Environ. Sci. Technol. 1994, 28, 2407-2414
Model of the Fate of Hydrophobic Contaminants in Cows Michael S. McLachlan
Ecological Chemistry and Geochemistry, University of Bayreuth, 95440 Bayreuth, FRG
A simple fugacity model is presented that describes the fate of trace organic pollutants in lactating cows. A t steady state, the fraction of ingested contaminant that is transferred to the milk is constant for persistent compounds with log Kow < 6.5. Thereafter the fraction transferred decreases rapidly with increasing KOW.The contaminant kinetics are similarly dependent on the properties of the compound, with superhydrophobic compounds showing longer half-lives. The model was successful in describing the measured steady-state behavior of chlorinated organic substances and did a reasonable job describing the kinetics obtained from feeding studies. An even simpler approach is suggested for calculating concentrations in nonlactating cattle, namely, dividing the amount of contaminant absorbed over the life of the animal by its body fat weight. The degree of absorption and the persistence of a compound are the key properties that determine whether it accumulates in animal foods.
Introduction Milk products are major sources of human exposure to persistent, hydrophobic, organic contaminants, contributing an estimated 28% to the average person’s uptake of polychlorinated biphenyls (PCBs) (I) and 32-43 % to the uptake of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) (2, 3). Hence, the behavior of these compounds in lactating cows is a particularly important factor determining human exposure. The fate of organic contaminants in cows has been extensively investigated. The most common experimental method is the feeding study, which emphasizes the kinetic behavior in the cow. Considerable progress has been made in modeling feeding study results, namely, the uptake and clearance behavior of single compounds (e.g., refs 4 and 5). However, less emphasis has been placed on understanding the steady-state behavior and the contaminant properties that determine this behavior. The most notable contribution has come from Travis and Arms (6). They presented an equation which linearly related the “biotransfer factor” (concentration in whole milk divided by daily contaminant uptake by the cow) to the n-octanollwater partition coefficient Kow. However, the high deviation (up to 2 orders of magnitude) of the measured biotransfer factors in their data set from the predicted values do not make their equation particularly convincing. Furthermore, the relationship is internally inconsistent, since it predicts biotransfer factors for compounds with log KOW values above 6.5 that would have the cow excreting more contaminant than it ingests. This paper represents an attempt to further our understanding in this area. A mathematical model of the fate of organic compounds in a lactating cow is presented. The steady-state model is parametrized using data from a mass balance experiment while the non-steady-state model is compared with the results of feeding studies. 0013-936X/94/0928-2407$04.50/0
0 1994 American Chemical Society
Goals of the Model
A mathematical model of an environmental process is always a compromise between twogoals. On the one hand, the model should account for as many aspects of the natural processes as possible. On the other hand, it should be easy to use and understand, as only in this case can the model be easily incorporated into multimedia models and find broad and appropriate application in the practical world. The first step in the modeling process was to decide which inputs and outputs were to be considered. Due to the importance of milk as a source of human exposure, the modeling emphasis was placed on predicting milk concentrations. Cow’s meat and organs are less important and were treated in a less rigorous manner. In a mass balance study of chlorinated organic compounds in cows, it was found that virtually all of the exposure comes through the ingestion of food (7,8). Inhalation may be a relevant pathway for compounds considerably more volatile than p-dimethoxytetrachlorobenzene, the most volatile compound looked at in this study. However, the residues of volatile organic compounds in milk are seldom of concern. Thus only ingestion and not dermal uptake or inhalation was included as an uptake pathway in the model. The relevant time frame is a further important modeling criterion. Feeding studies have shown that the half-life of many persistent organic compounds in milk is about 40-60 d (4,9). On the other hand, short-term kinetics in the order of minutes are not important as lactation is usually limited to twice per day. In order to adequately model a single ingestion of a large amount of contaminant or large daily fluctuations in the contaminant uptake, a time scale of 1 d would be necessary. However, these scenarios are unlikely in an agricultural environment where the same feed is fed for weeks at a time, although there have been exceptions such as the dioxin release at Seveso. It was decided that a model with a relevant time scale of weeks to months would be adequate. Model Structure The fugacity concept of Mackay (IO) was chosen for this model. The fugacity approach offers several advantages for this modeling task that will be come clear below. As in other pharmacokinetic models, the fugacity concept requires the division of the organism into compartments. Mathematical relationships are established for the equilibrium distribution of contaminant between the compartments, for the diffusive and advective transport, and for transformation processes. A mass balance is then written for each compartment, and the resulting set of equations is solved. For a detailed discussion of fugacity modeling see ref 10. The structure of the model is illustrated in Figure 1. The model consists of three compartments: the lumen of the digestive tract, blood, and fat. Diffusive transport is Environ. Scl. Technoi., Vol. 28, No. 13, 1994 2407
/-\ FAT
,
(VF)
FEED
,
DIGEST. TRACT
FECES
4
DA
BLOOD
DEGRADATION
Figure 1. Schematic of the structure of the cow model.
