Page 7 of 9 Alternate modeling approaches for estimating beef and milk concentrations

Webster and Connett (1990) compared five models which estimated the 2,3,7,8-TCDD content of cow's milk from 2,3,7,8-TCDD air contamination. The five models were described in Michaels (1989), Connett and Webster (1987), Stevens and Gerbec (1988), Travis and Hattemer-Frey (1987), and McKone and Ryan (1989). Ironically, a sixth model by Fries and Paustenbach (1990), noted by Webster and Connett as available but received too late for inclusion in their article, formed the basis for the approach taken in this assessment.

All five models compared by Webster and Connett have the same basic framework. Particulate-bound 2,3,7,8-TCDD deposits onto the ground and vegetation (cattle feed and pasture grass). Algorithms to estimate resulting vegetation and soil concentrations in these models are the same ones used in this approach, although parameter assignments are different. A daily dosage of 2,3,7,8-TCDD to the cattle is calculated and converted to a concentration in whole milk using a "biotransfer factor". This same structure was used to estimate concentrations in beef, using a beef biotransfer factor different than the milk biotransfer factor.
Mathematically, this is expressed as:

Equation V3 7-7

Further details on the models can be found in their primary references and in Webster and Connett's comparison. Some highlights, including comparisons of the five approaches to the approach taken in this assessment, are:

1) Two of the approaches, that of Stevens and Gerbec (1988), and McKone and Ryan (1989), consider inhalation of contaminated air by cattle to contribute to their daily dose of 2,3,7,8-TCDD. One of the approaches, that of Travis and Hattemer-Frey (1987), considers ingestion of contaminated water by cattle. A later assessment by Travis and Hattemer-Frey (1991) has all the components of their earlier assessment, and adds cattle inhalation exposures. This assessment does not consider cattle inhalation of contaminated air nor ingestion of contaminated water in estimating beef and milk concentrations. However, these intakes were shown to be insignificant when estimated by these researchers. Stevens and Gerbec estimate inhalation contributions to be less than 0.05% (0.0005 in fractional terms) of total daily dose, or an essentially insignificant amount. Travis and Hattemer-Frey (1991) estimate inhalation to contribute between 0.3 and 1.0% to milk and beef concentrations, respectively. McKone and Ryan (1989) did not provide sufficient information to easily determine the relative contribution of inhalation on estimation of cattle beef and milk concentrations by their estimations. Travis and Hattemer-Frey (1987, 1991) estimate water contributions to be less than 0.01% (0.0001) of total daily cattle dose of 2,3,7,8-TCDD.

2) None of the approaches considered vapor phase transfers from air to plant, although Webster and Connett recommended its inclusion in their article. The later assessment by Travis and Hattemer-Frey (1991) on 2,3,7,8-TCDD did include vapor phase transfers into vegetation consumed by cattle. According to results of the example scenarios in this assessment, these transfers appear to be particularly critical, and this was also the conclusion of Travis and Hattemer-Frey based on their modeling results.

3) Two of the assessments, that of Stevens and Gerbec (1988) and Fries and Paustenbach (1990) considered a period of residue-free grain only diet for a period of time before slaughter for purposes of fattening the cattle. Stevens and Gerbec (1988) assumed that the residues in cattle would depurate during the last 130 days of their lives on this regime. Assuming a half-life of 2,3,7,8-TCDD in cattle of 115 days, they showed a 54% reduction in beef concentrations due to this practice. Fries and Paustenbach (1990) note that cattle can gain as much as 60-70% in body weight, so dilution can also result in lower beef concentrations at slaughter. Procedures are not described in this assessment to estimate the reduction of concentrations in beef and milk fat due to depuration or dilution periods. However, the modeling result that residue concentrations in the beef are reduced by about 50% was used in the air-to-beef model validation exercise that was described in Section The procedures to estimate a reduction in concentration used by these researchers is straightforward. Assuming first order kinetics sufficiently describes reduction in concentrations during a period prior to slaughter, the fractional reduction during such a period is given as, 1 - exp(-kdt), where kd is the depuration rate constant, in days-1, and t is the depuration period, in days. The rate constant can be estimated from the depuration half-life, HL, as 0.693/HL. The 115 day half-life assumed by Stevens and Gerbec (1988) corresponds to a rate constant of 0.006 day-1, and assuming a 130 day depuration period, the fractional reduction is easily calculated as 0.54 (i.e., 1 - exp(-kdt)). The amount remaining after 130 days is estimated as the initial amount multiplied by 0.46 (i.e., exp(-kdt)).

