Estimating Dissolved Organic Carbon Partition Coefficients for

The KDOC data were evaluated as a function of the 1-octanol/water partition coefficients (KOW). ... For individual chemicals, ranges in KDOC values ap...
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Critical Review

Estimating Dissolved Organic Carbon Partition Coefficients for Nonionic Organic Chemicals LAWRENCE P. BURKHARD* U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, 6201 Congdon Boulevard, Duluth, Minnesota 55804

A literature search was performed for dissolved organic carbon/water partition coefficients for nonionic organic chemicals (KDOC), and KDOC data were taken from more than 70 references. The KDOC data were evaluated as a function of the 1-octanol/water partition coefficients (KOW). A predictive relationship of KDOC ) 0.08KOW with 95% confidence limits of a factor of 20 in either direction was developed using KDOC data based upon naturally occurring dissolved organic carbon. Inclusion of KDOC data for Aldrich humic acid, a reagent-grade organic carbon, resulted in a slightly different predictive relationship of KDOC ) 0.11KOW with 95% confidence limits of a factor of 14 in either direction. The large uncertainties in these relationships are, in part, caused by the variability in structure and composition of dissolved organic carbon (DOC) in sediments, soils, and surface waters. This variability is not accounted for by the hydrophobicity parameter. For individual chemicals, ranges in KDOC values approaching 2 orders of magnitude were observed among investigations using Aldrich humic acid as the DOC. These large ranges of KDOC values suggest that measurement techniques are also, in part, responsible for the large uncertainties in these relationships.

Introduction The bioavailability, fate, and behavior of hydrophobic organic chemicals (HOCs) in aquatic ecosystems are directly influenced by the dissolved and particulate organic carbon present. To understand and quantify the importance of dissolved organic carbon (DOC), numerous investigators have studied the binding/sorption of HOCs to DOC using a wide variety of DOCs. Sources of DOC studied include surface waters, sediment and soil porewaters, groundwaters, Aldrich humic acid and other commercially available humic and fulvic acids, and humic and fulvic acids isolated from sediments, soils and surface waters. Typically, sorption of HOCs to DOC is expressed as a partition coefficient of the chemical between the DOC and freely dissolved phases (KDOC) on an organic carbon basis, i.e., L/kg of organic carbon. Determination of the KDOC requires the measurement or calculation of the amount of chemical sorbed to the DOC and the freely dissolved concentration of the chemical in the aqueous phase. To determine freely dissolved concentrations of chemicals in solutions containing DOC, a variety of * Corresponding author phone: (218)529-5164; fax: (218)529-5003; e-mail:[email protected]. 10.1021/es001269l Not subject to U.S. Copyright. Publ. 2000 Am. Chem. Soc. Published on Web 10/21/2000

analytical techniques are available, fluorescence quenching (1), purging or sparging techniques (2, 3), solid-phase microextraction (SPME) (4, 5), equilibrium dialysis (6), solubility enhancement (7), ultrafiltration (8), reverse-phase HPLC separation (9), size exclusion chromatography (2), and liquid-liquid extraction (2, 10). Some of these techniques measure directly the concentration of the freely dissolved chemicals, while others physically separate the DOC-bound chemical from the freely dissolved chemical. All of the methods for measuring freely dissolved chemical in water have some type of limitation, and these limitations can lead to large uncertainties in the determinations of KDOC. The techniques that appear to have smaller biases are SPME, sparging, fluorescence quenching, and possibly equilibrium dialysis because these techniques cause the least disruption in the existing partitioning between the freely dissolved and sorbed phases while making the their measurements. Except for the SPME technique, Suffet et al. (11) has presented an excellent discussion on the individual techniques and their limitations. The reader is urged to consult Suffet et al. (11) as well as the individual references listed above for further information on the analytical techniques. The freely dissolved chemical concentrations in sediment porewaters and surface waters are generally accepted as being the best measure, currently available, for the bioavailable fraction of nonionic organic chemicals to aquatic organisms (11, 12). Freely dissolved concentrations can be estimated using a three-phase partitioning model (13):