possible between the digestive tract and the blood and between the blood and the fat compartments. Transformation may occur in either the digestive tract or the blood. There are three advective flows: feed into the digestive tract, feces out of the digestive tract, and milk out of the blood compartment. Contaminant storage is included only in the fat compartment. The mass balance equations for the three compart,ments are as follows: digestive tract
blood
fat
& ~ c f -~f ~ )= d(VF&fF)/dt
(3)
where N is the contaminant ingestion rate (moll d-l), f is the fugacity (Pa). D is the transport coefficient, defined for advective processes as the product of a volume flow rate (m3 d-l) and a fugacity capacity 2 (moll m-3 Pa-l); defined for diffusive processes as the product of a conductance (ml d-l), an interface area (m2),anda fugacity capacity; and defined for transformation as the product of a rate constant (d-l), a compartment volume V (m3), and a fugacity capacity. The subscripts are defined as follows: D for the digestive tract compartment; B for the blood compartment; F for the fat compartment; E for excretion of feces; A for absorption; M for milk lactation; BF for blood/fat diffusion; RD for reaction or transformation in the digestive tract compartment; and RB for reaction or transformation in the blood compartment. Fat Compartment. The contaminant storage capacity of the cow was treated as fat. A cow consists of 5-25% fat, so even for moderately hydrophobic compounds one would expect most of the storage to occur in fat and not in the other more hydrophilic tissues. This conclusion is supported by the literature. In several studies, the concentrations of various PCDD/F and PCB have been found to be at least an order of magnitude higher in fat than in other tissues (11-13). There is also evidence that fat from different tissues has similar contaminant storage properties. The concentrations of DDT and dieldrin measured in different tissues of commercial cattle were, when expressed on a fat basis, 2408
Envlron. Sci. Technol., Vol. 28, No. 13, 1994
not significantly different (14). In a particularly exhaustive study, 26 tissues from three cows that had been fed PCB 153 for 4 wk were analyzed. With the exception of the liver, brain, and some bones, the concentrations on a fat basis for a particular animal varied by only a factor of 2, even though the cows were not in steady state (15). In another experiment, the concentrations of PCDD/F in grip fat, kidney fat, muscle fat, and subcutaneous fat following a 15-wk clearance also only varied by a factor of 2, with the exception of ClsDD (16). This supports the assumption that a single fugacity capacity can be used to model the fat storage properties in all tissues in the cow. The fugacity capacity was defined by assuming that fat behaves like an equivalent volume of n-octanol. This approach has been employed successfully to model the behavior of organic contaminants in fish (17). The use of a single compartment to describe the contaminant storage in the cow is a significant simplification. Most clearance experiments using lactating cows have reported first-order kinetics for the decrease in milk concentration with time (9, 18-20) and have evaluated their data using a one-compartment model. However, several of these authors and others (9, 18, 21, 22) have noted a more rapid decrease in the first several days of the clearance phase. This suggests that there may be a relatively small compartment that releases the contaminant more quickly than the fat reservoir. This compartment would have to be considered if the model time scale were days and not weeks. Blood Compartment and Milk. Blood serves as the transport medium between the digestive tract, milk, and fat in the model. As the storage capacity of blood is much lower than that of fat, no storage was included in this compartment. Transformation processes are included, however, and simulate metabolism in the liver or other body tissues. Lactation was modeled as a continuous fat flow leaving the blood compartment. It has been shown that hydrophobic organic contaminants in the milk are associated with the fat fraction (23). About 90% of the fat in the milk is taken directly from the blood (24). This indicates that the lipophilic material in the blood and the milk glands are in intimate contact. It is therefore reasonable to assume that the hydrophobic compounds in the blood are in equilibrium with those in the milk glands. In those feeding studies with hydrophobic compounds where the blood and milk concentrations were both measured, the time courses were very similar ( 1 1 , 131, and where the concentrations were determined on a fat basis, they were virtually the same in blood and milk (25). The model does not address the periodic (usually twice daily) lactation of the cow. By treating the milk as a continuous excretion of fat from the blood, it fails to account for interactions between the blood and the milk during the storage period prior to lactation. Hence, the model generates lactation predictions with a time resolution that does not reflect reality and that may also not reflect the behavior in the cow for a particular lactation period, as becomes clear later. Digestive Tract Compartment. The model treats the digestive tract as a well-mixed compartment with the properties of the lumen contents as they are excreted from the cow, i.e., the feces. The feces excretion is modeled as an octanol flow, a reasonable approach for hydrophobic compounds in view of the high organic carbon content of