4) Two of the assessments did not assume any cattle ingestion of contaminated soil, and two of the assessments estimated the contribution to milk concentrations due to ingestion of contaminated soil was minor at 1 and 2%. Only one of the assessments, Travis and Hattemer-Frey (1987), estimated any significant impact due to soil ingestion, attributing 19% of the concentration due to ingestion of contaminated soil. Their later assessment (Travis and Hattemer-Frey (1991)) estimated soil to contribute 29 and 20% of beef and milk concentration estimations, respectively. They estimated this high a contribution by contaminated soil even though they assumed that contaminated soil comprised 1% of the total dry matter intake by cattle. Fries and Paustenbach (1990) recognized the importance of cattle soil ingestion, evaluating scenarios where cattle soil ingestion ranged from 1 to 8% of total cattle dry matter intake.

The example scenarios in Chapter 5 assumed that beef cattle ingestion of contaminated soil was 4% of their total dry matter intake, and 2% of a dairy cattle's intake was contaminated soil. The percentage of beef and milk concentrations of 2,3,7,8-TCDD attributed to soil, feed, and pasture grass, when soil contamination is the source and when stack emissions are the source, was examined in Section in Chapter 6. It is noted there that soil ingestion appears significantly more critical for soil contamination as compared to stack emissions. Soil ingestion by beef and dairy cattle explain around 90% of final beef and milk concentration for soil sources. On the other hand, soil ingestion explained only around 5% of final beef and milk concentration for the stack emission source.

The earlier literature noting only 1-2% impact by soil ingestion were more analogous to the stack emission source category than the soil source category, in that impacts were estimated starting from air-borne contaminants depositing onto soils and vegetations. One difference in the assessments estimating the 1-2% impact with this assessment indicating about 5% impact was that the other assessments assumed less soil ingestion, 0.5% in Stevens and Gerbec (1988) and 1-3% in Travis and Hattemer-Frey (1987) and McKone and Ryan (1989).

The critical focus of the Webster and Connett (1990) comparison, is the milk fat bioconcentration factor, BCFmf. As shown in Equation (7-7), the biotransfer factor, Fm, is estimated using experimental data which yields a milk fat bioconcentration factor, BCFmf. Experiments most relied upon by these modelers are those described in Jensen, et al. (1981), and Jensen and Hummel (1982). A key difference in the early modeling approaches is the interpretation of these two and other studies and the resulting assignment of BCFmf, with values ranging from 5 to 25. Webster and Connett (1990) discuss issues of experimental interpretation.

Parameter assignments and assumptions (cattle soil ingestion versus no ingestion, etc.) obviously all impact estimations and can be a critical source of variation and uncertainty in estimates of beef and milk concentrations. The uncertainty associated with the modeling framework described above was explored by McKone and Ryan (1989) using Monte Carlo techniques. They found that the 90% confidence range for human exposure to 2,3,7,8-TCDD, where the source was air contamination and the human exposure route was through milk, spanned two to three orders of magnitude.

The approach taken by all five researchers centers on the milk biotransfer factor, abbreviated Fm in Webster and Connett (1990) and in units of day/kg. Beef bioaccumulation was modeled in the same way using a beef biotransfer factor, Fb. Travisand Arms (1988) developed this concept to the fullest, taking several data sets from the literature on a variety of contaminants and animals, to derive empirical formulas for Fb and Fm, which they termed Bb and Bm, as a function of contaminant octanol water partition coefficient, Kow:

Equation V3 7-8a

Equation V3 7-8b

Given a log Kow of 6.64 for 2,3,7,8-TCDD (assumed in this assessment), Bb is solved for as 0.110 and Bm is solved for as 0.034. Travis and Hattemer-Frey (1991) used 0.80 and 0.03 for 2,3,7,8-TCDD Bb and Bm.

