than paint stripping products were present ( i.e., and not accounted for) during air monitoring.

The re is gen e ral confidence in the characterization of the hazard datab a se for acute and chronic effects used for the points of departure. However
, there is residual uncertainty i n do m ains of the hazard cha racterization for some outcomes

. These uncertaint ies are drawn from concern for potential developmental neurotoxicity and immunological effects as suggested by the modes of action affecting the nervous system both CNS depression and COHb and indications from acute inhalation st udy, specifically immunosuppressive effects that may be relevant for infectious diseases spread through inhalation.



## 3.6

. R ISK 

## C HARACTERIZATION 

## C ONCLUSIONS



### In this assessment, EPA focused on DCM use as a paint stripper in the home and in small commercial shops. Exposures of concern were by the inhalation route.

Non

- cancer risks were addressed by comparing consumer and worker exposures to levels of exposure that are known to cause effects, or are identified as thresholds for effects, in animals or humans . The ratio of this comparison serves as an indicator of EPA’s level concern for these effects. All consumer and worker exposure scenarios resulted in exposures that were very close to, or exceeded, the threshold of effect levels for DCM. Cancer risks w ere calculated only for worker exposure. Cancer incidence risks were calculated by multiplying the exposure estimates by the EPA cancer risk value. Cancer risks varied between levels of a few in a million to a few in a thousand. In 5 of the 7 worker exp osure scenarios the cancer risk was estimated to be a few in a thousand.

The assessment of consumer inhalation exposures found a potential risk of concern for human health in residential environments where DCM vapors are released during brush

- on or spray

- on applications of DCM

- based paint strippers. The POD for the acute hazard scenarios is based

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Page 70 

### upon impaired cognitive performance in humans ( Putz et al. , 1979 )

. 

### All of the MOE and some of the HQ acute 

### risk estimates ( i.e., acute non

- cancer inhalation exposures) indicate a potential risk of concern to human health in residential environments, for both users and non

- users, where DCM vapors are released during brush

- on or spray

- on applications of DCM

- based paint strippers

. 

### This conclusion is based on workplace air monitoring data and a modeling

- based approach employed to estimate acute inhalation exposures to residential users and non

- users.

Chronic worker inhalation exposure estimates were developed from published monitoring studies and modeled exposure estimates. The non

- cancer risk s of concern of these exposures was determined by comparing them to the POD which was based on a HEC developed from histopathological changes in the liver of rodents resulting from chronic inhalation ( US EPA, 2011b ) . The M OE calculations for specific use scenarios were compared to MOE for chronic and acute benchmarks.

EPA’s assessment found potential non

- cancer and cancer risks of potential concern for workers and non

- cancer risks for residential users and non

- users ( e. g. , children) who use DCM

- based paint strippers. MOEs indicate that there are potential risks of potential concern for occupational non

- cancer risks associated with exposures to DCM

- based paint strippers in the following industries: professional contract ors, aircraft paint stripping, workplace settings doing immersion stripping of wood, and wood and metal paint stripping.

For occupational chronic inhalation concerns, the MOEs for small

- shop workers handling DCM

based paint strippers were calculated. The ranges of MOEs for the different industries were below the level of concern ( i.e. , 1 0) with the following exception s ; some fur n iture refinishing and art restoration industry scenarios which had a low concern for non

- cancer risks based on MOE’s ranging from 31

- 38 derived from lower exposure scenarios

.

EPA determined that the probability of developing cancer ( i.e., chronic cancer risks) in all occupational scenarios was above 1 × 10 - 6 

### , with the exception of the estimates for the art restoration industry and some furniture refinishing scenarios with lower exposures , which indicated a marginal concern at 3 × 10 - 6 

### (Table 3

- 1 2 ).

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# Appendices

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### Appendix A: Summary of Environmental Effects

- Aquatic Toxicity

Acute Toxicity to Fish 

### Fathead minnows ( Pimephales promelas ) were exposed to unspecified measured concentrations of DCM under flow

- through conditions for 96 hours. A 96

- hour 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 flow

- through conditions for 96 hours. A 96

- hour LC 50 

### of 193 mg/L w as reported ( Alexander et al. , 1978 )

. Fathead minnows ( P. promelas ) were exposed to unspecified nominal concentrations of DCM under static conditions for 96 hours. A 96

- hour LC 50 

### of 310 mg/L was reported ( Alexander et al. , 1978 )

. Fathead minnows ( P. promelas ) were exposed to unspecified measured concentrations of DCM under flow

- t hrough conditions for 96 hours. A 96

- hour 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

- through conditions for 96 hours. A 96

- hour LC 50 

### of 502 mg/L was reported ( Dill et al. , 1987 )

. Sheepshead minnows ( Cyprinodon variegates ) were exposed to unspecified nominal concentrations of DCM under static conditions for 96 hours. A 96

- hour LC 50 

### of 330 mg/L was reported ( Heitmuller et al. , 1981 )

. Zebrafish ( Danio reio ) we re exposed to unspecified concentrations of DCM under unspecified conditions for 96 hours. The 96

- hour LC 50 

### of 254 mg/L was reported ( Roderer, 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 )

.
Chronic Toxicity to Fish 

### Fathead minnows ( P. promelas ) were exposed to measured concentrations 29, 55, 82, 142, 209, and 321 of DCM under flow

- through conditions for 28 days. The 28

- day lowest

- observed

- effect concentration (LOEC) ranged between 82.5 and 142 mg/L and a maximum acc eptable toxicant concentration (MATC) of 108 mg/L was reported ( Dill et al. , 1987 )

.
Acute Toxicity to Aquatic Invertebrates 

### Water fleas ( Da phnia magna ) were exposed to unspecified nominal concentrations of DCM under static conditions for 48 hr s. A 48

- hr EC 50 

### of 1,682 mg/L was reported ( Kühn et al. , 1989 )

.

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### 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 nomina l concentrations of DCM under static conditions for 48 hr s. A 48

- hr EC 50 

### of 220 mg/L was reported ( LeBla nc, 1980 )

. Opossum 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 ( Syracuse Res. Corp., 1978 )

.
Toxicity to Aquatic Plants 

### Green algae ( Pseudokirchneriella subcapitata ) 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 ( US EPA, 1978 )

. Diatoms ( Skeletomema costatum ) were exposed to unspecif ied nominal concentrations of DCM under static conditions for 96 hr s. A 96

- hr EC 50 

### of 662 mg/L was reported ( Syracuse Res. Corp., 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 )

.

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### Appendix B: Inventory Update Reporting Rule Data for DCM

The following information comes from EPA’s Inventory Update Reporting Rule public database for the 2006 reporting cycle ( US EPA, 2006a )

.

Table B

- 1. Manufacturing and Importing Company and Site Information for DCM. Company Site City State Zip Code Manufacture Import Basic Chemicals Company, LLC Basic Chemicals Co

- Geismar Geismar LA 70734 Yes No

Basic Chemicals Company, LLC Basic Chemicals Co

- Wichita Plant Wichita KS 67215 Yes No

Chemcentral Corporation Chemcentral International Pompano Beach FL 33069 No Yes

E. I. du Pont de Nemours and Company Dupont

- Headquarters (imported centrally through broker) Wilmington DE 19898 No Yes

Ineos Chlor Americas, Inc. Ineos Chlor Americas, Inc Wilmington DE 19810 No Yes

Petrochem Americas LLC Petrochem Americas LLC Plano TX 75093 No Yes

TR International, Inc. TR International Inc

- Seattle Seattle WA 98101 No Yes

The Dow Chemical Company Dow Chemical

- Freeport, TX Freeport TX 77541 Yes No

The Dow Chemical Company Dow Chemical

- Pittsburg, CA Pittsburg CA 94565 Yes No

The Dow Chemical Company Dow Chemical

- Headquarters Midland MI 48674 No Yes

The Dow Chemical Company Dow Chemical

- Plaquemine Plaquemine LA 70764 Yes No

Vulcan Materials Company Vulcan Materials Co

- Wichita Plant Wichita KS 67215 Yes No

Vulcan Materials Company Vulcan Materials Co

- Geismar Plant Geismar LA 70734 Yes No

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### Appendix C: Household Products Data for DCM

The following information comes from NIH’s Household Products Database.

Table C

- 1. Household Products Containing DCM from NIH’s Household Products Database.
Brand Category Form Percent DCM
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

- 70

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 Choke 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 Paint Remover Home maintenance Liquid 75

- 85
Klean

- Strip Premium Stripper, Aerosol Home maintenance Aerosol 70

- 95
Klean

- Strip Deep Down Stain Stripper

- old product Home maintenance Aerosol <60
Zinc It Electric Grade Lubricant Home maintenance Aerosol 32

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- 1. Household Products Containing DCM from NIH’s Household Products Database.
Brand Category Form Percent DCM Savogran Kutzit Paint & Varnish Remover

- old product Home maintenance Liquid > 24

Champion Sprayon Paint Off Home maintenance Aerosol 80

– 85 Sprayway Vandalism Mark and Stain Remover No. 870 Home maintenance Aerosol 43

Zinsser Adhesive Remover Home maintenance Liquid 71
Crown Solu

- Strip Semi

- Paste Adhesive Remover Home maintenance Liquid 80

- 90
Crown Handi

- Strip All Purpose Sprayable Stripper, Aerosol Home maintenance Aerosol 45

- 60

Savogran Adhesive Remover Home maintenance Liquid 85

- 90 Savogran Paint Stripper, Aerosol Home maintenance Aerosol 25

- 30 Savogran Heavy Duty SuperStrip Home maintenance Liquid 85

- 90
Klean

- Strip Brush Cleaner Home maintenance Liquid 1

- 3
Klean

- S trip KS

- 3 Premium Stripper Home maintenance Liquid 60

- 100
Klean

- Strip Premium Sprayable Stripper Home maintenance Liquid 70

- 85
Klean

- Strip Strip

- X Stripper Home maintenance Liquid 30

- 50
Ja sco Semi

- Paste Varnish & Stain Remover Home maintenance Liquid 25

- 40
Klean

- Strip Graffiti Remover

- old product Home maintenance Aerosol 75

- 80 Savogran Strypeeze Paint/Varnish Remover

- old product Home maintenance Liquid >10

Parks Pro Liquid Paint Stripper

- discontinued Home maintenance Liquid 40

- 90 Paint & Varnish Remover No. 2600, Aerosol Home maintenance Aerosol
Klean

- Strip Adhesive Remover Inside the home Liquid 60

- 100 Aqua Mix Sealer and Adhesive Remover

- old product Inside the home Liquid

Parks Adhesive Remover

- discontinued Inside the home Liquid 40

- 90 Radio Shack Rosin Flux Stripper Inside the home Liquid 39.83
Parks Adhesive Remover

- 09/04/1998

- discontinued Inside the home Liquid 65

- 70

Monsanto Amplify Herbicide (agricultural) Pesticides Granules <16

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### Appendix D : Paint Stripping Processes and Associated Worker Activities, and Facility and Population Data and Information

This appendix presents background information related to the analysis of worker exposures.


## Descriptions of Processes and Activities Techniques for paint stripping typically include manual coating, tank dipping, and spray application ( TNO, 1999 ) . Pouring, wiping, and rolling are also possible application techniques, and application can be manual or automated ( ECHA, 2011 ) . An i ndividual’s exposure to paint stripping chemicals greatly depends on control measures taken and work practices adopted ( TNO, 1999 ) . The following sections summarize processes and activities for the industries found to employ paint stripping.

Paint Stripping By Professional Con tractors 

### 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 tha t commonly range from one liter up to five gallons, although they may also purchase consumer paint stripper products from hardware stores. Stripper is typically applied to wall or floor surfaces using a hand

- held brush. Strippers used in these applicatio ns often have a high viscosity since they can be applied to vertical surfaces. After application, the stripper is allowed to set and soften the old coating. Once the stripper has finished setting, the old coating is removed from the surface by scraping

a nd brushing. During wood floor stripping, old coating and stripper may also be removed using an electric floor buffer. After the old coating is removed, the surface is wiped clean before moving to the next stages of the job. The stripping process is oft en completed on an incremental basis with treatment for one section of wall or flooring being completed before moving to the next section ( EU, 2007b ; IRTA, 2006 ; NIOSH, 1993 ; TNO, 1999 )

. Professional contractors may also be employed to refinish or reglaze bathtubs. Various health case studies have noted the use of DCM

- based strippers during bathtub refinishing or reglazing ( CDC, 2012b
, a ; MSU/MIFACE, 2011 ) . Case studies have identified professional bathtub refinishers that repaire d and resurfaced countertops, tubs, and sinks in both apartment buildings and private homes ( CDC, 2012a ; MSU/MIFACE, 2011 ) . The OSHA IMIS data identified a single OSHA inspection in 2007 of two bathtub reglazers. The bathtub reglazers’ company

w as identified under NAICS code 811420

– Reupholstery and Furniture Repair ( OSHA, 2012 )

. However, this assessment discusses bathtub reglazing in the context of professional contractors, as professional contractors and professional bathtub refinishers or reglazers are both expected to perform their work at customer si tes (for example, in the cited case studies of bathtub refinishers/reglazers, apartment buildings, and private homes). This professional
contractor

- type work differs from furniture refinishing, which typically entails the refinishing of customer furniture at fixed furniture refinishing facilities.

A case study has indicated that bathtub refinishing or reglazing can involve a worker pouring and brushing stripper onto a bathtub using a paintbrush. The worker then scrapes the finish

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### from the bathtub after l eaving the stripper in contact with the bathtub for 20 to 30 minutes ( CDC, 2012a ; MSU/MIFACE, 2011 ) . This case study has noted a stripper DCM concentration of 60 to 100 percent ( CDC, 2012a ; MSU/MIFACE, 2011 ) ; however, multiple health case studies have noted the use of aircraft and marine coating remover in bathtub refinishing/reglazing ( CDC, 2012b )

.
Paint Stripping at Automotive Body Repair and Maintenance Shops 

### Automotive refinishing shops apply coatings to motor vehicles subsequent to the original manufacturing process. The overall refinishing process typically involves the following steps:

• St ructural repair;

• Surface preparation (cleaning and sanding);

• Primer coat mixing;

• Spray application of primer coat;

• Curing;

• Sanding;

• Solvent wipe

- down;

• Topcoat (basecoat color and clearcoat) mixing;

• Spray application of topcoat; and

• Curing.