this matrix. There is a diffusive link between the digestive tract and the blood, and transformation processes with first-order kinetics are included to account for the transformation of compounds like DDT and the hexachlorocyclohexanes (HCHs) in the digestive tract. A single well-mixed compartment model is a drastic simplification of the cow’s digestive tract. In reality, there are four stomachs in addition to the intestine. The flow in the system is not unidirectional but is complicated by the ruminating process. A detailed description of the behavior of organic contaminants would be complicated and extremely difficult to parametrize in view of the limited information on the behavior of these compounds in the different digestive organs. It is believed that the simple model utilized here accounts for the most important aspects of the contaminant behavior. The model treats absorption as a reversible diffusive process. Dietary fats are known to be taken up by diffusion through the wall of the intestine, a process that is facilitated by the high surface area and high blood perfusion of the intestinal wall. The hydrophobic fatty acids and monoglycerides are transported from the lumen to the intestinal wall in micelles, which provide for intimate contact between the hydrophobic molecules and the intestinal wall (26). Active transport is not involved. It is reasonable to expect a similar absorption mechanism for organic contaminants. There is some evidence indicating that the absorption process in the cow is reversible. For instance, a significant transport of polybrominated biphenyls from the blood to the lumen during the clearance phase following a contamination incident was reported (27). Parametrization of the Model There are eight coefficients in the model equations, two of which are defined by the user-the contaminant ingestion rate N a n d the milk transfer coefficient DM(the product of the lactation rate in m3 fat/d and ZF). The remaining six can be divided into three groups associated with three stages of increasing model sophistication: (a) steady-state model (DA,the transfer coefficient for absorption, and DE, the transfer coefficient for excretion); (b) non-steady-state model (DBF,the transfer coefficient for bloodlfat diffusion, and VFZF,the contaminant storage capacity of the cow); (c) transformation (DRD,the transfer coefficient for transformation in the digestive tract, and DRB,the transfer coefficientfor transformation in the blood and organs). The development of each of these three levels of the model will be discussed in the following. Steady-State Model (DAand DE). The parametrization of the steady-state model borrows from the fish digestion model developed by Gobas and co-workers (28). For a cow a t steady state ( f ~= fF from eq 3) and for compounds that are not transformed in the digestive tract, eqs 1-3 can be simplified to
(4)
where DE, DA, and DRBare the undefined coefficients. When the compound is quickly metabolized in the cow, the fugacity in the blood fB becomes negligible, a maximum absorption is obtained, and eq 4 can be simplified to
N = DEfD + DAfD
(6)
Defining the maximum fractional absorption EMas the quotient of the amount absorbed (=D& and the amount ingested (N) and substituting in eq 6, one obtains
E M = DA/(DE + DA)
(7)
It is now useful to apply the two-resistance theory to the absorption transfer coefficient DA. The wall of the digestive tract is modeled as a water film and an octanol film in series. DA is then given by 1/DA = 1/DAo f 1/DAw
(8)
where 0 and W refer to the octanol and water film, respectively. The transfer coefficient is the product of the fugacity capacity of the phase and a Q value (with units of m3/d). Equation 8 can then be rewritten as 1/DA = l/(&AOZO)f U(QAwZw)
(9)
where QAO and QAW are the product of the absorptive surface area and the conductance of the octanol and water films, respectively. ZWand ZOare the fugacity capacities of the substance in water and n-octanol and can be calculated from the Henry’s law constant and the Kow value (IO). DE can also be redefined in terms of a fugacity capacity and a Q value: DE = QEZo
(10)
where the excrement is modeled as octanol as described above and QE represents the volumetric excretion rate of feces expressed in octanol equivalents. Inverting eq 7 and substituting in eqs 9 and 10, one obtains
