Risk Analysis, Vol. 12, No. 4, 1992

Estimating Dermal Uptake of Nonionic Organic Chemicals from Water and Soil: I. Unified Fugacity-Based Models for Risk Assessments Thomas E. McKonel and Robert A. H ~ w d * * ~ Received November 20, 1991; revised April 6, 1992

Contamination of water and soil that might eventually contact human skin makes it imperative to include the dermal uptake route in efforts to assess potential environmental health risks. Direct measurements of dermal uptake from either water or soil are only available for a small number of the thousands of chemicals likely to be found in the environment. We propose here a mass-transfer model for estimating skin permeability and dermal uptake for organic chemicals that contaminate soil and water. Statistical relationships between measured permeabilities and chemical properties and reveal that permeability varies primarily with the octanol-water partition coefficient (KO,,,) secondarily with the molecular weight. From these results, we derive a fugacity-based model for skin permeability that addresses the inherent permeability of the skin, the interaction of the skin with the environmental medium on skin (water or soil), and retains a relatively simple algebraic form. Model predictions are compared to measured human skin permeabilities for some 50 compounds in water and four compounds in soil. The model is adjusted to account for dermal uptake during both short-term (10-20 min) and long-term (several hour) exposures. This model is recommended for compounds with molecular weight less than or equal to 280 g. KEY WORDS: Dermal uptake contaminated water; contaminated soil; exposure assessment; fugacity; skin; mass transfer; permeability.

1. INTRODUCTION

sands of chemicals likely t o be found in the environment. This leaves two choices for the risk assessment process(1)ignore the dermal route for those chemicals with n o experimental data available, o r (2) use predictive models for dermal uptake in the absence of experimentally measured uptake. Under the premise that the first choice is unacceptable in a comprehensive risk assessment, we propose here a mass-transfer model for estimating skin permeability and dermal uptake for organic chemicals that contaminate soil and water in contact with human skin. The model here is distinguished from other models in that, in addition to addressing the inherent permeability of the skin, it addresses the interaction of the skin with the contacted medium (i.e., water or soil), and how this differs between experiments (primarily with diffusion cells) and actual exposure conditions. The model

Contamination of groundwater and soil that might eventually contact human skin make it imperative to include the dermal uptake route in efforts to assess and manage potential heaIth risks at hazardous waste sites. Direct measurements of dermal uptake from either water or soil are only available for a small number of the thouUniversity of California, Lawrence Livermore National Laboratory, P.O. Box 808, L-453,Livermore, California 94550. California Environmental Protection Agency, Department of Toxic Substances Control, P.O. Box 0806, Sacramento, California 958120806. Current address: California Environmental Protection Agency, Office of Environmental Health Hazard Assessment, 2151 Berkeley Way, Annex 11, Berkeley, California 94704.

543

0272-4332/92/12W-0543$06.50/1 0 1992 Socicry for Risk Analysis

544

allows for boundary-layer effects, diffusion in both liquid and fat components of skin, and tortuous-diffusionlength corrections. Because the model provides consistent precision among chemicals with large variations in water and lipid solubility and requires limited chemical data as input, we believe it can be particulariy useful for risk assessments. Two chemical-properties are required as primary inputs for this model-(1) molecular weight and (2) octanol-water partition coefficient. The Henry’s law constant is also needed to estimate contaminant uptake from soil on skin. 2. HUMAN SKIN: PHYSICAL STRUCTURE AND

PERMEABILITY The skin is a large and complex organ that interacts with and adapts to the environment. It serves as a chemical barrier, a physical barrier, a site of body-temperature regulation, and as a sensory organ. The skin consists of two distinct layers, the epidermis or outermost layer and the dermis. There are two main layers in the epidermis: stratum corneum and stratum germinativum. The stratum corneum is a layer of metabolically inactive cells and is formed and continuously replenished by the slow, upward migration of cells from the stratum germinativum. The stratum corneum is very thin and uniform in most regions of the body, ranging from 13-15 p,m thick. However, on the soles and palms it can be as much as 600 bm in thickness.(’) The dried cornified cells of the stratum corneum are extremely elongated and flat (approximately 1 p,m thick). Their intracellular composition is characterized by an absence of organelles, a large fraction of proteins as fibrils, a low water content, and a modified cell membrane.c2) The intercellular space of the stratum corneum is some 30% by volume.(2) Lipids, some 10% of stratum corneum by dry mass, occupy much of the intercellular space and the modified membrane. The lipids are arranged in layers and consist primarily of ceramides (-50%), fatty acids (-20%), and sterols (-20%).(2) In their comprehensive review of skin permeability, Scheuplein and Blankc3) point out that the “barrier” function of the epidermis resides almost entirely in the stratum corneum and that for low-molecular-weight electrolytes it has about 1000 times the diffusive resistance of underlying skin layers. In addition, they note that (a) the stratum corneum is always partially hydrated with a water content on the order of 15-50%; (b) lipid solubility of a chemical plays a crucial role in determining its permeability through the stratum corneum; (c) measurements of skin permeability made in vitro can differ sig-

McKone and Howd nificantly from those made in vivo; and (d) the effective diffusion coefficient through the stratum corneum is on the order of 10-13 to 10-14 m21sec for low molecular weight compounds and 10-15 to lo-’’ m2/sec for higher molecular weight compounds.

3. EXISTING MODELS

Models of dermal permeation generally account for the dependence of permeability on water solubility, lipid/ water partitioning, diffusivity in water and lipid phases, air-water partition coefficient, and molecular weight. For organic chemicals, we consider here four permeability models in watedskin systems and one in a soil/skin system. These models provide the basis for our proposed model. ~) a model that relates Michaels et ~ l . (proposed permeability to the octanol-water partition coefficient and addresses diffusion in the lipid and protein phases of the stratum corneum. This model takes the form

D, 1.16 + 0.0017 (KowDL/D,,) K, = 0.36 KO, (1) Dp 0.16 + (KowDL/Dp) where K, is the skin permeability, c m h ; KO, is the octanol/water partition coefficient used to approximate the partitioning of a chemical between lipid and protein phases of skin; and DJD, is the ratio of diffusivities of penetrant in the lipid and protein phases of skin. Albery and HadgrafP proposed a mass-transfer model that is structured as two resistances in a seriesa transcellular (trans) route and an intercellular (inter) route. The total permeability KJtotaZ) through both routes is given by