ffd ) 1/(1 + [POC]KPOC + [DOC]KDOC) t Cfd w ) Cw ffd

where ffd is the fraction of chemical freely dissolved, [POC] is the concentration of particulate organic carbon, KPOC is the partition coefficient between particulate organic carbon and freely dissolved chemical, [DOC] is the concentration of the dissolved organic carbon, KDOC is the partition coefficient between dissolved organic carbon and freely dissolved chemical, Cfd w is the freely dissolved concentration of the chemical in the water, and Ctw is the total concentration in the water sample, i.e., the sum of the chemical sorbed to POC and DOC, and the freely dissolved chemical. With proper knowledge of the POC and DOC partition coefficients, freely dissolved concentrations of chemical can be estimated. The above definition of the bioavailable chemical in water, i.e., the freely dissolved chemical, has been used to determine KDOC values with aquatic organisms (14). In performing these determinations, organisms were exposed to chemicals in the presence of varying concentrations of DOC, and bioconcentration factors (BCFs) were measured. With the measured VOL. 34, NO. 22, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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BCFs, KDOC is determined using nonlinear regression analysis with the following equation (14):

BCFDOC ) BCF0/(1 + KDOC[DOC]) where BCFDOC is the bioconcentration factor for a chemical in water containing DOC, and BCF0 is the bioconcentration factor for a chemical in water containing none of the DOC of interest, e.g., dilution water used in toxicity testing. In solving this equation for KDOC, BCFDOC values determined using four to eight DOC concentrations are required. This method of determining KDOC differs from the analytical techniques listed above in that the freely dissolved chemical concentrations do not have to be measured. This method assumes that no particulate organic carbon is present and that only the freely dissolved chemical can be taken up by the aquatic organisms. Biotransformation of the HOC by the organisms should not be an issue with this technique because regardless of the DOC content of the water, all BCFs would be similarly affected (15). Research performed to date suggests that KDOC is not strongly dependent upon the hydrophobicity of the chemical, i.e., 1-octanol/water partition coefficient of the chemical (KOW). For example, Kukkonen and Oikari (16) and Evans (17), using a variety of surface water samples with differing DOC concentrations, reported ranges for KDOC values of more than an order of magnitude for benzo[a]pyrene and PCB congeners. Similarly, Perminova et al. (18) using 26 different humic materials reported ranges for KDOC values of approximately an order of magnitude for pyrene, fluoranthene, and anthracene. Using Lake Michigan data, Eadie et al. (19) developed a log KDOC - log KOW relationship with a slope of 0.24, which also suggests a weak dependence of KDOC upon KOW. However, McCarthy and Jimenez (20) and Freidig et al. (21) reported log KDOC - log KOW relationships using Aldrich humic acid with slopes (correlation coefficient) of 1.03 (0.98) and 0.67 (0.90), respectively, which suggest that there is some dependence of KDOC upon KOW. In contrast, partition coefficients between sediments/soils organic carbon and water (KOC) have been found to be strongly dependent upon the KOW of the chemical. In a recent evaluation of the KOC data by Seth et al. (22), KOC was found to be equal to 0.35KOW with 95% confidence limits of a factor of 2.5 in either direction. Previously, Karickhoff (23) and DiToro et al. (11) reported strong dependence of KOC upon KOW, KOC ) 0.41KOW and KOC ) KOW, respectively. Humic substances are the major component of the natural organic carbon in water, sediment, and soil systems, e.g., 50-80% (18, 24). Therefore, much research has been focused on determining the sorption/binding affinity of HOCs to humic substances as related to composition and structure of the humic substances, e.g., the aromaticity, H/C and O/C atomic ratios, UV absorptivity, pH, molecular weight, and NMR descriptors of structure (16, 18, 25-27). In general, the affinities of HOCs for fulvic acids are smaller than those for humic acids, thus resulting in smaller KDOC values for fulvic acids in comparison to humic acids. Aldrich humic acid, a commonly used reagent-grade humic acid, has binding/ sorption affinities for HOCs that are larger than those for DOC and naturally occurring humic and fulvic acids (11). Unfortunately, a definitive model for predicting KDOC values is not available for DOCs from surface waters or sediments. Nevertheless, predictive relationships have been developed because of the dire need for such a model. These include a relationship of KDOC ≈ 0.135KOW derived by Kopinke et al. (28) using Hildebrand solubility parameters and a relationship of KDOC ) 0.1 KOW proposed by the U.S. Environmental Protection Agency for use in deriving freely dissolved chemical 4664

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concentrations with the three-phase partitioning model (29). These relationships as well as those based upon Aldrich humic acid above were developed using small KDOC data sets, both in numbers of chemicals and types of DOC. In this study, the results of a literature review for KDOC measurements are reported and evaluated. The objective of this report is to develop predictive relationships for KDOC using KOW with a comprehensive KDOC data set. Sources of DOC used in the measurements include (a) Aldrich humic acid; (b) humic and fulvic acids isolated from surface waters, sediments, and soils; (c) sediment and soil porewaters; (d) groundwaters; and (e) surface waters, e.g., lakes, rivers, and estuaries.

