Environ. Sei. Technol. 1904, 18, 439-444 Contract No. 68-31-4313 (MRI Project 4309-1). Beck, B. E.; Wood, C. D.; Whenham, G. R. Vet. Pathol. 1977, 14, 128. Dollahite, J. W.; Pierce, K. R. Am. J . Vet. Res. 1969, 30, (8), 1461. Sugden, E. A.; Greenhalgh, R.; Pettit, J. R. Environ. Sci. Technol. 1980,14, 1498. Hamilton, A.; Hardy, H. L. “Industrial Toxicology”; Publishing, Sciences Group Inc.: Acton, MA, 1974; p 316. Sarokin, M. Med. J . Aust. 1969, 1, 506. Susser, M.; Stein, Z. Br. J . Ind. Med. 1957, 14, 111. Murray, D. A. J. J . Fish, Res. Board Can. 1975, 32, 457. Mayer, F. L.; Adams, W. J.; Finley, M. T.; Michael, P. R.; Mehrle, P. M.; Saeger, V. W. In “Aquatic Toxicology and Hazard Assessment: Fourth Conference”; Branson, D. R.; Dickson, K. L., Eds.; American Society for Testing and Materials: Philadelphia, PA, 1981; ASTM STP 737, pp 103-123. Sheldon, L. S.; Hites, R. A. Environ. Sei. Technol. 1978, 12, 1188. Lebel, G. L.; Williams, D. T.; Benoit, F. M. J . Assoc. Off. Anal. Chem. 1981,64, 991. Sanders, H. 0.;Hunn, J. B.; Robinson-Wilson, E., submitted for publication in Environ. Toxicol. Chem. Mayer, F. L.; Buckler, D. R., submitted for publication in Environ. Toxicol. Chem. Lambardo, P.; Egry, I. J. J . Assoc. Off. Anal. Chem. 1979, 62, 47.
Johnson, B. T. Tech. Pap. US.Fish Wildl. Serv. 1982,No. 107,15-21. Jones, J. R. Trans. Mo. Acad. Sci. 1977, 10, 58. Johnson, B. T.; Lulves, W. J. J. Fish. Res. Board Can. 1975, 32, 333. Gledhill, W. E. Appl. Microbiol. 1975, 30, 922. Huckins, J. N.; Stalling, D. L.; Smith, W. A. J . Assoc. Off. Anal. Chem. 1978, 61, 32. Huckins, J. N.; Petty, J. D. Chemosphere 1983, 12, 799. Saeger, V. W.; Hicks, 0.; Kaley, R. G.; Michael, P. R.; Mieure, J. P.; Tucker, E. S. Enuiron. Sci. Technol. 1979, 13, 840. Watson, J. R. Water Res. 1977, 11, 153. Fannin, T. E., Marcus, M. D.; Anderson, D. A,; Bergman, H. L. Appl. Environ. Microbiol. 1981, 42, 936. Boethling, R. S.; Alexander, M. Appl. .. Enuiron. Microbiol. 1979, 37,-1211. Barret, H.; Butler, R.; Wilson, I. B. Biochemistry 1969,8, 1042. Booth, G. H.; Robb, J. A. J . Appl. Chem. 1968, 18, 194. Mills, J.; Eggins, H. 0. W. Int. Biodeterior. Bull. 1974,10, 39. Pickard, M. A.; Whelihan, J. A,; Westlake, D. W. S. Can. J . Microbiol. 1975, 21, 140.
Received for review May 31, 1983. .Revised manuscript received December 9,1983. Accepted January 23, 1984.