a relationship between the maximum fractional absorption and the Kow of the compound. The KOWdependence can be explained as follows. The fractional absorption is determined by two competitive processes: advection through the digestive tract and diffusion through the wall of the digestive tract into the blood. As long as the diffusive resistance for absorption is dominated by the octanol film (i.e., Kow is small), both processes are linearly dependent on the fugacity capacity of the compound in octanol: excretion is governed by the solubility in the octanol fraction of the feces and absorption by the solubility in the octanol film. These two dependencies cancel each other out, and the fraction absorbed is independent of the properties of the compound. However, as KOWincreases Zw decreases with respect to 20, and eventually the resistance of the water film begins to dominate the total diffusive resistance. In this case, absorption becomes proportional to Zw while the excretion is still proportional to 20. The fraction absorbed is related to the quotient of absorption and excretion or 1IKow. Asimilar approach can be taken for the case of persistent compounds where one cannot assume that fB is negligible. In this case, the absorption is no longer a maximum but is reduced by the blood fugacity, and the fraction absorbed should decrease. By substituting eqs 4 and 5 into the definition of the fraction absorbed, one obtains Envlron. Scl. Technol., Vol. 28, No. 13, 1994 2400
1
where Eo is the fractional absorption assuming zero transformation. Invoking the two-resistance model once again and expressing DM as
0.8 06
Fractional Absorption
7 y -
-
.__ -
DM = QMZO
(13)
where QM is the volumetric flow of milk fat, eq 12 becomes
1/Eo = 1
QE/Q,
+ QE/QAO
-I-(QE/QAW)KOW
(14)
This is very similar to eq 11. The coefficient of the KOW term is identical while the constant contains a second contribution (&E/&). The presence of this term means that the absorption of a persistent compound will always be less than the absorption of an easily metabolized compound at steady state. This is in agreement with the intuitive expectation stated above. The &E/& term also indicates that the ratio of the feces and the milk transfer coefficients determine the degree to which the absorption is restricted. This is to be expected, since the rapid excretion of a compound in the milk means that it will not have the opportunity to accumulate in the blood. Milk excretion and feces excretion are competing removal processes occurring on opposite sides of the diffusion barrier. Both of these processes depend linearly on 20, and hence their quotient is independent of Kow. Thus, the absorption of persistent compounds will be a constant fraction less than the absorption of labile compounds as long as the octanol film is the dominant diffusive resistance. With increasing KOW,the water film becomes more dominant, reducing absorption. For very high Kow values, the diffusive resistance becomes so high and absorption so low that the milk flux can readily remove the absorbed contaminant, and the fugacity in the blood is essentially zero. In this case, there is virtually no difference between the fractional absorption of persistent and labile compounds. The model of absorption was fitted to data obtained from a mass balance study of a lactating cow. The test animal was a 4-year-old Simmenthal cow producing 27 kg of milk (1.31 kg of milk fat) per day in her third month of lactation. Polychlorinated benzenes, PCBs, PCDDs, PCDFs, and a variety of other compounds were analyzed. The details of the study and the results have been published elsewhere (7, 8). Here, use is made of the absorption data. Note that the PCDD/F absorption data in ref 7 were subsequently increased by 18%as the result of a more accurate calculation of the amount of feces excreted. Several congeners that showed large discrepancies in the mass balance were not included. The fractional absorption for the persistent (Eo) and labile (EM)compounds from this study are plotted against log Kow in Figure 2. Each of the data sets was fitted to an equation of the form 1/E = a + b log Kow using a handwritten algorithm, which minimized the sum of the squares of the error in E. In a second step, both data sets were optimized simultaneously using two equations with a common value of b. The resulting equations and the correlation coefficients of the predicted and measured values of E were
l/EM= 1.200 + 2.875 X lo-' KO,
rz = 0.85
(15)
l/Eo= 1.283 + 2.875 X
r2 = 0.90
(16)
2410
lo-'
KO,
Environ. Sci. Technol., Vol. 28, No. 13, 1994
_____~_
o,4 02
_..__
~
~
Labile Compounds (measured) + Persistent Compounds (measured) -Labile Compounds (modelled) -Persistent Compounds (modelled) ~ _ _ J
L------O-
45
$ \ __I___-_
5
65 I log Kou
6
55
75
8
1-_ 85
9
Figure 2. Plot ofthe digestivetract absorption of organic Contaminants in a cow as a function of log KOW. The symbols represent measured data from refs 7 and 8. The lines give the behavior predicted by the steady-state model.