Methods A literature search was performed using SciFinder by CAS (30), and the KDOC data, obtained from 73 references, are reported in Table 1 (in Supporting Information). For some reports, KDOC values were estimated from the figures because numerical values for the KDOC values were not reported. In this analysis, KDOC data for effluents from industrial facilities were not used because the DOC in these effluents was believed to be substantially different from that in the environment. KDOC data for ionizable (polar) organics were not used in this analysis as well because the partitioning behaviors of ionic and nonionic organic chemicals are different (31). These data, even though they were not used, are reported in Table 1 (in Supporting Information). Also included in Table 1 (in Supporting Information) are KDOC values determined by model calculations from field measured KD values, the partition coefficient of the chemical between the POC and the water passing a filter. These values were not used in the data analysis but were plotted in the figures for comparison purposes. In Table 1 (in Supporting Information), three data sets are reported that were not used in the data analysis. These were the fulvic acid data of Burgess and Ryba (32), which differed by an order of magnitude between the two measurement techniques used in the study; the Aldrich humic acid data of Johnsen (10), where equilibrium conditions were not obtained; and the ambient water data of Naes et al. (33) determined using polyurethane foam plugs, a technique not used by any other investigator. All regression analyses were performed using the geometric mean regression technique (34) because both the X and Y variables were measured with error. These regressions were performed using the equations provided by Ricker (34) and Webb et al. (35).

Results and Discussion In Figure 1, KDOC values are plotted for five DOC sources as a function of the chemicals’ KOW. For DOCs consisting of Aldrich humic acid and sediment porewaters, linear relationships between log KDOC and log KOW were observed with slopes of approximately 1 with correlation coefficients of 0.77 and 0.64, respectively (Table 2). In contrast, log KDOC data for humic and fulvic acids without Aldrich humic acids, soil porewaters and groundwaters, and surface waters have a slight dependence upon log KOW although their slopes are similar to 1. For the latter three DOC sources, their correlation coefficients are rather small, ≈0.3; therefore, their regression equations should be viewed with some caution. For most of the DOC sources, the KDOC data are very unevenly weighted among the individual chemicals. For example, biphenyl and benzo[a]pyrene had 4 and 49 KDOC measurements, respectively, for DOC from surface waters. This unevenness caused some difficulties in the regression analyses because the regression fits are skewed toward the chemicals with more measurements. From an analytical and methodological perspective, the Aldrich humic acid KDOC data should provide the best measure of overall analytical precision among the investigations

ment, and the 10th, 50th, (median), and 90th percentile and pooled standard deviations for these measurements were 0.08, 0.24, 0.47, and 0.40 on a log KDOC basis, respectively. The differences between the smallest and the largest measurements ranged from 0.02 to 1.92 log units with a median difference of 0.48 among the 41 chemicals. An estimate of the 95% confidence limits on a relative scale can be obtained by doubling the pooled standard deviation and then transforming to the antilog scale. This results in a 95% confidence limits of a factor of 6.3 in either direction. Comparing these limits to those of Seth et al. (22) for KOC, a factor of 2.5 demonstrates that measurement of KDOC is less precise than for other partitioning measurements. Because the Aldrich humic acid studies were all performed using a common source of DOC, the range of a factor of 6.3 in either direction does not include variability due to differences in DOC composition and structure. Therefore, one should expect even larger confidence limits when other DOC sources are included in the analysis. A quick perusal of Figure 1 reveals this trend. Visual comparison of the KDOC values (Figure 1) suggests that the measurement methods, in general, provide similar KDOC data. If any biases exist, the biologically determined KDOC data might be slightly higher, on average, than those observed with the other techniques; the equilibrium dialysis and solubility enhancement techniques appear to provide slightly lower KDOC values than the other techniques for the humic and fulvic acids (Figure 1). Given the differences in DOC sources, composition, and structure among the investigations, a robust analysis for analytical and methodological biases is not possible with the data. The KDOC data arising from surface water DOC appears to have slightly more scatter or variability than that observed for the other DOC sources. On a diagenesis basis, surface water DOC might be expected to be more variable than DOC from sediments, soils, and humic and fulvic acids because surface water DOC contains detritus from recently deceased plankton and algae, macrophytes, etc. Some of the variability in all sources of DOC including surface waters is caused by differences among the measurement techniques. Comparisons of the reverse-phase and dialysis techniques by Landrum et al. (9) and Kukkonen and Pellinen (36) suggest that differences of an order of magnitude or more can occur between these two methods in some cases. More typically, these investigators found the dialysis technique providing higher values, i.e., factors of 2-5. Landrum et al. (9) performed side-by-side KDOC measurements with biphenyl, log KOW ) 4.09, using water samples from Lake Erie and Huron River. The KDOC data differed by factors of 3 and 34 between these two techniques, respectively. Some of the variability in the KDOC data from surface waters might also be related to when these measurements were made because most of the measurements occurred in the 1980s when methodologies for measuring KDOC values were evolving or new.

