Environ. Sci. Technol. 1994, 28, 640-645
Adsorption of Organic Vapors on Polar Mineral Surfaces and on a Bulk Water Surface: Development of an Empirical Predictive Model Kai-Uwe Goss'
Ecological Chemistry and Geochemistry, University of Bayreuth, D-95440 Bayreuth, Germany
A statistical evaluation of adsorption data for organic vapors on polar surfaces was conducted. The result was an empirical predictive model based on several physicochemicalparameters. Good agreement was found between the experimental values used for the development of the model and the corresponding calculated data. Experimental adsorption data that were not used for the regression analysis as well as data from the literature were predicted with the same accuracy. This was also true for the prediction of vapor adsorption on a bulk water surface, which represents an interesting special case. Introduction
Vapor sorption is an important process for the environmental fate of gaseous substances. Earlier work has shown that the adsorption of organic vapors on polar surfaces depends primarily on two environmental parameters: ambient temperature and relative humidity (1-4). A linear adsorption isotherm exists for the low vapor concentrations that prevail in the environment. In this case, adsorption is described by an adsorption coefficient. Because adsorption is proportional to the specific surface area of the sorbent, the adsorption coefficients ( K )can be related to this specific surface area in order to make them comparable for different sorbents [K = (mg of substance/ surface area of sorbent (cm2))/(mgof substance/volume of gas phase (cm3))1. The investigations presented previously revealed that not only the dependence of the adsorption coefficient on the absolute temperature (7'') but also the dependence on relative humidity (RH) followed an exponential relationship (5, 6). This relationship can be described by eq 1. Here the logarithmic form of the exponential function is given because this is more suitable for the following multiple regression analysis: In K = A
+ B/T + CRH
(1)
This general equation was found to be valid for all tested organic vapors and for all tested mineral surfaces [quartz sand, Na-kaolinite, and Ca-kaolinite, and Ca-bentonite (5, 6 ) ] . It is restricted to relative humidities above the one corresponding to an adsorbed monolayer of water on the sorbent (typically between 20 and 30% RH). Small deviations from this equation were also found for the adsorption on clay minerals at a relative humidity of 90 9% (6).
In order to use eq 1 for the prediction of K , the parameters A , B, and C must be known. These parameters are believed to depend on the physicochemical properties of the organic vapors. Using a large number of experimental adsorption coefficients from previous work (5-7), a linear multiple regression analysis (program SPSS,
* Present address: Gray Freshwater Biological Institute, University of Minnesota, P.O. Box 100, Navarre, MN 55392. 640
Environ. Sci. Technoi., Voi. 28, No. 4, 1994
stepwise method) was applied in order to find correlations between A , B and C and physicochemical properties of the compounds. A suitable model may substitute further experiments, especially in those cases where the experimental method is not applicable. Furthermore, a high correlation between the adsorption behavior and certain physicochemical parameters may provide insight in the molecular fundamentals of adsorption and thus contribute to a better understanding of this process. Statistical Procedure
