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Comment on “Reevaluation of Air-Water Exchange Fluxes of PCBs in Green Bay and Southern Lake Michigan” Using the example of the water solubility and octanol-water partition coefficient for DDT and DDE, Pontolillo and Eganhouse (1) recently discussed the importance of accurate physical-chemical property data and how erroneous data could result in serious misinterpretation. The issue was discussed further in a recent Environ. Sci. Technol. feature paper (2), which also highlighted a clear need for accurate partitioning data and how they vary with temperature. Regrettably, few undertake the demanding work of generating such data. In this comment, we would like to expand on this issue and show that even very precise data generated by experienced groups can lead to misinterpretations and wrong conclusions. Recent papers by a highly respected group illustrate these pitfalls. Bamford et al. (3) performed extensive and much needed determinations of air-water partition coefficients or Henry’s law coefficients (H) for the polychlorinated biphenyls (PCBs) as a function of temperature. The bubble stripping technique they used is well-established, and the generated data were very precise. These data, however, showed disagreement with previous less extensive results, prompting Totten et al. (4) to reinterpret air and water concentrations of PCBs from the Great Lakes. This reinterpretation is influenced strongly by any error in H (i.e., both direction and rate of PCB transfer across the air-water interface are sensitive to the selection of H and its temperature dependence). We first examine the H data in the light of recent consistency evaluations. Four studies have experimentally determined H for a large number of PCB congeners (3, 5-7). Whereas these studies generally agree about the value of H for the lighter congeners (1 < log(H/Pa‚m3‚mol-1) < 2), the values reported for the heavier congeners by Bamford et al. (3) are consistently higher than those reported by both Brunner et al. (5) and Murphy et al. (7) (see Figure 1). Dunnivant et al. (6) only reported H for three congeners with more than five chlorines. A recent data evaluation exercise (8) revealed that the higher values by Bamford et al. (3) are not only inconsistent with these earlier measurements of H but also thermodynamically incompatible with the bulk of the empirical evidence for other physical-chemical properties (vapor pressure, solubility in water and n-octanol, KOW, and KOA) of the heavier PCB congeners. This assessment is based on the constraints imposed on the partitioning properties of an organic compound by the thermodynamic relationships between these properties (9, 10). The lower H for the higher chlorinated PCB congeners reported in the other studies, in particular by Murphy et al. (7), agree better with these constraints (8). Bamford et al. (3) used the bubble stripping technique to measure H. We suspect that their higher H values may be artifacts caused by the sorption of the higher PCB congeners to the surface of the gas bubbles in the gas purging column. Some of the sorbed chemical is injected into the air following bubble bursting, resulting in an overestimation of the air concentrations (and hence H). Using poly-parameter linear free energy relationships for adsorption to the water surface (11), the adsorption coefficients (KIA) for the PCBs at 25 °C can be estimated to fall in the range of 1 mm-2 cm, increasing with the degree of chlorination. Assuming equilibrium partitioning and spherical bubbles of radius (r), the factor by which H would be overestimated as a result of sorption to 1626
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FIGURE 1. Relationship between the Henry’s law coefficient at 25 °C and the number of chlorine substitutions for polychlorinated biphenyls, using experimental data by Murphy et al. (7), Dunnivant et al. (6), Brunner et al. (5), and Bamford et al. (3) and the final adjusted value of an extensive data selection procedure by Li et al. (8). the bubble surface is 3KIA/r + 1. If the bubbles in the gas purging apparatus had a radius of 1-5 mm, the error in H would be a factor of 2-5 for PCB-28 to a factor of 15-70 for PCB-180. This would not only explain why the H values for the highly chlorinated congeners by Bamford et al. (3) are too high by more than an order of magnitude but also why that discrepancy does not occur for the lighter congeners. Brunner et al. (5) and Murphy et al. (7) used techniques that are not subject to this artifact. Dunnivant et al. (6) also used the bubble stripping technique but did not report H for highly chlorinated congeners, for which this artifact would be most pronounced. An even clearer indication that the H data by Bamford et al. (3) are not valid stems from an unreasonably large variability of the enthalpies of air-water exchange (∆HH), which describe the temperature dependence of the partitioning process. The reported ∆HH values for the hexachlorobiphenyls vary between 30 and 160 kJ/mol (3). Such a large range is not plausible, being at odds with the current understanding of the thermodynamic behavior of organic molecules. Differences of that magnitude in the interaction energies of closely related isomers have never previously been reported and cannot be explained through intermolecular interactions. Neither are there any models, which would predict such large differences in the interaction energies of closely related isomers in water (12-14). All hexachlorobiphenyls have an enthalpy of vaporization on the order of 80-90 kJ/mol (15-17). A hexachlorobiphenyl with a ∆HH of 160 kJ/mol would thus have an enthalpy of solubilization in water of -70 to -80 kJ/mol. There are no indications in the literature of any organic substance having such highly exothermic enthalpies of solubilization. These energies rather range between -20 kJ/mol for small polar molecules to >+10 kJ/mol for larger nonpolar aromatic compounds (18-20). ∆HH values in the range of 55-75 kJ/mol, reported by Burkhard et al. (21), are in much better agreement with the thermodynamic constraints (8). The measurement of ∆HH values below 50 kJ/mol, reported for the lighter congeners by Bamford et al. (3), may also be an artifact related to the sorption of PCBs to the 10.1021/es030567q CCC: $27.50