K,(total) =

1

l/K,(trans)

+ l/K,(inter)

(2)

The K, for either mass-transfer route is calculated as L K,(route) = +

a

ki

%kin

a

Y KowD‘4

(3)

where a is the area fraction of the mass-transfer route; ki is the interfacial transfer coefficient, cm/hr; tiskinis the thickness of the stratum corneum, cm; y is an empirically derived parameter; and DA is the diffusion coefficient of the mass-transfer route, cm2/hr. ~) a model for estimating Kasting et ~ l . (proposed

Unified Dermal Uptake Models

545

steady-state chemical flux through the skin membrane. This model takes the form,

Jss = Dskin -K,,,, C, b i n

=

-C,,,

Dskin

(4)

sskin

where J, is the steady-state flux, mol/cm2-hr, through a skin membrane of thickness askin in cm; Dskinis the skin diffusion coefficient, cm2/hr; K,,,, is the membrane-vehicle partition coefficient, no units; C, is chemical concentration in the vehicle, mol/cm3; and C,,,is the chemical concentration at the skin boundary, mol/m3, and is equal to the product of C, and K,,,,. The skin diffusion coefficient D takes the form, D = Do exp(pv), where v is the van der Waals volume of the penetrating chemical and Do and p are properties of the skin. Kasting et aZ.@) measured the maximum flux of chemical solute across a skin membrane from saturated propylene glycol solutions to determine the parameters Do and p of this model. They observed that a solvent brought in contact with skin will result in a saturation of the skin at the skin-solvent boundary and determined that the maximum flux, J,,,, is equal to (D/SskinxS,where S is the solubility of the chemical in skin. They developed the following equation for estimated permeability through the skin membrane based on solubility. log KJskin) = log S

+ 1.129 - 0.00812~

(5)

In a recent U.S. Environmental Protection Agency (EPA) report,(') it is reported that Potts and Guy@)have shown that Eq. (5) can be used to estimate permeability for water-skin experiments by converting it to the form 10-(o-oo61 MW) (6) K,(skin,water) = 0.0019 where KO, and MW are, respectively, the octanol-water partition coefficient and molecular weight of the solute. This relationship has a very severe dependence on molecular weight, which is not consistent with theories of diffusivity discussed below. However, the model does appear to approximate measured Kp over a large range of KO, and MW with reasonable precision. Based on some 100 permeability coefficients for aqueous solutions on human skin available in the existing literature, Flynno developed an algorithm for calculating permeability as a function of octanol-water partition coefficient, KO,, and molecular weight, MW. In the EPA report on dermal exposure,(7)this algorithm has been updated to an estimation equation based on KO, and MW, K,(skin,water) = 0.27 E;u792 MW- 1.45

(7) Based on a model for skin uptake of 2,3,7,8 tetrachlo-

rodibenzo-p-dioxin (TCDD) from soil proposed by Kissel and MacAvoy,('O) McKonec") proposed a general model for estimating uptake fraction from an air-soilskin system. This model includes two concepts that are not included in any of the permeability models for waterskin systems-(1) tortuous diffusion pathways through soil and skin, and (2) boundary layer effects at the soilair interface. Central to the approach is a fugacity model (see fugacity discussion below) that uses the physical and chemical properties of the compound, skin, and soil to estimate transport across the combined skin and soil layer, taking evaporation into account. In the McKone(") version of the mode!, the overall mass-transfer coefficient from soil through the combined skin and soil layer, &(skin, soil) (cmhr), should be calculated as Kp(skin, soil)

=

[

ssoil

Dsoil

&skin zsoil

+ Dskin Zskin

The thickness of the soil layer, tjsoil(cm), is calculated from the soil loading on the skin, (mg/cm2) divided by the total density of the soil, (mg/ml). Dsoi,and Dskin are the diffusion coefficients for soil and skin, cm2hr. &kin is the chemical-specific fugacity capacity of skin (mol/ cm3-Pa) and Zwil is the chemical-specific fugacity capacity of soil (mol/ml-Pa). The ratio Zso&kin is the soilskin partition coefficient for the chemical in question. The overall mass-transfer coefficient from soil through the combined soil and air boundary layer, KJsoil, air) (cmhr), is given by

where 6, is the boundary layer thickness in the air above the soil layer, which is assumed to be on the order of 0.5 cm. On smooth surfaces, the boundary layer thickness varies from about 1 cm in still air to 0.1 cm when the air moves over the surface at 1 m/sec. The term Zsoil/ Zairrelates the total concentration in the skin soil layer to the concentration in the gas phase. Dairis the diffusion coefficient of the specific organic chemical in pure air, which is on the order of 5 x m2/sec (180 cmhr) for many organic compounds. The fraction of the soilbound chemical that is transferred through the soil layer and the stratum corneum is calculated as uptake fraction =

KJskin, soil) KJskin, soil) + Kp(soil, air) x [l - exp(-b x El")] (10)

where ET is the exposure time (hr) and b is the inverse of the chemical residence time on skin, h-l. McKone'")

McKone and Howd

546

assumed that diffusion is primarily in the intercellular space and that chemicals diffuse through the intercellular phase according to a tortuous pathway model, with Dskin represented by D, c$4'3, where is the volume fraction of the skin occupied by the intercellular material and Di, is the diffusion coefficient of the intercellular material. D, is assumed proportional to the diffusion coefficient of water.