The surface preparation step of the refinishing process involves:

“removing residual wax, grease, or other contaminants from the surface to be painted, to ensure adhesion of the new coating. The new coating may be applied over an existing coating if it is free of c hips or cracks after it has been roughened through sanding. Alternatively, the previous coating may be removed using a mechanical method ( e.g. , sanding) or a paint

- removing solvent. After the coating is roughened or removed, the surface is typically wipe d down with a solvent

- or water

- based surface preparation product” ( OECD, 2010 )

.
Wood Furniture Stripping 

### During furniture stripping, paint stripper may be applied to the furniture by either dipping the furniture in an open tank containing the stripper, brushing or spraying the stripper onto the furniture surface, or manually applying the stripper. Larger facilities may pump the stripper through a brush. The application method depend s on the size and structure of the furniture as well as the capabilities of the facility. The application area typically has a sloped surface to allow for collection and recycling of unused stripper. Larger facilities use a flow tray to apply the strippe r to parts. The flow tray is a sloped, shallow tank with a drain at the lower end. After application, the stripper is left to soak on the furniture surface to soften the surface coating. Once soaking is complete, the unwanted coating is scraped and brus hed 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 wa ter may contain oxalic acid to

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### brighten the wood surface. Wash water is collected and either recycled or disposed of as waste. After washing, the furniture is transferred to a drying area where it is allowed to dry before being transferred to other refin ishing processes ( e.g. , sanding, painting, reupholstery) ( HSE, 2001 ; IRTA, 2006 ; NIOSH, 1990 , 1992 )

. 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 p art long enough to strip the coating ( IRTA, 2006 )

.
Figure D

- 1 shows a typical flow tray used by larger furniture strippers to apply stripper to furniture parts, obtained from Cal EPA (2006 ) . Figure D

- 2 shows a typical water wash booth used to wash stripper and coating residue from stripped furniture, obtained from IRTA (2006 )

. Figure D

- 3 shows an example diagram of a dipping tank for furniture stripping complete with local exhaust ventilation, obtained from HSE (2001 )

.

Source: IRTA (2006 )

.
Figure D

- 1. Typical Flow Tray for Applying Stripper to Furniture.

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.
Figure D

- 1 . Typical Water Wash Booth Used to Wash Stripper and Coating Residue from Furniture.

Source: HSE (2001 )

.
Figure D

- 2 . Example Diagram of a Dippi ng Tank for Furniture Stripping.

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### Art restoration and conservation can include the care and maintenance of paintings to reverse negative effects of aging and dirt accumulation. It can also include repairing paintings that have suffered paint loss, weakened canvas, tears, water damage, fire damage, and insect damage ( Smithsonian, 2012b ) . Art restoration and conservation can include paint cleaning, which can entail removing dirt and other obscuring material, removing varnish, or removing overpaint while maintaining the original layer of paint ( Smithsonian, 2012a ) . These activities can involve the use of paint strippers. Although paint strippers used in this field can contain DCM, the use of DCM is not always favored, as DCM can penetrate through the overpaint layer that is being removed and into the original paint layer that is being conserved. N

- Methylpyrrolidone (NMP) may serve as a suitable substitute for DCM in strippers used in this field ( Wollbrinck, 1993 )

. More detailed information on the use of paint strippers in art restoration and co nservation was not identified. It is anticipated that paint strippers are applied manually in this field.

Aircraft Paint Stripping 

### During aircraft paint stripping, paint stripper is pumped from bulk storage containers and applied to the body of the aircr aft using hoses. Once the paint stripper has been applied, it is allowed to set for a certain period of time (usually about 30 minutes) to allow the paint to soften. Once setting is complete, the stripper and loose paint are scraped down into a collectio n area. Any remaining stripper and paint residue are then brushed away with water and brushes. Once the surface of the aircraft has dried, a new layer of primer, paint, and top coat are applied ( NIOSH, 1977 )

.
Ship Paint Stripping 

### Process description information for paint stripping of ships has not been identified. It is antici pated that paint stripping of ships may involve similar processes as the paint stripping of aircraft.

Respiratory Protection 

### If respiratory protection is required, OSHA requires supplied

- air respirators, as air

- purifying respirators do not provide adequat e respiratory protection against DCM ( OSHA, 1997b ) . Of the 13 MSDSs for paint strippers obtained through the literature search, 10 of the MSDSs were for DCM

- containing paint strip pers. Eight of the 10 MSDSs recommended a NIOSH

- approved, self

contained breathing apparatus or air

- supplied respirator if respiratory protection is required. One MSDS recommends NIOSH

- approved respiratory protection for organic solvent vapors, which may include the use of supplied air. The remaining MSDS only recommends a NIOSH

approved respirator for organic solvent vapors without further specification of the respirator type ( WM Barr, 2008 , 2009a , b
, c , 2010a , b , 2011a , c , b , 2012 )

. 

## Facility and Worker Population Data This section summarizes data on the number of establishments, number of paid employees and workers, and production hr s and work day estimates (for manufacturing industries). Some of

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### these data are useful for determining the average number of workers per e stablishment, which can indicate relative sizes of the businesses.

Paint Stripping By Professional Contractors 

### Table D

- 1 summarizes the number of establishments and average number of construction workers for painting and wall covering contractors and floo ring contractors according to the 2007 US Economic Census ( US Census, 2007b ) . The Census data do not include hr s worked for construction industry sectors. Note that these Census data do not include bathtub refinishers/reglazers. Census data that include bathtub refinishers/reglazers were not identified.

Table D

- 1. 2007 US Economic Census Data for Painting and Wall Covering and Flooring Contractors.

2007 NAICS 2007 NAICS Title 2007 Number of Establishments 2007 Average Number of Construction Workers
238320 Painting and wall covering contractors 35,619 174,276

238330 Flooring contractors 14,575 49,085

Source: US Census (2007b )

.


### The number of painting and wall covering contractors and flooring contractors who use DCM

- based paint strippers, or the number of jobs per year a contractor uses DCM

- based paint strippers, and the number of construction workers within a job site exposed to DCM

- based paint strippers is unknown. The number of establishments and construction work ers from the US Census provide some context for potential numbers of establishments and construction workers potentially exposed to DCM during paint stripping; while some fraction of these workers may be exposed to DCM, the Census data do not include self

- employed, single person businesses, and some of these workers may also be exposed to DCM.

Paint Stripping at Automotive Body Repair and Maintenance Shops 

### Table D

- 2 summarizes the number of establishments and average number of paid employees for automotive body, paint, and interior repair and maintenance according to the 2007 US Economic Census ( US Census, 2007b ) . The Census data do not include hr s worked for this industry sector.

Table D

- 2. 2007 US Economic Census Data for Automotive Body, Paint, and Interior Repair and Maintenance.

2007 NAICS 2007 NAICS Title 2007 Number of Establishments 2007 Number of Paid Employees
811121 Automotive body, paint, and interior repair and maintenance 35,581 223,942

Source: US Census (2007b )

.

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### 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 199 8 (that used DCM) is representative of body shops within the entire US Rhode Island DEM recommends eliminating the use of DCM

- based paint strippers as a pollution prevention measure ( RIDEM, 2011 ) . Therefore, it is uncertain if the 20 percent of shops that used DCM in 1998 is representative of the fraction of shops that use DCM in the present day.

The present day number of automotive body repair and maintenance shops within the US that use DCM

- based paint strippers, and the number of employees within an establishment exposed to DCM

- based paint strippers are unknown. Therefore, the number of establishments and employees from the US Ce nsus are possibly overestimates of the number of establishments and employees potentially exposed to DCM during paint stripping.

A 2003 Rhode Island study that monitored exposures to DCM in a vehicle repainting shop noted a use rate of DCM of one to two g allons per week for that particular facility ( Enander et al.
, 2004 )

.

Wood Furni ture Stripping 

### Table D

- 3 summarizes the number of establishments and average number of paid employees for reupholstery and furniture repair according to the 2007 US Economic Census ( US Census, 2007b ) . The Census data do not include hr s worked for this industry sector.

Table D

- 3. 2007 US Economic Census Data for Reupholstery and Furniture Repair.

2007 NAICS 2007 NAICS Title 2007 Number of Establishments 2007 Number of Paid Employees
811420 Reupholstery and furniture repair 4,693 16,142

Source: US Census (2007b )

.


### OSHA conducted a Regulatory Impact Analysis (RIA) in 1996 of the 1997 OSHA Methylene Chloride Standard. In the RIA, OSHA estimated 6,152 establishments engaged in furniture paint stripping using DCM and estimated 7,872 workers exposed during this activity . The 2010 OSHA Regulatory Review of the Methylene Chloride Standard estimates that the number of reupholstery and furniture repair facilities decreased to fewer than 6,000 by 2003. The 2007 US Economic Census reports a further decline in the total numbe r of establishments. However, it is unknown if these data are representative of the number of establishments and workers that use DCM in the present day ( OSHA, 2010b )

. The present day number of reupholstery and furniture repair establishments that use DCM

based paint strippers and the number of employe es within an establishment exposed to DCM

based paint strippers are unknown. Therefore, the number of establishments and employees

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### from the US Census are possibly overestimates of the number of establishments and employees potentially exposed to DCM durin g 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 D

- 4). IRTA then used these data to estimate the number of firms in the state of California that use DCM

- based strippers ( IRTA, 2006 ) . The source did not identify the year in which t hese data were obtained. These data are presented in Table D

- 4. It is unknown if the distribution of facility annual use rate of stripper is representative of firms across the entire US.

Table D

- 4. Estimated Annual DCM Based Stripper Usage in Californi 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 496 a

a IRTA (2006 ) no tes a total of 596 firms in California. However, an actual summation of the firms gives a total of 496. Source: IRTA (2006 )

. 

### IRTA (2006 ) identifies the facilities that use >200 gallons/year of stripper as larger facilities that purchase stripper in drum quantities from suppliers. The firms that use <200 gallons/year of stripper likely use hand stripping and purchase their stripper from hardware and home improvement stores ( IRTA, 2006 )

.

Art Restoration and Conservation 

### Table D

- 5 summarizes the number of establishments and average number of paid employees for independent artists, writers, and performers and museums according to the 2007 US Economic Census ( US Census, 2007b ) . The Census data do not include hr s worked for these industry sectors.

Table D

- 5. 2007 US 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: US Census (2007b )

.

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### NAICS code 711510 includes a wide variety of professions, including independent art restorers and independent conservators. The majority of the professions listed within this NAICS code according to the US Census Bureau are not expected to engage in paint stripping. Furthermore, the extent that art restorers and conservators engage in paint stripping, particularly using DCM

- based paint strippers is unknown. Similarly, the num ber of museums within NAICS code 712110 that engage in paint stripping, and use DCM

- based paint strippers, is unknown. Therefore, the number of establishments and employees from the US Census are likely overestimates of the number of establishments and em ployees potentially exposed to DCM during paint stripping.

Aircraft Paint Stripping 

### Table D

- 6 summarizes the number of establishments, average number of production workers, and production workers hr s for aircraft manufacturing according to the 2007 US Eco nomic Census ( US Census, 2007b ) . The table also estimates the average worker days per year and average worker hr s per day. These parameters are estimated from the production workers hr s and the average number of production workers. The average worker days per year are estimated assuming eight worker hr s per day, and the average worker hr s per day are estimated assuming 250 worker days per year. The estimates of worker days per year and worker hr s per day are within 10 percent of the EPA New Chemicals Program default values of 250 days/year and eight hr s/day, respectively.

Table D

- 6. 20 07 US Economic Census Data for Aircraft Manufacturing.

2007 Economic Census Data Parameters Calculated from the Corresponding 2007

Economic Census Data

2007 NAICS Code 2007 NAICS Title Number of Establishments Average Number of Production

Workers Production Workers Hr s (1,000 Hr s) Average Worker Days per Year (Assuming 8 Hr s/Day) Average Worker Hr s per Day (Assuming 250 Days/Year)

336411 Aircraft manufacturing 254 81,456 157,589 242 7.74

Source: US Census (2007b )

.


### In the RIA, OSHA estimated 300 establishments engaged in paint stripping of aircraft using DCM and estimated 2,470 workers potentially exposed during this activity. However, it is unknown if these data are representative of the number of establishments and workers that use DCM in the present day ( OSHA, 2010b ) . The 1996 RIA number of DCM

- using establishments estimate is similar to the 2007 US Economic Census number of establishments. However, the 2007 US Economic Census presents a much greater number of workers than the RIA estimate of number of workers exposed to DCM.

The present day number of aircraft manufacturing establishments that use DCM

- based paint strippers and the number of employees within an establishm ent exposed to DCM

- based paint

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### strippers are unknown. Therefore, the number of establishments and employees from the US Census are possibly overestimates of the number of establishments and employees potentially exposed to DCM during paint stripping.

Ship Paint Stripping 

### Table D

- 7 summarizes the number of establishments, average number of production workers, and production workers hr s for ship building and repairing according to the 2007 US Economic Census ( US Census, 2007b ) . The table also estimates the average worker days per year and average worker hr s per day. These parameters are estimated from the production workers hr s and the average number of production workers. The average worker days per year are estimated assuming eight worker hr s per day, and the average worker hr s per day are estimated assuming 250 worker days per year. The estimates of worker days per year and worker hr s per day are wit hin 10 percent of the EPA New Chemicals Program default values of 250 days/year and eight hr s/day, respectively.

Table D

- 7. 2007 US Economic Census Data for Ship Building and Repairing.

2007 Economic Census Data Parameters Calculated from the Corresponding 2007

Economic Census Data

2007 NAICS Code 2007 NAICS Title Number of Establishments Average Number of Production

Workers Production Workers Hr s (1,000 Hr s) Average Worker Days per Year (Assuming 8 Hr s/Day) Average Worker Hr s per Day (Assuming 250 Days/Year)

336611 Ship building and repairing 656 65,737 136,929 260 8.33

Source: US Census (2007b )

.



### The number of ship building and repair establishments that use DCM

- based paint strippers and the number of employees within an establishment exposed to DCM

- based paint strippers are unknown. Therefore, the number of establishments and employees from the US Census are
p ossibly overestimates of the number of establishments and employees potentially exposed to DCM during paint stripping.

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### Appendix **E : Occupational Exposure Literature Data** 

This assessment uses existing inhalation exposure data to estimate occupational expo sures to DCM. Multiple exposure studies were identified through a literature search. Additionally, inhalation exposure data from OSHA and state health inspections were obtained from the OSHA IMIS database. A summary of relevant data from the literature search follows.


## Professional Contractors

Bathtub Refinishing Exposures and Fatalities In 2012, the US Centers for Disease Control and Prevention (CDC) reported on bathtub refinisher fatalities associated with DCM stripping agents. Key excerpts from the CDC Morbidity and Mortality Weekly Report (MMWR) follow.

