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xvEPA
United States
Environmental Protection Agency
Office of Chemical Safety and
Pollution Prevention
Draft Risk Evaluation for
Methylene Chloride
(Dichloromethane, DCM)
Draft Supplemental Information on Consumer Exposure
Assessment
NOTICE: This information is distributed solely for the purpose of pre-dissemination peer
review under applicable information quality guidelines. It has not been formally disseminated by
EPA. It does not represent and should not be construed to represent any Agency determination
or policy. It is being circulated for review of its technical accuracy and science policy
implications.
CASRN: 75-09-2
H
October 2019

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Table of Contents
1	Consumer and General Population Exposure	1
1.1	Consumer Exposure	1
1.2	Consumer Modeling	2
1.2.1 CEM Approach	3
2	Model Sensitivity Analyses	10
2.1 CEM Sensitivity Analysis	10
3	References	12

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1 Consumer and General Population Exposure
The United States Environmental Protection Agency (U.S. EPA) evaluated methylene chloride
(DCM) exposure resulting from the use of consumer products and industrial processes. The U.S.
EPA utilized a modeling approach to evaluate exposure because chemical specific personal
monitoring data was not identified for consumers during data gathering and literature searches
performed as part of Systematic Review.
1.1 Consumer Exposure
Consumer products containing DCM are readily available at retail stores and via the internet for
purchase and use. Use of these products can result in exposures of the consumer user and
bystanders to DCM during and after product use. Consumer exposure can occur via inhalation,
dermal, and oral routes.
Consumer products containing DCM were identified through review and searches of a variety of
sources, including the National Institutes of Health (NIH) Household Products Database, various
government and trade association sources for products containing DCM, company websites for
Safety Data Sheets (SDS), Kirk-Othmer Encyclopedia of Chemical Technology, and the internet
in general. Identified consumer products were then categorized into fifteen consumer use groups
considering (1) consumer use patterns, (2) information reported in SDS, (3) product availability
to the public, and (4) potential risk to consumers. Table 1-1 summarizes the fifteen consumer use
groups evaluated as well as the routes of exposure for which they were evaluated.
Table 1-1: Consumer Uses and Routes of Exposure Assessed
C onsumer I ses
Uoules of Kxposure
1. Auto Leak Sealer (Aerosol)