Three-Parameter Equation Describing the Uptake of Organic Compounds by Fish Donald Mackay” and Am1 I. Hughes Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronoto, Ontario, Canada M5S 1A4
A three-parameter equation is derived by using the fugacity concept, which describes the uptake of organic chemicals from water by fish. The equation is successfully applied to two sets of published uptake data, a study of bioconcentration of a series of PCB congeners and a study of narcosis induced by aqueous solutions of n-alkyl esters of p-aminobenzoic acid, both in goldfish. It is shown that the time constant for uptake and clearance is dependent on the chemicals’ hydrophobicity expressed as the octanol-water partition coefficient, highly hydrophobic chemicals having long equilibration times. This time constant can be broken down into times attributable to water-phase and lipid-phase diffusion-flow processes. Introduction The rates and equilibria that apply to uptake of organic compounds by fish are important environmental processes influencing the toxicity exerted by the compounds to the fish. They also influence the lipid accumulation of these compounds and thus their ultimate consumption by other predators, including humans. It is valuable to have reliable methods of predicting these rates and equilibria from a knowledge of physical-chemical properties of the compounds as reviewed recently by Spacie and Hamelink (I). Such a capability can be used to screen the behavior of potentially toxic substances, especially within a homologous series. In this work we derive and illustrate the use of a simple three-parameter equation which has the potential to describe the uptake, release, and a selected toxic effect of a series of homologous organic compounds. The equation is derived by using the fugacity concept which 0013-936X/84/0918-0439$01.50/0
has been described elsewhere (2-4), but the final equation can be used without a knowledge of the method of derivation. The equation is applied to two studies. The first is an application to data obtained in a comprehensive study of uptake and elimination of a series of di-, tri-, and tetrachlorinated biphenyls in goldfish (Carassius auratus) by Bruggeman et al. (5). The second is a study of the narcotic effects of six n-alkyl esters of p-aminobenzoic acid to the same organism by Yalkowsky et al. (6, 7). In both cases, chemical or biochemical reaction of the active substance could be ignored in the experimental times in question. In the Bruggeman study, the bioaccumulation kinetics of five chlorinated biphenyls were studied for up to 150 days after exposure to contaminated water or food. A kinetic model was developed to account for differences in compound properties and fish lipid content. In the Yalkowsky study, goldfish were placed in solutions of the p-aminobenzoate esters, and the “turnover” or “tipping” time was measured. This is the time until the fish became unable to bring itself to an upright position after being turned on its side by a glass rod, Le., the fish lost its righting reflex as a result of the narcotic effect of the drug. The turnover time varied from a minimum practical experimental time of 20 s to 70 min. In both cases, there was a designed variation in the test chemicals’hydrophobicity, lipophilicity, or water solubility. Model Derivation Using the Fugacity Approach Equilibrium between Phases. When two phases are in equilibrium, the fugacities f (Pa) of the solute in each phase are equal, but the concentrations C (moi/m3) gen-
0 1984 American Chemical Society
Environ. Sci. Technol., Vol. 18, No. 6, 1984 439
erally differ. A fugacity capacity Z [mol/(m3.Pa)] is introduced for each phase such that C is Zf. Methods of estimating Z for phases such as air, water, and lipid have been discussed by Mackay and Paterson (3). If there are two phases with a common fugacity f , but concentrations C1 and C2 and fugacity capacities Z1 and Z2, it can be shown that the partition coefficient K12defined as C1/C2 is Zl/Z2. Z may be defined for the fish as a whole, or only the part which is lipid, or less specifically for an organic phase. The use of Z instead of partition coefficients is convenient for multiphase systems. When there are only two phases, water and “organic” or “biotic”, the use of two Z values instead of one partition coefficient is of little benefit. But in cases where partitioning is into different biotic materials, the use of Z may be advantageous. Diffusive Interphase Transport. When solute diffuses from one phase to another, the rate or “flux” can be expressed as N (mol/h) by