In addition to three deaths identified by the Michigan Fatality Assessment and Control Evaluation (FACE) program, OSHA identified 10 other bathtub refinisher fatalities associated with DCM stripping agents that had been investigated in nine states during 2000 to 2011. Each death occurred in a residential bathroom with inadequate ventilation. Protective equipment, including a respirator, either was not used or was inadequate to protect against DCM v apor, which 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, 2012b )

. A review of the IMIS, a database for federal and state OSHA investigations, identified 12 DCM

- related deaths associated with professional bathtub refinishing operations during 2000 to 2011. One of the three 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). Twelve we re 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 p ercentage of DCM in the products ranged from 60 to 100 percent ( CDC, 2012b )

. Toxicology tests from specimens collected at autopsy indicated DCM blood levels ranging from 18 to 223 mg/L in the six decedents for whom values were recorded; a level of <2 mg/L is expected in a person working within the OSHA allowable air standard for exposure to DCM fumes. Among the five decedents whose COHb level s were tested, levels ranged from absent to mildly elevated (range: zero to five percent), indicating that CO was unlikely to have been the primary cause of death (although the durations of exposure to DCM and receipt of oxygen during resuscitation efforts , two factors that can affect COHb levels, were not known). Analysis of IMIS data regarding deaths from DCM showed an increase in cases involving bathtub refinishing since 2000. During 1976 to 1999, only two (eight percent) of all DCM deaths investigated by OSHA were linked to bathtub refinishing. Since 2000, 13 (75 percent) of the DCM deaths investigated by OSHA occurred during bathtub refinishing ( CDC, 2012b )

.

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### A report of a May 2010 fatality investigated by the Michigan FACE program contained estimated exposure concentrations. Based on the size of the bathroom, size of the tub, and an estimate that six fluid ounces (177 mL) of DCM

- based s tripper was used during a typical job, and the aircraft paint stripper product used contained 60 to 100 percent DCM, exposure levels were estimated for both the tub and bathroom environments. The concentration of DCM vapor was estimated at 92,949 to 154,9 16 ppm in the bathtub and 5,099 to 8,499 ppm in the bathroom. These concentrations exceed the NIOSH Immediately Dangerous to Life and Health (IDLH) level of 2,300 ppm ( CDC, 2012b ) . Further details are available in the MMWR ( CDC, 2012b ) , the NIOSH FACE Program Michigan Case Report 10MI013 ( CDC, 2012a ) , and the Michigan State University (MSU)/FACE Report ( MSU/MIFACE, 2011 )

. The MSU/Michigan FACE report noted that Washington State’s Department of Labor and Indu stries Division of Occupational Safety and Health (DOSH) inspection data include a case of a high DCM exposure while stripping a bathtub. A bathtub refinishing employee was monitored while stripping a residential bathtub with Kleen Strip Aircraft Remover. The MSDS indicated the product contained <85 percent DCM. Information sheets with the product recommended the use of supplied air. The employee had purchased ventilation equipment, which was in use at the time of monitoring. The employee wore a half

- f ace air purifying respirator. Two personal samples were taken in the breathing zone of the employee for 15 minutes during the stripping task. These personal samples were 2,180 and 2,000 ppm DCM. Two area samples were also taken and were 545 and 314 ppm DCM. All of the samples significantly exceeded the OSHA 15

- minute TWA STEL of 125 ppm, and the two breathing zone samples were close to the NIOSH IDLH value of 2,300 ppm ( MSU/MIFACE, 2011 ) . Although the exact date of the Washington DOSH inspection was not cited, the inspectio n occurred in the time period between April 2003 and August 2008 ( Lofgren et al. , 2010 )

. Paint Stripping by Professional Contractors DCM exposure data for paint stripping conducted by professional contractors were not identified in the literature search. However, some DCM exposure data were identified for consumer use of DCM

- based paint strippers in a European Union (EU) report. The E U report states that there is “probably...no fundamental difference between the application of paint removers by professional painters and consumers” and goes on to further state that, in regard to the cited consumer exposure studies, “the test situations an d data described...are assumed valid for occupational exposure during professional use as well” ( TNO, 1999 ) . However, professional contractors are expected to have a higher frequency of exposure as compared to consumers. It is also not clear whether overall activity patterns and practices of contractors match those of consumers or whether the overall distributions of exposures of contractors and consumers have any semblance to one another. Despite these uncertainties, some of the literature data for consumers may be considered.

The EU report identified the following consumer exposures to DCM during paint stripping from a literature review. A 1990 EPA investigation estimated consumer exposure levels ranging from 35 mg/m 3 

### (10 ppm) to a few short

- term exposures of over 14,100 mg/m 3 

### (4,063 ppm). The

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### majority of the exposures were below 1,770 mg/m 3 

### (510 ppm). A separate study conducted by a solvent manufacturer measured exposures during tests conducted in a small room. One test conducted with ventilation (although the ventilation rate or air change rate were not specified) measured a two

- hr TWA exposure of 289 mg/m 3 

### (83.3 ppm). 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), with a maximum of 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, eight

- hr TWA exposures under supplier

- recommended ventilation would be 187 to 226 mg/m 3 

### (54 to 65 ppm) ( TNO, 1999 )

. The same EU report also cites a literature review conducted by the United Kingdom (UK) in 1998, which identified reports of one

- 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. An older study from 1981 found eight

- hr TWA exposures of 460 to 2,980 mg/m 3 

### (133 to 859 ppm) in unventilated rooms and 60 to 400 mg/m 3 

### (17 to 115 ppm) in ventilated rooms ( TNO, 1999 )

. Midwest Research Institute (MRI) prepared a report for EPA in 1994 that resulted from an experimental investigation of consumer exposures to solvents contained 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 pl ywood panel coated with a primer coat and two finish coats. The air exchange rate for the experiments ranged from 0.54 to 0.76 air changes per hr (ACH), with an average of 0.58 ACH. The air exchange rate of approximately 0.5 ACH was intended to replicate the ventilation rate of an enclosed room in a typical residence as
a worst

- case scenario. During each experiment, the following samples were taken: a personal breathing zone sample of the test subject using the paint stripper; two stationary air samples for the duration of the paint stripping task; and one stationary air sample beginning at the start of the paint stripping and lasting for eight hr s ( US EPA, 1994b )

. In the MRI investigation, the first DCM

- based paint stripper was spray applied. The breathing zone concentrations of DCM were 3,000 and 3,400 mg/m 3 

### (865 and 980 ppm). The stationary length

- of

- task concentrations ranged from 2,900 to 3,600 mg/m 3 

### (836 to 1,037 ppm). The eight

- hr TWA concentration ranged from 1,700 to 2,000 mg/m 3 

### (490 to 576 ppm). The second DCM

- based paint stripper was brush applied. The bre athing zone and stationary length

- of

- task concentrations ranged from 380 to 490 mg/m 3 

### (110 to 141 ppm). The eight

- hr TWA concentration ranged from 230 to 270 mg/m 3 

### (66 to 78 ppm) ( US EPA, 1994b )

. DCM exposure data were identified in the OSHA IMIS data set. Table E

- 1 provides a summary by job category of the OSHA inspect ion data. For both wall and flooring contractors, the inspection exposures ranged from zero to 28.3 mg/m 3 

### (zero to 8.2 ppm) and include both eight

- hr TWA and STEL/ceiling exposures. These exposures include a wide variety of job activities, although two m onitored worker activities appear to have involved stripping but

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### without specification of the application method ( OSHA, 2012 ) . The relevance of these exposures to DCM

- based paint stripping is uncertain.

Table E

- 1. Summary by Industry and Job Category of OSHA IMIS Data for DCM from 1992 to 2012.

NAICS/SIC Code Job Category Sample Type Exposure Type Data Type Concentration (mg/m 3 ) a Number of Data Points
336411 (Aircraft Manufacturing) Painter Personal TWA Minimum 0 3 Average 12.7
Maximum 20.8
8999 (Aircraft Refinishing) b Finisher Personal TWA Minimum 7.3 4 Average 16.9
Maximum 33.7
336611 (Ship Building and Repairing) Assembler Personal TWA Minimum 6.1 3 Average 19.5
Maximum 33.7
Foamer Personal TWA Minimum 3.5 3 Average 13.9
Maximum 27.8
General laborer Personal TWA Single data point 3.5 1

Gluer Personal TWA Minimum 0 2 Average 5.2
Maximum 10.4 Mechanic/ electrician Personal STEL Single data point 0 1

Refrigeration Personal TWA Two data points 0 2

Upholsterer Personal TWA Minimum 1.11 2 Average 1.20
Maximum 1.29
238320 (Painting and Wall Covering Contractors) Manager Personal Ceiling Single data point 3.5 1

Painter Personal TWA Minimum 0 2 Average 6.9
Maximum 13.9 Stripper Personal Ceiling Minimum 0 4 Average 0

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- 1. Summary by Industry and Job Category of OSHA IMIS Data for DCM from 1992 to 2012.

NAICS/SIC Code Job Category Sample Type Exposure Type Data Type Concentration (mg/m 3 ) a Number of Data Points
Maximum 0
TWA Minimum 6.3 2 Average 11.0
Maximum 15.8
238330 (Flooring Contractors) Carpet installer Personal STEL Single data point 27.8 1

General laborer Personal TWA Single data point 28.3 1

H&S Officer Personal STEL Single data point 4.5 1

711510 (Independent Artists, Writers, and Performers) Manager Personal TWA Single data point 2.0 1

811121 (Automotive Body, Paint, and Interior Repair and Maintenance) Adhesive application Personal STEL Single data point 6.9 1

TWA Minimum 13.9 2 Average 19.1
Maximum 24.3 Autobody repairman Personal Ceiling Single data point 27.8 1

STEL Single data point 13.9 1

TWA Minimum 0.0 2 Average 15.6
Maximum 31.3
Bed liner Personal Ceiling Single data point 0 1

General laborer Personal TWA Single data point 1.3 1

Gluer Personal TWA Minimum 6.9 2 Average 13.4
Maximum 19.8
Owner Personal STEL Single data point 27.8 1

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- 1. Summary by Industry and Job Category of OSHA IMIS Data for DCM from 1992 to 2012.

NAICS/SIC Code Job Category Sample Type Exposure Type Data Type Concentration (mg/m 3 ) a Number of Data Points
Painter Personal STEL Minimum 3.5 2 Average 14.1
Maximum 24.8
TWA Minimum 0.5 5 Average 3.8
Maximum 12.3
Sander Personal STEL Single data point 3.1 1

Spray painter Personal TWA Single data point 2.4 1

Stripper Personal STEL Minimum 6.2 2 Average 10.7
Maximum 15.3
TWA Single data point 28.6 1

Surface preparation Personal STEL Minimum 6.9 2 Average 20.6
Maximum 34.3
TWA Single Data Point 8.9 1

Upholsterer Personal STEL Single Data Point 10.4 1

811420 (Reupholstery and Furniture Repair) Area sample Area TWA Minimum 0.0 3 Average 13.9
Maximum 31.3
Bathtub reglazer Personal STEL Single data point 0 1

Caser Personal TWA Single data point 24.3 1

Degreaser Personal TWA Single data point 3.5 1

Finisher Personal STEL Single data point 1.3 1

TWA Minimum 3.8 6 Average 8.1

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- 1. Summary by Industry and Job Category of OSHA IMIS Data for DCM from 1992 to 2012.

NAICS/SIC Code Job Category Sample Type Exposure Type Data Type Concentration (mg/m 3 ) a Number of Data Points
Maximum 17.0
General laborer Personal Ceiling Single data point 0 1

STEL Minimum 0 5 Average 9.9
Maximum 20.8
TWA Minimum 0 2 Average 8.7
Maximum 17.4
Gluer Personal TWA Minimum 6.9 3 Average 12.0
Maximum 17.4
H&S officer Personal Ceiling Single data point 16.3 1

TWA Minimum 1.7 6 Average 11.6
Maximum 30.1
Industrial hygienist Personal Ceiling Single data point 0 1

Owner Personal Ceiling Single data point 0 1

STEL Minimum 0 3 Average 11.7
Maximum 21.2
TWA Minimum 6.9 5 Average 19.8
Maximum 25.7
Refinisher Area STEL Single data point 0 1

Personal Ceiling Minimum 10.4 2 Average 12.2
Maximum 13.9
STEL Minimum 0 11 Average 10.1

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- 1. Summary by Industry and Job Category of OSHA IMIS Data for DCM from 1992 to 2012.

NAICS/SIC Code Job Category Sample Type Exposure Type Data Type Concentration (mg/m 3 ) a Number of Data Points
Maximum 20.8
TWA Minimum 0.8 11 Average 13.3
Maximum 30.7 Repairman Personal Ceiling Single data point 31.3 1

STEL Minimum 31.3 2 Average 32.7
Maximum 34.0
TWA Single data point 0.74 1

Restorer Area Ceiling Single data point 0 1

Personal Ceiling Single data point 0 1

STEL Minimum 17.4 2 Average 24.3
Maximum 31.3
TWA Minimum 3.5 4 Average 11.2
Maximum 19.1
Sander Personal TWA Minimum 9.0 2 Average 19.3
Maximum 29.5
Seamstress Personal TWA Minimum 13.9 3 Average 18.1
Maximum 25.9 Secretary Personal TWA Single data point 19.1 1

Spray painter Personal TWA Single data point 12.5 1

Spray room with vent Personal STEL Single data point 11.1 1

Stripper Area TWA Minimum 6.9 2

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- 1. Summary by Industry and Job Category of OSHA IMIS Data for DCM from 1992 to 2012.

NAICS/SIC Code Job Category Sample Type Exposure Type Data Type Concentration (mg/m 3 ) a Number of Data Points Average 13.9
Maximum 20.8
Personal Ceiling Minimum 6.9 3 Average 18.5
Maximum 27.8
STEL Minimum 0 31 Average 14.9
Maximum 31.3
TWA Minimum 0 35 Average 15.7
Maximum 33.9
Unknown Personal TWA Single data point 3.5 1

Upholsterer Area TWA Single data point 20.8 1

Personal Ceiling Single data point 3.5 1

TWA Minimum 3.5 5 Average 9.2
Maximum 24.3
STEL Minimum 10.4 2 Average 10.4
Maximum 10.4 Utility worker Personal TWA Single data point 33.4 1

Wood worker Personal STEL Single data point 0 1

TWA Single data point 17.0 1

a Original concentrations were given in ppm. These values were converted to mg/m 3 using the conversion of 1 ppm = 3.47 mg/m 3 ( NIOSH, 2011a ) . This conversion assumes standard temperature and pressure of 1 atm and 25 °C. b Standard Industry Classification (SIC) code 8999 is for Services, Not Elsewhere Classified. This particular inspection data point was for a facility called Aircraft Refinishing Technology, Inc., and was assumed to be applicable for aircraft refinishing.