2. Auto AC Refrigerant (Aerosol)

3. Glues and Adhesives (Liquid)

4. Adhesive Remover (Liquid)

5. Brake Cleaner (Aerosol)

6. Brush Cleaner (Liquid)

7. Carbon Remover (Aerosol)

8. Carburetor Cleaner (Aerosol)
Inhalation and Dermal
9. Sealant AKA Coil Cleaner (Aerosol)

10. Cold Pipe Insulation Spray (Aerosol)

11. Electronics Cleaner (Aerosol)

12. Engine Cleaner (Aerosol)

13. Gasket Remover (Aerosol)

14. Sealants (Aerosol)

15. Weld Spatter Protectant (Aerosol)

The U.S. EPA evaluated acute inhalation and dermal exposure of the consumer to DCM for this
evaluation. Acute inhalation exposure is an expected route of exposure for all fifteen consumer
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use groups. Acute dermal exposure is also a possible route of exposure for all fifteen consumer
use groups. The U.S. EPA does not expect exposure under any of the fifteen consumer use
groups evaluated to be chronic in nature and therefore does not present chronic exposure for
consumers. The U.S. EPA does not expect oral exposure to occur under any of the fifteen
consumer use groups evaluated and therefore did not evaluate the oral route of exposure.
The U.S. EPA evaluated inhalation and dermal exposure for the consumer user and evaluated
only inhalation exposure for a non-user (bystander) located within the residence during product
use. The consumer user consisted of three age groups (adult, greater than 21 years of age; Youth
A, 16-20 years of age; and Youth B, 11-15 years of age) which includes the susceptible
population woman of childbearing age. The bystander can include individuals of any age (infant
through elderly).
1.2 Consumer Modeling
The model used to evaluate consumer exposures was EPA's Consumer Exposure Model (CEM).
Table 1-2 summarizes the specific models used for each consumer use group and the associated
routes of exposure evaluated.
Table 1-2: Models Used for Routes of Exposure Evaluated,
Consumer I ses
Routes of l-\posuie
Inhalation
Dermal
1. Auto Leak Sealer
CEM
CEM
2. Auto AC Refrigerant
CEM
CEM
3. Glues and Adhesives
CEM
CEM
4. Adhesive Remover
CEM
CEM
5. Brake Cleaner
CEM
CEM
6. Brush Cleaner
CEM
CEM
7. Carbon Remover
CEM
CEM
8. Carburetor Cleaner
CEM
CEM
9. Sealant AKA Coil Cleaner
CEM
CEM
10. Cold Pipe Insulation Spray
CEM
CEM
11. Electronics Cleaner
CEM
CEM
12. Engine Cleaner
CEM
CEM
13. Gasket Remover
CEM
CEM
14. Sealants
CEM
CEM
15. Weld Spatter Protectant
CEM
CEM
Readers are referred to each model's user guide and associated user guide appendices for details
on each model, as well as information related to equations used within the models, default
values, and the basis for default values. Each model is peer reviewed. Default values within
CEM are a combination of high end and mean or central tendency values derived from U.S.
EPA's Exposure Factors Handbook, literature, and other studies.
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1.2.1 CEM Approach
CEM is a deterministic model which utilizes user provided input parameters and various
assumptions (or defaults) to generate exposure estimates. In addition to pre-defined scenarios,
which align well with the fifteen consumer uses identified in Table 1-1, CEM is peer reviewed,
provides flexibility to the user allowing modification of certain default parameters when
chemical-specific information is available and does not require chemical-specific emissions data
(which may be required to run more complex indoor/consumer models).
CEM predicts indoor air concentrations from consumer product use through a deterministic,
mass-balance calculation derived from emission calculation profiles within the model. There are
six emission calculation profiles within CEM (E1-E6) which are summarized in the CEM users
guide and associated appendices https://www.epa.gov/tsca-screening-tools. If selected, CEM
provides a time series air concentration profile for each run. These are intermediate values
produced prior to applying pre-defined activity patterns.
CEM uses a two-zone representation of the building of use when predicting indoor air
concentrations. Zone 1 represents the room where the consumer product is used. Zone 2
represents the remainder of the building. Each zone is considered well mixed. CEM allows
further division of Zone 1 into a near field and far field to accommodate situations where a
higher concentration of product is expected very near the product user when the product is used.
Zone 1-near field represents the breathing zone of the user at the location of the product use
while Zone 1 far field represents the remainder of the Zone 1 room.
Inhalation exposure is estimated in CEM based on zones and pre-defined activity patterns. The
simulation run by CEM places the product user within Zone 1 for the duration of product use
while the bystander is placed in Zone 2 for the duration of product use. Following the duration of
product use, the user and bystander follow one of three pre-defined activity patterns established
within CEM, based on modeler selection. The selected activity pattern takes the user and
bystander in and out of Zone 1 and Zone 2 for the period of the simulation. The user and
bystander inhale airborne concentrations within those zones, which will vary over time, resulting
in the overall estimated exposure to the user and bystander.
CEM contains two methodologies for estimating dermal exposure to chemicals in products, the
fraction absorbed method (P-DER2A) and the permeability method (P-DER2B). Each
methodology has associated assumptions, uncertainties and data input needs within the CEM
model. Both methodologies factor in the dermal surface area to body weight ratio and weight
fraction of chemical in a consumer product.
The permeability model is based on the ability of a chemical to penetrate the skin layer once