+

4. DATA ON DERMAL UPTAKE FROM SOIL

AND WATER 4.1. Measured Permeability for Organic Compounds from Water through Skin

Table I provides for the listed chemicals, values for the molecular weight, octanol-water partition coefficient, and steady-state experimentally measured permeability coefficient KJskin, water, exp.) obtained from the indicated references. The K, values were measured in vitro or in vivo in experiments to estimate human dermal uptake of chemicals from water. Based on experiments with human epidermis in vitro, permeability values for alcohols were reported at 30°C by Blank et al.(I4)and at 30°C by Scheuplein and Blank.(12) Southwell et al. (13) used hydrated human abdominal stratum corneum in vitro to measure the permeability of methanol and octanol. Bond and Barry(") measured skin permeability of hexanol in vitro for abdominal skin at 31°C. Permeability values for phenols listed in Table I are taken largely from Roberts et a1.,(l6) who used in v i m the epidermal membrane of human abdominal tissue with a receptor cell containing stirred distilled water in a system maintained at 25°C. Bogen et al.(") estimated human skin permeability for chloroform, perchloroethylene, and trichloroethylene using the measured dermal in vivo uptake by hairless guinea pigs of 14Clabeled compounds from dilute solutions and compared their results for chloroform to human skin permeability derived from the in vivo measurements by Jo et af.(") of chloroform levels in the breath of human volunteers taking showers. Based on studies using human skin in vitro from both sexes and a broad range of ages, Bronaugh et al. (I8) have reported an average skin permeability value of 0.0015 cm/hr for water. Dutkiewicz and T y r a ~ ( ~ ' ,measured ~~) skin absorption rates of ethylbenzene, toluene, styrene, and xylene using direct and indirect methods. In the direct method, human subjects immersed their hands in an aqueous solution for 1 hr. The skin uptake measurement was based on the loss of

compound from the solution. For the indirect method, excretion of major metabolites for 24 hr after the l-hr hand exposure was used to estimate uptake. The two methods gave comparable results. Because the latter experiments involved a relatively short exposure period, we expect the results to reflect transient uptake, which, because it includes partitioning of chemicals from solution to skin, could differ significantly from steady-state uptake. The list of compounds in Table I differs from the list compiled by others, such as Flynn,o because we included only compounds for which we could verify the value of the octanol-water partition coefficient from Vers ~ h u e r e n , ( ~Howard,(26) ~) or Hansch and Leo("); included only compounds for which permeability in human skin was measured (at least indirectly); and excluded compounds that have an appreciable acid dissociation constant. Such compounds constitute a large fraction of pharmaceutical compounds. For ionic compounds, the process of skin permeation is likely to be complicated by the simultaneous presence of both ionized and nonionic species in solution, each of which can permeate the skin at different rates. We elected not to model such processes in the current version of the model.

4.2. Measured Permeability for Organic Compounds from Soil Through Skin Direct measurements of dermal uptake from soil through human skin are only available for a few compounds. Roy et al.(28)applied TCDD in soil to human skin in vitro. Using soil loadings of 10 mg/cm2 in loworganic carbon soils (0.77%)with TCDD concentrations of 1ppm, Roy et al.(28)measured 2 5 5 % dermal uptake of the TCDD in 96 hr. Wester et al. (29) measured dermal uptake of dichloro-diphenyl-trichloroethane (DDT) and benzo[a]pyrene (BaP) from soil both in v i m with human skin and in vivo using rhesus monkeys. A relatively high organic-carbon soil (26% sand, 26% clay, 48% silt) with 10 ppm 14C-labeled compound was applied to the skin samples at a loading of 40 mg/cm2. After 25 hr, an average of only 0.04% of the applied DDT was found to have passed through the skin and an average of 1% was bound to the skin layer. An average of 0.01% of the applied BaP was observed to pass through the skin sample and 1.4% was bound to the skin sample. Wester et al.(2g)also measured an average 3.3% uptake of DDT and 13.2% uptake of BaP when these compounds were applied in soil for 24 hr to the abdominal skin of rhesus monkeys. Using the McKone(") model, we calculate 1%

Unified Dermal Uptake Models

547

Table 1. Valucs for Molecular Weight, Octanol-Water Partition Coefficient, and Permeability Coefficient K,(skin, water, exp.) in cm/hr That Have Been Measured Experimentally In V i m or In Vivo for the Purpose of Estimating Uptake Through Human Skin in Contact with an Aqueous Solution

MW Alcohols

Phenols

Volatile organic chemicals

Others

Methanol Methanol Ethanol Propanol Propanol Butanol Pentanol Hexanol Hexanol Heptanol Heptanol Octanol Octanol Nonanol Deconol Phenol p-Cresol 0-Cresol m-Cresol Resorcinol o-Chlorophenol p-Chlorophenol 3,4-Xylenol 4-Ethylphenol 2,4-Dichloro-phenol p-Nitrophenol m-Nitrophenol 4-Chlorocresol b-Naphthol Thymol Methyl-4-hydroxy benzoate Chloroxylenol 2,4,6-trichloro-phenol 4-Bromophenol Chloroform Trichloroethylene (TCE) Perchloroethylene WE) Water Methylethylketone (2-Butanone) Ethyl ether Benzene Butyric (butanoic) acid 2,3-Butanediol 2-Ethoxyethanol Toluene Aniline Styrene Benzyl alcohol Isoquinoline Ethyl benzene Nitroglycerine

32.0 32.0 46.1 60.1 60.1 74.1 88.2 102.2 102.2 116.2 116.2 130.2 130.2 144.3 158.3 94.1 108.1 108.1 108.1 110 112 112 122.2 122.2 127.6 139.1 139.1 142.6 144.2 150.2 152.1

KO, 0.18 0.18 0.48 2.2 2.2 7.6 25 110 110 260 260 1,400 1,400 4,200 10.000 29 85 89 96 6.1 150 260 220 250 1,202 91 100 1,260 690 2,187 91

156.6 162 173 119.4 131.5

2,460 4,900 389 93 240

165.8

400

18 72.1

0.042 1.8

74.1 78.1 88.1

6.3 135 6.2

90.1 90.1 92.1 93.1 104.1 108.1 129 184.2 227.1

0.12 0.29 490 8.7 890 13 120 1,400 100

K, (water to skin in cm/hr)

5.0 1.6 8.0 1.4 1.7 2.5 6.0 1.3 2.8 3.2 3.8 5.2 6.1 6.0 8.0 8.2 1.8 1.6 1.5 2.4 3.3 3.6 3.6 3.5 6.0 5.6 5.6

x x x x x x x x x x x x X

2.8 5.2 9.1

x x x x x x x x x x x x x x x x x x

5.9 5.9 3.6 1.3 2.3

x x x x x

5.5

10-4 10-3 10-4 10-3 10-3 10-3 10-3

lo-*

10-3 10-2 10-3 10-2 10-2 10-3 10-3 10-2

lo-* 10-3

Reference 12 13 12 12 14 12 12 12 15 12 14 12 13 12 12 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16

10-1 lo-'

16 16 16 17 17

3.7 x 10-1

17

1.5 x 10-3 4.5 x 10-3

18 14

1.6 x 1.1 x 10-1 1.0 x 10-3

14 19 3

4.0 x 2.5 x 1.0 x 3.8 x 6.8 x 6.0 x 1.7 x 1.2 x 1.1 x

3 14 20 21 20 3 22 23

10-2 10-2

10-5 10-4 100

10-1 10-3 100 10-2

5

McKone and Howd

548

7

uptake for TCDD, 0.4% uptake for DDT, and 0.3% uptake for BaP for the conditions described above.