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### Paint Stripping a t Automotive Body Repair and Maintenance Shops A 2004 publication describes a study in Rhode Island that conducted personal air sampling of workers in two complete vehicle repainting facilities (shops that specialize in repainting the entire surface of car s and small trucks) and one vocational technical school. The DCM monitoring was conducted on a single worker in a vehicle repainting shop for one day in the spring and one day in the fall. This worker engaged in paint stripping one to two times per week and three to four hr s per day. The spring TWA exposure was 26 ppm and the fall TWA exposure was 120 ppm. These exposures exceeded OSHA’s eight

- hr TWA action level (12.5 ppm) and PEL (25 ppm), respectively. Additionally, three task

- based samples were tak en in the spring (with sampling times ranging from nine to 18 minutes). These exposures were 72, 93, and 120 ppm, which were all below the OSHA STEL (125 ppm) ( Enander et al. , 2004 )

. DCM exposure data were identified in the OSHA IMIS data set. Table E

- 1 provides a summary by job category of the OSHA inspection data. F or automotive body repair and maintenance, the inspection exposures ranged from zero to 34.3 mg/m 3 

### (zero to 9.9 ppm) and include both eight

hr TWA and STEL/ceiling exposures. These exposures include a wide variety of job activities, although three separat e monitored worker activities appear to include stripping (note that stripping could include sanding, which is a mechanical paint stripping method as opposed to the chemical paint stripping method, such as the use of DCM) ( OSHA, 2012 ) . The relevance of these exposures to DCM

- based paint stripping is uncertain.

Wood Furniture Stripping In 1992, the NIOSH surveyed a furniture refinishing shop located in Littleton, Colorado. NIOSH was invited to conduct the survey by the facility owner. The facility stripped furniture in a separate room using a pump and brush technique to apply paint str ipper and remove the paint. The stripper is pumped from a 55

- gallon drum to the brush, collected from the table, and recycled. The facility employed five refinishers. The stripping time of each worker averaged at a few hr s per week, but reached as high as three to four hr s in a day. While stripping, the workers wore rubber aprons, full

- length rubber gauntlets, a face shield, and plastic upper arm covers, and they also may have worn the safety goggles they wore in the wood shop area ( NIOSH, 1992 )

. NIOSH conducted three surveys: an initial survey on October 10, 1992; a second survey on November 20, 1992 after an exhaust ventilation system was installed on the furniture strippin g booth; and a third survey on February 10, 1993 after an exhaust ventilation system was installed on the wash booth ( NIOSH, 1992 ) . Tables E

- 2, E

- 3, and E

- 4 present the measure ments that NIOSH made during these three surveys. The results indicate that the addition of engineering controls reduced exposure concentrations in both the personal and area samples.

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- 2. Summary of Personal and Area Concentrations in a Furniture Refinishing Shop that Uses a Pump and Brush Stripping Technique Measured Before Engineering Controls were Added. Initial Survey (Before Controls Added) Personal Samples Area Samples

Activity Concentration (ppm) Sampling Time (Minutes) Location Concentration (ppm) Sampling Time (Minutes) Stripping large chest 414 78 Door at room entrance 166 102

Stripping headboard 523 101 Door at room entrance 167 78

Stripping wicker chairs 398 23 Edge of stripping booth above recycle can 246 59

Stripping large dresser and drawers 445 58 Above water reservoir between wash booth and outside wall 52 62

Stripping large dresser and drawers 393 30 Workbench south of wash booth 37 182

Hand strip table with Palco gel stripper 83 14 Above drum of bulk stripper 120 60

Hand strip table with gel 174 16 Above drum of bulk stripper 86 102

Source: NIOSH (1992 )

.

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- 3. 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) Personal Samples Area Samples

Activity Concentration (ppm) Sampling Time (Minutes) Location Concentration (ppm) Sampling Time (Minutes) Stripping six chairs 10 35 Center of room (before ventilation system turned on) 32 18

Stripping crib 95 33 Above newly stripped chairs 85 82 Strip large desk 110 103 South central part of room near newly stripped crib 25 42

Near newly stripped desk drawers 32 59

Edge of wash booth (near worker breathing zone) 120 33

Edge of wash booth (near worker breathing zone) 58 34

Edge of wash booth (near worker breathing zone) 59 101

On work bench behind wash booth 4.5 102

Above DCM waste buckets 15 215 Above wash sludge tank 6.3 57

Source: NIOSH (1992 )

.

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- 4. Summary of Personal and Area Concentrations in a Furniture Refinishing Shop that Uses a Pump and Brush Stripping Technique Measured After Engineering Controls were Added to the Stripping Booth and Wash Booth. Third Survey (After Controls Added to Stripping Booth and Wash Booth)

Personal Samples Area Samples

Activity Concentration (ppm) Sampling Time (Minutes) Location Concentration (ppm) Sampling Time (Minutes) Stripping rocking chair 19 24 Center of room 2.1 30

Stripping seven chairs 90 52 Near entrance to

room 5.4 102

Stripping chairs 36 97 Above door to entrance of room 4 84

Stripping large dresser 70 113 Above door to entrance of room 8.4 178

Stripping dresser drawers 110 61 Above stripping drum <4 25

Above stripping drum 2.6 75 Above stripping drum 5 87 Above stripping drum ND 182 Above wash sludge tank 5 92

Near drying chairs 11 113
Above dresser while drying 18 107

ND

– not detected at a limit of 0.01 mg per sample

Source: NIOSH (1992 )

. 

### The initial survey indicated that personal exposure concentrations associated with stripping activities ranged from 83 to 523 ppm (over a range of sampling times) with an average of 347 ppm. 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 to 110 ppm (over a range of sampling times) with an average of 72 ppm. This range and average concentration are generally consistent with the personal exposure concentrations associated with stripping activities observed on the third survey (after controls were added to the wash booth). Per sonal samples were not taken during washing activities, and area samples were not taken at consistent, wash

- booth area locations during all surveys. However, the area samples altogether do indicate a reduction in concentrations after installation of the v entilation systems. The eight

- hr TWA exposures (eight

- hr averages of the individual samples and not the samples themselves) were below the pre

- 1997 OSHA PEL of 500

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### ppm but above the ACGIH Threshold Limit Value (TLV) of 50 ppm. NIOSH noted that after the ventilation systems were installed, the eight

- hr TWA exposures were all below 50 ppm ( NIOSH, 1992 )

. A 2007 publication describes follow

- up activities by OSHA in the inspection of a small business that repaired and restored custom

- made furniture. The facility employed 18 workers, but only a single worker worked three to four days per week using DCM to remove paint and varnish from furniture in one section of the facility. The w orker 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 and measured an eight

- hr TWA exposure of 108 ppm, which was above the OSHA PEL of 25 ppm. OSHA also measured seven STEL sampling results, which ranged from 153 to 662 ppm, with an average of 404 ppm. These measurements were all above the OSHA STEL of 125 ppm. The worker was observ ed wearing a full

- face elastomeric respirator with organic vapor cartridges and impervious gloves and an apron. The facility was cited for the overexposure and required to implement controls, including work practice and engineering controls and the use of a NIOSH

- approved supplied

- air respirator ( Grevenkamp, 2007 )

. A 1991 publication describes a NIOSH industrial hygiene survey of 14 furniture stripping workers exposed to DCM across five furniture stripping shops. NIOSH measured personal TWA exposures of the workers to DCM rang ing from 15 to 366 ppm. The highest average exposures to DCM by job category were: 191 ppm (strippers); 145 ppm (washers); and 31 ppm (refinishers) ( IARC, 1999 ; McCammon et al. , 1991 ) . These TWA exposures were below the pre

1997 OSHA PEL of 500 ppm.

In 1990, NIOSH conducted a survey of a furniture stripping workshop in Meadow Lands, Pennsylvania. This workshop u sed a flow

- over tank with a solution recycling system to strip furniture. The furniture is placed in tank, covered with stripping solution, and then scrubbed by a worker. During scrubbing, the worker alternates between brushing the furniture and covering it with more stripping solution. After stripping, the furniture is rinsed and brushed, dried, sanded, and refinished. The facility used a stripping solution that contained 60 volume percent DCM. The workshop installed a ventilation system in response t o the results of an OSHA inspection. The NIOSH survey was conducted after installation of the ventilation system to determine its adequacy. NIOSH found the ventilation system to be inadequate as exposure levels exceeded the pre

- 1997 OSHA PEL of 500 ppm. Measurements conducted by NIOSH found TWA exposure levels ranging from 613 to 1,152 ppm during stripping (averaged over stripping times of 177 to 260 minutes). NIOSH made recommendations for improving the ventilation system. After modifications to the v entilation system were made, NIOSH measured personal exposures during stripping on three different days and found DCM concentrations during stripping ranging from 22 to 35 ppm over stripping times of 4.5 to 6.25 hr s. The corresponding eight

- hr TWA exposur es ranged from 13 to 27 ppm. Additional personal samples measured for various ventilation system configurations resulted in DCM concentrations ranging from seven to 59 ppm (averaged over time periods of 49 to 147 minutes). NIOSH also

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### measured task

- specif ic exposures for various ventilation system configurations and found the following ranges of DCM area concentrations for each task ( NIOSH, 1991 ) :

• Stripping area: 8 to 31 ppm;

• Rinsing area: 5 to 94 ppm;

• Stripping solution 55

- gallon drum area: 0 to 293 ppm; and

• Other areas: 5 to 89 ppm.

The percentages of a worker’s entire exposure due to each task area were as follows ( NIOSH, 1991 ) :

• Stripping area: 14 to 73 percent;

• Rinsing area: 12 to 51 percent;

• Stripping solution 55

- gallon drum area: 0 to 22 percent; and

• Other areas: 2 to 51 percent.

In 1990, NIOSH conducted a survey of a furniture stripping facility in Cinc innati, 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 one

- hr TWA concentrations of breathing zone and area samples. NIOSH observed breathing zone concentrations of 100 and 77 ppm of the facility owner and the NIOSH employee, respectively. NIOSH observed three area concentrations of 20, 63, and 90 ppm. The hig hest 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. NIOSH noted local exhaust near the dip tank with very low intake velocity and generally inadequate air movement in the stripping area. NIOSH also noted that the facility owner wore neoprene gloves and boots while stripping, rinsing, and handling th e solution

- soaked furniture, but no other personal protective equipment was worn ( NIOSH, 199 0 )

. A 1990 EPA source cites exposure levels in furniture paint stripping with inadequate control measures as ranging from 258 to 3,812 mg/m 3 

### (74 to 1,099 ppm) ( TNO, 1999 )

. DCM exposure data were identified in the OSHA IMIS data set. Table E

- 1 provides a summary by job category of the OSHA inspection data. For furniture refinishing, the inspection exposures ranged from zero to 34.0 mg/m 3 

### (zero to 9.8 ppm) and included both eight

- hr TWA and STEL/ceiling exposures. These exposures include a wide variety of job activities , although of the 170 data points, 71 data points appear to have involved stripping, 26 data points appear to have involved refinishing, and one data point was for a bathtub reglazer. Only one of the 71 stripping data points, which was a STEL measurement, indicated the job activity as “spraying MC” (presumably MC stands for methylene chloride). None of the other job activities indicated the application method ( OSHA, 2012 ) . The relevance of these exposures to DCM

- based paint stripping is uncertain.

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### Art Restoration and Conservation Exposure data associated with art restoration and conservation were not identified in the literature search. A single exposure data point was identified in the OSHA IMIS data set (Table E

- 1) with an eight

- hr TWA exposure of two mg/m 3 

### (0.58 ppm). This exposure was for a
manager ( OSHA, 2012 ) . The relevance of this exposure to DCM

- based paint strippi ng is uncertain.

Aircraft Paint Stripping DCM exposure data of the breathing zone of workers engaged in paint stripping of aircraft in the US in 1977 were identified. A set of 23 breathing zone samples of paint stripping of wide body aircraft (over a ran ge of sampling times of 56 to 126 minutes) had a range of exposures of 79 to 950 mg/m 3 

### (23 to 274 ppm) with a mean of 393 mg/m 3 

### (113 ppm). A set of 20 breathing zone samples of paint stripping of narrow body aircraft (over a range of sampling times of 16 to 33 minutes) had a range of exposures of 38 to 2,820 mg/m 3 

### (11 to 813 ppm) with a mean of 795 mg/m 3 

### (229 ppm) ( IARC, 2010 )

. A UK study observed aircraft paint stripping using a spray process and found DCM eight

- hr TWA exposures of 29 to 95 ppm, with a mean of 62 ppm (210 mg/m 3 

### ). Peak levels were as high as 1,600 ppm (5,400 mg/m 3 

### ) ( EU, 2007a ; TNO, 1999 )

.

A French s tudy in 1994 observed the paint stripping of a Boeing 747 in an aeronautical workshop. During paint stripping operations, DCM concentrations ranged from 299.2 mg/m 3 

### (83.1 ppm) to 1,888.9 mg/m 3 

### (524.7 ppm). The eight

- hr TWA exposures to DCM ranged from 86 mg/m 3 

### (23.9 ppm) to 1,239.5 mg/m 3 

### (344.3 ppm) ( EU, 2007a ; IARC, 1999 ; Vincent et al.
, 1994 )

. Norwegian studies from 2001 and 2002 found eight

- hr TWA exposures to DCM associated with paint removal of aircraft of 1,444 and 3,802 mg/m 3 

### (416 and 1,096 ppm) from personal samples ( EU, 2007a )

. DCM exposure data were identified in the OSHA IMIS data set. Table E

- 1 provides a summary by job category of the OSHA inspection data. For aircraft manufacturing and refinishing, the inspection exposures ranged from zero to 33.7 mg/m 3 

### (zero to 9.7 ppm) all as eight

- hr TWA exposures. These exposures include both painting and finishi ng activities ( OSHA, 2012 ) . The relevance of these exposures to DCM

- based paint stripping is uncertain.

Ship Paint Stripping Limited data were identified for paint stripping of ships. A 1980 UK study observed eight painters over two days in a dockyard. The study results include a mean concentration of DCM associated with one painter conducting paint stripping of 214.7 mg/m 3 

### (61.9 ppm) ( IARC, 2010 )

. DCM exposure data were identified in the OSHA IMIS d ata set. Table E

- 1 provides a summary by job category of the OSHA inspection data. For ship building and repairing, the inspection exposures ranged from zero to 33.7 mg/m 3 

### (zero to 9.7 ppm) and included both eight

- hr TWA

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### and STEL exposures. These exposures did not appear to explicitly include monitored paint stripping activities ( OSHA, 2012 ) . The relevance of these exposures to DCM

- based paint stripping is uncertain.

Paint Stripping in Non

- specific Workplace Settings Some EU exposure data were identified that were characterized fo r “general industrial use.” However, more specific information on the industries (such as applicable NAICS or Standard Industrial Classification [SIC] codes, primary industrial functions or products, or number of sites or workers) was not provided in the identified reference.

A 1998 report by the UK identified exposures during immersion stripping of wood. They reported eight

- hr TWA exposures ranging from 38.5 to 7,000 mg/m 3 

### (11 to 2,017 ppm) with a mean of 700 mg/m 3 

### (202 ppm) for the period of 1980 to 19 94. The eight

- 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) and a mean of 350 to 420 mg/m 3 

### (101 to 121 ppm) ( TNO, 1999 )

. A 1980 US study observed the breathing zone of three workers engaged in paint stripping from wood and metal and obtained seven samples ranging in DCM TWA concentration from 633 to 1,017 mg/m 3 

### (182 to 293 ppm) ( TNO, 1999 )

. 