contact occurs. The permeability model assumes a constant supply of chemical, directly in
contact with the skin, throughout the exposure duration. The ability to use the permeability
method can be beneficial when chemical-specific skin permeability coefficients are available in
the scientific literature. However, the permeability model within CEM does not consider
evaporative losses when it estimates dermal exposure and therefore may be more representative
of a dermal exposure resulting from a constant supply of chemical to the skin due to a barrier or
other factor that may restrict evaporation of the chemical of interest from the skin (a product
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soaked rag against the hand while using a product), or immersion of a body part into a pool of
product. Either of these examples has the potential to cause an increased duration of dermal
contact and permeation of the chemical into the skin resulting in dermal exposure.
The fraction absorbed method is based on the absorbed dose of a chemical. This method
essentially measures two competing processes, evaporation of the chemical from the skin and
penetration of the chemical deeper into the skin. This methodology assumes the application of
the chemical of concern occurs once to an input thickness and then absorption occurs over an
estimated absorption time. The fraction absorbed method can be beneficial when chemical
specific fractional absorption measurements are available in the scientific literature. The
consideration of evaporative losses by the fraction absorbed method within CEM may make this
model more representative of a dermal exposure resulting from scenarios that allow for
continuous evaporation and typically would not involve a constant supply of product for dermal
permeation. Examples of such scenarios include spraying a product onto a mirror and a small
amount of mist falling onto an unprotected hand.
All consumer use groups identified in Table 1-2 and evaluated with CEM used CEM's El, E2, or
E3 emission model and profile for inhalation exposure. For the El emission model, the model
assumes a constant application rate over a user-specified duration of use. Each instantaneously
applied segment has an emission rate that declines exponentially over time, at a rate that depends
on the chemical's molecular weight and vapor pressure. For the E2 emission model, the model
assumes an initial fast release by evaporation followed by a slow release dominated by diffusion.
Finally, the E3 emission model assumes a percentage of a consumer product used is aerosolized
(e.g. overspray) and therefore immediately available for uptake by inhalation. The associated
inhalation model within CEM for all three emission models used for DCM is P-INH2. The U.S.
EPA also used the near-field and far-field option within CEM for all consumer use groups
evaluated with CEM. For dermal exposure within CEM, either the absorption fraction method
model, P-DER2b, or the permeability method model, P-DER2a, were used. The dermal model
used was based on the particular product.
In an effort to characterize a potential range of consumer inhalation exposures, the EPA varied
three key parameters within the CEM model while keeping all other input parameters constant.
The key parameters varied were duration of use per event (minutes/use), amount of chemical in
the product (weight fraction), and mass of product used per event (gram(s)/use). These key
parameters were varied because they provide representative consumer behavior patterns for
product use. Additionally, CEM is highly sensitive to two of these three parameters (duration of
use and weight fraction). A detailed summary of a sensitivity analysis performed of CEM is
provided within the CEM users guide and associated CEM user guide appendices. Finally, all
three parameters had a range of documented values within literature identified as part of
Systematic Review allowing the EPA to evaluate inhalation exposures across a spectrum of use
conditions.
To characterize a potential range of consumer dermal exposures, the EPA varied two key
parameters within CEM while keeping all other input parameters constant. The key parameters
varied for dermal exposure evaluation were weight fraction and duration of use per event. The
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mass of product used is not a factor in the dermal exposure equations within CEM and therefore
was not varied.
Once the data was gathered for the parameters varied, modeling was performed to cover all
possible combinations of these three parameters. This approach results in a maximum of 27
different iterations for each consumer use. Certain uses, however, only had a single value for one
or more of the parameters varied which reduces the total number of iterations. Table 1-3
summarizes the potential iterations.
Table 1-3: Example Structure of CEM Cases for Each Consumer Use Group Scenario Modeled
ci:\i sci
Scenario
Characterization
(Duration-Weight
Traction-Product
Mass)
Duration of
Product I se
IV-r \.\ cut
(min use)
| not scalable|
Weight Traction
ofChemical in
Product
(iinitless)
| scalable |
Mass of Product
I sed
(g use)
| scalable |
Set 1
(Low
Duration)
Case 1: Low-Low-
Low
Low
Low
Low
Case 2: Low-Low-Mid
Mid
Case 3: Low-Low-
High
High
Case 4: Low-Mid-Low
Mid
Low
Case 5: Low-Mid-Mid
Mid
Case 6: Low-Mid-
High
High
Case 7: Low-High-
Low
High
Low
Case 8: Low-High-
Mid
Mid
Case 9: Low-High-
High
High
Set 2
(Mid
Duration)
Case 10: Mid-Low-
Low
Mid
Low
Low
Case 11: Mid-Low-
Mid
Mid
Case 12: Mid-Low-
High
High
Case 13: Mid-Mid-
Low
Mid
Low
Case 14: Mid-Mid-
Mid
Mid
Case 15: Mid-Mid-
High
High
Case 16: Mid-High-
Low
High
Low
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Case 17: Mid-High-
Mid