Simple transformations can show how the earlier approaches, summarized above in Equation (7-7), and the approach of Fries and Paustenbach (1990), the one used in this assessment, are the same. First, the concentration of dioxin-like compounds in the fat of beef and milk is given in this assessment by (also see Chapter 4):

Equation V3 7-9

Transformation steps are:

1) factor out the BCF from Equation (7-9) ,

2) multiply Equation (7-9) by unity expressed as Q/Q, where Q equals total dry matter intake by cattle;

3) the multiplication of Q by the diet fraction terms, DFs, DFg, and DFf, gives the values for soil dry matter intake, Qs, grass - Qg, and feed - Qf,

4) with BCF factored out, and Q*DFs replaced by Qs, etc., the parenthetical now reads, (Qs*Bs*ACs + Qg*ACg + Qf*ACf) - this is the "Dose" term defined earlier in Equation (7-7),

5) finally, multiply the right hand side of Equation (7-9) by fat content, say fm for milk, which would transform the right and hence left hand side of that equation to whole product concentration. Transformed Equation (7-9) is analogous to Equation (7-7):

Equation V3 7-10

One critical theoretical assumption not explored in the earlier literature is whether 2,3,7,8-TCDD bioaccumulates equally in beef fat and milk fat - are the BCFmf and BCFbf equal? Fries and Paustenbach (1990) emphasize that differences in observed concentrations in beef and milk are critically a function of the differences in the diets of cattle raised for beef versus those raised for milk. They assumed that the beef and milk bioconcentration factor was equal for their example calculations. The key difference Fries and Paustenbach cite is the tendency for beef cattle to graze while lactating cattle are more often barn fed. Grazing cattle intake more contaminated soil than barn fed cattle. Fries and Paustenbach derived F for higher chlorinated dioxin-like compounds from experimental data, noting that the F value is less with higher chlorination. Webster and Connett (1990) made the analogous observation, saying that 2,3,7,8-TCDD equivalents transferred from air to milk less efficiently than 2,3,7,8-TCDD. This is also consistent with the data of McLachlan, et al (1990), which is used in this assessment for assignment of BCFs to dioxin-like compounds.

Some conclusions from this analysis of earlier efforts for estimating bioconcentration in beef and milk are:

• Although the framework of the earlier approaches looks different than the framework used in this assessment, they are actually the same with a simple mathematical transformation;

• The possible dosage to cattle of 2,3,7,8-TCDD via contaminated air or water was considered in earlier assessments, but was not found to be a significant pathway, and was not considered in this assessment;

• Earlier assessments did not consider vapor phase transfers to vegetation consumed by cattle; the results of the demonstration scenarios suggest that this transfer is particularly critical;

• Even though the structure of the analysis has been consistent from the earlier to the current approaches, different assumptions on parameter values greatly impacts modeling results. The critical bioconcentration factor, earlier termed BCFm (for milk) and termed simply BCF in this assessment, has been estimated to be between 5 and 25 for 2,3,7,8-TCDD in different assessments. This assessment uses a BCF value of 4.3 for 2,3,7,8-TCDD. Using Monte Carlo techniques on this model structure for estimating human exposure to milk resulting from air contamination of 2,3,7,8-TCDD, McKone and Ryan (1989) showed a 90% confidence interval spanning 2 to 3 orders of magnitude.


The purpose of this section is to qualitatively describe the uncertainties associated with exposure estimates for the exposure pathways that are included in this methodology. The principal focus is on the exposure parameters - the contact rates and fractions, exposure durations, and so on. A brief summary is also presented on some of the findings pertaining to the fate, transport, and transfer algorithms used to estimate the exposure media concentrations.

This summary will highlight findings that have been included in other sections of this chapter as well as a section in Chapter 6 on User Considerations. Sections 7.2.3 and 7.2.4 above make comparisons between estimated exposure media concentrations and observed concentrations, and discuss alternate models to use for estimation of exposure media concentrations, respectively. Section 6.3 of Chapter 6 discusses the sensitivity of model estimations of exposure media concentrations with changes in required model parameters.

Each section below includes a table summarizing key points of uncertainty. Section 7.3.1 looks at three key exposure parameters which are common among all pathways - lifetime, body weights, and exposure durations. Sections 7.3.2. to 7.3.11 are pathway-by-pathway discussions.