## Summary of OSHA IMIS Data As noted previously, 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. IMIS data may be examined to provide insights in some occupational categories where no other data are found to be directly attributable to the use of DCM

- containing paint stripping products.

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### APPENDIX F : RESIDENTIAL/ CONSUMER EXPOSURE ASSESSMENT

**F**

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

In 1993, MRI conducted a series of chamber studi es for EPA on paint stripping products ( US EPA, 1994b ) . For each st udy, 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 an integrated sample on activated charcoal. These data were analyz ed and a process was undertaken to fit the data to exponential equations to represent the time

- varying emission profile that led to the air concentrations. The US EPA (1994b ) study tested five products, three of which contained either DCM or NMP, as described in Table F

- 1.

Table F

- 1. US EPA (1994b ) Study: Products Emissions Fit to Exponential Profile.
Product Application Type Chemical BIX Spray

- On Stripper Spray DCM Strypeeze Brush DCM
Wood Finisher’s Pride Brush NMP



### In evaluating the experimental data, an exponential emission was chosen because of the general shape of the concentration profile and similarity to other emission behavior ( e.g. , chemicals from paint). The emission equation has the following form:

( F

- 1)



### where: 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

Integrating Equation E

- 1 to time of infinity gives the mass released represented by the exponential, as follows:

Mass Released ( F

- 2)

Or:

( F

- 3)

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### Integration of the single compartment, mass

- balance equation for the air concentration equation for a single and double exponential representation of the emissions is given in Equations F

- 4 and F

- 5 ( US EPA, 1997 )
, respectively.

( F

- 4)



### where:

V = chamber volume, m 3 

### Q = air flow rate in and out of the chamber, m 3 

### / hr

( F

- 5)



### 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 expone ntial, hr - 1



### The two DCM products were applied in eight, approximately one

- minute applications, with each one

- minute application followed by an approximately 10

- minute wait time prior to the start of the subsequent application, resulting in about 11 minute s between applications. In each case, the emissions from each application are represented by a single or double exponential, with each exponential identical to the other seven, but with a different start time set at the midpoint of the application period. Based on this approach, the start times of the eight DCM exponentials are 0.5, 11.5, 22.5, 33.5, 44.5, 55.5, 66.5, and 77.5 minutes from the start of the stripping activity.

For the two DCM products, a single exponential was found to provide a good fit to the data. The fitting process involves:

(1) Extracting measured concentration values from the US EPA (1994b ) data and co

- plot the points with Equation F

- 4. The concentration values were extracted for runs 4, 5, and 6 for BIX Spray

- On and runs 7, 8, and 9 at each 0.5

- hr time point as well as peaks and significant changes in slope. This resulted 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.

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### (3) Iterating to obtain the best fit to the experimental data by varying the “Fraction Released” and the first

- order rate constant ( k) using Equation F

- 4 and the following relationship:

( F

- 6)



### This analysis was conducted using Excel to solve the equations and plot the results. The best fit was arrived at by visual comparison of the results of Equation F

- 4 with the extracted US EPA (1994b ) data, attempting to fit the Equation F

- 4 curve midway between the maximum and minimum values of the data. In general, the height of the concentration curve is related primarily to the DCM mass released, and the length and shape of the decay portion of the curve is closely related to the first

- order rate constant, k. The resulting fit for the BIX Spray

- On Strippe r product is shown in Figure F

- 1, and the fit for the Strypeeze product (brush application) is shown in Figure F

- 2. In each figure, the underlying eight exponentials are shown in the lower part of the figure, with the sum shown as the fitted, dashed line. The parameters for these two DCM cases are shown in Table F

- 2.

Figure F

- 1. Model Fit to MRI ( US EPA, 1994b ) Data for BIX Spray

- On (Spray Application). 

### Published data/EPA report

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### From Published data/EPA report

Figure F

- 2. Model Fit to MRI ( US EPA, 1994b ) Data for Strypeeze (Brush Application).

Table F

- 2. Fitted Parameters to the US EPA (1994b ) Study Results for the Two DCM

- Containing Paint Strippers.

Product Mass of Product Applied, g DCM Mass Applied, g DCM Fraction Released First

- Order Rate Constant, Hr - 1
BIX Spray

- On Stripper 540 495 0.66 10 Strypeeze 722 121 0.33 10



### A numerical integration of the fitted “sum of 8 exponentials” shown in Figures F

- 1 and F

- 2 was performed by using the average concentration for each one

- minute interval and conducting a

mass

- balance calculation for the test chamber, accounting for the mass in the chamber and the mass that has been removed through ventilation. The resulting m ass released from the product as a function of time is shown in Figures F

- 3 and F

- 4 for BIX Spray

- On and Strypeeze stripper, respectively.

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- 3. Theoretical Cumulative Mass of DCM Released for BIX Spray

- On Stripper.

Figure F

- 4. Theoretical Cumulative Mass of DCM Released for Strypeeze Stripper. 111

111 minutes

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## Discussion and Conclusions From the exponential fits to the US EPA (1994b ) data, we estimate that 66 percent of the applied DCM in the spray product (Figure F

- 1) was released to air, versus 33 percent of the applied DCM in the brush product (Figure F

- 2). We estimate that virtually all of the 66 and 33 percent of the DCM mass will be released by two hr s after application for the spray and brush product, respect ively, very shortly after the last scraping is finished, due to the higher volatility. Thus, the concentration

- decline part of Figures F

- 1 and F

- 2, after the peak, is due almost exclusively to ventilation rather than to declining emissions, and therefore, these exposures could be virtually eliminated through ventilation.

Factors that should be considered in applying these findings to a model

- based approach using MCCEM include the effect of varying the product use behavior and the effect of the quantity of the chemical applied. It appears that the off

- gassing rate is a function of the mass applied and the duration of application; based on the limited data available, the emission rate does not exhibit significant inhibition of volatilization due to increase d concentrations in the range of air concentrations observed in the US EPA (1994b ) study. If this holds true, the results of this analysis can be applied to a variety of product use behavior by modifying MCCEM to represent this behavior. MCCEM’s capability of representing the application as an incremental

e xponential may further improve the representativeness of the predicted concentrations.

**F**

**- 2.**  **Sensitivity Analysis for Inhalation Scenarios**

For this analysis, each input that could be measured on a continuum ( e.g. , emission rate, airflow rate) was first halved and then doubled while holding all others at their base

- case values. For an input to which the model output is directly and linearly proportional, and for which the exposure measure for the base case is deno ted as X , the result for the halved case would be 1⁄2X and the result for the doubled case would be 2X . Computing and averaging the two differences from the base case gives the following result:

([X

- 1/2X] + [2X

- X]) / 2) / X = 3⁄4 or 75 percent ( F

- 7)

For an input that cannot be varied over a continuum, or that can be dealt with only discretely or perhaps dichotomously ( e.g. , in the use zone or not at certain key times), the above procedure can still be used, but the sensitivity measure reduces to:

|Y

- X| / X (expressed as a percent) ( F

- 8)

where Y is the output associated with the change in location pattern from the base case.

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### F

**- 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. Exposures were assessed for both brush

- on and spray

- on products due to differences in chemical release characteristics, DCM wei ght fraction of products, application rates, and time required for application, as discussed below.

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 

### ) calculated from the US EPA (1994b ) chamber tes ts and the surface areas of objects to be stripped (ft 2 

### ). Surface areas were selected so that the resulting product mass corresponded approximately to central (near the median) and upper

- end (near the 90 th 

### percentile) estimates for the amount of paint
str ipper product used per event from the large nationwide survey by Abt (1992 ) , as reported in EFH (US EPA 2011c) Table 17

- 20. The EFH reports a median value of 32 fluid ounces or 1⁄4 gallon. Conversion to metric units (3.75 liters per gallon) and consideration o f the nominal product density (~1.1 g/cm 3 

### ) ( calculated fro m Brown, 2012 ) yields 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 is 80 oz or 2,500 g. Similarly, the small Riley et al. (2001 ) survey reported 32 ounces as the median amount of paint stripper product used. Specific product masses used in this assessment for the brush

- on scenarios were 900 g for Scenarios 1 and 2 and 2,250 g for Scenario 3.

For Scenario 7, a lower mass (477 g, d erived from largest application amount identified in the NIOSH report) was used, but the application occurred in a confined space (bathroom) and was assumed to be performed by a professional, as opposed to a DIY worker for the other scenarios. Product mas ses for the spray

- on scenarios were 680 g for Scenarios 4 and 5 and 1,700 g for Scenario 6.

As previously mentioned, the application amounts assumed in this assessment for Scenarios 1 through 6 are a product of application rates calculated from the US EPA (1994b ) experiments and the surface area of objects t o 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

- containing product (540 g of product applied to 8 ft 2 

### ). These application rates are 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/cm 3 

### ) 5 

### . The applied surface areas selected for cent ral and upper

- end values were 10 and 25 ft 2 

### . The upper

- end surface area is 2.5 times higher than the central surface area and provides sufficient distinction from the central case. Application targets with 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

5 See the following URL: http://www.savogran.com/Information/removerfaq.html

.

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### for the top surface was selected for the central case (10 ft 2 

### ) 6 

### and a chest of drawers with nominal dimens ions of 4 ft high by 2.5 ft wide by 1.5 ft deep 7 

### was selected for the upper

- end case (4 × 2.5 ft 2 

### for front + 2.5 × 1.5 ft 2 

### for top + 2 × 4.5 × 1.5 ft 2 

### for sides ≈25 ft 2 

### ). For the bathroom scenario, a bathtub surface 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, which 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 applicati on segments of 6.25 ft 2 

### each and 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 corresponds to instructions on the majority of product labels indicating that the stripping procedures should be repeated to remove multiple coats of paint or stubborn paint. All residuals from the scraping were assumed to be removed from the house on completion of the last segment/application.

The entire stripping sequence for each segment consisted of applying the product to the target surf ace followed by a wait or effect period and then scraping the treated surface. 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 fo r spray applications. Application was followed by a 15

- minute wait period and then a four

- minute scraping period per segment. For the bathtub scenario (brush

- on only) with a larger surface area, the applying time was increased to three minutes per segmen t and the scraping time was increased to six minutes per segment; the wait time remained the same at 15 minutes per segment. The wait time of 15 minutes was selected based on wait times on the product labels, which varied from five minutes to two hr s, wit h the majority of labels indicating a wait time of 15 minutes.

Back

- to

- back stripping sequences with no overlapping activities were modeled because it is likely that the user will take breaks during the wait time. In the Riley survey ( Riley et al. , 200 1 )
, 65 percent of the participants reported taking breaks outside the work area and 20 percent of the participants reported taking breaks inside the work area, with break times ranging from five to 30 minutes. The number of breaks was not reported. Ad ditionally, 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.

6 See the following URL: http://furniture.about.com/od/furnishingdesignresources/a/measurements.htm

. 7 See the following URL for an illustrative chest of drawers with nearly the same dimensions: http://www.furnitureunfinished.com/product_info.php?cPath=116_135&products_id=1093

.

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### As an example, the timing of the entire sequen ce for a brush

- on application to the chest surface is shown in Table F

- 3. For this scenario, the table indicates a total duration of 21 minutes per segment or 168 minutes for the entire episode of product use. For the coffee table with half the number of segments, the duration of the episode was 84 minutes. For the bathtub scenario, the total durations increased to 24 minutes per segment or 192 minutes for the entire episode. For the spray

- on application (applicable to the coffee table and chest but not the tub), the application time was cut in half ( i.e. , from two minutes to one) while retaining the waiting time of 15 minutes and the scraping time of four minutes, resulting in slightly lower total durations than the brush

- on scenarios.

Table F

- 3. Time 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 Second 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

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 i s released to indoor air.

From the product list developed by Brown (2012 ) , the median DC M 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 we re 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 abo ve methods, then the product was assigned to the brush category, as 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 t he product list, then the average of the minimum and maximum weight fractions was used in calculations. The weight fractions were not weighted to reflect the market share of products.

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### Analysis of the US EPA (1994b ) data indicated DCM release fractions of 0.33 for brush

- on and 0.66 for spray

- on. The resultant mass released for the different application targets and methods is summarized in Table F

- 4.

Table F

- 4. DCM Mass Released, by Application Target and Method. Target (Surface Area) and Method Application Rate, g/ft 2a 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 Chest 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

a Reflects repeat application for each segment. b For the coffee

- table case, two weight fractions are given; one for central and one for near

- high

- end.



### Airflow Rates and Volumes. The model run requires conceptualization of a residence in terms of the number of zones and their respective volumes. The airflow rates needed to model the central and upper

- end scenarios described above are: (1) rates between indoors and outdoors for ea ch zone; and (2) rates between the zones. The occupational scenario simulation (tub stripping in bathroom), which is somewhat more complex to conceptualize, is described below, after the central and upper

- end scenarios.

For the central and upper

- end scen arios, the house in which the modeled stripper application occurs is conceptualized as having two zones: (1) the workshop where application occurs; and (2) the ROH. The house volume chosen for the model runs (492 m 3 

### ) was the central value listed in the EF H. The volume assigned to the in

- house workshop area was 54 m 3 

### , corresponding to a 12 ft × 20 ft with 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 v olume 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 bathtub scenario, the bathroom volume was set at 9 m 3 

### for consistency with that reported in CDC, 2012.

The indo or

- outdoor airflow for any zone of the house is governed by the choice of air exchange rate, in ACH. The central and low

- end values for the air exchange rate, 0.45/ hr and 0.18/ hr
, used in assigning the indoor

- outdoor airflow rate for the ROH are the mean and 10 th 

### percentile values, respectively, from the EFH. (Note that a low

- end ACH would be expected to contribute to upper

- end concentration estimates.) For the workshop, it was assumed that multiple windows were opened. T he indoor

- outdoor airflow rate a ssigned 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

-

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### exchange

- rate distribution from the EFH, thought to be a reasonable representation of the open

window case.

The use of open wi ndows in the room of use is supported by both label instructions and survey data. The majority of the labels indicate that adequate ventilation must be used and that, to prevent build

- up of vapors, windows and doors should be opened to achieve cross venti lation. Additionally, Pollack

- Nelson (1995 ) reported that an average of 70.7 percent of paint stripper users (all products) kept a window or door open during use based on data from the Westat Inc. (1987 ) survey and that 88.8 percent of paint stripper users (all products) kept a window or door open during use based on data from the Abt (1992 ) survey. The increase was significant between the survey years (before and after CPSC labeling requirements took effect). The more recent small 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 percenta ge of fan users was not reported in Pollack

- Nelson (1995 ) . The Riley et al. (2001 ) data suggest that only ~27 percent of the users who worked indoors used an open window and fan. Due to the small percentage of respondents who reported using a fan, coupled with the fact that some of labels indicate that the product should be kept away from heat, sparks, flame, and all other sources of ignition, none of the s cenarios were assumed to involve use of a fan in the room of product application.