I I

0

4t

*

4.3. Dependence of Skin Permeability from Water on Chemical Properties For the 51 entries in Table I, roughly 72% of the variance in the logarithm of the listed water-skin permeabilities, log Kp(skin, water), can be related to the variance in the logarithm of two chemical propertiesoctanol-water partition coefficient and molecular weight, log KO, and log MW. There is no significant correlation of permeability with vapor pressure. Stepwise regression reveals that the major proportion of the variance in log Kp is related to variance in log KO, (3= 0.69), whereas less variation in log Kp is related to variation in log MW (12= 0.32). It is of interest that correlation of log K, with MW has 12=0.30, which is similar to the correlation with log MW. The scattergrams in Fig. l a and b show the variation of log Kp with log KO, and log MW for the 51 entries listed in Table I.

In a typical in vitro skin permeability experiment, a sample of skin (typically stratum corneum) is contacted on its external surface with a solution of chemical and on its internal surface with water, physiological saline, or Ringers solution and the steady-state rate of transport of chemical from the upper solution to the receiving medium is In this way, the flux, J , in mg/ cm2/hr, through the stratum corneum can be estimated. If the tissue layer is homogeneous and if the solute permeates the skin by simple molecular diffusion, the flux can be represented by Fick's first law equation,

where D s k i n is the chemical diffusivity in the skin membrane, cm2/hr; ACski,is the change in chemical concentration across the skin membrane, mg/cm3; and 8skin is the thickness of the skin membrane, cm. In most cases the chemical concentration at the downstream boundary is maintained at or close to zero so that 2

c*,kin Dskin sskin

n 0 0

0

0

.4.5

1.2

I

0

t

0

1.4

1.6

1.8

('4

2

1.2

2.4

too

Fig. 1. Scattergrams for the logarithm of the measured dermal permeability of chemicals in waterhkin systems, log K,,, vs. (a) the logarithm of the octanol-water partition coefficient, log Kow (r2=0.69), and (b) the logarithm of molecular weight, log MW (r2=0.32). The correlation of log K,, iwth MW (not shown) has a correlation with rZ=0.30.

5. INTERMEDIA TRANSFER FACTORS IN WATER-SKIN A N D SOICSKIN SYSTEMS

J

-

0.

..5.

(12)

where C Z i n is the tissue concentration of chemical at the surface in contact with donor solution, mg/cm3. Because

the direct determination of c z k i n is difficult, it is common practice to express the flux in terms of the chemical concentration Co, in mg/cm3, in the donor solution,

J

Kp Co (13) where K, is the observed permeability of the donor solution-skin system in cmhr. When the boundary layer resistance to mass transfer of the chemical from solution to skin surface can be ignored, the concentration c$in can be expressed as

CO

(14) where Km is the equilibrium skin/solvent partition coefficient, the ratio of chemical concentration in skin (mg/ ml) to that in solvent (mg/ml) when the two are well mixed. Thus, when the boundary-layer resistance is ignored, c:kin

K, =

=

Km

-

Km Dskin

&kin

However, it should be recognized that for highly lipophilic compounds that might diffuse rather easily through

Unified Dermal Uptake Models

549

the skin membrane, the K,, as expressed in Eq. (13) relates to the permeability of the intermedia skin-water system. If the boundary-layer resistance is significant, then Eq. (15) is not appropriate as an approximation. Indeed, it is the goal of our model to allow for the effect of this boundary-layer resistance. This is separated using fugacity models to identify the diffusivity of the stratum corneum and deal with other substances in contact with skin (i.e., soil).

coefficient depends only on the mass-transfer coefficient on either side of the interface.

5.1. Fugacity Models

5.2. Fugacity Capacities (Air, Water, Skin, and Soil)

Fugacity models have been used extensively for modeling the transport and transformation of nonionic organic chemicals in complex environmental systems. Fugacity is a way of representing chemical activity at low concentrations. Fugacity has units of pressure (pascal [Pa]) and can be regarded physically as the partial pressure exerted by a chemical in one physical phase or compartment on another.(3G32)When two or more media are in equilibrium, the fugacity of a chemical is the same in all phases. This characteristic of fugacity-based modeling often simplifies the mathematics involved in calculating partitioning. At low concentrations, typically of environmental interest, fugacity, f (Pa), is linearly related to concentration, C (mg/ml), by the fugacity capacity, Z (mg/mlPa),

C = P

(16)

Z depends on the physical and chemical properties of the chemical and on various characteristics of phase, such as temperature and density. The property that fugacities are equal at equilibrium allows for simple determination of Z values from partition coefficients:

_ c1 -- _ fzl --_z1 - K12 c 2

Pz

ZZ

(17)

where K12 is a dimensionless partition coefficient such as Kow. One of the major advantages of fugacity models is their ability to represent diffusive and advective intermedia transport processes. In a fugacity model, the net diffusive flux, in mol/cm*-hr, across an interface is given by flux =

- f2)

(18) where YI2 is the fugacity mass-transfer coefficient across the boundary between medium 1 and medium 2 with units mol/(cm2-Pa-hr),andf, andf, are the fugacities of medium 1 and medium 2. The fugacity mass-transfer y12 Vl

Y12

=

[$ 3‘ +

-1

(19)

z2u2

where U,and U, are the mass-transfer coefficients (cm/ hr) in the boundary layers in medium 1 and medium 2, and Z, and Z, are the fugacity capacities of medium 1 and medium 2.