N = D(fi- f z )
N =
(fl
-fz)/r
(1)
where D [mol/(Pa-h)] is a transport parameter or “conductivity” and r (Pa-h/mol) is its reciprocal, a resistance. For situations in which a mass transfer coefficient K (m/h) applies, it can be shown that D is K A Z , where A (m2)is the transfer area (3). The resistance to transfer, r, is then l / ( K A Z ) . If several resistances apply in series the total resistance, rT, is defined by N
rT = rl
+ r2 + ... + rN = i=l Cri
(2)
and rT = 1/DT
(3)
or 1/DT = 1 / D 1 + 1/D2
+ ... + 1 / D ,
N
= C ( l / D i ) (4) i=l
Usually one (high) resistance or (low) D value dominates the transfer process. It can be shown (3)that this reduces to the familiar “two resistance theory” for diffusion through two films in series. If a diffusivity d (m2/h) and path length Y (m) apply, then D is dAZ/ Y , or r is Y / ( d A Z ) ,K being equivalent to d / Y. Nondiffusive Transport. If the solute is conveyed by a fluid flow G (m3/h) in which the concentration is C (mol/m3), it is apparent that N is GC (mol/h) or GZf (mol/h). A transport parameter D of GZ [mol/(Pa.h)] can thus be defined such that the rate N is D f (mol/h), as in the diffusive case. It follows that the resistance r is 1/(GZ) (Pa-h/mol) . Nondiffusive transport occurs in only one direction at a rate N of Of, whereas diffusive transport can be regarded as the net flow of Ofi in one direction and Ofi in the other, the difference being D ( f l - f z ) . Reaction. It is assumed that if the solute reacts, it is by a first-order process in the solute concentration with a rate constant k (h-l), such that the rate is N = VkC = VkZf = Df (mol/h) where V is the phase volume (m3) and D is a transformation parameter identical in units with the transport parameter. In summary, equilibria between phases are characterized by Z values, one for each phase. The lipid-water partition coefficient KLW is thus ZL/Z,. Transport and reaction rates are characterized by D values where D can take the form of (i) a mass transfer coefficient, area, and fugacity 440
Environ. Sci. Technol., Vol. 18, No. 6, 1984
capacity product ( K A Z ) , (ii) a diffusivity, area, and fugacity capacity product divided by a path length (dAZ/ Y), (iii) a flow rate and fugacity capacity product (GZ), or (iv) a reaction rate constant, volume, and fugacity capacity product ( k V Z ) . The rate N of the process is in each case D f or f / r where f is the appropriate phase fugacity. For a multicompartment system such as a fish, a series of differential equations thus govern the uptake and release of the solute chemical, each of which, ignoring reaction, has the general form
VjdCi/(dt) = ViZidfi/(dt) = C(Dj$j) - fiCDik = I
k
where Cl(Dl$l) is the sum of all j of the Df products corresponding to compartments from which solute can diffuse to i and fiCkDik is the sum of all D values corresponding to compartments t o which solute can diffuse from i and any reaction D terms (if applicable). If all the V , 2, and D (or r ) terms are known, it is possible to integrate these equations from a defined initial condition and thus explore uptake and depuration kinetics. In practice, the model complexity greatly exceeds the detail of the experimental information; thus, it is essential to introduce simplifying assumptions to reduce the number of parameters. This has the benefit of yielding simple equations that describe the dominant processes and their dependencies on solute and organism properties. The first simplifying assumption is that the chemical is conserved or does not react in the time of concern. This excludes chemicals whose concentration is controlled by a metabolism rate. The second simplifying assumption is that of “steady state” for a particular compartment. If a compartment contains relatively little solute, then the error introduced by assuming that V,Z,dfi/(dt)is zero is slight since this accumulation is small compared to the amounts flowing to and from the compartment. The differential equation then becomes algebraic, and one fugacity can be eliminated. We apply this assumption to all but the “target” compartment. The third simplifying assumption is that the D parameter falls into one of two categories, either the process occurs in an aqueous phase (w) or in an organic phase (0). It follows that when several D values add, they can be categorized into a group designated Do (all containing 2,) and a group designated D, (all containing 2,). Usually there is insufficient experimental information to discriminate between, or determine, all the D values individually, but there may be enough information to determine both D, and Do or r, and r,. We propose that the rate of transfer from the water to the target within the fish can be described by an overall or total D value ( D ) which is postulated to consist of an organic (Do)group and a water (D,) group. For convenience, we designate each D by QZ, writing 1 / D = l / D w + l / D o = r, -t r, = l / ( Q w Z w + ) l/(QoZo) (6)
The Q, and Q, quantities can be viewed as hypothetical effective flow rates (m3/h) of water and organic matter between the water and the target in the fish. Each Q consists of a combination of diffusive transfer terms ( K A or dA/ Y) and real flow rates (G) in the respective phases. Although Q, and Q, cannot be measured directly, information about their values can be obtained by measuring D for a series of chemicals with different 2, and Z, values and then fitting Q, and Q, to the data. Whereas 2, can
be determined from the physical-chemical properties of a given chemical, there is doubt surrounding 2,. The organic-aqueous phase partition coefficient (Z,/Z,) is not known, there being uncertainty about, and diversity in, the various organic phases present in the fish. The only SOlution is to resort to the use of the octanol-water partition coefficient, KO,, assume that it is Z,/Z, and redefine Q, as the effective flow rate of octanol. Even if Z for octanol and the organic phase differ, this can be accounted for by a corresponding difference in Q, such that the QZ product is correct. A differential equation can now be proposed: (7) VTZT~~TIW =W ) w -f ~ ) where subscript T refers to the target(s) in the fish and W to the water, Integrating with constant fw and an initial fT of zero gives (8) fT = f W [ l - exp[-tD/(VTzT)ll Now since fT is CT/ZT and fw is Cw/Zw CT =
cW(zT/zW)[l -
exp[-tD/(vTzT)ll
(9)
This is equivalent in form to the solution of the traditional bioconcentration differential equation d C ~ / ( d t= ) klCw - k & ~ (10) where kl and k2 are “uptake” and “clearance” rate constants, which when integrated gives
CT = cw(k,/k2)[1
-
exp(-kzt)l
(11)
The groups kl/k2 or &/Zw can be viewed as bioconcentration factors. Equations 6 and 9 combine to give CT =
cw(ZT/zw) [ 1 - exP[-t / ( VTZT/Qwzw -I-V T ~ TQ/ o ~ o 1) ~ (12)
Equation 12 forms the basis from which the correlating equation is suggested by using the following arguments. Usually, VT and ZT are unknown, but since the ultimate target is probably organic, zT/zoand the group [ v T z T / (Q,Z,)] should not vary significantly with changing hydrophobicity or KO,. The group is thus designated as a constant r,, having dimensions of time. The ratio zT/zW on the contrary is l i h l y to vary linearly with KO,; thus, we designate the group VTZT/(QwZw)as r&,, where r, is a second constant, again with dimensions of time. The other (zT/zw)ratio is designated KTW, a target-water partition coefficient, where the target is determined by the nature of the concentration measurement CT. We thus propose the correlating equation for uptake:
CT = CwKTw[l - exp(-kzt)]
(13) + 7., For clearance from initial conwhere l / k z = T&, centration CTO into solute-free water, this becomes CT = CTO exp(-k2t) (14) There are thus three parameters, KTW, T,, and T,, the latter two being combined with KO,to give the clearance rate constant k2. The significance of the three quantities is discussed below. KTW is the bioconentration factor KB if the target is regarded as the whole fish. It is the ratio cT/cw which is reached at long times. I t should be linearly related to KO, as has been discussed previously by Mackay (8),who proposed that KBis approximately 0.048K0,.In the case of toxicity experiments CT is not measurable but (cT/Kw) can be measured as the threshold water concentration which produces the given toxic effect at long exposure
WATER
OCTANOL
ClRC J L A T I O N
C IRC U L A 1 I ON
I
15
I
fugacities
,f
rw
res~stances
r,
l/rw:GwZw
corducfivities
,f
:D ,
f,
Do:l/r,:G,Z,
Figure 1. Schematic illustration of water and octanol equivalent lipid circulations within a fish, modified from Bruggeman et al. (5).