The interzonal airflow rate was estimated using the following algorithm, developed by US EPA (1995a ) :

Q = (0.078 + 0.31*ACH) * house volume



### 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 corresponding number for the upper

- end scenario, with an air exchange rate of 0.18/ hr , was 65.8 m 3 

### / hr . Figure F

- 5 depicts the volumes and airflows that were used for the workshop scenarios.

Figure F

- 5. Zone Volumes and Airflow Rates for Workshop Scenarios.



### As previously mentione d, the bathroom scenario (Figure F

- 6) is more complex. Because the user is working in close proximity to the target (bathtub) for an extended period, a third zone Room of

Use (54 m 3 ) 68

m 3 /hr 107

m 3 /hr Rest of House (438 m 3 ) 197

m 3 /hr Central Values

Room of Use (54 m 3 ) 68

m 3 /hr 65.8

m 3 /hr Rest of House (438 m 3 ) 78.8

m 3 /hr Values for Upper

- end Concentration Scenarios

d enotes air flow

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### (“source cloud”) was created within the bathroom to represent the DCM concentrations in the vicinity of the tub; this is a virtual zone, with no physical boundaries. The airflow rate between the cloud and the rest of the bathroom was based on the study by Matthews et al. (1989 ) , who determined experimentally that such an airflow could be estimated as the product of the room air velocity (in m/ hr ) and the entry/exit surface area (in m 2 

### ). Using their suggested value of 65 m/ hr for air velocity together with an assumed entry/exit surface area of 5 ft by 2 ft (10 ft 2 

### or 0.93 m 2 

### ) yields an estimated airflow rate of 60 m 3 

### / hr between the source cloud and the rest of the bathroom. Based on professional judgment, the interzonal airflow rate between the bathroom and rest of the house was assumed to be ~2/3 lower than t hat for the workshop central scenarios, given the small bathroom volume. The indoor

- outdoor airflows were based on an assumed air exchange rate of 0.18 ACH.

Figure F

- 6. Zone Volumes and Airflow Rates for Bathroom Scenario.



### Locations of Exposed Indiv iduals. Two location patterns were specified, one for a product user and one for a non

- user. The user was assumed to be in the work area for stripper application and scraping for all scenarios. For the waiting phase of the stripping process, the user was assumed to be in the ROH as a central

- tendency assumption for the user (Scenarios 1 and 4), in the workshop as an upper

- end assumption for the user (Scenarios 2 and 5), and in the ROH for Scenarios 3, 6, and 7, which were developed to model upper

- end concentratio ns 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 is assumed to be aware of inhalation health concerns from the label warnings (“Vapor Harmful”) and b ecause some labels such as the Klean Strip® products specifically state 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 taki ng breaks outside the work area. Breaks typically involved a specific break activity and location, such as going to the kitchen and making a sandwich or going outside to do yard work. For the upper

- end Scenarios 2 and 5, it was assumed that the user woul d stay in the workshop, based on the fact that some people do not read/skim labels (~28 percent in 1990) d enotes 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

60

m 3 /hr

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### ( Pollack

- Nelson, 1995 ) and may therefore not be aware of health concerns or prec autionary techniques. Many labels do not specifically state to leave room during the wait period, and the Riley et al. (2001 ) survey indicated that 20 percent of participants reported taking breaks inside the work area. For all scenarios, the user was assumed to leave the workroom immediately after the stripping process, based on the Westat Inc. (1987 ) and Abt (1992 ) surveys with a median value of zero minutes spent in the room after using the product ( US EPA, 2011b )

.

The non

- user was assumed to be in the ROH throughout the model run, as was the user for the portion of the run after all applying/scraping was completed. For the bathroom scenario, the user was assumed to be in the ROH during the wait times.

It was further assumed that the scrapings were removed from the house as soon as scraping was completed for the last segmen t. The implication for modeling purposes is that any remaining DCM emissions would be truncated at that time. However, the modeled DCM emissions were not truncated as an expedience; given the high volatility of DCM (vapor pressure = 352.5 Torr), its emis sion rate would essentially drop to zero in a very short time, on the order of 10 minutes.

**F.4. Inhalation Model Outputs and Exposure Calculations** 

Personal Concentrations 

### Peak TWA concentrations for different averaging periods, described below, were calculated from the one

- minute averages for both the user and non

- user based on their respective personal concentration time series. The calculations took into account the possibility that the user can change zones within a one

- minute interval ( e.g. , at a n elapsed time of 6.25 minutes). The personal concentration was calculated for each one

- minute interval in the modeling period (24 hr s or 1,440 one

- minute intervals) as follows:

For each time interval, i to i +1 , for i = 0 to 1,440:

( F

- 9)



### Where: PC i,i+1 = the personal 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, illustrated in Figure F

- 7, were implemented in an Excel spreadsheet for each of the seven scenarios.

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Page 133 Figure F

- 7. Example of the Personal Concentration Calculation as Defined in Equation F

- 9. 

### TWA Concentrations In addition to the maximum one

- minute concentration and the 24

- hr average concentration to which the user and non

- user were exposed, a peak TWA personal concentration was calculated for each of the following averaging periods: 10 minutes, 30 minutes, one hr , four hr s, and eight hr s. The peak TWA concentration for any a veraging period was defined as the highest value of the consecutive running averages for that averaging period. For any averaging period, there are (1,440

– length of the averaging period) TWA concentration values within the 24

- hr (1,440

- minute) time seri es. 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.

Modeling Results The zone

- specific and personal concentrations predicted by MCCEM are presented in Figures F

- 8 though F

- 11 8 

### . Figure F

- 8 shows the zone

- specific and the user’s personal

- concentration results for Scenario 1 (brush application in the workshop with central parameter values, top two figures) and Scenario 4 (spray application) in the workshop using central parameter values. T he dips in the user’s personal concentration during the application periods reflect temporary relocation to the ROH (Zone 2) during wait times between applying and scraping. The non

user’s personal concentrations are the same as those in the ROH. As indi cated in Figure F

- 8, the peak concentrations are higher for the spray

- application scenario than those for the brush

application scenario, even though the mass of product applied is higher for brush application (900 g stripper applied for brush as compared to 680 g for spray). This difference is explained primarily by two factors: (1) the weight fraction of DCM in the stripper product (0.8 for the spray product as compared to 0.53 for the brush product); and (2) the higher fraction of the

8 Figures F

- 8 through F

- 11 are provided at the end of this section. Time Interval

= (D5 + D4) / 2

Fraction of Time Spent in Use Zone

= H5 * J5 + I5 * (1

- J5)

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Page 134 

### applied mass emitt ed, double that for the spray application as compared to the brush application ( i.e. , 66 percent as compared to 33 percent) based on analysis of the US EPA (1994b ) chamber data. As a result, the DCM mass emitted for the spray stripping is ~2.25 times as high as the mass released during the brush stripping (6 80 g × 0.8 × 0.66 = 359 g for the spray activity as compared to 900 g × 0.53 × 0.33 = 160 g for the brush activity).

Other than the mass of DCM emitted and some minor differences in application time, Scenarios 1 and 4 are identical, which leads to a simil ar ratio in air concentrations. For example, for Scenario 4, the peak concentration in Zone 1 is 1,800 mg/m 3 

### , whereas the peak for Scenario 1 is 780, a ratio of 2.30. The similar ratios for applied mass and resultant peak air concentration apply when oth er model inputs, such as room volumes and air exchange rates, are kept at the same or similar values. The shape of the user’s personal concentration profile reflects the location of the user at various times during the stripping, waiting, and scraping
act ivities.
Figure F

- 9 shows the zone and user personal concentration results for Scenarios 2 and 5 (brush and spray application, respectively) for the workshop with parameter values selected to estimate upper

- end concentrations for the user. In this compar ison, the emitted DCM mass is 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 have a ratio (1.54) that is similar to that for the applied mass.
Figure F

- 10 shows the zone and user personal concentration results for Scenarios 3 and 6 (brush and spray application, respectively) for the workshop with parameter values selected to estimate upper

- end concentrations for the non

- user as well as the user . In this comparison, the
spray

- to

- brush ratio of ~1.5 for applied mass translates directly to the 24

- hr TWA concentration to which the non

- user is 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 worksho p vs . 0.18/ hr for the ROH. Due to the higher dilution rate, the workshop concentrations fall more quickly after the stripping activity is completed than do the concentrations in the ROH.
Figure F

- 11 shows the air concentrations for the simulation scenari o, namely the bathtub stripping activity with a modeled peak concentration of ~3,500 mg/m 3 

### . The saw

- tooth appearance of the concentration rise associated with the stripping activity

— particularly pronounced in this scenario but evident in the other scenari os as well

— is due to the eight application segments. Scenario 7 was intended, in part, to simulate the situation described in a CDC/NIOSH case fatality assessment ( CDC , 2012a , b ) . The modeled peak concentration reported here for Scenario 7, on the order of 1,000 ppm, is substantially lower than that calculated (155,000 ppm) for the fatality assessment, but the value repo rted by CDC/NIOSH was a bounding estimate obtained by assuming that all DCM mass is released instantaneously. By comparison, monitoring of a bathtub application by Washington State Occupational Safety and Health staff, as described in the CDC/NIOSH report , indicated a 15

- minute TWA personal concentration for the applicator on the order of 2,000 ppm.

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b) Scenario 4, Spray Applied

Figure F

- 8. Modeled DCM Concentrations for Scenarios 1 and 4, Stripper Application in Workshop using Central Parameter Values. (Non

- user assumed to be in ROH)

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b) Scenario 5, Spray Applied

Figure F

- 9. Modeled DCM Concent rations for Scenarios 2 and 5, Stripper Application in Workshop using Parameter Values selected for Upper

end User’s Exposure. (Non

- user assumed to be in ROH)

(Non

- user assumed to be in ROH)

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Page 137 a) Scenario 3, Brush Applied

b) Scenario 6, Spray Applied

Figure F

- 10. Modeled DCM Concentrations for Scenarios 3 and 6, Stripper Application in Workshop using Parameter Values Selected for Upper

- End

- user’s and Non

- user’s Exposure. (Non

- user assumed to be in ROH)

(Non

- user assumed to be in ROH)

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- 11. Modeled DCM Concentrations for Scenario 7, Brush Application in Bathroom (Simulation). (Non

- user assumed to be in ROH)

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### F.5. **MCCEM Inhalation Modeling Scenario Summaries**

Formula: CH2Cl2 CAS Number: 75

- 09

- 2 Molecular Weight: 84.93 g/mol Density: 1.33 g/cm 2 (liquid) Appearance colorless liquid Melting Point:

- 96.7 deg C =

- 142 deg F = 176 K Boiling Point: 39.6 deg C = 103 deg F = 313 K Solubility in Water: 13 g/L @ 20 deg C Vapor Pressure: 47 kPa = 352.535 Torr = 0.4639 atm = 6.817 psi Conversion units: 1 ppm = 3.4736 mg/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 fraction) × 0.33 (release fraction) = 157.4 g For each of the 4 application sections: k = 10/hr Mass = 157.4/4 = 39.35 g Eo = Mass * k = 393.5 g/hr ( NOTE: only k and Mass are needed as MCCEM inputs) Application Times by Section:

Episode Elapsed time from time zero, minutes

Apply Wait Scrap

e 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

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Page 140 second 1/2, 2nd time 63

- 65 min 65

- 80 min 80

- 84 min

Model Run Time: 0

- 24 hr s User takes out scrapings after 84 minutes, emissions truncated Activity Patterns: User in workshop during appl ication and scrape periods, in ROH during wait periods User in ROH for the remainder of the run (22 hr s, 36 minutes)

MCCEM Results Summary Personal Exposures (maximum values over first 24 hr s):

In mg/m 3
Individ ual 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 Individ ual 1 min 10 min 30 min 1 hr 4 hr 8 hr 24 hr User 182.1 108.3 77.6 64.5 34.7 19.7 6.7 Other 37.9 37.8 37.3 35.6 23.6 14.1 4.8

Plots:

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Page 142 DCM Scenario 2. Coffee Table, Brush

- On, Workshop, User in Workshop during wait time, 0.45 ACH, 0.88 Weight Fraction

MCCEM Input Summary Application Method: Brush

- on Volumes: Workshop volume = 54 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 × 0.88 (wt fraction) × 0.33 (release fraction) = 261.4 g For each of the 4 application sections: k = 10/hr Mass = 261.4/4 = 65.35 g Eo = Mass * k = 653.5 g/hr ( NOTE: only k and Mass are needed as MCCEM inputs) Application Times by Section:

Episode Elapsed time from time zero, minutes Apply Wait Scrape
first 1/2, 1st time 0

- 2 min 2

- 17 min 17

- 21 min
second 1/2, 1st time 21

- 23 min 23

- 38 min 38

- 42 min
first 1/2, 2nd time 42

- 44 min 44

- 59 min 59

- 63 min
second 1/2, 2nd time 63

- 65 min 65

- 80 min 80

- 84 min

Model Run Time: 0

- 24 hr s User takes out scrapings after 84 minutes, emissions truncated Activity Patterns: User in workshop during appl ication , wait and scrape periods User in ROH for the remainder of the run (22 hr s, 36 minutes)

MCCEM Results Summary Personal Exposures (maximum values over first 24 hr s):

In mg/m 3

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Page 143 Indivi dual 1 min 10 min 30 min 1 hr 4 hr s 8 hr

s 24 hr

s User 1,292.4 1,251.7 1,136 .7 1,058 .0 416.7 223. 8 75.3

Other 218.7 218.3 215.1 205.6 136.3 81.5 27.9

In ppm Individ ual 1 min 10 min 30 min 1 hr 4 hr s 8 hr s 24 hr

s 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

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Page 145 DCM Scenario 3. Chest, Brush

- On, Workshop, User in ROH during wait time, 0.18 ACH, 0.88 Weight Fraction

MCCEM Input Summary Application Method: Brush

- on Volumes: Workshop volume = 54 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 = 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 M ass = 653.4/8 = 81.675 g Eo = Mass * k = 816.75 g/hr ( NOTE: only k and Mass are needed as MCCEM inputs) Application Times by Section:

Episode Elapsed time from time zero, minutes Apply Wait Scrape

first 1/4, 1st time 0

- 2 min 2

- 17 min 17

- 21 min

second 1/4, 1st time 21

- 23 min 23

- 38 min 38

- 42 min

third 1/4, 1st time 42

- 44 min 44

- 59 min 59

- 63 min

fourth 1/4, 1st time 63

- 65 min 65

- 80 min 80

- 84 min

first 1/4, 2nd time 84

- 86 min 86

- 101 min 101

- 105 min

second 1/4, 2nd time 105

- 107 min 107

- 122 min 122

- 126 min

third 1/4, 2nd time 126

- 128 min 128

- 143 min 143

- 147 min

fourth 1/4, 2nd time 147

- 149 min 149

- 164 min 164

- 168 min

Model Run Time: 0

- 24 hr s

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Page 146 User takes out scrapings after 168 minutes, emissions truncated Activity Patterns: User in workshop during appl ication and scrape periods, in ROH during wait periods User in ROH for the remainder of the run (21 hr s, 12 minutes)