The fugacity capacity of air, Zair, is given by z . a’r

=-

1

RT

where R is the universal gas constant, 8.314 x lo6 Paml/mol-OK, and T is temperature in kelvins (OK). The fugacity capacity of water is given by

where H is the Henry’s law constant, Pa-ml/mol, which expresses the ratio of equilibrium activities of a chemical in air (expressed as vapor pressure, Pa) and in water (mol/ml) when the two phases are well mixed. The Henry’s law constant can be estimated as the ratio of a chemical’s measured vapor pressure to its water solubility (mol/ml). For a medium such as a soil matrix, which has air, water, and solid components all at the same fugacity, the fugacity capacity in mol/ml-Pa is the volume-weighted average of the fugacity capacities of its component phases: Zsoil

=

asoilzair

+

PsoilZwater

+ (1 -

+soid Zss

(22)

where aWil is the volume fraction of air in the soil compartment, Psoil is the volume fraction of water, (1 is the volume fraction of solid, +soil (= asoil + PSoi1)is the total void fraction in soil, and Zssis the fugacity capacity of the soil solids. The fugacity capacity of the solid phase of soil is given by

is the sorption coefficient, the ratio at equiwhere KDsSoil librium of chemical concentration attached to soil solids (mol/g) to chemical concentration in soil solution (mol/ ml). KD,,,il is the product of foc,soil, the fraction organic carbon in the soil and KO,,the organic carbon partition

McKone and Howd

550

coefficient. Kari~khoff(~~) has shown that K , can be related to KO,. The term ps,soi, is the density of soil solids, g/ml. From a mass-transfer perspective, stratum corneum is similar to soil, because it is composed of multiple phases-an aqueous phase and a nonaqueous phase (consisting of lipids and cell material). Thus, we represent the fugacity capacity of skin in terms of these two major components, Zskin

=

PskinZwater

+ (l

-

(24)

Pskin) zna

where Pskinis the aqueous volume fraction of skin; Z,,,, is the fugacity capacity of water, mol/ml-Pa; ( l - p s k h ) is the nonaqueous volume fraction and Z, is the fugacity capacity of the nonaqueous phases of the skin, mol/mlPa. By analogy with the nonfluid phase of soil, we expect a fugacity capacity of stratum corneum of the form Z,

=

K W ) ” b-

ZskiJZwater

=

Pskin

K,,,= 0.64

+ 0.25 (K0,)o.8

(27)

The relationship of K,,, to KO,derived using this formula is compared to measured skin-water partition coefficients in Fig. 2. Also shown in Fig. 2 is the 95% confidence interval of the empirical estimation. The ? of this fit is 0.90 and the difference between the estimated K,,, and measured values has a geometric standard deviation of 1.3 for the eight alcohols. The first term in Eq. (27) implies that the fully hydrated skin used in the partition experiments has a water content of 64%. Based on the relative densities of water and stratum corneum tissue, we estimate that this is equivalent to a hydrated skin thickness of 25 bm.

H

where b and a are constants that are based on a correlation of the skin-water partition coefficient with the octanol-water partition coefficient. The unitless skin-water partition coefficient, K,, is given by the ratio of skin to water fugacity capacities, Km =

plein and Blank(l*) for eight alcohols, we empirically estimated the skin-water partition coefficient based on the octanol-water partition coefficient in the form of Eq. (26). The resulting estimate is

+ b (1

-

(26)

Pskin) (KO,)”

Using measured values of K,,, compiled by Scheu-

5.3. Molecular Diffusion Coefficients in Air, Water, Lipid, and Skin

Molecular diffusion is the net transport of a molecule in a liquid or gas phase and is the result of intermolecular collisions rather than turbulence or bulk transport. Mass transport via molecular diffusion is driven by concentration (or fugacity) gradients. A diffusion coefficient depends on properties of both the chemical species being transported and the phase or phases through which it is transported.

5.3.1. Dijjhion in Air

0.1

J . . . . ...., . . . ..... . . . . ...., . . . ....., . . ..-.I I

0.1

1

10

im

1000

i0,Wo

--Pr(fllon~s(nn,K,

Fig. 2. An empirical estimation of the relationship between the skinwater partition coefficient (K,,,) and the octanol-water partition coefficient (K-) for eight alcohols with K , ranging from 0.184400. The eight alcohols included in the sample are methanol, ethanol, propanol, butanol, pentanol, hexanol, heptanol, and octanol. The dotted lines indicate the 95% confidence interval associated with the estimation error. The estimated K,,, and the measured K,,, correlate with ?=0.90.

Analytical methods for estimating the diffusion coefficient of a binary gas system have been reviewed by Reid et al.(34)and Lyman et af.(35)These methods have their foundations in a theoretical relationship referred to as the Chapman-Enskog model for dilute gases at low pressure^,(^^*'^) which relates diffusivity of one gas through another to the molecular weights and molecular volumes of the two species. Estimates of molecular diffusivity in air based on these methods ranges from 36 cm2/hr for a large organic molecule such as TCDD (MW = 322) to 720 cm2/hr for a small molecule such as methane (MW= 16). We use 180 cm2/hr as a representative value of diffusivity in air for organic species.

551

Unified Dermal Uptake Models

5.3.2. Diffusion in Liquid Phases (Water and Skin Lipids)

Reid et al.(34)and Lyman et al.(3s)have also reviewed several methods for estimating liquid diffusion coefficients and found these methods are all based on the Stokes-Einstein equation relating diffusivity to the temperature and viscosity of the solvent and the molecular radius of the solute. As noted by Reid el al., one of the oldest but still widely used empirical estimation methods for binary diffusion in liquids is that of Wilke and Chang,f3’) 2.7 x 10-4

D, =

llyv,o.6

T

Fig. 3. The two parallel regions that we considered when modeling mass transfer in human stratum corneum-(1) the bulk of the skin in which mass transfer occurs through the tortuous pathways in the water and lipid phases in the intercellular spaces, and (2) shunt pathways associated with skin pores and hair follicles containing water and lipids in which mass transfer is by direct diffusion.

(28)

where D, is the diffusion coefficient in of solute x in solvent y , cm2/hr; is the association factor of solvent y , unitless; My is the molecular weight of the solvent, g/mol; T is the temperature of the solute-solvent system, K; qy is the viscosity of the solvent y , cP; and V , is molecular volume of the solute at its normal boiling temperature, cm3/mol. Wilke and Chang(37)report an average estimation error of 10% in predicting diffusion coefficients for 251 solute-solvent systems. They recommend an association factor of 2.6 for water, 1.9 for methanol, or 1.5 for ethanol as solvents and 1.0 for unassociated solvents. The viscosity of water is 0.79 CP at 30°C. Molecular volume can be estimated by the LeBas incremental method as described in Lyman et al. (3s) We expect diffusion coefficients in skin lipids to be described by an equation in the form of Eq. (28), with a different association factor and the appropriate value for viscosity of skin lipids. We note that this equation indicates that diffusivity scales with molecular volume to the -0.6 power and because we expect molecular volume to scale with molecular weight, we expect a similar power relationship for the variation of diffusivity with molecular weight.