There was little difference between the regressions obtained by fitting the two data sets separately and those obtained by fitting them simultaneously. The fit was very good for both data sets. The largest deviations were obtained for compounds with a log KOWbetween 7 and 8. This is the part of the absorption function that is extremely sensitive to Kow, with a change of 0.2 in the log Kow value resulting in a 10% change in predicted absorption. Hence, errors in the log Kow value can have a large effect on the predicted absorption. The determination of Kow for such hydrophobic compounds is extremely difficult and subject to error. Three equations arise from the data fit, namely QAO
QAW
= Q~/0.200
(17)
= QE12.875 X
(18)
Q E = 0.083QM
(19)
Equation 19 can be solved directly using the milk fat excretion rate of 1.31 kgld and a milk fat density of 931 kg/m3, giving QE
= 1.16 X
lo4 m3/d
(20)
This is the feces excretion rate expressed in octanol equivalents. The dry weight feces excretion rate was 7 kg/d in the experiment. Assuming a dry feces density of 1300 kg/m3 gives a feces octanol equivalent of 2.2% on a dry weight basis. It should be noted that this number 1s associated with a large degree of uncertainty as QE was calculated from the difference of two large numbers. The other two eqs 17 and 18 can now be solved, giving values for the transfer coefficients through the water and octanol diffusion films: QAO
= 0.00058 m3/d
(21)
= 4030 m3/d
(22)
QAW
The relative values of the three coefficients QE, QAW, and QAOare less uncertain as they are directly related to the shape of the curve in Figure 2. However, the absolute values of QAW and QAOare directly tied to QE and are therefore also associated with the same uncertainty. It is difficult to obtain independent estimates of the values of QE, QAW,and QAO. Of the three, QE would seem to offer the most promising experimental possibilities. If
one could determine the fugacity capacity of the feces, one could establish the feces excretion rate in octanol equivalents, which is QE. A method to determine the fugacity capacity of organic compounds in fish feces was recently reported (29). In summary, the model describes the steady-state behavior observed in the mass transfer experiment very well. However, it is based on a single experiment with one cow and a limited number of compounds. I t would be desirable to expand the available data base and the number of compounds. Non-Steady-State Model (&F and VFZF).For nonsteady-state conditions, the storage and buffering functions of the body tissues have to be considered. The relevant parameters in the model are the transfer coefficient for bloodlfat diffusion (DBF)and the storage capacity of the cow, modeled as a single fat compartment ( VFZF). The clearance of a persistent compound is a useful special case of kinetic behavior which allows the transformation terms and the contaminant input N in eq 1to be set to zero. This equation can then be solved for f D and substituted into eq 2, yielding fB
-= fF
D, -tD ,
DBF D , - D?/(DE
DA)
(23)
This equation predicts that there must be a constant ratio between body fat and blood or milk fat concentrations of a persistent contaminant during clearance. This behavior has been observed in many feeding studies as reviewed by Fries ( 4 )and is reflected in his model. In reality, a constant ratio will only be achieved some time after contaminant ingestion is stopped due to the lag time in clearing the digestive tract. Reorganizing eq 23, the following relation for DBF is obtained:
DBFis a function of the steady-state coefficients, which can be calculated, and the ratio of the body fat and milk fat fugacities (or concentrations) during clearance, which must be measured. Hence, this equation is useful for modeling experimental data but cannot be used in a predictive manner. It is conceivable that DBFis also a two-film resistance that can be described in a manner similar to DA: 1/DBF
= 1/(QBFOZO)+ 1/(QBFWZW)
(25)
or
ZolDm = 1/QBFo Kow/Qmw
(26)
In this case DBFIZO would be constant until a certain value of Kow was exceeded, at which point the aqueous resistance would begin to dominate causing DBFIZo to decrease. Referring to eq 23, one would expect the ratio of the milk fat and body fat concentrations during clearance also to decrease when DBFIZO decreases a t high KOW. This is in agreement with the observations of Derks et al. (16),who observed decreasing ratios with increasing chlorination for a number of dioxins, and Fries (41, who reported the ratio of the milk and body fat concentrations for a number of chlorinated organic compounds. The average ratios for
Z,/D,,
(dlm3) I
1200
,
1
1000 L
I I
I*
"0
10
5 KOw
15
x 10-6
Figure 3. Plot of Z0/hFas a function of Kow. The symbols represent estlmates obtained from eq 24 using the steady-state model and data from ref 4. The line was obtalned through a llnear regression of the data points.