FIGURE 1. KDOC values determined using the reverse-phase (circle), equilibrium dialysis (open square), sparging (plus diamond), calculated/model-derived (downward triangle), fluorescence quenching (upward triangle), solubility enhancement (open diamond), biological (plus square), and solid-phase microextraction (open plus diamond) techniques for DOCs from different sources. The geometric mean regression and their 95% prediction confidence limits are plotted. because the DOC was the same in all measurements. Fortyone chemicals were found to have more than one measure-

To provide a comparison of the KDOC values for all DOC sources, KDOC values for each chemical were averaged across analytical methods within each DOC source and replotted (Figure 2). Average values were determined in part because of the rather unevenness of the data set in numbers of measurements per chemical. The plot of log KDOC versus log KOW shows considerable consistency, and a strong dependence of KDOC upon KOW is apparent (Figure 2). The average KDOCvalues for the Aldrich humic acids are on average higher that those derived from natural sources (Figure 2), and these results are consistent with the differences in affinities for Aldrich humic acid and naturally occurring organic carbon reported in the literature for HOCs (11). The data used in these regressions contained average KDOC values for 14, 110, 84, 7, and 22 chemicals for the DOC sources of naturally VOL. 34, NO. 22, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 2. Geometric Mean Regression Equations for KDOC upon KOW DOC source

geometric mean regression equation

na

r

sxy

Aldrich humic acid humic and fulvic acids without Aldrich humic acid sediment porewaters soil porewaters and groundwaters surface waters all DOC including Aldrich humic acid naturally occurring DOC (no Aldrich humic acid) PCBs, naturally occurring DOC (no Aldrich humic acid) PAHs, naturally occurring DOC (no Aldrich humic acid)

log KDOC ) 0.85 ((0.03)b‚log KOW + 0.27 ((0.20) log KDOC ) 0.88 ((0.06)‚log KOW - 0.11 ((0.31) log KDOC ) 0.99 ((0.04)‚log KOW - 0.88 ((0.23) log KDOC ) 0.91 ((0.13)‚log KOW - 0.22 ((0.68) log KDOC ) 0.97 ((0.06)‚log KOW - 1.27 ((0.40) log KDOC ) 0.85 ((0.04)‚log KOW - 0.11 ((0.21) log KDOC ) 0.85 ((0.06)‚log KOW - 0.25 ((0.34) log KDOC ) 0.71 ((0.06)‚log KOW - 0.50 ((0.36) log KDOC ) 1.18 ((0.13)‚log KOW - 1.56 ((0.72)

269 230 396 47 210 223 127 77 33

0.77 0.29 0.64 0.31 0.32 0.78 0.67 0.69 0.76

0.52 0.65 0.66 0.61 0.99 0.52 0.60 0.41 0.73

a

n ) number of data points, r ) correlation coefficient, sxy ) standard error of estimate. b ((standard deviation).

FIGURE 3. Residuals between measured log KDOC values and log KDOC values predicted using the relationship of KDOC ) 0.08 KOW. DOC sources: humic and fulvic acids without Aldrich humic acid (open diamond), sediment porewaters (downward triangle), soil porewaters and groundwaters (plus square), and surface waters (upward triangle). The 95% confidence limits are plotted.