Mid

Case 18: Mid-High-
High


High

Case 19: High-Low-
Low


Low

Case 20: High-Low-
Mid

Low
Mid

Case 21: High-Low-
High


High
Set 3
(High
Duration)
Case 22: High-Mid-
Low


Low
Case 23: High-Mid-
Mid
High
Mid
Mid
Case 24: High-Mid-
High


High

Case 25: High-High-
Low


Low

Case 26: High-High-
Mid

High
Mid

Case 27: High-High-
High


High
The U.S. EPA utilized an option within CEM to obtain the intermediate time series concentration
values from each model run. These values are calculated for every 30 seconds (0.5 minute)
period for each zone for the entire length of the model run. This approach allowed the U.S. EPA
to perform post-processing within Excel to determine personal concentration exposures for the
user and bystander. This post-processing was conducted by independently assigning the Zone 1,
Zone 2, and outside (zero) concentration to the user and bystander. These zone concentrations
were assigned based on the pre-defined activity patterns within CEM. Time-weighted average
concentration exposures were then calculated from the personal exposure time series to develop
estimates for all iterations within each consumer use category. Time weighted average (TWA)
concentrations were determined for 1 hour, 3 hours, 8 hours, and 24 hours, although for this
evaluation the 24-hour TWA concentration was utilized based on health endpoints used to
calculate risks.
1.2.1.1 CEM Inputs
Numerous input parameters are required to generate exposure estimates within CEM. These
parameters include physical chemical properties of the chemical of concern, product information
(product density, water solubility, vapor pressure, etc.), model selection and scenario inputs
(pathways, CEM emission model(s), emission rate, activity pattern, product user, background
concentration, etc.), product or article property inputs (frequency of use, aerosol fraction, etc.),
environmental inputs (building volume, room of use, near-field volume in room of use, air
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exchange rates, etc.), and receptor exposure factor inputs (body weight, averaging time, exposure
duration inhalation rate, etc.). Several of these input parameters have default values within CEM
based on the pre-defined use scenario selected. Default parameters within CEM are a
combination of high end and mean or median values found within the literature or based on data
taken from U.S. EPA's Exposure Factors Handbook (EPA. 2011). Details on those parameters
can be found within the CEM Users Guide and associated Users Guide Appendices at
https://www.epa.gov/tsca-screening-tools. or can be cross referenced to U.S. EPA's Exposure
Factors Handbook (EPA. 2011). As discussed earlier, while default values are initially set in pre-
defined use scenarios, CEM has flexibility which allows users to change certain pre-set default
parameters and input several other parameters.
Key input parameters for the fifteen consumer uses identified in Table 1-5 evaluated with CEM
are discussed below. Detailed spreadsheets of all input parameters used for each consumer use
evaluated with CEM are provided in DCM Supplemental File: Information on Consumer
Exposure Assessment Model Input Parameters.
Physical chemical properties of DCM were kept constant across all consumer uses and iterations
evaluated. The saturation concentration in air (one of the factors considered for scaling purposes)
was estimated by CEM as 1.98E+06 milligrams per cubic meter. A chemical-specific skin
permeability coefficient of 7.17E-03 centimeters per hour was estimated within CEM and
utilized for all scenarios modeled for dermal exposure. This estimate is calculated using the log
octanol-water partition coefficient and the molecular weight of the chemical.
Model selection is discussed in the previous section (CEM modeling approaches). Scenario
inputs were also kept constant across all consumer uses and iterations. Emission rate was
estimated using CEM. The activity pattern selected within CEM was stay-at-home. The start
time for product use was 9:00 AM and the product user was adult (>21 years of age) and Youth
(16 through 20 years of age). The background concentration of DCM for this evaluation was
considered negligible and therefore set at zero milligrams per cubic meter.
Frequency of use for acute exposure calculations was held constant at one event per day. The
aerosol fraction (amount of overspray immediately available for uptake via inhalation) selected
within CEM for all consumer uses evaluated was six percent. Building volume used for all
consumer uses was the default value for a residence within CEM (492 cubic meters). The near-
field volume selected for all consumer uses was one cubic meter. Averaging time for acute