MCCEM Results Summary Personal Exposures (maximum values over first 24 hr s):

In mg/m 3
Indivi dual 1 min 10 min 30 min 1 hr 4 hr s 8 hr s 24 hr

s 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 Individ ual 1 min 10 min 30 min 1 hr 4 hr s 8 hr s 24 hr

s 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

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Page 148 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
1 Wait Scrap

e 1
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 hr s User takes out scrapings after 80 minutes, emissions truncated Activity Patterns: User in workshop during appl ication and scrape periods, in ROH during wait periods User in ROH for the remainder of the run (22 hr s, 40 minutes)

MCCEM Results Summary Personal Exposures (maximum values over first 24 hr s):

In mg/m 3
Individ 1 min 10 30 1 hr 4 hr s 8 hr s 24

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Page 149 ual min min hr s 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 Individ ual 1 min 10 min 30 min 1 hr 4 hr s 8 hr s 24 hr

s 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

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Page 151 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 product mass = 68 g/sq ft = 680 g DCM mass = 680 g × 0.87 (wt fraction) × 0.66 (release fraction) = 390.5 g For each of the 4 application sections: k = 10/hr Mass = 390.5/4 = 97.625 g Eo = Mass * k = 976.25 g/hr ( NOTE: only k and Mass are needed as MCCEM inputs) Application Times by Section:

Episode Elapsed time from time zero, minutes Apply

1 Wait Scrap

e 1
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 hr s User takes out scrapings after 80 minutes, emissions truncated Activity Patterns: User in workshop during appl ication , wait and scrape periods User in ROH for the remainder of the run (22 hr s, 40 minutes)

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Page 152 MCCEM Results Summary Personal Exposures (maximum values over first 24 hr s):

In mg/m 3
Indivi dual 1 min 10 min 30 min 1 hr 4 hr s 8 hr s 24 hr

s User 1,99 1.0 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 Individ ual 1 min 10 min 30 min 1 hr 4 hr s 8 hr s 24 hr

s 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

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Page 154 DCM Scenario 6. Chest, Spray

- On, Workshop, User in ROH during wait time, 0.18 ACH, 0.87 Weight Fraction

MCCEM Input Summary Application Method: Spray

- on Volumes: Workshop volume = 54 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 M ass = 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 hr s User takes out scrapings after 160 minutes, emissions truncated

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MCCEM Results Summary Personal Exposures (maximum values over first 24 hr s):

In mg/m 3
Indivi dual 1 min 10 min 30 min 1 hr 4 hr s 8 hr

s 24 hr

s User 2,82 1.3 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 Individ ual 1 min 10 min 30 min 1 hr 4 hr s 8 hr s 24 hr

s 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

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Page 157 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 m 3 Rest of Bathroom volume = 9

- 1 = 8 m 3 ROH volume = 492

– 9 = 483 m 3 Airflows: Source Cloud

Bathroom 60 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/sq ft = 3,240 g DCM mass = 477 g × 0.1.0 (wt fraction) × 0.33 (release fraction) = 157.4 g For each of the 8 application sections: k = 10/hr Mass = 157.4/8 = 19.7 g Eo = Mass * k = 197 g/hr ( NOTE: only k and Mass are needed as MCCEM inputs) Application Times by Section:

Episode Elapsed time from time zero, minutes Apply Wait Scrape
first 1/4, 1st time 0

- 3 min 3

- 18 min 18

- 24 min
second 1/4, 1st time 24

- 27 min 27

- 42 min 42

- 48 min
third 1/4, 1st time 48

- 51 min 51

- 66 min 66

- 72 min

fourth 1/4, 1st time 72

- 75 min 75

- 90 min 90

- 96 min
first 1/4, 2nd time 96

- 99 min 99

- 114 min 114

- 120 min
second 1/4, 2nd time 120

- 123 min 123

- 138 min 138

- 144 min
third 1/4, 2nd time 144

- 147 min 147

- 162 min 162

- 168 min
fourth 1/4, 2nd time 168

- 171 min 171

- 186 min 186

- 192 min

Model Run Time:

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- 24 hr s User takes out scrapings after 192 minutes, emissions truncated Activity Patterns: User in source cloud during appl ication and scrape periods, in ROH during wait periods User in ROH for the remainder of the run (20 hr s, 48 minutes)

MCCEM Results Summary Personal Exposures (maximum values over first 24 hr s):

In mg/m 3
Indivi dual 1 min 10 min 30 min 1 hr 4 hr s 8 hr s 24 hr

s User 2,684. 7 1,545.7 938.2 843.7 563.9 354.0 140.2

Other 223.7 223.6 222.2 218.2 186.8 149.5 69.5

In ppm Individ ual 1 min 10 min 30 min 1 hr 4 hr s 8 hr s 24 hr

s User 772.9 445.0 270.1 242.9 162.3 101.9 40.4 Other 64.4 64.4 64.0 62.8 53.8 43.0 20.0

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### Appendix G : Human Health Toxicity Summary

The information presented in this section is not intended to be an exhaustive discussion of DCM’s toxicity, but rather a summary of its toxicity via the inhalation route of exposure. Thus, the reader is referred to the original documents for detailed toxicity data supporting the summary presented in this document.

A two

- generation inhalation exposure to DCM revealed no significant effects on reproductive performance in rats (up to 1,500 ppm) ( Nitschke et al. , 1988b ; as cited in US EPA, 2011b )

. Some evidence of a decrease in fertility index was seen in male mice exposed to 150 and 200 ppm ( Raje et al. , 1988 ; as cited in US EPA, 2011b ) , and no adverse effects on fetal development of mice or rats expo sed to up to 1,250 ppm were seen by Schwetz et al. (1975 ); ( as cited in US EPA, 2011b ) . Dec reases in fetal body weight and changes in behavioral habituation were observed in offspring of Long

- Evans rats exposed to 4,500 ppm during the gestational period ( Bornschein et al. , 1980 ; Hardin and Manson, 1980 ; as cited in US EPA, 2011b )

.
Exposure

- related non

- cancer effects on the lungs consisted of foreign

- body pneumonia in rats exposed to 8,400 ppm, six hr s/day for 13 weeks ( NTP, 1986 ; as cited in US EPA, 2011b ) . Several neurological mediated parameters, including decreased activity ( Kjellstrand et al. , 1985 ; Weinstein et al. , 1972 ; Heppel and Neal, 1944 ; Heppel et al. , 1944 ; as cited in US EPA, 2011b )
, impairment of learning and memory ( Alexeeff and Kilgore, 1983 ; as cited in US EPA, 2011b ) , and changes in responses to sensory stimuli ( Rebert et al. , 1989 ; as cited in US EPA, 2011b ) , are reported fro m acute and short

- term DCM exposure. Evidence of a localized immunosuppressive effect in the lung resulting from inhalation DCM exposure was seen in an acute exposure (three hr s, 100 ppm) study in CD

- 1 mice ( Aranyi et al. , 1986 ; as cited in US EPA, 2011b )

. DCM is “likely to be carcinogenic in humans” under the Guidelines for Carcinogen Risk Assessment ( US EPA, 2005 ; as cited in US EPA, 2011b ) . Results from two

- year bioass ays provide adequate evidence of the carcinogenicity of DCM in mice and rats exposed by inhalation, as well as adequate data to describe dose

- response relationships. Oral exposure to DCM produced statistically significant increases in hepatocellular adeno mas and carcinomas in male B6C3F1 mice ( Serota et al. , 1986 ; Hazleton Laboratories, 1983 ; as cited in US EPA, 2011b )

. Inhalation exposure to concentrations of 2,000 or 4,000 ppm DCM produced increased incidences of lung and liver tumors in male and female B6C3F1 mice ( Maronpot et al. , 1995 ; Foley et al. , 1993 ; Kari et al. , 1993 ; Mennear et al. , 1988 ; NTP, 1986 ; as cited in US EPA, 2011b )

. Significantly increased incidences of benign mammary tumors (adenomas or fibroadenomas) were observed in male and female F344/N rats exposed by inhalation to 2,000 or 4,000 ppm ( NTP, 1986 ; Mennear et al. , 1988 ; as cited in US EPA, 2011b )

.

While not statistically significant an increased incidence of CNS tumors w as observed in a two

year study using relative ly low exposure levels (0, 50, 200, and 500 ppm) in Sprague

- Dawley rats observed a total of six astrocytoma or glioma (mixed glial cell) tumors in the exposed
groups ( Nitschke et al. , 1988a ; as cited in US EPA, 2011b ) . These tumors are exceedingly rare in

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### rats, and there are few examples of statistically significant trends in animal bioassays ( Sills et al. , 1999 ; as cited in US EPA, 2011b ) . Studies i n humans also provide evidence for an association between occupational exposure to DCM and increased risk for some specific cancers, including brain cancer ( Hearne and Pifer, 1999 ; Heineman et al. , 1994 ; Tomenson, 2011 ; as cited in US EPA, 2011b ) , liver cancer ( Lanes et al. , 1993 ; Lanes et al. , 1990 ; as cited in US EPA, 2011b ) , non

- Hodgkin lymphoma ( Barry et al. , 2011 ; Wang et al. , 2009 ; Seidler et al.
, 2007 ; Miligi et al. , 2006 ; as cited in US EPA, 2011b ) , and multiple myeloma ( Gold et al. , 2011 ; as cited in US EPA, 2011b )

. The hypothesized mode of action for DCM

- induced lung and liver tumors is through a mutagenic mode of carcinogenic action. Key events within this hypothesis are: (1) DCM metabolized via glutathione S

- transferase (GST) metabolism, with increasing metabolism through this pathway with increasing exposure levels above the saturation of cytochrome P450 enzyme (CYP2E1); (2) reaction of GST

- pathway metabolites with deoxyribonucleic acid (DNA), leading to (3) mutations i n critical genes that result in tumor initiation; and (4) tumor growth promoted by unidentified molecular or cellular events. In this proposed mode of action, metabolism by CYP2E1, which is more predominant at lower exposures (or tissues concentrations) t han metabolism by GST, is considered a protective mechanism against the formation of putatively carcinogenic metabolites from the GST pathway ( US EPA, 2011b )

. The weight of evidence from a large collection of in vivo and in vitro studies support the proposed mutagenicity of DCM and the key role of GST metabolism and the formation of DNA

reactive GST

- pathway metabolites. The data pertaining to chromosomal damage provide greater weight to this collection of evidence than the indicator genotoxicity assays; among chromosomal damage studies, in vivo evidence provides greater weight than in vitro evidence ( US EPA, 2011b ) . The database for DCM provides support along each of these lines: (1) in vivo evidence of chromosomal mutations (chromosomal aberr ations) in the mouse lung and peripheral red blood cells in the absence of evidence of cytoxicity (these observations were not seen in the mouse bone marrow, a site that would be expected to be much more limited in terms of degree of DCM metabolism); (2) i n vitro chromosomal instability evidence in human cells, other mammalian cells ( i.e. , Chinese hamster ovary cell [CHO]), and bacterial systems; and (3) positive DNA damage assays in numerous in vivo and in vitro studies ( US EPA, 2011b ) . As noted previously, unscheduled DNA synthesis is generally a relatively insensitive measure of genotoxicity, and is given little weight in this synthesis of the data. Available studies also demonstrate target tissue specificity, with DNA

- protein cross

- links, single

- stranded DNA

binding proteins (DNA SSBs), and sister chromatid exchanges seen in liver and lung cells of B6C3F1 mice following a cute inhalation exposure to concentrations producing liver and lung tumors with chronic exposure ( Casanova et al. , 1996 ; Casanova et al. , 1992 ; Graves et al.
, 1995 ; Allen et al. , 1990 ; as cited in US EPA, 2011b ) . Dose

- response concordance and temporality have also been seen, with evidence of mutagenicity (as determined by the micronucleus test or presence of chromosome aberrations) and genotoxicity ( as determined by the presence of DNA

- protein cross links or DNA SSBs) at the exposure levels inducing liver tumors in B6C3F1 mice ( NTP, 1986 ; as cited in US EPA, 2011b ) . Similar results were seen in inhalation exposure

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### studies in liver and lung cells of B6C3F1 mice in studies using the dose range used in the NTP (1986 ) study ( US EPA, 2011b )

. Certain human subpopulations may be more susceptible to exposure to DCM than others. One basis for this conc ern is the potential effect of COHb, a metabolic byproduct of DCM exposure. The COHb generated from DCM is expected to be additive to COHb from other sources. Thus, DCM exposure at high concentrations may pose an additional human health burden. Of parti cular concern are smokers (who maintain significant constant levels of COHb) and persons with existing cardiovascular disease. In addition, higher

- than

- normal levels of CO may result when alcoholics are exposed to DCM, since ethanol increases the expressi on and activity of CYP2E1 ( Carpenter et al. , 1996 ; as cited in ATSDR, 2000 ) . Similarly, enhanced expression of CYP2E1 occurs in the condition of diabetes, although insulin erases that effect ( Thomas et al.
, 1987 ; as cited in ATSDR, 2000 )

.
Varying sus ceptibility to DCM may be correlated with polymorphism in its metabolizing enzymes. Genetic polymorphisms have been identified for both glutathione S

- transferase theta

- 1 and CYP2E1 ( Garte and Crosti, 1999 ; as cited in ATSDR, 2000 ) , and the health consequences of these variants are being investigated ( d'Errico et al. , 1999 ; Lang and Pelkonen, 1999 ; Pelkonen et al. , 1999 ; Strange and Fryer, 1999 ; Stubbins and Wolf, 1999 ; as cited in ATSDR, 2000 )

. Hemoglobin in the fetus has a higher affinity for CO than does adult hemoglobin. Thus, the neurotoxic and cardiovascular effects may be exacerbated in fetuses and in infants with higher residual levels of fetal hemoglobin when exposed to high concentratio ns of DCM ( OEHHA, 2001 ) . For repeated exposures, steady

- state considerations te nd to eliminate the difference between children and adults after a short time ( ATSDR, 2000 )

.

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### Appendix H : Human Health Dose

- Response Assessment

The reader is referred to the IRIS as sessment ( US EPA, 2011b ) , the Acute Exposure Guideline Levels technical support document ( US EPA, 2008 ) , the Technical Support Document Supporting the California’s Acute Reference Exposure Level and the National Academies’ Spacecraft Maximum Allowable Concentrations for Sele cted Airborne Contaminants (Volumes 2 and 5; NRC, 1996 , 2008 ) for detailed explanations of toxicological studies and derivation approaches for these values.