+

5.3.3. D i f i i o n in Tortuous, Multiphase Systems Such as Skin

Human stratum comeum is neither homogeneous nor single phase. Figure 3 illustrates that mass transfer in human stratum corneum can occur both in the bulk of the skin via tortuous pathways in the water and lipid phases of the intercellular volume and via shunt pathways associated with skin pores and hair follicles containing water and lipids in which mass transfer is by direct diffusion. When air and water occupy the tortuous

pathways between stationary particles in a porous mehave shown that the efdium, Millington and fective diffusivity, Deffin cm2/hr, of a chemical in each fluid of the mixture is given by where o is the volume fraction occupied by this fluid, 4 is the total void fraction in the medium (the volume occupied by all fluids), and Dpurcis the diffusion coefficient of the chemical in the pure fluid in cm2/hr. Jury et al. (39) have shown that the effective tortuous diffusivity in the water and air of soils is given by

+-

Zwater

Zsoil

pl0!3

+L x

DW,,,,

(30)

where DWilis the effective tortuous, mixed-phase diffusion coefficient in soil (cm2/hr), the Z’s are the fugacity capacities derived previously, and other parameters are as defined previously. We would expect an equation also of the form of Eq. (30) to describe the effective diffusion in combined water and lipid phases of stratum comeum. However, there are insufficient data at this time to derive all of the terms in such an expression. In addition, the fact that there are multiple lipid phases in the skin could lead to an expression with more than two terms. Thus, effective diffusivity in skin must be derived indirectly. 6. REVISED SKIN-WATER AND SKIN-SOIL PERMEABILITY MODELS

Our revised models are based on first fitting the data in Table I primarily to the conditions of experiments

McKone and Howd

552

in which these values were measured-that is, steadystate mass transfer through excised skin in diffusion cells with a stagnant water solution in the upper cell. This resulting skin-water permeability model is used to estimate the skin diffusion coefficient. It is this skin diffusion coefficient that is used in the revised models. This diffusion coefficient is used in a general two-compartment model for estimating transfer from a donor matrix-water or soil-to and/or through stratum comeurn under conditions more representative of actual exposure scenarios.

6.1. Predicting Measured Water-Skin Permeability in Experiments

We develop our revised permeability models for skin-water and skin-soil systems by first developing a model describing the permeability as measured in vitro primarily with diffusion cells. To do this, we assume that, for a chemical in a stagnant water layer on the skin surface, the overall steady-state permeability from water through stratum corneum as measured in experiments, K,(skin, water, exp) in cmhr, is given by a two-resistance model of the form

raised to the power d . Based on these assumptions, we obtain Kp(skin, water, exp) = h4w: [cbl

(31)

where is the boundary layer thickness (under experimental conditions) of the water layer on the skin surface, cm; &kin is the thickness of fully hydrated stratum corneum through which diffusion occurs, cm; Dwater is the diffusion coefficient of a chemical in the water layer on skin, cm2hr; K, is the unitless skin-water partition coefficient; and Dskinis the diffusion coefficient in skin, cm2/hr. Using a model membrane, Hadgraft and RidouP2) have shown that the water boundary layer on the skin surface can play a significant role in altering the measured permeability of skin. We restructure Eq. (31) based on three major assumptions: (1) that diffusion in the water on skin is proportional to molecular weight to some power, d , but that other factors contributing to the magnitude of this term are independent of the chemical; (2) that skin-water partitioning is described by Eq. (27); and (3) that diffusivity in skin depends on multiple terms relating overall skin diffusivity to diffusivity in the water and lipid phases of skin (both the bulk skin and the skin penetrations) but that all these diffusivities correlate to molecular weight

6skin

(C, + c , e w ) where MWx is the molecular weight of the chemical, g/ mol; a and d are constants; &kin is the thickness of hydrated skin, cm; K, is the octanol-water partition coef, are constants that are ficient; and Cb,, C, and C representative of the skin-water system and essentially chemically independent. From Eq. (27) above, the pararmeter a is 0.8 and the skin thickness is 0.0025 cm. Other constants in Eq. (32) were determined by optimizing the predictions of Eq. (32) against the values in Table I. Our optimization was based on two criteria: (1) minimizing the mean square error of the estimated values of log K, relative to measured values; and (2) developing an unbiased estimate of log Kp relative to measured values. From this, we obtain the following estimates, cb,

= 0.33 hr/cm

C, = 2.4 x 10-6cm2hr

C,

= 3.0 x 10-5cm2/hr

d = -0.6

-1

K,(skin, water, exp) =

+

Substituting these values into Eq. (32) gives

[

K,(skin, water, exp) = MW,-o-6 0.33

+ (2.4

&kin

x

10-6

+3x

1 0 - 5 ~ 3

6.2. Model Predictions vs. Measurements In Figure 4, we plot the estimation of K, by Eq. (33) against KO, for the 51 entries in Table I. To reflect the dependence of Kp on molecular weight, we use three ranges of molecular weight, 18 IMW I79, 80 5 MW 5 129, and 130 s MW s 230. As can be observed from the data in Fig. 4, measured permeabilities tend to reach a maximum value at a KO, of 1000 and remain flat or move slightly downward with increasing KO,. Our model explicitly follows this trend. Mathematically, this curvature results from the relative magnitude of the two terms inside the bracket of Eq. (33). When KO, becomes large, the first term inside the bracket of Eq. (33) dominates. Physically, this suggests that once KO, exceeds

Unified Dermal Uptake Models

f-

1.o

C

3

553

185

+

--

Y" 0.1

mw

-

5 79

0

0

measured values model results

0 -d.---

0.01 measured valuer 10-3

10-4

10-5

0.01

0.1

1

103

100

10

log

104

Octanol-water partition coefficient, KO, Fig. 4. The value of log K,,vs. log K, for the 51 entries in Table I (symbols) compared to the values estimated using Eq. (33) (lines). To reflect the dependence of K,,on molecular weight, we use three ranges of molecular weight, 18 s MW s 79, 80 s MW s 129, and 130 s MW 5

230.