7.3.1. Lifetime, Body Weights, and Exposure Durations

As discussed in EPA (1989), values for lifetime of 70 years and adult body weight of 70 kg are derived from large national studies and are not expected to introduce significant uncertainty into exposure estimates. The assumed child body weight of 17 kg (for ages 2-6) is similarly well founded and not expected to introduce much uncertainty into soil ingestion exposure estimates.

Assumptions on exposure durations are the most uncertain of the three parameters discussed here. A value of 9 years assumed for central exposure scenarios was an average derived from census survey data (EPA, 1989) which only asked of respondents the amount of time they lived in their current residences. It is likely to therefore be an underestimate as an average amount of time spent in one residence (i.e., respondents are expected to continue to live at their residence). The estimate of 20 years for the average residence time of farming families (used to define high end exposure scenarios) was not based on data but rather on judgement that farming families live at their farm site longer than non-farming families.

Exposure durations are also tied to assumptions about source strength over time. Assuming 20 years of exposure to stack emissions, for example, assumes that the source of stack emissions will be (or has been) in operation for this length of time with the same stack emission controls in place. The same is noted for the effluent discharge source category. If the source is contaminated soil, assumptions include whether or not the soil will be removed, the site will be capped, and so on. Another consideration is the dissipation of soil residues. Section 7.2.1. discussed uncertainties with the assumption of non-degradation of dioxin-like compounds in soil when the soil itself is contaminated.

A ten-year dissipation half-life is assumed for circumstances where residues migrate to an exposure site to impact only a thin layer of surface soil. This is relevant for the erosion from an off-site soil contamination site to an exposure site and the deposition of residues emitted from a stack. An assumption of non-degradation is appropriate given:

1) evidence that suggests little if any degradation of 2,3,7,8-TCDD (and by extrapolation, other dioxin-like compounds) except via photolysis, which would not impact residues below the soil surface,

2) a mass balance exercise conducted in Section 6.4., Chapter 6, which evaluated the possibility that routes of dissipation considered would deplete an available reservoir of 2,3,7,8-TCDD prior to or near an assumed duration, showed that it would take 90 years to deplete a reservoir of 2,3,7,8-TCDD extending only 6 inches into the soil, and

3) simply that the fate, transport, and transfer algorithms of this assessment have been characterized as screening level in their theoretical sophistication although site specific in their application. In site specific assessments, which are either based on past or projected exposures, more precise statements to address the strength of the contamination source over time should be considered.

Exposure estimates are linearly related to all three exposure parameters - increasing body weight and lifetime decreases exposures in an inverse linear fashion, while increasing exposure durations increase estimates in a direct linear fashion.

Uncertainties associated with body weight, lifetime, and exposure durations are summarized in Table 7-13.

7.3.2. Soil Ingestion Exposure

This exposure is directly a function of the concentration of contaminants in surface soil layers. For example Scenarios 1 and 2, demonstrating the on-site soil source category, soil at the site of exposure was contaminated to a specified level. For example Scenario 3, demonstrating the off-site source categories, erosion onto the site of exposure deposited residues into a thin, no-till, surface layer of 5 cm, and a thicker, 20-cm, till layer of soil. Soil ingestion exposures were based on concentrations in the 5-cm layer. In Scenarios 4 and 5 demonstrating the stack emission source category, contaminated particles deposited onto the exposure site, also creating a till and a no-till concentration. The no-till depth for this category was 1 cm instead of 5 cm, based on hypothesized differences in fate of contaminated particles when they were transported as eroded soil versus particle deposition from the air.

Discussions on the methodology to estimate exposure site soil concentrations resulting from erosion of contaminated soil from a nearby site are contained in Section 6.3.2, Chapter 6, which was on sensitivity analysis and the impact of different parameter values on estimated exposure site soil concentrations, and in Section above discussing literature reports of off-site impacts from soil contamination. While off-site impacts were noted in the literature, no data could be found that was directly amenable to comparison with the scenarios of Chapter 5. The closest site for which data was available was the Dow Site in Midland, Michigan. The ratio of soil concentrations of 2,3,7,8-TCDD in areas described as "background" in the 600 ha site to soil concentrations in the contaminated areas was 1/8 to 1/2 as much (depending on how the contaminated area soil concentration was interpreted) as the ratio modeled in the off-site demonstration scenario.