times. If CT is relatively constant for a homologous series, then the threshold concentration will be inversely proportional to KTW and probably also to KO,; thus, we can postulate CT/KTW= CN/KO, (15) where CN is an adjustable parameter and is the actual concentration at the target which causes the toxic effect, assuming that the target is octanol. For toxicity correlation purposes we rewrite eq 13 as
C, = CwK,,[l - exp(-k2t)l
(16)
The adjustable parameter CNis best evaluated from experimental data obtained at long exposure times when kzt is large and CN approaches CWK,,. r, is essentially (VT/QW), has dimensions of time, and corresponds to the time required for a hypothetical volume of water (equal to the volume of the target) to circulate within the fish from source to target. It can be conceived and termed as a “hypothetical water transport time” and is presumably quite short. This time is multiplied by KO, when k2 is calculated because the capacity of the circulating water to convey a chemical is proportional to the concentration of the chemical in the water which is in turn inversely proportional to KO,. Thus, to transport a given quantity of a hydrophobic chemical of low solubility and high KO,requires a large water circulation time of order of T W K O W . r, is essentially (VT/Qo),has dimensions of time, and corresponds to the time required for a hypothetical volume of lipid (equivalent to octanol and equal to the volume of the target) to circulate from source to target. r o can be conceived of and termed as a “hypothetical octanolequivalent lipid transport time” and may be quite long in cases where there is slow transfer of lipids. Figure 1 illustrates these transport times schematically. In summary, for bioconcentration data, we suggest using eq 13 for uptake (eq 14 for clearance), expecting that Kw or KB is linearly related to Kow. For toxicity data, we suggest using eq 16 where CN is an adjustable parameter which should be relatively constant for a homologous series. It should be noted that although these formulations are novel, they are similar in character to the equations derived and used by Bruggeman et al. ( 5 ) and by Yalkowsky et al. (6, 7). It can be shown that they reduce under certain circumstances to forms presented by these authors. It must be emphasized that eq 13 and 16 cannot be derived unless a number of simplifying assumptions are accepted, especially the assumption of nonmetabolism. The derivation is presented primarily as a justification for the use of these variable groupings or equations for correlating data. They should be regarded as semiempirical Environ. Sci. Technol., Vol. 18, No. 6, 1984
441
-__
Table I . Bioconcentration and Clearance Rate Constant Data for PCBs in Goldfish ( 5 ) a exptl k, x
congener
log KO,
day-'
2,52,2',52,4',52,2' ,5,5'2,3',4',5-
a
lo3,
5.18 (9) 5.59 ( 1 0 ) 5.77 ( 9 ) 6.26 (9) 6.39 ( 9 ) 7 8 References are given in parentheses.
66 48 21 15 10
calcd k, x lo3, day-'
exptl 1log KB
52.3 37.2 29.8 13.4 10.4 2.9 0.30
correlated log KB 3.9 4.31 4.49 4.98 5.11 5.72 6.72
4.14 4.3 4.63 4.69 4.62
1 butyl
/
,
10
I
i
2 x;os
1 x I06
KO,
Figure 2. Correlation of l l k 2 vs.
30
40
50
60
70
Figure 3. Plot of water concentration-KO, product vs. reciprocal tipping time, illustrating the convergence toward a common C , value at long exposure times (zero reciprocal time).
KO, for PCB uptake by goldfish
illustrating the "resistances" attributable to water and octanol equivalent lipid circulations.
equations whose usefulness can only be assessed by testing them against experimental data. It is believed, however, that the derivation includes a reasonable repreBentation of the dominant processeg controlling solute transport and provides insights into the physical meaning of the parameters KB, T ~ r,, , and CN. When the fugacity approach is used for evaluative environmeotal modeling purposes ( 4 ) , a D value must be defined for fish-water exchange. It can be shown that D is k2VFZ,or VFZ,/(T,K~, + ro)and that the "half-time" for uptake or depuratiod is 0.693/kz or 0.693(~&~,+ ro), where subscript F refers to the whole fish. This characterizes only uptake from water, not from food.