2004 American Chemical Society Published on Web 01/27/2004
FIGURE 2. Relationship between the logarithm of the Henry’s law coefficient (ln H) and the enthalpy of air-water exchange (∆HH) reported by Bamford et al. (3). bubble surface. The adsorption coefficient at the water surface KIA is much higher at lower temperatures, so the error in H measured with the gas stripping method is expected to be higher at low temperatures. At temperatures as low as 4 °C, even the lighter PCB congeners have sufficiently high surface sorption to cause a significant error. In other words, this artifact would lead to energies of air-water exchange that are erroneously low (i.e., the apparent temperature dependence is less than it should be). This artifact cannot however explain the unreasonably large ∆HH values reported by Bamford et al. (3). The fact that a predictive relationship was developed from the measured H values does not support their validity (22). This predictive relationship is based on a correlation between ∆HH and ∆SH for the 26 PCB congeners whose H and ∆HH had been measured (3). Because ∆GH ) ∆HH - T∆SH, a linear relationship between ∆HH and ∆SH also implies a linear relationship between ∆HH and ∆G and thus ln H for a given temperature. However, Figure 2 clearly shows that such a relationship does not exist for the data in ref 3. The fact that ∆HH and ∆SH are correlated with each other is due to the specific numerical situation (i.e., the variation of ∆GH values is very small as compared to the variation in ∆HH, so that ∆SH must be correlated to ∆HH). However, the relationship between ∆HH and ∆SH cannot be used to predict ∆HH because it does not contain any independent information about the variation of ∆HH. ∆HH can only be predicted from a single experimental ln H value if a correlation between ln H and ∆HH has been demonstrated for the compound class that is studied. This is not the case here. In summary, there is little reason to believe that the experimental H values and their temperature dependence reported by Bamford et al. (3) are any more reliable or closer to the truth than the ones that had been used earlier. In fact, the weight of evidence clearly suggests the opposite. The extrapolation of these experimental H and ∆HH values to the other PCB congeners is based on a mathematical artifact. The paper by Totten et al. (4) contained no uncertainty analysis of the air-water exchange flux estimates. Air-water exchange calculations are only meaningful if the uncertainty of the air and surface water concentrations, the mass transfer coefficient, and the air-water partitioning coefficient are taken into account (23-25). If the chemical is close to a partitioning equilibrium, as the PCBs purportedly were for southern Lake Michigan, it is generally not possible to state the direction, let alone the magnitude, of the air-water exchange flux. This is the classic problem of calculating a small difference from two large and uncertain numbers, in this case net exchange as the difference between volatilization
and absorption. The uncertainty in the measured concentrations is an important aspect of this problem. For instance, volatilization and absorption fluxes of 10 and 8, respectively, calculated from water and air concentrations with a standard deviation of 20% each yield a nominal net volatilization of 2, but there is a relatively high likelihood that the net exchange is indeed in the opposite direction. The influence of the uncertainty in H on the flux calculation was amply illustrated in the paper by Totten et al. (4). By choosing a different set of H values, the direction and magnitude of the PCB fluxes changed dramatically, as did the interpretation of PCB fate in the water bodies studied. As discussed above, we do not believe that the H values used were more correct (less uncertain) than others in the literature. In the absence of a scientifically based evaluation of the uncertainty of the parameters in the flux calculation, the conclusions on the direction and magnitude of the flux must be doubted. We conclude that there is not only a need for accurate physical-chemical property data (1, 2) but also a need for careful checking of thermodynamic consistency. Precision and high reproducibility must not be taken as indications of accuracy. Even well-established laboratories are vulnerable to the possibility of generating erroneous property data. It is important to prevent propagation of inaccurate data in the refereed literature and data compilations. Independent and rigorous measurements of a variety of related properties from different groups and use of techniques for assessing the thermodynamic consistency of data (8, 10) are the most likely route to constrain the true value of these properties. Finally, when reaching conclusions on environmental fate, it is critical to include an analysis of the uncertainty including a consideration of possible errors in the physical-chemical data.