This might imply that the model overpredicts off-site soil impacts, except that the "background" areas in the Dow Site appear substantially further away than the 150 meters in the off-site demonstration scenario. Also, data was unavailable to determine the erodibility of soil at the Dow Site, which along with other site-specific information, may have allowed for a more precise test of the algorithms of this assessment. Still, a key finding in the sensitivity analysis exercises was that the erosion algorithms may be overestimating off-site impacts. If so, the overestimation is most likely the result of assuming an "enrichment ratio" of 3 for soil erosion (the concentration on eroded soil divided by the concentration of in-situ soil).

table Table 7-13. Uncertainties associated with the lifetime, body weight, and exposure duration parameters..
No information is available on estimating how much of an overestimation may have resulted, and this finding is not a definite conclusion.

If the algorithm overestimated the impact from soil erosion, it is unlikely that overestimation exceeded the factor of 3 attributed to the enrichment ratio.

Other sensitivity analyses exercises indicated that different parameters values for individual parameters result in roughly an order of magnitude difference in soil concentration estimation around the concentration which was estimated using all parameters assumed for the demonstration scenarios in Chapter 5.
expand table Table V3 7-13

In addition to the enrichment ratio, the depth of mixing is an uncertain parameter. This is a theoretical parameter for which little data is available. Others have also assumed depths of mixing of 1 cm for analogous applications. Evidence from radioactive fallout suggests depths no deeper than 5 cm. Sensitivity analysis on the erosion algorithms showed that assuming a depth of 1 cm instead of 5 cm would have increased soil concentrations by a factor of 2.5, while decreasing the mixing depth to 10 cm decreases soil concentrations by 60%.

No information could be found in the literature which could be used to evaluate the algorithm for soil concentrations resulting from particulate depositions from stack emissions as modeled by the COMPDEP model. However, evaluation of the air-to-soil algorithm of the stack emission source category suggests that the model may be underpredicting soil concentrations, possibly by about an order of magnitude. Soil concentrations are, of course, not an issue for the on-site soil source category, where that concentration is a principal input and not an estimated value.

Another issue is whether children should be assumed to be exposed to tilled soils, tilled by home gardening, farming, etc., or untilled soils. It is feasible that children would be exposed to tilled soils in farming or home garden settings. If the soil was impacted by stack emission depositions or erosion from a nearby site of soil contamination, then tilling would reduce soil concentrations. However, it is more reasonable to assume that they generally play outside in areas that are not mechanically tilled.

The estimated soil ingestion quantity is based on field measurements, using trace elements, of soil ingested by relatively small groups of children over brief periods. Methodological issues in these studies remain to be addressed. In particular, ingestion estimates may have been lower if dietary intake of the trace elements was taken into account. Research is underway to refine soil ingestion estimates obtained through trace element measurements. Given the available data, 0.2 g/day is used as a typical value for soil ingestion in young children. Due to the behavior known as pica, some children are known to be high ingesters of various non-food materials. Estimates of pica ingestion of soil by children have ranged as high as 5 g/day. Although no quantitative data on soil ingestion are available for children known to exhibit pica, the use of the high-end estimate of 0.8 g/day may better reflect such behavior.

Soil ingestion exposure estimates also depend on the duration of the period over which children are assumed to ingest soil. Data on soil ingestion by age are not available, and the estimate that significant ingestion occurs between ages 2 and 6 is broadly supportable on behavioral grounds.

No measurement data are available on soil ingestion in infants (0-2 yrs. old) or in older children or adults, and no ingestion is assumed for these groups. While some soil ingestion will occur in these groups, e.g., through contact of soiled hands with food, it is plausible that such ingestion is of a lesser degree than occurs in early childhood. If Hawley's (1985) estimate that an adult ingests an average 0.060 g/d of soil is used, after accounting for differences in exposure duration (9-20 yrs versus 5 yr) and body weight (70 kg versus 17 kg), the adult soil ingestion exposure is close to the estimated exposure for children (at 0.2 g/d).