each of the compounds in Fries' data set that are persistent once absorbed (DDE, DDT, PCB, PBB, HCB) were substituted into eq 24 along with the values of D M ,DA, and DE determined using the steady-state model and an assumed lactation rate of 1 kg of fatld. The resulting values of DBFwere then inverted, multiplied by 20,and plotted against Kow (see Figure 3). A simple linear regression yielded the relationship
Zo/DBF = 192 + 0.000058K0w (d/m3)
rz = 0.88 (27)
giving estimates for the unknown coefficients in eq 26. This predictive relationship for DBFis only a first estimate, however, as the data for each compound were obtained from different cows. It is likely that the assumed lactation rate and the calculated values of DA and DE (the steadystate model is based on just one cow) were not appropriate for many of the cows used in the feeding studies. Furthermore, DBFis also dependent on the properties of the animal and likely varies between breeds and individuals. Diffusive transport is a function of not only the nature and thickness of the films but also of the surface area of the barrier. A cow with a large amount of body fat will have a larger bloodlfat surface area and hence would be expected to have a higher value of DBF. The work of Ewers (30),who examined the influence of body fat weight on the kinetics of several PCB congeners in cows, supports this hypothesis. The quotient of the milk fat and body fat concentrations of PCB 138 during the clearance was slightly less than 1 for a cow with a high body fat content, 0.84 for a cow with a medium body fat content, and 0.67 for a lean cow. The simplest approach to modeling this effect would be a linear relationship between DBFand body fat weight. However, this could break down for very lean animals. Insufficient information was found in the literature to obtain an empirical expression. The second coefficient required for the kinetic solution is the storage capacity of the cow, VFZF. It can also be determined from a clearance experiment with a persistent compound. Substituting eq 23 in eq 3 and assuming VFZF to be constant, one obtains
Envlron. Sci. Technol.. Vol. 28, No. 13, 1994
2411
The right-hand side of the equation represents the time constant for a first-order kinetic process. It can easily be obtained from a semilog plot of body fat (or milk fat) concentrations against time from a clearance experiment. The only unknown is VFZF,which can then be solved for. A method of independently determining this parameter would be desirable. As ZFis assumed equal to the fugacity capacity of n-octanol, the unknown is VF, the volume of fat in the cow. This can in practice be estimated if the range of fat volumes for a particular species is known. The range can be quite large. A complete analysis of a lean and a fat Holstein-Fresian cow yielded body fat weights of 38 and 134 kg, respectively (15). The bones, meat, intestine, kidney, and remaining offals all made significant contributions to the total fat depot. It should be noted that the body fat weight of the cow can change with time. If this change is significant compared to the total body fat weight, then the excretion behavior will be affected, and a numerical solution of eqs 1-3 is necessary. The influence of the body fat weight on the clearance kinetics is widely accepted and has been incorporated in other models of contaminant behavior in cows (e.g., refs 4 and 5 ) . The kinetic behavior of the model was tested using the feeding study data of Ewers (30). The steady-state parameters determined above were employed. DBFwas obtained using the ratio of the measured body fat and milk fat concentrations during the clearance. VF was estimated using the milk concentrations during the clearance. It was assumed to be constant as no information was available on the changes in body weight of the animals during the experiment. The model was then run, first in clearance mode using an estimated background feed contamination and the subcutaneous fat concentration measured at the beginning of the clearance as an initial value. The results for PCB 138 in cow 1272 are plotted on the right side of Figure 4. The model follows the body fat and milk fat concentrations reasonably well considering the limitations in the data set. The good fit was to be expected as the parameters were optimized using the clearance data. The model was then run for the uptake part of the experiment using the measured start concentration in subcutaneous fat and the given feeding rate plus a correction for background feed contamination. The results are shown on the left side of Figure 4. The model underpredicts both the body fat and milk fat concentrations. This indicates that the mass balance is wrong, as 2412
Envlron. Scl. Technol., Vol. 28, No. 13, 1994
the product of VF and the measured fat concentration at week 4 plus the total amount of PCB 138 excreted in the milk to that date is greater than the amount ingested in the first four weeks. The likely reason is that VF was significantly lower during the accumulation phase than during the clearance. A large change in body fat content over several months is plausible for a lean cow such as the one in this study. As the VF employed in the model was determined using the clearance data, a lower body fat volume during uptake would mean that the predicted fat concentrations during the accumulation would be too low. This illustrates the need to carefully monitor the total body fat weight for studies of contaminant kinetics. The underprediction of the milk concentration illustrates a more fundamental problem. The gradual increase in milk concentration is typical for all attempts to model contaminant uptake. This contrasts with the behavior observed during feeding studies where the milk concentration generally exceeds 50% of its plateau value within 1-2 wk of beginning feeding. As the body fat concentration is still low at this time, this implies that DM > DBF(see eq 2). From eq 23, this would mean that during the clearance f B / f F must be less than 0.5. This contradicts the observed behavior, however, as f B / f F is almost always greater than 0.5. There is apparently a problem with the model that leads to poor prediction of the contaminant uptake kinetics. Transformation (&D and &B). There is at the moment no satisfactory modeling approach to predict the transformation of organic compounds in the cow. For certain classes of compounds such as the PCBs, PCDDs, and PCDFs, the substitution patterns that are the key to persistence have been identified (7,8). However, as a rule the transformation coefficients can only be determined with the help of experimental evidence or inferred from the behavior of other substances. The site of transformation is an important factor. Whereas metabolism of labile compounds within the animal is often nearly complete and differences between individuals can be expected to be small, this is not the case in the digestive tract. Here the transformation process competes with absorption, and the compound that is absorbed may be persistent within the animal (e.g., HCHs, DDT). Differences in the factors affecting this competitive situation such as the kind of feed, conditions in the digestive tract, or physiology may lead to considerable differences in contaminant uptake between individuals.