exposure was held constant at one day.
Certain model input parameters were varied across consumer use scenarios but kept constant for
all model iterations run for that particular consumer use. These input parameters include product
density, room of use, and pre-defined product scenarios within CEM. Product densities were
extracted from product-specific SDS. Room of use was extracted from an EPA directed survey
of consumer behavior patterns in the United States titled Household Solvent Products: A
National Usage Survev(U.S. EPA. 1987). identified in the literature search as part of systematic
review. U.S. EPA (1987) is a nationwide survey which provides information on product usage
habits for thirty-two different product categories. The information was collected via
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questionnaire or telephone from 4,920 respondents across the United States. U.S. EPA (1987)
was rated as a high-quality study during data evaluation within the systematic review process.
The room of use selected for this evaluation is based on the room in which U.S. EPA (1987)
results reported the highest percentage of respondents that last used a product within the room.
When U.S. EPA (1987) identified the room of use where the highest percentage of respondents
last used the product as "other inside room", the utility room was selected within CEM for
modeling. The pre-defined product scenarios within CEM were selected based on a cross-walk to
similar product categories within U.S. EPA (1987). A crosswalk between the DCM Consumer
Use Scenarios and the corresponding U.S. EPA (1987) product category selected to represent the
exposure scenario is provided below. In instances where a pre-defined product was not available
within CEM, a generic model scenario was assigned in CEM with would run the requisite
inhalation, emission, and dermal models.
Table 1-4: Crosswalk Between DCM Consumer Use Scenarios and U.S. EPA (1987) Product
Category
DCM Consumer I so Scenario
Uepresonlsilivc I .S. KIW ( ) Product Csilcgorv
1.
Auto leak sealer
! Engine Cleaner
2.
Auto AC refrigerant
i Engine Cleaner
->
J.
Glues and adhesives
s Contact Cement, Super Glues, and Spray Adhesives
4.
Adhesive remover
i Adhesive Removers
5.
Brake cleaner
i Brake Quieters/Cleaners
6.
Brush cleaner
i Paint Removers/Strippers
7.
Carbon remover
i! Solvent-type Cleaning Fluids or Degreasers
8.
Carburetor cleaner
i! Carburetor Cleaner
9.
Sealant aka coil cleaner
i Solvent-type Cleaning Fluids or Degreasers
10
Cold pipe insulation spray
Rust Removers
1 1
Electronics cleaner
i Specialized Electronic Cleaners
12
Engine cleaner
i Engine Degreasers
13
Gasket remover
i Gasket Remover
14
Sealants
!i Gasket Remover
15
Weld spatter protectant
i Rust Removers
Additional key model input parameters were varied across both consumer use scenario and
model iterations. These key parameters were duration of use per event (minutes/use), amount of
chemical in the product (weight fraction), and mass of product used per event (gram(s)/use).
Duration of use and mass of product used per event values were both extracted from U.S. EPA
(1987). To allow evaluation across a spectrum of use conditions, the EPA chose the U.S. EPA
(1987) results for these two parameters from the above cross-walked product categories
representing the tenth, fiftieth (median), and ninety-fifth percentile data, as presented in U.S.
EPA (1987).
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The amount of chemical in the product (weight fraction) was extracted from product specific
SDS. This value was varied across the given range of products within the same category to
obtain three values, when available. Unlike the survey results which gave percentile data,
however, product specific SDS across products did not have percentile data so the values chosen
represented the lowest weight fraction, mean weight fraction (of the range available), and the
highest weight fraction found. Even using this approach, some SDS were only available for a
single product with a single weight fraction or very small range, or multiple products which only
provided a single weight fraction or a very small range. For these product scenarios, only a single
weight fraction was used in CEM for modeling. The following table summarizes the input
parameter values used for these three parameters by consumer use.
Table 1-5: Model Input Parameters Varied by Consumer Use
( onsiiiiicr I so
Durntion (»T I so
Mnss of Product I sod
Amount of ( hcinicnl
In Product
(in i ii ii t cs/usc)
(«r;iin(s)/usc)
(weight IVsiction)
10"'
50"'
95"'
1 ()lh
50"'
95th
1-OW
Mosul
High
Auto Leak
Sealer
5
15
120
88.18 (single)
0.01 (single)
Auto AC
Refrigerant
5
15
120
103.95
414.36
1714.59
0.01
0.03