Dependent Variables. The purpose of the statistical regression approach presented here is to predict the variables A , B, and C in eq 1 with the help of physicochemical data from the literature. It is useful, however, to transform eq 1and, thus, the variables before starting the regression analysis. Variable A , which is the y-intercept in a plot of eq 1,represents the value for In K at 0% RH and at 1/T 0. These conditions, however, are far from both experimental and environmental conditions, especially with regard to temperature. For the calculation of In K , this implies extrapolation over a wide range, inevitably leading to large errors in In K even when the errors in B and C are small. The extrapolation error can be minimized, however, if a new parameter, A*, which more closely describes environmental conditions, is incorporated in eq 1. The resulting eq 2 is equivalent to eq 1, but now A* corresponds to the value of In K at 100% RH and 50 OC:
-
In K = A*
+ B ( l / T - 1/323.15) - C(100 - RH)
(2)
A reference value of 100% was chosen for relative humidity because this is an interesting borderline case. At 100% RH, adsorption on the water-covered mineral surface is the same as adsorption on a bulk water surface, as is shown later. The lowest of the experimental temperatures, i.e., 50 "C, was chosen since it is nearest to environmentally relevant temperatures. According to the van't Hoff equation, parameter B can be replaced by the heat of adsorption, AH8, divided by the negative value of the universal gas constant, R: iw, In K = A* - -(l/TR
U323.15) - C(100 - RH) (3)
The units for this equation in its logarithmic form cannot balance because it is not possible to take the logarithm of a dimension. Thus, the units which are used must be defined: m8; kJ mol-l; R , kJ mol-l K-l; T, Kelvin; RH, dimensionless (% ); C, A*, dimensionless, (yielding K in cm). Now the dependent variables that must be predicted from physicochemical parameters are A*, AHs and C. Predictors, A set of nine physicochemical variables describing different substance properties were used for 0013-936X/94/0928-0640$04.50/0
0 1994 American Chemical Society
Table 1. Values of Variables and Predictors
A",
A", (kJ/mol)"
compound
(kJ/mol)
C
A*
benzene toluene m-xylene p-xylene n-hexane n-octane n-nonane chlorobenzene 1,2-dichlorobenzene 1,3-dichlorobenzene 1,3,5-trichlorobenzene 1,2,4-trichlorobenzene 1,2,3-trichlorobenzene naphthalene dichloromethane trichloromethane trichloroethylene tetrachloroethylene l,l,l-trichloroethane 1,2-dichloroethane trans-1,2-dichloroethen cyclohexane ethanol acetone acetonitrile diethyl ether ethyl acetate anisole
-27.7 -32.6 -37.7 -37.9 -23.6 -36.5 -37.8 -32.9 -39.4 -38.5 -42.6 -44.0 -47.0 -46.2 -24.0 -27.0 -26.5 -29.0 -26.1 -31.5 -24.9 -22.3 -48.1 -48.7 -40.6 -46.3 -50.2 -46.0
-0.0268 -0.0266 -0.0299 -0.0314 -0.0179 -0.0289 -0,0325 -0.0305 -0.0333 -0.0313 -0.0311 -0.0355 -0.0378 -0.0390 -0.0229 -0.0243 -0.0223 -0.0242 -0.0262 -0.0344
-10.97 -10.04 -9.26 -9.30 -11.69 -10.18 -9.56 -9.91 -8.78 -9.09 -8.50 -8.08 -7.70 -7.60 -11.64 -11.18 -11.23 -10.88 -11.16 -10.49
-0.0187 -0.0367 -0.0523 -0.0406 -0.0478
-11.82 -7.48 -8.18 -8.45 -9.47