AEGLs Air concentrations of DCM may reach dangerous levels in enclosed environments when individuals are using DCM

- based paint strippers on a single daily use. Thus, air concentration thresholds for disability (AEGL

- 2) are compared with the inhalation exposure estimates for residential users 9 

### and other residential occupants ( e.g. , children). This risk assessment retained the same POD and UFs used in the AEGL derivations.

AEGLs represent threshold exposure limits for the general public, including infants and children as well as other individuals who may be sensitive or susceptible. They are applicable for once

in

- a

- lifetime acute exposures ( i.e. , ≤24 hr s) to airborne concentrations of highly toxic chemicals typically occurring during emergency response situations. AEGL values are developed for three different health effect end point tiers (discomfort = AEGL

- 1 threshold; disability = AEGL

- 2 threshold; and death = AEGL

- 3 threshold) at different durations of exposure (10 minutes; 30 minutes; one hr ; four hr s; and eight hr s). Figure H

- 1 depicts the three AEGL tiers and the associated health effects.

Two t oxic endpoints were of importance for setting the AEGL

- values with PBPK modeling: CNS depression caused by the concentration of the parent compound in brain and the formation of COHb from the CO metabolite. A GST isozyme is responsible for the metabolic pathway yielding CO. It is estimated that 20 percent of the US population lack this enzyme resulting in higher COHb levels in enzyme

- deficient individuals ( US EPA, 2008 )

. CNS effects are expected to occur soon after the onset of exposure, while peak levels of COHb can be reached hr s after cessation of exposure. Likewise, it was expected that the toxic endpoint of interest would change over an exposure range of 10 minutes to eight 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 ( US EPA, 2008 )

.

9 A user is defined as an individual(s) applying the product such as a DIY homeowner or a professional contractor. Other residential occupants are defined as other individual(s) present in the house that are not involved in the paint

- stripping activity and are located in a house zone other than the one in which the paint

- stripping activity is taking place (see Exposu re section).

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.
Figure H

- 1. Illustration of the Different AEGL Threshold 10 Levels.



### 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 

### ) led to light

- headedness and difficulties in enunciation ( Stewart et al. , 1972 ; as cited in US EPA, 2008 )

. These effects were absent at a

one

- hr exposure to 514 or 515 ppm (1,836 or 1,839 mg/m 3 

### ). The concentration of 514 ppm was used as the POD for the AEGL

- 1 derivations. These effects could be attributed to the DCM concentration in the brain rather than to CO ( US EPA, 2008 ) . A PBPK model estimated that 0.063 mM was the human brain concentration of DCM following a one

- hr exposure to 514 ppm. Since susceptibility for gross CNS

- depressing effects do not vary by more than a factor of two

to three

- fold in humans, an intraspecies UF of three was applied, resulting in a maximum target concentration of DCM in the human brain o f 0.021 mM. The human PBPK model used this concentration to estimate the AEGL values for the different time durations ( i.e. , 10 minutes to eight hr s). Because the calculated AEGL

- 1 values at four and eight hr s (160 and 140 ppm, respectively) were at or a bove the corresponding AEGL

- 2 values, no AEGL

- 1 values for these time periods were recommended ( US EPA, 2008 )

.

10 AEGLs are considered threshold levels that represent an es timated point of transition and reflect the best efforts to establish quantitat ively a demarcation between one defined set of symptoms or adverse effects and another defined set of sy mptoms or adverse effects ( NRC, 2001 )

.

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### AEGL

- 2 derivations were estimated for CNS effects based on a human study reporting the absence of AEGL

- 2 related CNS effects 11 

### during a DCM exposure to 751 ppm (2,682 mg/m 3 

### ) for 230 minutes ( Winneke, 1974 ; as cited in US EPA, 2008 ) . A PBPK model estimated that 0.137 mM was the human brain concentration of DCM. AEGL

- 2 values were also estimated for the formation of COHb formation, assuming a maximum COHb level of four percent in patient s with coronary artery disease humans ( NRC, 2010 ) . PBPK modeling was used to calculate exposure concentrations for both types of effects ( i.e. , CNS effects and COHb formation). The lowest value selected as the AEGL

- 2 value for each time period. An intraspecies UF of one for the CNS effects was considered sufficient since the toxic effects studied were less severe than those defined for AEGL

- 2 and the application of a greater value would result in values that were inconsistent with the available human data. Similarly, an intraspecies UF of one was applied for the effects associated to COHb formation because the POD was based on experimental data on the most susceptib le individuals ( i.e. , coronary artery disease patients), which is also protective for other human subpopulations ( NRC, 2010 )

.

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 four hr s ( Haskell Laboratory, 1982 ; as cited in US EPA, 2008 ) . A rat PBPK model estimated that 3.01 mM was the maximum target DCM concentration in rat brain. AEGL

- 2 values were also estimated for the formation of COHb formation, assuming a maximum COHb level of approxim ately 15 percent in humans ( NRC, 2010 ) . PBPK modeling was used to calculate exposure concentrations for both types of effects. The lowest value selected as the AEGL

- 2 v alue for each time period. An interspecies UF of one for the CNS effects was considered to be sufficient since the differences in susceptibility regarding mortality between species appear to be very small and because a human PBPK model is used to calculat e the external human exposure ( US EPA, 2008 ) . An intraspecies UF of three was applied since the susceptibility for CNS

- depressing effects is not expecte d to vary by more than a factor of two

- to three

- fold in the human population ( US EPA, 2008 ) . Application of an overall UF of three results in a maximum target DCM concentration in human brain of 1.0 mM. Similarly, an intraspecies factor of three was applied for the effects associated to COHb formation because the POD was supported by information on effects, such as myocardial infarction and stillbirths, reported in more susceptible subpopulations ( NRC, 2010 )

. AEGLs are designed for once

- in

- a

- lifetime exposures to airborne chemicals. However, a single exposure may not be realistic for a user exposed to DCM

- based strippers on an intermittent basis 12 

### . On this basis, it could be argued that they are not appropriate to evaluate the risks of DCM

- based paint strippers. DCM’s short half

- life and recent reports of human fatalities led us to focus the analysis on a single daily use of the paint stripping p roduct. DCM’s plasma half

- life is estimated to be 40 minutes after inhalation exposure ( DiVincenzo et al. , 1972 ; as cited in ATSDR, 2000 )

. DCM

- based paint stripping products have caused fatal acute exposures among

11 This is an effect level and should not be considered as a NOAEL.
12 Intermittent exposures cou ld be short

- term, subchronic
, or chronic with the key characteristic that the exposure is discontinuous ( Felter et al. , 2011 )

. The gap of time between exposures would be sufficiently long to prevent that the steady

- state levels of the chemical would not be achi eved or maintained ( Felter et al. , 2011 )

.

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### bathtub refinishers ( CDC, 2012b ) . Such real

- life situations support our current approach of using the AEGLs to determine if levels would surpass the AEGL

- 2 threshold for disability.

California’s Acute REL Risks to acute intermittent exposures in users and other residential occupants ( e.g. , children) are evaluated with the one

- hr acute REL developed by OEHHA. This risk assessment retained the same POD and UFs used in the acute REL derivations.

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, exposed on an intermittent basis ( OEHHA, 1999 ) . Since safety factors are incorporated to address data gaps and uncertainties, exceeding the REL does not automatically indicate an

a dverse health impact ( OEHHA, 1999 )

. OEHHA developed a one

- hr acute REL based on Putz et al. (1979 ) . The study reported significant performance decrements on dual

- task and auditory vigilance tests in volunteers (n = 12) exposed to 195 ppm DCM (696 mg/m 3 

### ) for 1.5 hr s ( Putz et al. , 1979 ; as cited in OEHHA, 2008 ) . 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 six was applied to the LOAEL 13 

### to develop a NOAEL and an intraspecies UF of 10 was applied to account for variability in the human populatio n. An equivalent one

- hr exposure was estimated from the 1.5

- hr exposure using the ten Berge equation (C n 

### * T = k, n = 2) resulting in a

one

- hr acute REL of four ppm (14 mg/m 3 

### ). The rationale for the choice of n = 2 was not documented in the OEHHA documen t.

SMAC SMACs are developed by NAS to provide guidance on chemical exposures that may occur during normal operations of spacecraft as well as emergency situations ( NRC, 1996 ) . This analysis is using 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 re sidential occupants that may be indirectly exposed ( e.g. , children). However, this risk assessment is applying an intraspecies UF of 10 to the SMAC’s POD to make it relevant to our exposure scenarios.

The one

- hr SMAC is the concentration of DCM that will not compromise the performance of specific tasks by healthy astronauts during emergency conditions or cause serious or permanent toxic effects. SMACs are designed for healthy individuals, and reversible effects might occur but they are not expected to im pair 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.

13 The acute REL documentation does not provide the justification for why a factor of six was selected over other possible value.

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### The following paragraphs were extract ed from NRC (1996 ) and explain the dose

- response evaluation leading to the selection of 100 ppm (350 mg/m 3 

### ) as the one

- hr SMAC:

“... one of the major acute effects of methylene chloride is CNS depression, which appears to be due to CO formed from methylene chloride's metabolism. A 4

- hr exposure to methylene chloride at 200 ppm, which yields 5% COHb in blood, imp airs the hand

- eye coordination and auditory vigilance ( Peterson, 1978 ) , but there are no data on the no

- observed

- adverse

- effect level (NOAEL) of methylene chloride. It makes sense to adopt the NOAEL of COHb used in setting the 1

- h and 24

- h SMACs of CO as a potential basis for setting the 1

- h and 24

- h SMACs of methylene chloride. Three percent COHb is the target COHb concentration used to set both the 1

- h and 24

- h SMACs for carbon monoxide ( Wong, 1990 ) . The task here is to determine the methylene chloride concentrations that produce about 3% COHb in 1 and 24 hr. Assuming a baseline COHb concentration of 0.6% due to endogenous CO production, the task is to determine the methylene chloride

conce ntrations 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 C x T by forcing the fitted line through the origin. All th e data in the above table 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 slo pe 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 

### ) is considered a NOAEL ( NRC, 2008 ) for CNS effects associated to COHb formation and is used as the POD for acute inhalation risk estimates. The application of UFs was not included in the derivation of the one

- hr SMAC value, which is consistent with the intended purpose of the SMA C values. 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 three percent COHb is considered protective of neurotoxic effects in most in dividuals ( 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 two or four percent, patients with coronary artery disease may experience a reduced time until onset of angina (chest pain) during physical exertion ( Allred et al. , 1989a ; Allred et al. , 1989b , 1991 ; as cited in NRC, 2010 ) . 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 ( Aronow et al. , 1972 ; Anderson et al. , 1973 ; Sheps et al. , 1987 ; Kleinman et al. , 1989 ; Kleinman et al.
, 1998 ; as cited in NRC, 2010 ) . Fetuses are at higher risk for CO toxicity because of higher CO affinity and slower CO elimination ( NRC, 2010 ) . There are no studies reporting effects on the unborn after a single acute exposure resulting in lower COHb levels ( US EPA, 2000 ; as cited in NRC, 2010 )

.

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### EPA’s RfC Non

- cancer risks to chronic inhalation exposures in small

- shop workers are evaluated with the EPA’s RfC. The RfC is defined as the estimate (with uncertainty spa nning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime.

Liver lesions characterized by he patic vacuolation are commonly reported in rodents repeatedly exposed to DCM by inhalation. The chronic RfC was based on a NOAEL of 200 ppm for hepatocyte vacuolation in female rats exposed to DCM for six hr s/day, five days/week for two
years ( Nitschke et al. , 1988a ; as cited in US EPA, 2011b ) . A rat PBPK model was used to estimate rat internal doses from the Nitschke et al. (1988a ) study. The rat internal doses and their corresponding incidence data for hepatic effects (hepatic vacu olation) were used to estimate the rat internal lower 95 percent confidence limit of the 10 percent benchmark dose (BMDL 10 

### ) ( US EPA, 2011b ) . Because the dose

- metric is a rate of metabolism and the clearance of these metabolites may be slower per volume tissue in the human compared with the rat, the rodent internal dose

- metric was adjusted by dividing by a pharmacokinetic all ometric scaling factor of BW 0.75 

### (operationalized as [BW human 

### /BW rat 

### ] 0.25 

### ≈ 4.09) to obtain a human equivalent internal BMDL 10 

### ( US EPA, 2011b ) . The human equivalent internal BMDL 10 

### was then converted to the human equivalent concentration (HEC) using a human PBPK model that provided a distribution of HECs. The 1 st 

### percentile of the distribution of HECs, 17.2 mg/m 3



### , was used as a POD for the RfC ( US EPA, 2011b )

. The POD was divided by a total UF of 30 to obtain a chronic RfC of 0.6 mg /m 3 

### . PBPK modeling supported the reduction of the default inter

- and intraspecies UFs. A factor of three was used to account for the toxicodynamic uncertainty of the animal to human extrapolation. Similarly, a factor of three was applied to account for possible toxicodynamic differences in sensitive humans. Another factor of three was used to address deficiencies in the DCM toxicity database at chronic low exposures.

EPA’s IUR EPA has concluded that DCM is carcinogenic by a mutagenic mode of action ( US EPA, 2011b )

. The EPA IUR (assuming a 70

- year human lifetime) is used to estimate cancer risks for chronic inhalation exposures in small

- shop workers. The IUR was derived from mouse liver and lung tumor incidence data ( Mennear et al. , 1988 ; NTP, 1986 ; as cited in US EPA, 2011b )

. A mouse PBPK model was used to calculate long

- term daily average internal liver doses. The selected internal dose

- metrics for liver tumors and lung tum ors were long

- term average daily mass of DCM metabolized via the GST pathway per unit volume of liver and lung, respectively. This approach was taken based on evidence that GST

- pathway metabolites produced from DCM are primarily responsible for its carcin ogenicity in mouse liver. The multistage dose

- response model (Benchmark Dose Software [BMDS] version 2.0) was used to fit the mouse liver tumor incidence and PBPK model

- derived internal dose data and to derive a mouse internal BMD and

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### BMDL 10 

### ( US EPA, 2011b ) . Because the metric is a rate of metabolism rather than the concentration of putative toxic metabolites, and data pertaining to the reactivity or clearance rate of the relevant metabolite(s) are lacking, the human BMDL 10 

### was derived by multiplying the mouse BMDL 10 

### by a BW 0.75 

### allometric scaling factor (operationalized as [BW human 

### /BW mouse 

### ] 0.25 ≈ 7) to account for the potential slower clearance per volume tissue in the human compared with the mouse. A linear extrapolation approach 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. Currently, there are no data from chronic inhalation cancer bioassays in mice or rats providing support for a nonlinear dose

- response relationship ( US EPA, 2011b )

. A probabilistic human PBPK model was used to determine a distribution of human internal doses from a unit of concentration (one μg/m 3 

### ) and corresponding IUR val ues expressed as external concentrations (μg/m 3 

### ). The mean of the distribution of candidate 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 

### or the inhalation risk, 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.