Glues and
Adhesives
0.50
4.25
60
1.22
10.16
175.65
0.3
0.6
0.9
Adhesive
Remover
3
60
480
22.07
263.53
2108.22
0.5
0.75

Brake Cleaner
1
15
120
45.31
181.23
724.91
0.1
0.35
0.6
Brush Cleaner
5
60
420
71.31
427.32
3418.58
0.01 (single)
Carbon
Remover
2
15
120
19.37
112.44
1107.10
0.4
0.7

Carburetor
Cleaner
1
7
45
41.77
167.07
644.89
0.2
0.45
0.7
Sealant AKA
Coil Cleaner
2
15
120
22.19
128.78
1267.96
0.6
1

Cold Pipe
Insulation
Spray
0.25
5
60
15.97
77.00
521.61
0.3
0.6

Electronics
Cleaner
0.17
2
30
1.50
18.78
281.65
0.05 (single)
Engine Cleaner
5
15
120
97.24
387.60
1603.88
0.2
0.45
0.7
Gasket
Remover
2
15
60
29.77
122.77
790.05
0.6
0.8

Sealants AKA
Sealant
0.25
5
60
17.43
84.06
569.43
0.1
0.3

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( onsiiiner I se
Duration of I se
Mass of Product I sed
Amount ol' Chemical
In Product
(minules/use)
(irram(s)/iisc)
(weight Tract ion)
10"'
50,h
95"'
10"'
50"'
95"'
l.ow Mean High
Weld Spatter
Protectant
2
15
60
30.12
124.19
799.19
0.9 (single)
1.2.1.2 CEM Results
All modeling results were exported into Excel workbooks for additional processing and
summarizing. All modeling outputs for each condition of use evaluated are included by condition
of use in DCM Supplemental File: Information on Consumer Exposure Assessment Model
Outputs.
2 Model Sensitivity Analyses
Model sensitivity analyses conducted on the models used for this evaluation enable users to
identify what input parameters have a greater impact on the model results (either positive or
negative). This information was used for this evaluation to help justify the approaches used and
input parameters varied for our modeling.
2.1 CEM Sensitivity Analysis
The CEM developers conducted a detailed sensitivity analysis for CEM version 1.5, as described
in Appendix C of the CEM User Guide.
In brief, the analysis was conducted on non-linear, continuous variables and categorical variables
that were used in CEM models. A base run of different models using various product or article
categories along with CEM defaults was used. Individual variables were modified, one at a time,
and the resulting Chronic Average Daily Dose (CADD) and Acute Dose Rate (ADR) were then
compared to the corresponding results for the base run. Two chemicals were used in the
analysis: bis(2-ethylhexyl) phthalate was chosen for the SVOC Article model (emission model
E6) and benzyl alcohol for other models. These chemicals were selected because bis(2-
ethylhexyl) phthalate is a SVOC, better modeled by the Article model, and benzyl alcohol is a
VOC, better modeled by other equations.
All model parameters were increased by 10% except those in the SVOC Article model (increased
by 900% because a 10% change in model parameters resulted in very small differences). The
measure of sensitivity for continuous variables was elasticity, defined as the ratio of percent
change in each result to the corresponding percent change in model input. A positive elasticity
means that an increase in the model parameter resulted in an increase in the model output
whereas a negative elasticity had an associated decrease in the model output. For categorical
variables such as receptor and room type, the percent difference in model outputs for different
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category pairs was used as the measure of sensitivity. The results are summarized below for
inhalation vs. dermal exposure models and for categorical vs. continuous user-defined variables.
Exposure Models
For the first five inhalation models (E1-E5) a negative elasticity was observed when increasing
the use environment, building size, air zone exchange rate, and interzone ventilation rate. All of
these factors decrease the chemical concentration, either by increasing the volume or by
replacing the indoor air with cleaner (outdoor) air. Increasing the weight fraction or amount of
product used had a positive elasticity because this change increases the amount of chemical
added to the air, resulting in higher exposure. Vapor pressure and molecular weight also tended
to have positive elasticities.