PCB Uptake Data We test eq 13 using the data of Bruggeman et al. (5) as summarized in Table I. The bioconcentration factor, KB, data correlate well with KO,, yielding KB = 0.052K0, (17) To obtain rw and T ~ we , plot l / k z vs. KO, expecting a straight line of intercept r o and slope .7, Figure 2 shows 442
20
RECIPROCAL TIPPING TIME(h-')
Environ. Sci. Technol., Vol. 18, No. 6, 1984
this plot and yields values for T, of 8.05 X h (2.9 s) and r oof 332 h (13.8 days). This plot illustrates the relative contributions of the water and octanol equivalent lipid transport times or the resistances to mass transfer. As KO, increases, the water-phase resistance increases because the solute is present at lower concentrations, and thus lower fluxes and more circulations are required. These correlating equations can be used to calculate the k2 and KB values given in Table I. The agreement is satisfactory. Other authors such as Ellgehausen et al. (11) and Southworth (12) have also noted that k z is smaller for more hydrophobic chemicals, in agreement with the model predictions. We suggest that eq 13 be tested for correlating kp. In some cases, non-first-order clearance is observed which is possibly attributable to slower clearance of chemical from less accessible lipid as discussed by Bruggeman et al. (5). PAB Ester Narcosis Data The data contained in the original reference were fitted to eq 16. Values of CN were first calculated by plotting CwKow vs. l / t and extrapolating the values to the intercept when t is infinite and CN equals C&,,. Properties are listed in Table 11. Figure 3 shows the convergence to an
Table 11. Property Data for n-Alkyl p-Aminobenzoate Esters ( 1 3 ) ester methyl ethyl propyl butyl pentyl hexyl
lo
Mr
log
151.14 165.15 179.16 193.17 207.18 221.19
x,,
1.12 1.65 2.18 2.70 3.23 3.76
LL
0 I
I
!
/ 001
LL
001
CORRELATED VALUES
.d
0 IO
0 01
OF
7
Flgure 5. Plot of experimental and correlated tipping times.
01 10
IO00
IO0
KOw
Flgure 4. Regression of narcosis data to obtain
7,
and
7,
values.
approximately common CN value averaged to be 4.36 moi/m3. Rearranging eq 14 yields -t/ln [ l - CN/(CwK,,)] = 7,KOw+ T, = l / k 2 which suggests plotting the group on the left (which is calculated from the test tipping time and the water concentration C,) vs. KO,. The intercept will then be r, and the slope .7, Direct linear regression of the data is not desirable because l / k 2 and KO,vary over 2 and 3 orders of magnitude, respectively; thus, the regression is weighted heavily in favor of the larger values. Further, the errors in l / k a and KO, are similar factors rather than similar absolute amounts, It is thus preferable to perform the regression on the logarithmic quantities, but using the linear equation. In practice it is usually satisfactory to fit such data by trial and error selection of the parameters based on repeated plotting of the curved line on a log (1/k2) vs. log KO,plot representing the linear relationship. The plot is shown in Figure 4, the intercept (7), being 8.4 X h (3.0 s) and the slope (TJ being 0.17 h (10 min). The 95% confidence limits in both parameters is approximately a factor of 1.5. Figure 5 is a plot of the experimental and correlated tipping times which extend over nearly 3 orders of magnitude. Agreement is excellent, 90% of the tipping times being correlated within a factor of 1.5 of the experimental values.