The high end example scenarios in Chapter 9 assumed that the exposed family was involved in farming operations. One implication is that individuals on the farm would be working closely with the soil, which may result in some soil or dust ingestion (dust ingestion is distinct from the particulate inhalation exposure pathway). The other implication is that, should this be the case, they would be in contact with tilled soil, whose concentration is 20 times less than the no-till soil for which children are assumed to be exposed.

Considering these uncertainties, the soil ingestion exposure estimates presented for children are plausible. Further consideration may be warranted for considering adult soil ingestion, particularly in farming situations. Uncertainties associated with the soil ingestion pathway are summarized in Table 7-14.

7.3.3. Soil Dermal Contact Pathway

Estimates of dermal exposure to soil rely largely on four factors unique to this pathway: exposed skin area, soil adherence, frequency of soil contact and fraction of contaminant absorbed. The uncertainty in these three terms are discussed below.

Before that discussion, a brief note is made on uncertainties associated with soil concentrations. Discussions above on the soil ingestion pathway addressed uncertainties associated with soil concentrations which result from migration of residues from a distant source to the site of exposure. Distant sources in this assessment include off-site soil contamination and stack emissions. Discussions in the soil ingestion pathway section above pertain to this exposure pathway and are not repeated here. However, there is one key difference in the soil dermal and soil ingestion pathways.

Soil ingestion exposures are assumed to occur only from surficial soil layers and from untilled soils, which translates to the 5-cm (soil contamination source categories) and 1-cm (stack emission source category) mixing depth for both the "central" (residential) and "high end" (farming properties) scenarios. Soil dermal contact for the high end scenario assumes many dermal contact events, 350 per year, that is based on farming activities; the soil concentrations pertinent for this behavior, therefore, are tilled soil concentrations. On the other hand, only 40 dermal contact events per year, which may correspond to some gardening or other contact, is assumed for the central scenario. The soil concentration used in these scenarios is the untilled soil concentrations.

The uncertainty in the assumed value for exposed skin area reflects primarily population variability. As reported in EPA (1992a), relatively accurate measurements have yielded a good data base on total skin area. Thus the uncertainty in this factor is derived more from the assumptions of how much of the total skin area is exposed. EPA (1992a) recommends approaching this issue by determining the coverage of normal apparel in the exposed population and assuming exposure is limited to the uncovered skin. As discussed in EPA (1992a), this assumption could lead to underestimates of exposure since studies have shown that some exposure can occur under clothing, especially in the case of vapors or fine particulates. A default assumption of 25% uncovered is recommended corresponding to short sleeved shirt, short pants, shoes, and socks. Thus the key uncertainty issue concerns the variability in clothing behavior of the exposed population. In this document the 25% assumption was adopted for residents and 5% was judged more reasonable for farmers who are more likely to wear long pants and long sleeved shirts for field work. Although clothing coverage is likely to vary over the year and with personal habits, these assumptions are judged to be reasonable averages and unlikely to introduce more than a factor of two uncertainty.

table Table 7-14. Uncertainties associated with the soil ingestion pathway..
The potential for soil adherence probably varies little across the population, but few actual measurements have been made. Thus the uncertainty in these estimates reflect primarily the lack of measurement data rather than population variability.

Site variability is probably important as well since soil properties such as moisture content, clay content and particle size distribution are likely to affect adherence.

EPA (1992a) reports four studies which estimated soil adherence on hands under both laboratory and field conditions. Data from these studies were analyzed to obtain a central estimate of 0.2 mg/cm2 and a high end estimate of 1.0 mg/cm2.
expand table Table V3 7-14

The uncertainty in these estimates are derived from unknown efficiencies in the collection methods, relatively small number of subjects, assumption that hand measurements apply to other parts of the body and assumption that child measurements apply to adults as well. The central default value 0.2 mg/cm2 was adopted here for the residents and the high end value of 1.0 mg/cm2 was adopted for farmers. The uncertainties in this estimate could combine to produce either under or over estimates and may vary by as much as a factor of 5 on the basis of the ratio of the high end to central estimates.