Literature Cited (1) Pontolillo, J.; Eganhouse, R. P. The search for reliable aqueous solubility (SW) and octanol-water partition coefficient (KOW) data for hydrophobic organic compounds: DDT and DDE as a case study; U.S. Geological Survey Water-Resources Investigations Report 01-4201; USGS: Denver, 2001; 51 pp. (2) Renner, R. Environ. Sci. Technol. 2002, 36, 410A-413A. (3) Bamford, H. A.; Poster, D. L.; Baker, J. E. J. Chem Eng. Data 2000, 45, 1069-1074. (4) Totten, L. A.; Gigliotti, C. O.; Offenberg, J. H.; Baker, J. E.; Eisenreich, S. J. Environ. Sci. Technol. 2003, 37, 1739-1743. (5) Brunner, S.; Hornung, E.; Santl, H.; Wolff, E.; Piringer, O. G.; Altschuh, J.; Bruggemann, R. Environ. Sci. Technol. 1990, 24, 1751-1754. (6) Dunnivant, F. M.; Coates, J. T.; Elzerman, A. W. Environ. Sci. Technol. 1988, 22, 448-453. (7) Murphy, T. J.; Mullin, M. D.; Meyer, J. A. Environ. Sci. Technol. 1987, 21, 155-162. (8) Li, N.; Wania, F.; Lei, Y. D.; Daly, G. L. A comprehensive and critical compilation, evaluation and selection of physical chemical property data for selected polychlorinated biphenyls. J. Phys. Chem. Ref. Data 2003, 32, 1535-1590. (9) Cole, J. G.; Mackay, D. Environ. Toxicol. Chem. 2000, 19, 265270. (10) Beyer, A., Wania, F.; Gouin, T.; Mackay, D.; Matthies, M. Environ. Toxicol. Chem. 2002, 21, 941-953. (11) Roth C. M.; Goss, K.-U.; Schwarzenbach, R. P. J. Colloid Interface Sci. 2002, 252, 21-30. (12) Braibanti, A.; Fisicaro, E.; Compari, C. J. Therm. Anal. Calorim. 2000, 61, 461-481. (13) Fredenslund, A.; Sørensen, J. M. Group Contribution Estimation Methods. In Models for Thermodynamic and Phase Equilibria Calculations; Sandler, S. I., Ed.; Marcel Dekker: New York, 1994; pp 287-361. (14) Ruelle, P.; Kesselring, U. W. Chemosphere 1997, 34, 275-298. (15) Goss, K.-U.; Schwarzenbach, R. P. Environ. Sci. Technol. 1999, 33, 3390-3393. (16) Hinckley, D. A.; Bidleman, T. F.; Foreman, W. T. J. Chem. Eng. Data 1990, 35, 232-237. (17) Falconer, R. L.; Bidleman, T. F. Atmos. Environ. 1994, 28, 547554. VOL. 38, NO. 5, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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(18) Hovorka, S.; Dohnal, V.; Roux, A. H.; Roux-Desgranges, G. Fluid Phase Equilib. 2002, 201, 135-164. (19) Schwarzenbach, R. P.; Gschwend, P. M.; Imboden, D. M. Environmental Organic Chemistry, 2nd ed.; John Wiley & Sons: Hoboken, NY, 2002. (20) Benes, M.; Dohnal, V. J. Chem. Eng. Data 1999, 44, 1097-1102. (21) Burkhard, L. P.; Armstrong, D. E.; Andren, A. W. Environ. Sci. Technol. 1985, 19, 590-596. (22) Bamford, H. A.; Poster, D. L.; Huie, R.; Baker, J. E. Environ. Sci. Technol. 2002, 36, 4395-4402. (23) Hoff, R. M. J. Great Lakes Res. 1994, 20, 229-239. (24) Hoff. R. M.; Strachan, W. M. J.; Sweet, C. W.; Chan, C. H.; Shackleton, M.; Bidleman, T. F.; Brice, K. A.; Burniston, D. A.; Cussion, S.; Gatz, D. F.; Harlin, K.; Schroeder, W. H. Atmos. Environ. 1996, 20, 3505-3527. (25) Bruhn, R.; Lakaschus, S.; McLachlan, M. S. Atmos. Environ. 2003, 37, 3445-3454.
Frank Wania Department of Physical and Environmental Sciences University of Toronto at Scarborough 1265 Military Trail Toronto, Ontario, Canada M1C 1A4
Michael S. McLachlan Institute for Baltic Sea Research Seestrasse 15 D-18119 Rostock-Warnemu ¨ nde, Germany
Donald Mackay Canadian Environmental Modeling Centre Trent University Peterborough, Ontario, Canada K9J 7B8
Rene´ P. Schwarzenbach Kai-Uwe Goss* Swiss Institute of Environmental Science and Technology (EAWAG) U ¨ berlandstrasse 133 CH-8600 Du ¨ bendorf, Switzerland
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Swiss Institute of Environmental Science and Technology (EAWAG) U ¨ berlandstrasse 133 CH-8600 Du ¨ bendorf, Switzerland ES030567Q