Discussion It is encouraging that the bioconcentration and toxicity equations, which are derived from the same basic equation, correlate the data so well. The use of rw and r, is believed to provide an insight into the factors controlling uptake and release of organic chemicals in fish. The equations
contain the effect noted by Bruggeman et al. (5) that, when the lipid reservoir is large, k2 is small and net uptake becomes slow. This occurs because 7, and 7, are then both large, being proportional to the volume of the target. I t is striking that the water circulation times, T,, are almost identical in the two sets of data. However, noting that both experiments used the same organism, goldfish, a common transport process is apparent.’ The T, values are quite different (14 days for PCBs and 10 min for PAB esters), suggesting that the PCB transfer is into a less accessible target. PCB uptake is probably limited by the slow rate of transfer and exchange of blood lipids with the target lipid tissues. In the case of the PAB esters, the target is presumably in the nervous system and is very rapidly accessible to the blood. Although it is difficult to make detailed pharmacokinetic interpretations, it is clear by “probing” the organism with solutes which are chemically similar but differ in KO,it is possible to elucidate the relative roles of aqueous and lipid (or octanol-equivalent lipid) transfer. Carefully designed and conducted experiments such as those evaluated here are invaluable as sources of fundamental data about mechanism of bioconcentration and toxicity. It would be interesting to test if the calculated values of r, and 7 , from one set of data apply to the bioconcentration of other compounds in goldfish. It is expected that if the uptake mechanisms are similar, then the rw and r, values will be similar. It would also be instructive to compile and compare r, and 7, data for other organisms and thus build up a capability of quantifying the uptake and depuration kinetics for a variety of compounds in a variety of organisms. We suggest that the environmental effects of highly hydrophobic compounds are mitigated to some extent because they have very low water solubilities and bioconcentrate very slowly form the water. For example, as is shown in Table I, k 2 for PCBs of log KO,equal to 7 and day-l, and 8 will be respectively 2.9 X lo9 and 0.3 X the half-times correspondingly 0.66 and 6.39 years. Highly hydrophobic compounds thus partition into fish very slowly from water solution because of the large volume of water that must be transported within the fish to accomplish the necessary transport; i.e., r&,, is very large. They Environ. Scl. Technol., Vol. 18, No. 6, 1984 443
Environ. Sci. Technol. 1904, 18, 444-450
may, however, be taken up more readily from food which is a process not considered here. Another implication is that when bioconcentration experiments are conducted, it is important to recognize that the uptake times of hydrophobic contaminants may be very long; thus, equilibrium may not be reached. An example is the recent study of chlorobenzene (CB) congener uptake by Oliver and Niimi (14). In this case, the halftimes for uptake were approximately the following: tetra-CB, 15 days; penta-CB, 50 days; in which the hexa-CB congener had not reached equilibrium after 120 days. This is the trend predicted by the equation. These authors correctly identified that the experimental BCF of HCB after 120 days was not an equilibrium value and showed that this could lead to erroneous prediction of fish concentrations in Lake Ontario. It should be emphasized that although the narcotic effect of PAB esters is well described by this equation, not all toxic effects are likely to be amenable to such simple analysis. It is apparent that by formulating the equations in the fugacity format, it becomes easier to manipulate the variables and new insights are obtained into the pharmacokinetic processes. It is relatively easy to formulate and test equations describing uptake from food, to include metabolic degrading reactions, and thus to build up more comprehensive equations describing these pharmacokinetic processes. Registry No. 2,5-Dichlorobiphenyl, 34883-39-1; 2,2’,5-trichlorobiphenyl, 37680-65-2; 2,4’,5-trichlorobiphenyl,16606-02-3; 2,2‘,5,5‘-tetrachlorobiphenyl,35693-99-3; 2,3’,4’,5-tetrachlorobiphenyl, 32598-11-1; methyl p-aminobenzoate, 619-45-4; ethyl
p-aminobenzoate, 94-09-7;propyl p-aminobenzoate, 94-12-2; butyl p-aminobenzoate, 94-25-7; pentyl p-aminobenzoate, 13110-37-7; hexyl p-aminobenzoate, 13476-55-6.