Discussion The steady-state model performed very well and is simple. The information most commonly required in risk analysis work is the carryover rate (the quotient of the amount of contaminant excreted in the milk and the amount ingested at steady state) of a persistent contaminant (i.e., Eo). This can be easily determined using eq 16, value of the compound is required. for which only the KOW Although the model is based on experimental results from just one cow, the carryover rates from the experimental study were in reasonable agreement with those obtained from other studies (7, 8). However, more studies of contaminant absorption in cows are required to establish the variation between individuals and breeds and to examine the behavior of other compounds beside chlorinated organics. The composition of the feed could play
FEED
’DIGEST. TRACT
FECES
&
BLOOD
DEGRADATION LACTATION (Reset fu=O)
Flgure 5. Schematic of the structure of the cow model modified to give a better description of the kinetics of contaminant uptake.
an important role by influencing the conditions in the digestive tract and the fugacity capacity of the feces. The form in which the contaminant is present in the feed can also be an important factor in determining absorption, as has been shown for rats (31). This could be a particularly significant consideration when soil ingestion is a primary route of contaminant uptake. The influence of the rate of lactation on the carryover rate should be quite small according to the model. Assuming that the value of DEremains unchanged, halving the value of DM results in a decrease in the maximum carryover rate from 78% to 73 96. It should be noted that the milk concentrations will be almost twice as high though, since just 6 % less contaminant is present in half the quantity of milk. The relative insensitivity of the carryover rate to the lactation rate is desirable, since a parameter characterizing a process should be independent of the main variables in the process. Other parameters that have been proposed to describe the steady-state behavior of contaminants in cows include the biotransfer factor [the ratio of the concentration in milk (ng/g of milk) to the daily ingestion of contaminant (ng/d)l (6) and the “bioconcentration” or bioaccumulation factor [the ratio of the concentration in milk fat (ng/g of fat) to the concentration in feed (ng/g)l(32). Thelatter twoparameters arelinearly dependent on variables such as the lactation rate, fat content of the milk, or feed consumption rate. These variables must be defined for each given value of the parameter, which is awkward and is often neglected, leading to inappropriate generalizations of the parameter values. The carryover rate, being relatively independent of these variables, is a better descriptor of contaminant behavior in the cow. The kinetic model describes the clearance behavior resonably well but is not able to predict the rapid rise in milk concentration that accompanies an increase in contaminant uptake. This weakness is common to all cow models that the author is aware of. It is believed that the problem lies with the model’s treatment of lactation. Lactation is not a continuous process as described in the model. The milk accumulates over a period of 12 h and is then excreted, after which the cycle repeats itself. A more realistic model that includes intermittent lactation is illustrated in Figure 5. An udder compartment is added with a storage capacity Vu equal to the amount of fat excreted during a milking. This compartment is emptied after a time representing the milking interval by resetting the fugacity to zero. The transfer coefficient to the udder
DSUis considerably larger than DBF. During uptake, the contaminant is transferred to the udder so rapidly that an equilibrium between the udder and the blood is established within several hours. After 12 h, the udder is emptied and begins to fill again. During clearance, the body fat would release the compound slowly to the blood, and this would be transferred rapidly to the udder. The udder would fill up slowly but could still reach equilibrium with the fat before being emptied. This model, although still a simplification, would appear to be a physiologically more reasonable explanation that decouples the concentration in the milk from the ratio of& to& during contaminant accumulation. However, such a model would be considerably more complicated than the one described in this paper. It is believed that the simpler model is adequate for addressing many questions involving contaminant kinetics in cows. This paper has focussed on predicting the Contaminant levels in milk. The model can, however, be used to predict the levels in other tissues in cows. As mentioned above, similar concentrations of persistent organic contaminants are found in different tissues (with the exception of the liver) when they are expressed on a fat basis, even when the animals are not at steady state (14-16). Thus, the milk fat fugacity obtained from the steady-state model or the body fat fugacity obtained from the kinetic model can be used to predict concentrations in meat and organs (but not in the liver). The behavior of