FIGURE 2. Average KDOC values for individual chemicals for different DOC sources: humic and fulvic acids (open diamond), sediment porewaters (downward triangle), soil porewaters and groundwaters (plus square), and surface waters (upward triangle). The geometric mean regression and their 95% prediction confidence limits are plotted. occurring humic and fulvic acids (no Aldrich humic acid), all humic and fulvic acids including Aldrich humic acid, sediment porewaters, soil porewaters and groundwaters, and surface waters, respectively (Table 2). On a theoretical basis, the equation log KDOC, KPOC, or KOC ) A log KOW + B has a slope of 1 when the ratio of the activity coefficients of the chemical in octanol to that in the organic carbon phase is constant for chemicals with different KOW values (22). The relationships derived by Seth et al. (22), DiToro et al. (12), and Karickhoff (23) of log KOC ) A log KOW + B had slopes of 1 and are clearly consistent with the hypothesis that the ratio of activity coefficients is constant. Given the above theoretical basis and experimental data, a slope of 1 was assumed for the relationship in this investigation, i.e., log KDOC ) log KOW + B. This equation, by rearrangement, results in B ) log KDOC - log KOW ) log(KDOC/KOW), and B can be found by averaging the differences of the log KDOC and log KOW for the individual chemicals or by averaging the logarithms of the ratio of the KDOC to KOW for the individual chemicals. For the data set consisting of naturally occurring DOC (no Aldrich humic acid), an average difference (standard deviation, number of data points) of -1.11 (0.659, 127) was obtained. Transforming the average difference to an antilog scale results in a predictive relation4666

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ship of KDOC ) 0.08KOW with the 95% confidence limits of a factor of 20 [antilog of (st(R ) 5%,df ) 126) ) 0.659 × 1.979)] in either direction from the predicted mean KDOC. When Aldrich humic acids are included, an average difference (standard deviation, number of data points) of -0.966 (0.578, 223) was obtained, and after transformation to an antilog scale, a predictive relationship of KDOC ) 0.11KOW with 95% confidence limits of a factor of 14 in either direction was obtained. The residuals for the predictive relationship, experimental log KDOC values minus predicted log KDOC values, with naturally occurring DOC have a slight dependence upon the KOW (Figure 3). The distribution of the residuals is normally distributed (R ) 10%) with 64 negative and 63 positive residuals. Analyses of the average KDOC values were also performed on a chemical class basis using the subsets of polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs). The regressions with and without the Aldrich humic acid data were about the same; therefore, only the regressions without the Aldrich data were reported in Table 2. The slope of the PAH regression was not significant different from 1.0 (R ) 0.05) whereas the slope of the PCB regression was slighly lower and significantly different from 1.0. However, PCB data extend to much higher KOWvalues, and the depression of the slope is caused, I believe, by the difficulties in performing the freely dissolved measurements for log KOW values exceeding 6.5. These difficulties would cause the reported KDOC values to be too small. With some PCB data, log KDOC values increase linearly with increasing log KOW (37) whereas with other data, log KDOC values plateau with increasing log KOW (38). These inconsistencies among PCB data for higher KOW PCBs are suggestive and consistent with a methodological bias and/or analytical difficulties. The average differences (standard deviation, number of data points) of the log KDOC and log KOW for the individual PCBs and PAHs were -1.24