1000, it is the water boundary layer that is controlling permeability in experimental skin-water systems. With regard to predicting the 51 Kp values in Table I, we calculate that Eq. 33 has an estimation error with a geometric standard deviation (GSD) of 3.0 (i.e., 68% of the predicted values are within a factor of 3 of the measured value, and 95% of the predicted values are within a factor of 9 of the measured value). We also determined that the correlation of the log Kp predicted by Eq. (33) vs. measured values has an 12 of 0.745. For the same 51 chemicals, the EPA-recommended permeability e ~ t i m a t e , ( as ~ ~reflected ~) in Eq. (6), has an estimation error with a GSD of 3.8 and the correlation of the log Kp predicted by Eq. (6) vs. measured values has an 9 of 0.717. When the Kp estimate in Eq. (7) (also discussed in the EPA report@))is applied to these 51 compounds, the resulting estimation error has a GSD of 3.5 and the correlation of the log Kp predicted by Eq. (7) vs. measured values has an 12 of 0.722.

a number of reasons for this complexity, but clearly a dominant reason is the heterogeneous structure of the stratum corneum. Nonetheless, we can use Eqs. (27), (31), and (33) to indirectly estimate this diffusion coefficient. By comparing Eq. (33) to Eq. (31), we can determine that D,,,,/S;,,,, is equal to MW~O.70.33cmhr and that

2.4 x

Because of the complexity of mass transfer through the stratum corneum, it is not possible to define an accurate expression for estimating Dskjn directly. There are

10-5e$

&kin

]

(34)

or

Dsbn = 2.4 x

+3

x 10-sKo,$

Km = Mw;o.6

6.3. Predicting the Diffusion Coefficient of Skin

+3x

2.4 x 10-6 0.64

[

+ 3 x 10-5g: + 0.25e:

1

This is the diffusivity that we believe is the appropriate value to use in modeling the resistance of skin with respect to any donor matrix (water, soil, or other) for com-

McKone and Howd

554

pounds with MW 5 280. For the compounds listed in Table I, the skin diffusivity predicted by Eq. (35) is in the range of 8 x to 8 x cm2/hr (2 x to 2 x 10-13 m2/sec), with most compounds in the upper part of this range. This is consistent with the observation by Scheuplein and Blankc3) that the effective diffusion coefficient through the stratum corneum is on the order of 10-14 to 10-13 m2/sec for low molecular weight compounds. 6.4. Steady-State, Water-Skin Permeability for Actual Exposure Conditions

For dermal exposures to water-borne contaminants during showers, baths, and swimming, where the water layer on skin is much more turbulent than is typical of experiments, we expect the steady-state permeability in the skin-water system, K,(skin, water) to be in the form of Eq. (31) but to have a smaller boundary layer thickness than occurs in the stagnant diffusion cells. Thus, we believe that the steady-state permeability for actual exposure conditions takes the form, -1

KJskin, water) =

(36)

where S,,,,, is the boundary layer thickness in actual exposure conditions. Because of the turbulent nature of water layers on the skin of individuals who are bathing, showering, and swimming, we consider this term to be negligible for the exposure model we suggest below. The is obtained from Eq. (34) with &kin factor, 8skin/(K,$skin) in the range 0.0015-0.0025 cm.

6.5. A Revised Steady-State, Soil-Skin Permeability Model Equation (35) can be substituted into Eq. (8) along with the substitution of ZskiJZ,,,,, for K, and of K,, for Zsoil/Zwater (Ksw is the soil-water partition coefficient and equal to Eq. (22) multiplied by H) to obtain an estimate of permeability, Kp in cmhr, in a skin-soil system as,

of 0.0015 cm (15 pm) instead of 25 km, because skin in contact with a soil layer is not as fully hydrated as is the skin used in experiments to measure permeability from water. 6.6. Mass Transfer During the Lag Time Before Steady-State

It should be noted that the permeability predicted by Eqs. (33) and (37) is only valid at steady state, when the stratum corneum is fully saturated with the chemical being transported through it. As is observed in experiments designed to measure permeability from a donor solution, there is a lag time before steady-state, which is the time it takes for the chemical to penetrate the stratum corneum.(16) Based on an exact solution of the time-dependent diffusion equation as applied to a membrane such as skin, Flynno has shown that this lag time, LT in hr, can be calculated as

LT

=

S:kin -

For the chemicals in Table I, the lag time calculated with Eq. (38) varies from 0.13 hr (8 min) to 1.5 hr (90 min) with the majority of these compounds in the range 10-15 min. This range is comparable to that observed by Roberts et al.(16)for phenolic compounds. These values are also comparable to the exposure time associated with baths and showers. Creek and B~nge(~') have shown that mass transfer to skin from water during this lag time is much larger than steady-state uptake in an equivalent amount of time. During the lag time, chemicals in water (or soil) on skin are being transferred to skin through a mix of diffusion and partitioning. Steady-state permeation only takes place when the full thickness of the stratum corneum is saturated relative to the water layerthat is, when the equilibrium ratio K, has been achieved at the surface. It we assume a linear concentration gradient from a concentration C, x K, at the stratum corneum surface to zero at the lower surface, the amount of chemical in mg/cm*(skin) per mg/cm3(water) that must be absorbed from the water layer to achieve chemical saturation is given by uptake before saturation =

where &soil is the soil thickness, cm, and Dsoilis the soil diffusion coefficient in cm2/hr. In applying this expression to model soil uptake, we use a skin thickness

(38)

Dskin

Sskin Km 2

(39)

This uptake can be considered as an absorption ratio from water, AR,, the amount taken up in mg/cm2 during an event divided by the concentration applied in mg/cm3. This absorption ratio from water to stratum corneum is much larger than the absorption ratio that would be pre-

Unified Dermal Uptake Models

555

dicted from steady-state permeability-that is, - [(K,n Dski,,/8&.in]X 0.15 hr, which is roughly a factor Of 20 less. Thus, it is important to recognize uptake to skin during this lag time in an exposure assessment. It should also be noted that not all of the chemical absorbed from water or soil to stratum corneum during this lag time will ultimately pass through the stratum corneum to underlying viable tissue, but there is no experimental basis at this time to determine what fraction evaporates off the stratum corneum.