Exposure frequency to soil reflects largely personal habits and thus the uncertainty is primarily based on population variability. Seasonal and climate conditions can also affect this behavior introducing site variability as well. EPA (1992a) suggests a central frequency of 40 days/yr corresponding to someone who does yard work, gardens or plays outdoors on most weekends and a high end estimate of 350 days/yr corresponding to a farmer or serious gardener in a warm climate. These recommendations were based on judgement rather than actual survey data. In this document, 40 days/year was selected for the residential scenarios and 350 days/yr for the farmer. The lack of survey data to support these estimates introduces uncertainty, but the values are judged to be reasonable and to create relatively little uncertainty.

The dermal absorption fraction of compounds varies widely across chemicals, whereas skin properties that affect absorption, i.e. thickness and composition vary little across the population. Thus the uncertainty in this factor is derived primarily from measurement error rather than population variability. Soil properties, such as organic carbon content, can also affect the extent of dermal absorption and thus create site variability as well. EPA (1992a) reports two studies which measured dermal absorption of 2,3,7,8-TCDD from soil. Testing included human skin in vitro, rat skin in vitro and rat skin in vivo. On the basis of these tests, a range of 0.1 - 3.0% was recommended in EPA (1992a). Dermal absorption testing, especially for soils, is a relatively new field and many uncertainty issues are involved. These include extrapolation of animal tests to humans, extrapolation of in vitro to in vivo conditions, and extrapolation of experimental conditions to expected exposure conditions. Extrapolation of the tests on 2,3,7,8-TCDD to the other dioxin like compounds (which have not been tested) introduces further uncertainties. A dermal absorption fraction of 3.0% was adopted here for application to all the dioxin like compounds. Based on the observed range of values for 2,3,7,8-TCDD this assumption may lead to overestimates of a factor of 30. Considering all possible uncertainties, under estimates are also possible, though judged less likely.

In summary, dermal exposure estimations rely on a number of parameters whose values are not well established. Although it is difficult to estimate the overall uncertainty with this pathway, it is judged to be plus or minus one to two orders of magnitude. A summary of the uncertainties associated with the dermal absorption pathway is given in Table 7-15.

7.3.4 Water Ingestion

The strong sorptive tendencies of the dioxin-like compounds result in very low water concentrations. Monitoring for PCDDs and PCDFs mostly have not found these compounds at a detection limit around 1 pg/L (ppq), and when found, have generally been very near this concentration. The one exception is an upstate New York community water system, where tetra through octa-CDFs were found at concentrations ranging from 2 pg/L (tetra) to over 200 pg/L (octa). The surface water concentrations predicted by the algorithms of this assessment for all source categories are 10-2 pg/L and lower, which is consistent with the sparse monitoring data. Although there was no data found that could be directly applicable to the source categories, it does not appear that the models estimating water concentrations will introduce significant uncertainty into water ingestion exposure estimates.

The classically assumed water ingestion rate of 2.0 L/day was examined in EPA (1989).

table Table 7-15. Uncertainties associated with the dermal exposure pathway.

The conclusion was that this estimate is more appropriately described as an upper percentile consumption rate for adults, and recommended 1.4 L/day for use as an average.

This value was used for water ingestion in the central scenarios. EPA (1989) cautions that data on consumption rate for sensitive subpopulations such as manual laborers are unavailable. As such, the 1.4 L/day rate for individuals in farming families who work the field may be low.

For this reason, a 2.0 L/day was assumed in the high end, farming, scenarios.

expand table Table V3 7-15

The contact fraction is defined as the fraction of total contact with an exposure media that is contact with contaminated media. For drinking water, this translates to the fraction of water ingestion that comes from the contaminated water source.

In the example scenarios, it was assumed that the impacted water was a river which supplied water to the exposed individuals, perhaps through a public water system. The contact fraction of 0.75 for central scenarios is based on time use surveys which showed roughly this fraction of time spent in and around the home environment on the average.

The upper recommended limit in EPA (1989) was 1.00; this was felt to be unrealistic for the example scenarios which involved relatively small sources and consequently the likelihood that contamination would not be widespread. Thus, a farmer would likely obtain some water from outside his home where the water supply was not contaminated. An assumption of 0.90 for farming familes was selected for the high end scenarios of this assessment. The uncertaintainties associated with the water ingestion pathway are summarized in Table 7-16.