organic contaminants in nonlactating cattle is less well studied than the behavior in cows. The model can be modified for nonlactating animals by setting DM to zero. The only route of excretion of stored chemical is then diffusion from the blood into the lumen of the digestive tract and subsequent elimination through the feces. This results in much slower kinetics, extending the clearance half-life from 50 to 500 d for a compound with a log Kow of 7 and an animal with a body fat weight of 50 kgcompared to the same animal with a milk fat production of 1 kg/d. Considering the uncertainty associated with the absolute magnitudes of DAand DE,which are the crucial parameters for feces elimination, this result is in reasonable agreement with a recent clearance study using nonlactating cattle where values of 160-280 d for 11different PCDD/F were reported (33). The slow excretion rate also means that the steady-state concentration is much higher than in the lactating animal-for the hypothetical case above a factor of 10. However, it will take 6 yr to approach this steady state, much longer than the 1.5 yr that beef cattle typically live. During this time, the animal is also growing, continuously diluting its contaminant reservoir. As a result, the contaminant levels in commercial beef fat are generally not much higher than in milk fat (1-3). Simply dividing the total amount of contaminant absorbed during the life of the animal by the weight of body fat would appear to be a simple and adequate approach to estimating concentrations in nonlactating cattle. This presupposes a knowledge of the absorption rate, which again emphasizes the need for more information in this area, especially on the influence of dietary factors. To summarize the results of the cow model, the carryover of persistent organic contaminants into cow’s milk is independent of Kow over a broad range. For superhydrophobic compounds, the carryover decreases. Similarly, the clearance half-life is independent of Kow over a broad range but would appear to be slower for very hydrophobic Envlron. Sci. Technol., Vol. 28,
No. 13, 1994 2413
compounds, especially in lean cows. This study stands in clear contradiction to the work of Travis and Arms (6), who proposed that the biotransfer factor (comparable t o the carryover rate) increases linearly with increasing Kow. This contradiction would appear to be due t o these authors not having considered transformation in their interpretation. Many contaminants with low Kow values are easily degraded in the cow and, thus, have lower biotransfer factors. While this gives the impression that increasing biotransfer factors are related t o increasing KOWvalues, one should not confuse the effects of hydrophobicity and persistence. Very hydrophobic compounds such as most PCDD/Fs are almost fully metabolized, and the inverse is also true. The primary challenge in predicting the fate of most contaminants in cows lies not in estimating their KOW,as these authors imply, but rather in estimating their persistence.
(7) McLachlan, M. S.; Thoma, H.; Reissinger, M.; Hutzinger, 0. Chemosphere 1990, 20, 1013-1020. (8) McLachlan, M. S. J.Agric. Food Chem. 1993,41,474-480. (9) Olling, M.; Derks, H. J. G. M.; Berende, P. L. M.; Liem, A. K. D.; de Jong, A. P. J. M. Chemosphere 1991,23, 13771385. (10) Mackay, D. Multimedia Environmental Models: The Fugacity Approach; Lewis Publishers: Ann Arbor, 1991. (11) Jones, D.; Safe, S.; Morcom, E.; Holcomb, M.; Coppock, C.; Ivie, W. Chemosphere 1987, 16, 1743-1748. (12) Jensen, D. J.; Hummel, R. A.; Mahle, N. H.; Kocher, C. W.; Higgins, H. S. J. Agric. Food Chem. 1981, 29, 265-268. (13) Arnott, D. R.; Bullock, D. H.; Platonow, N. S. J.Food Prot. 1977,40, 296-299. (14) Frank, R.; Braun, H. E.; Fleming, G. J.Food Prot. 1983,46, 893-900. (15) Ewers, C.;Reichmuth, J.;Wetzel, S.;Vemmer,H.; Heeschen, W. Kiel. Milchwirtsch. Forschungsber. 1989,41 (2), 75-95. (16) Derks, H. J. G. M.; Berende, P. L. M.; Olling, M.; Liem, A.
K. D.; Everts, H.; de Jong, A. P. J. M. Toxicokinetics of PCDDs and PCDFs in the Lactating Cow (ZI);Report 328904002; Rijksinstituut voor Volksgezondheid en Milieuhygiene (RIVM): Bilthoven, The Netherlands, 1991.
L i s t of Symbols
D EM
Eo
f N
8 t V
z
D value, a fugacity conductance or transport coefficient (moll Pa-l d-l) fractionalabsorption of a compound that is readily degraded in the cow fractional absorption of a compound that is persistent in the cow fugacity (Pa) contaminant ingestion rate (moll d-l) 012, with units of flow (m3 d-1) time (d) volume (m3) fugacity capacity (moll m-3 Pa-')
Sukscripts
A B BF D
E F M 0 R W
absorption blood compartment bloodifat diffusion digestive tract compartment excretion of feces fat compartment milk lactation octanol or octanol film reaction or transformation water or water film
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2414 Environ. Sci. Technol., Vol. 28, No. 13, 1994
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Received f o r review M a y 26,1994. Revised manuscript received September 6, 1994. Accepted September 9, 1994."
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Abstractpublished in Advance ACSAbstracts, October 15,1994.