(c) If exposure time per event, ET, is greater than the lag time, LT, then

ARwater = 7. IMPLICATIONS FOR EXPOSURE AND RISK ASSESSMENT

EF ATED x CF x C,

ADD = A&,,,,

(a) Calculate the lag time (LT) from Eq. (38). (b) If the exposure time per event, ET, is less than or equal to the lag time then

x

SA, BW

x

(40)

[UF,/BW] is the uptake factor per unit body weight for contaminant in exposure medium k, ml(water or soil)/ kg(body weight) - d . UF, expresses the uptake in mg/d per day per unit concentration (mg/ml) in the donor matrix. EF is the exposure frequency, days per year; ED is the exposure duration, years; AT is the averaging time, L/ml for water days; CF is a conversion factor, and 0.0015 kg/ml for soil; and C, is the concentration in soil or water, mg/L or mgkg. The uptake factor UF, is the product of three terms: (1) the absorption ratio, AR, in cm; (2) the amount of skin surface exposed, cm2; and (3) the number of exposure events per day. AR, expresses the ratio of the absorbed dose per event (referred to as DA,,, by EPA)(') to exposure medium concentration and is equal to uptake per unit area of skin per unit concentration in the donor matrix, mg/cm2 per mg/cm3. Based on our revised model, the absorption ratio for water, A&,,,, in mg/cm2(skin) per mg/cm3(water), is calculated according to the following steps:

x K, x

Dskin (42) sskin

where the term KmD&in/sskinis calculated from Eq. (34) and we make the assumption that boundary layer resistance can be ignored (i.e., Swat,,P 0). For one exposure event per day, we calculate the ADD for dermal contact with water as

Based on EPA recomrnendation~,(~?~~) when environmental chemical concentrations are constant in time, the average exposure for a specified population exposed to a concentration C, (m@L water or mgkg soil) in exposure medium k (i.e., water or soil) is expressed as the average daily potential dose (ADD), in mgkg-d, during some exposure duration and is given by ADD=[Z]x

&in K m + (ET - LT) 2

'

ED x EF AT x C, x 1 eventld

(43)

where SAWis the skin surface area, cm2, in contact with the contaminated water during exposure; C, is contaminant concentration in water, m a ; and other factors are as defined previously. Because the skin is not fully hydrated when in contact with soil, it is less thick and the lag time is only two thirds as large as it is for water content. In addition, exposure times for soil contact are often much longer than the lag time. We find little difference in the uptake predicted by our model with or without the lag-time effect for soil exposures lasting more than 1 hr. Thus, based on our revised model, the absorption ratio for soil, ARSoi,in mg/cm2(skin)per mg/cm3(soil), is adapted from the McKone(") model according to the following steps: (a) Calculate intermediate parameters g and n, g =

K,(skin, soil)

n = g +

8soi1

K (soil, air) p

-

Osoil

(44) (45)

where Ssoi,is the soil loading on skin in ml/cm2, and KJskin, soil) and KJsoil, air) are obtained from Eqs. (37) and (9). (b) Then calculate absorption ratio using these

McKone and Howd

556

parameters in expression ARsoiI =

ssoil

(I) (1

- exp(-n x ET)}

(46)

For one exposure event per day, we calculate the ADD for dermal contact with soil as SAsoil ED x EF ADD = ARsoil X AT BW x 0.0015 kdml x C, x 1 eventld

(47)

where SAsoi, is the skin surface area, cm2, in contact with the contaminated soil during exposure; C, is the contaminant concentration in soil, mgkg; and other factors are as defined previously. For exposure and risk assessments, Eqs. (43) and (47) provide the basis for estimating dermally absorbed doses from contact with contaminants in water and soil. For dermal exposures to water-borne contaminants during showers and baths, where the exposure time is comparable to the lag time for skin penetration, partitioning of contaminant from water to skin is the major contribution to contact. For dermal exposures to soil-borne contaminants during outdoor work and recreation, where the exposure time is much larger then the lag time for skin penetration, steady-state permeability from soil to skin is the major contribution to the estimate of exposure.

8. SUMMARY AND DISCUSSION

We present here models for estimating permeability of nonionic organic chemicals in contact with human skin at low concentrations in either water or soil. We also present a method for using the measurement of permeability in skin-water systems (primarily in v i m diffusion cells) to derive the diffusivity of a given chemical in stratum corneum. We combine this information into a process for estimating contaminant uptake from soil or water to or through the stratum corneum. These procedures require the assumptions that (a) dermal uptake of contaminants occurs by a transient partitioning to, followed by steady-state passive diffusion through, the stratum corneum; (b) resistance to diffusive flux through layers other than the stratum corneum is negligible; and (c) the gradient of concentration across the stratum corneum is so large that the chemical concentration at its lower surface is negligible. However, unlike other models for mass transfer from a donor matrix to

skin, our model incorporates the mass transfer resistance attributable to the concentration gradient in the water or soil on the skin surface. This effect appears to be important for interpreting measured permeability from water for compounds with a KO, greater than lo3 and in soils for compounds with KO, greater than lo5. We believe this model can be used reliably for compounds with MW 5 280 g. Our model reveals that transport is proportional to the area contacted, the partition coefficient between the donor matrix (soil or water), the diffusion coefficient in the skin, the concentration in the donor matrix, and the diffusion coefficient in the donor matrix. For estimating experimentally measured permeabilities, this model has an estimation error with a geometric standard deviation of 3, which is lower than existing models. Nonetheless, there are many uncertainties in this modeling approach that remain to be identified, quantified, and reduced.

ACKNOWLEDGMENTS

This work was performed under the auspices of the U.S. Department of Energy (DOE) at Lawrence Livermore National Laboratory under contract W-7405-Eng48 with funding provided in part by the California Department of Toxic Substances Control through Memorandum of Understanding Agreement 91-TOO38 and in part by the Office of Research and Development of the U.S. Environmental Protection Agency (EPA) under Inter-Agency Agreement contract DW-8993-4205. The views expressed are those of the authors and not necessarily those of the DOE, EPA, or CDHS.

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