Literature Cited (1) Spacie, A,; Hamelink, J. L. Environ. Toricol. Chem. 1982, 1, 309-320. (2) Mackay, D. Enuiron. Sci. Technol. 1979, 13, 1218-1223. (3) Mackay, D.; Paterson, S. Environ. Sci. Technol. 1981,15, 1006-1014. (4) Mackay, D.; Paterson, D. Environ. Sci. Technol. 1982,16, 654A-660A. (5) Bruggeman, W. A.; Martron, L. B. J. .; Kooiman, D.; Hutzinger, 0. Chemosphere 1982, 10, 811-832. (6) Yalkowsky, S. H.; Carpenter, 0. S.; Flynn, G. L.; Slunick, T. G. J . Pharm. Sci. 1973, 62, 1949-1954. (7) Yalkowsky, S. H.; Slunick, T. G.; Flynn, G. L. J . Pharm. Sci. 1974, 63, 691-695. (8) Mackay, D. Enuiron. Sci. Technol. 1982, 16, 274-278. (9) Bruggeman, W. A.; Van Der Steen, J.; Hutzinger, 0. J . Chromatogr. 1982, 238, 335-346. (10) Woodburn, K. B. M. S. Thesis, University of Wisconsin, Madison, WI 1982. (11) Ellgehausen, H.; Guth, J. A,; Esser, H. 0. Ecotoxicol. Environ. Saf. 1980, 4, 134-157. (12) Southworth, G. R.; Beauchamp, J. J.; Schmeider, P. L. Enuiron. Sci. Technol. 1978, 12, 1062-1066. (13) Yalkowsky, S. H.; Valvani, S. C. J . Pharm. Sci. 1980, 69, 912-922. (14) Oliver, B. G.; Niimi, A. J. Environ. Sci. Technol. 1983,17, 287-291.
Received for review June 6,1983. Accepted December 7,1983. This work was supported by the Ontario Ministry of Environment.
Environmental Fate of Combustion-Generated Polychlorinated Dioxins and Furans Jean M. Czuczwa and Ronald A. Hites” School of Public and Environmental Affairs and Department of Chemistry, Indiana University, Bloomington, Indiana 47405
Polychlorinated dioxins and furans were found in sediments from the Saginaw River and Bay and from Lake Huron. The congener distributions of the dioxins and furans indicate that combustion may be the major source of these compounds. The depth vs. concentration profiles in dated sediment cores showed that emission of dioxins and furans has increased greatly since 1940. This historical increase is similar to trends for the production, use, and disposal of chlorinated organic compounds and suggests that chlorinated precursors of dioxins and furans, present in incinerator combustion fuels, may be the main source of the dioxins and furans found in these sediments. Introduction Polychlorinated dibenzodioxins (PCDD) and dibenzofurans (PCDF) are the subject of a recent, often heated debate because some of these compounds are very toxic. For example, 2,3,7,8-tetrachlorodibenzodioxin(2,3,7,8-TCDD) has been found to be acnegenic to humans ( I ) , teratogenic to mice (2),carcinogenic to rats (3),and acutely toxic to guinea pigs (4). Other isomers of PCDD (75 total) show differing degrees of toxicity; isomers of PCDF (135 total) are generally as toxic as the corresponding PCDD. Initially, PCDD and PCDF were discovered as trace impurities in various chlorinated aromatic compounds. We will call these “industrially generated” dioxins and furans. 444
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PCDD and PCDF were found in chlorophenols (5-7), herbicides @-IO), and PCB’s (11). Industrially generated PCDD and PCDF have entered the environment through accidental release during chlorophenol production (12), aerial application of phenoxy herbicides (13),and improper disposal of wastes (14). These events tend to be sporadic and localized. More recently, PCDD and PCDF have been identified in effluents from combustion processes. In particular, dioxins and furans have been found in the fly ash and flue gas of municipal incinerators (15-18). The PCDD and PCDF may be associated with small particulates, which have long residence times in the atmosphere, and in this manner, combustion-generated dioxins and furans could become distributed over large areas. Thus, combustion may have made PCDD and PCDF ubiquitous in the environment. The initial reports of PCDD and PCDF in municipal incinerator fly ash led to an investigation of a variety of combustion processes each of which was a possible source of PCDD and PCDF (19). PCDD and PCDF were measured in particulates from the combustion of municipal and chemical wastes and fossil fuels, and in some unusual samples such as cigarette smoke and charcoal-broiledsteak. The researchers concluded that PCDD and PCDF are ubiquitous products of the combustion of organic materials. In an interview (20),an author of this paper stated,
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0 1984 American Chemical Society