For most inhalation models, the saturation concentration did not have a notable effect on the
ADR or the CADD. Mass of product used and weight fraction both had a positive linear
relationship with dose. All negative parameters had elasticities less than 0. 4, indicating that
some terms (e.g., air exchange rates, building volume) mitigated the full effect of dilution. That
is, even though the concentration is lowered, the effect of removal/dilution is not stronger than
that of the chemical emission rate. Most models had an increase in dose with increasing duration
of use. Increasing this parameter typically increases the peak concentration of the product, thus
giving a higher overall exposure.
The results for the dermal model were different from the inhalation models, in that the elasticities
for CADD and ADR were nearly the same. This outcome is consistent with the model structure,
in that the chemical is placed on the skin so there is no time factor for a peak concentration to
occur. The modeled exposure is based on the ability of a chemical to penetrate the skin layer
once contact occurs. Dermal permeability had a near linear elasticity whereas log Kow and
molecular weight had zero elasticities.
User-defined Variables
These variables were separated into categorical vs. continuous. For categorical variables there
were multiple parameters that affected other model inputs. For example, varying the room type
changed the ventilation rates, volume size and the amount of time per day that a person spent in
the room. Thus, each modeling result was calculated as the percent difference from the base run.
For continuous variables, each modeling result was calculated as elasticity.
Among the categorical variables, both inhalation and dermal model results had a positive change
when comparing an adult to a child and to a youth, with dermal having a smaller change between
receptors than inhalation and the largest difference occurring between an adult and a child for
both models. The time of day when the product was used and the duration of use occurred while
the person was at home; thus, there was no effect on the ADR because the acute exposure period
was too short to be affected by work schedule. Most rooms had a negative percent difference for
inhalation, with the single exception of the bedroom where the receptor spent a large amount of
time with a smaller volume than the living room. For dermal, the only room that resulted in a
large percent difference was office/school, due to the fact that the person spent only V2 hour at
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
that location when the stay-at-home activity pattern was selected. For inhalation, changing from
a far field to a near field base resulted in a higher ADR and CADD, likely because the near field
has a smaller volume than that of the total room.
There are three input parameters for the near-field, far-field option for CEM product inhalation
models. To determine the sensitivity of model results to these inputs, CEM first was run in base
scenario with the near-field option, after which separate runs were performed whereby the near-
field volume was increased by 10%, the far-field volume was increased by 10%, and the air
exchange rate was increased by 10%. For inhalation, both the air exchange rate and volume had
negative elasticities, but the air exchange rate had a much higher elasticity (near one) than the
volume (0.11).
3 References
EPA. US. (201 1). Exposure factors handbook: 201 1 edition (final) [EPA Report], (EPA/600/R-
090/052F). Washington, DC: U.S. Environmental Protection Agency, Office of Research
and Development, National Center for Environmental Assessment.
http://cfpub. epa.gov/ncea/cfm/recordisplav. cfm?deid=236252
U.S. EPA. (1987). Household solvent products: A national usage survey. (EPA-OTS 560/5-87-
005). Washington, DC: Office of Toxic Substances, Office of Pesticides and Toxic
Substances.
https://ntrl.ntis.gov/NTRL/dashboard/searchResults.xhtml?searchQuerv=PB88132881
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