(0.529, 77) and -0.58 (0.705, 33), respectively. Transforming these average differences to the antilog scale results in predictive relationships of KDOC ) 0.06KOW and 0.26KOW for the PCBs and PAHs, respectively. Although there is some difference in the predictive relationships on a class basis, this difference is not statistically significant (R ) 0.1). The variability of the overall predictive relationship, i.e., KDOC ) 0.08 KOW, is much larger than the factor of 2.5 reported by Seth et al. (22) for KOC and is larger than the variability observed with Aldrich humic acid alone (Figure 1), approximately a factor 10 in either direction, i.e., antilog of (sxyt(R)5%,df)268) ) 0.52 × 1.969). This larger variability is clearly consistent with the findings of Kukkonen and Oikari (16) and others where hydrophobicity of the chemical is not the only factor affecting the association of HOCs with DOC. The above relationship, KDOC ) 0.08 KOW, provides a useful rule of thumb for modelers and environmental scientists when selecting values of KDOC for HOCs in the absence of measured values. The large 95% confidence limits, a factor of 20 in either direction, associated with the predictive relationship might or might not result in large uncertainties in outputs from models employing this relationship. These uncertainties will be dependent upon the model, its input parameters, and the hydrophobicity of the chemical. For example, using the threephase partitioning model (eq 1), the fraction of chemical freely dissolved ( ffd) in an ambient water for a chemical with a log KOW of 4 with 2 mg/L DOC, 0.1 mg/L POC, and KPOC ) KOW would be 99.7% with a 95% confidence limit of 96.899.9%; essentially no difference. In contrast, for a chemical with a log KOW of 7, ffd would be 27.8% with a 95% confidence limit of 2.9-48%. These 95% confidence limits have an overall range of a factor of 16, and this range is substantially smaller than the factor of 20 in either direction for the predicted KDOC. Users of the KDOC - KOW relationship must fully evaluate and understand the effects of the large uncertainties in their individual applications. The variability in the structure and composition of DOC in sediments, soils, and ambient waters and the analytical difficulties in making KDOC measurements results in substantial variability in measured KDOC values. Predictive relationships based solely upon the hydrophobicity of the chemical will have large uncertainties as illustrated by the above predictive relationship. However, the underlying importance of hydrophobicity of the chemical is well supported by the data. The data suggest that any model for predicting the association of a wide range of HOCs to DOC will require the inclusion of a parameter for the chemical’s hydrophobicity. To lower uncertainties, substantial improvements in characterizing the composition of DOC as well as substantial improvements in understanding how the different components of the DOC interact with HOCs will be required. Characterizing DOC by just measuring total dissolved organic carbon does not adequately describe this phase! Recent research results by Perminova et al. (18) suggests for humic acids that the ratio of the aromatic to aliphatic carbon content of humic acids might be a very useful characterization tool. The relatively large variability observed among investigations using Aldrich humic acid as the DOC source suggests that refinements and improvements in measurement techniques will also be required for lower uncertainties.

Acknowledgments I thank David Mount, Patricia Kosian, and Larry Heinis for their constructive reviews; Keith Sappington, Philip Cook, and Erik Winchester for helpful discussions; and Robert Burgess and Kristoffer Naes for providing numerical KDOC data from their reports.

Supporting Information Available KDOC data are reported in Table 1 with the chemical name, DOC source and type classification, DOC (mg/L) (when available), log KOW, log KDOC or KDOC, method used to perform the measurement, and source of data for each entry (29 pages). This material is available free of charge via the Internet at http://pubs.acs.org.

Literature Cited (1) Gauther, T. D.; Shane, E. C.; Guerin, W. F.; Seitz, W. R.; Grant, C. L. Environ. Sci. Technol. 1986, 20, 1162-1166. (2) Hassett, J. P.; Milicic, E. Environ. Sci. Technol. 1985, 19, 638643. (3) Yin, C.; Hassett, J. P. Environ. Sci. Technol. 1986, 20, 12131217. (4) Poerschmann, J.; Zhang, Z.; Kopinke, F.-D.; Pawliszyn, J. Anal. Chem. 1997, 69, 597-600. (5) Ramos, E. U.; Meijer, S. N.; Vaes, W. H. J.; Verhaar, H. J. M.; Hermans, J. L. M. Environ. Sci. Technol. 1998, 22, 3430-3435. (6) Carter, C. W.; Suffet, I. H. Environ. Sci. Technol. 1982, 16, 735740. (7) Chiou, C. T.; Kile, D. E.; Brinton, T. I.; Malcolm, R. L.; Leenheer, J. A.; MacCarthy, P. Environ. Sci. Technol. 1987, 21, 1231-1234. (8) Means, J. C.; Wijayaratne, R. Science 1982, 215, 968-970. (9) Landrum, P. F.; Nihart, S. R.; Eadie, B. J.; Gardner, W. S. Environ. Sci. Technol. 1984, 18, 187-192. (10) Johnsen, S. Sci. Total Environ. 1987, 67, 269-278. (11) Suffet, I. H.; Jafvert, C. T.; Kukkonen, J.; Servos, M. R.; Spacie, A.; Williams, L. L.; Noblet, J. A. Synopsis of Discussion Session: Influences of Particulate and Dissolved Material on the Bioavailability Of Organic Compounds. In Bioavailability: Physical, Chemical, and Biological Interactions; Hamelink, J. L., Landrum, P. F., Bergman, H. L., Benson, W. H., Eds.; Lewis Publishers: Ann Arbor, MI, 1994; Chapter 3. (12) DiToro, D. M.; Zarba, C. S.; Hansen, D. J.; Berry, W. J.; Swartz, R. C.; Cowan, C. E.; Pavlou, S. P.; Allen, H. E.; Thomas, N. A.; Paquin, P. R. Environ. Toxicol. Chem. 1991, 10, 1541-1583. (13) Chin, Y.; Gschwend, P. M. Environ. Sci. Technol. 1992, 26, 16211626. (14) Haitzer, M.; Burnison, B. K.; Hoss, S.; Traunspurger, W.; Steinburg, C. E. W. Environ. Toxicol. Chem. 1999, 18, 459-465. (15) Haitzer, M.; Hoss, S.; Traunspurger, W.; Steinburg, C. Chemosphere 1998, 37, 1335-1362. (16) Kukkonen, J.; Oikari, A. Water Res. 1991, 23, 455-463. (17) Evans, H. E. Chemosphere 1988, 12, 2325-2338. (18) Perminova; I. V.; Grechishcheva, N. Y.; Petrosyan, V. S. Environ. Sci. Technol. 1999, 33, 3781-3787. (19) Eadie, B. J.; Morehead, N. R.; Landrum, P. F. Chemosphere 1990, 20, 161-178. (20) McCarthy, J. F.; Jimenez, B. D. Environ. Sci. Technol. 1985, 19, 1072-1076. (21) Freidig, A. P.; Garicano, E. A.; Busser, F. J. M.; Hermans, J. L. M. Environ. Toxicol. Chem. 1998, 17, 998-1004. (22) Seth, R.; MacKay, D.; Muncke, J. Environ. Sci. Technol. 1999, 33, 2390-2394. (23) Karickhoff, S. W. J. Hydraul. Div. Am. Soc. Civ. Eng. 1984, 110, 707-735. (24) Thurman, E. M. Organic Geochemistry of Natural Waters; Martinus Nijhoff/Dr. W. Junk: Dordrecht, The Netherlands, 1985. (25) Chin, Y. P.; Aiken, G. R.; Danielsen, K. M. Environ. Sci. Technol. 1997, 31, 1630-1635. (26) Gauther, T. D.; Seitz, W. R.; Grant, C. L. Environ. Sci. Technol. 1987, 21, 243-252. (27) De Paolis, F.; Kukkonen, J. Chemosphere 1997, 34, 1693-1704. (28) Kopinke, F.-D.; Porschmann, J.; Stottmeister, U. Environ. Sci. Technol. 1995, 29, 941-950. (29) Ambient Water Quality Criteria Derivation Methodology Human Health: Technical Support Document. Final Draft; U.S. Environmental Protection Agency, Office of Water; U.S. Government Printing Office: Washington, DC, 1998; EPA-822-B-98-005. (30) Chemical Abstract Service, Columbus, OH, 1999. (31) Schwarzenbach, R. P.; Gschwend, P. W.; Imboden, D. M. Environmental Organic Chemistry; Wiley: New York, 1993. (32) Burgess, R. M.; Ryba, S. A. Chemosphere 1998, 36, 2549-2568. VOL. 34, NO. 22, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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(33) Naes, K.; Axelman, J.; Naf, C.; Broman, D. Environ. Sci. Technol. 1998, 32, 1786-1792. (34) Ricker, W. E. J. Fish. Res. Board Can. 1973, 30, 409-434. (35) Webb, T., III; Howe, S. E.; Bradshaw, R. H. W.; Heide, K. M. Rev. Palaeobot. Palynol. 1981, 34, 269-300. (36) Kukkonen, J.; Pellinen, J. Sci. Total Environ. 1994, 152, 19-29. (37) Ozretich, R. J.; Smith, L. M.; Roberts, F. A. Environ. Toxicol. Chem. 1995, 14, 1261-1272.

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(38) Burgess, R. M.; McKinney, R. A.; Brown, W. A. Environ. Sci. Technol. 1996, 30, 2556-2566.

Received for review May 16, 2000. Revised manuscript received September 6, 2000. Accepted September 11, 2000. ES001269L