a
lnvp (25OC) p(D) (Pa)
-34.2 -36.0 -41.6 -41.2 -32.0 -38.7 -43.9 -38.1 -46.0 -43.9 -47.1 -48.0 -47.7 -51.7 -31.8 -31.5 -34.9 -38.8 -33.7 -30.6 -30.4 -32.9 -40.6 -32.1 -34.3 -29.2 -34.9 -43.9
9.45d 8.25d 7.00d 7.07d 9.W 7.588 6.44" 7.37d 5.3~5~ 5.72h 4.34' 3.64d 3.96k 4.00" 10.96d 10.13d 9.2@ 7.81' 9.71' 9.33d 10.62d 9.47f 8.81d 10.lgd 9.41" 11.1@ 9.31d 6.02m
(20 "C) (mN/m)
a a*b
0.000 0.40e 0.33f 0.10e 0.03f
0.59 0.55 0.51 0.51 0.00 0.OW 0.01 0.OW 0.00 1.60e 0.71 2.500 0.80 1.72" 0.75 0.001 0.70 1.29 0.75 2.31, 0.80 O.OOe 0.70 1.80e 0.82 l . l O e 0.58 0.801 0.53 0.001 0.28 1.79 0.49 2.37' 0.81 O.OOe 0.44 O.O@ 0.00 1.70e 0.40 2.84 0.71 3.448 0.75 1.W 0.27 1.78' 0.55 1.39 0.73
mRa 26.49 31.14 35.79 35.79 29.94 39.23 43.88 31.31 36.12 36.12 40.94 40.94 40.94 44.03 16.34 21.15 25.32 30.13 25.80 20.98 20.50 27.88 12.88 16.06 11.13 22.29 22.35 32.78
28.W 28.46" 28.900 28.37" 18.43" 21.800 22.700 33.59" 32.13" 39.10d 39.82e 28.001 27.14" 30.03e 33.05O 24.50e 32.301 23.26" 25.500 22.501 24.50e 29.300 17.01" 23.97" 35.77e
Ob
ab
'XC
0.10 0.11 0.12 0.12 0.00 0.00 0.00 0.07 0.03 0.03 0.00 0.00 0.00 0.15 0.10 0.10 0.05 0.05 0.10 0.10 0.05 0.00 0.45 0.48 0.31 0.47 0.45 0.32
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.33 0.04 0.09 0.00 0.00 0.00
3.00 3.39 3.79 3.79 2.91 3.91 4.41 3.39 3.81 3.79 4.18 4.20 4.21 4.97 1.41 1.73 2.27 2.64 2.00 1.91 1.91 3.00 1.41 1.73 1.41 2.41 2.77 3.93
*
Ref 16. Ref 14. c Ref 17. d Ref 15. e Ref 25. f Ref 20. g Ref 19. Ref 18. I Ref 21. J Ref 24. Ref 23. Ref 10. Ref 22.
Table 2. Intercorrelation Matrix of the variables
A* AHC In Vp P T*
mR a
P
a 'X
ilw,
C
A*
A",
lnvp(25OC)
P
a*
mR
a (20 "C)
P
a
'X
LOO0 0.877 -0.959 0.551 0.498 -0.344 -0.293 -0.191 -0.087 -0.492 -0.108 -0.303
0.877 1.OOO -0.777 0.177 0.150 -0.583 -0.352 0.113 -0.012 -0.701 -0.061 -0.001
-0.959 -0.777 1.000 -0.682 -0.627 0.329 0.408 0.240 0.281 0.370 0.138 0.358
0.551 0.177 -0.682 1.OOO 0.966 0.215 -0.236 -0.772 -0.576 0.350 0.176 -0.801
0.498 0.150 -0.627 0.966 1.000 0.197 -0.277 -0.829 -0.662 0.466 0.324 -0.847
-0,344 -0,583 0.329 0.215 0.197 1.000 0.572 -0.546 -0.004 0.508 0.264 -0.506
-0.293 -0.352 0.408 -0.236 -0.277 0.572 1.000 -0.121 0.653 0.104 0.074 -0.073
-0.191 0.113 0.240 -0.772 -0.829 -0.546 -0.121 1.000 0.322 -0.664 -0.605 0.972
-0.087 -0.012 0.281 -0.576 -0.662 -0.004 0.653 0.322 1.000 -0.323 -0.198 0.348
-0.492 -0.701 0.370 0.350 0.466 0.508 0.104 -0.664 -0.323 1.00 0.481 -0.553
-0.108 -0.061 0.138 0.176 0.324 0.264 0.074 -0.605 -0.198 0.481 1.000 -0.587
-0.303 -0.001 0.358 -0.801 -0.847 -0.506 -0.073 0.972 0.348 -0.553 -0.587 1.000
the multiple regression analysis. The following variables were finally chosen for the prediction of A*, AHs, and C: (1)Logarithm of the vapor pressure (In vp) at 25 "C. For solid compounds, the vapor pressure of the subcooled liquid must be used. Earlier works (8,9)showed that the logarithm of the adsorption coefficient of a substance is linearily correlated with the logarithm of its vapor pressure. (2) The molar refraction (mR). The molar refraction is a measure of the polarizability of a compound (10). A correlation between mR and the heat of adsorption (10, 111, and also between mR and the adsorption coefficient (12),was described by several authors. (3) The hydrogen bond acceptor (0).It is a measure of the ability of a substance to form hydrogen bonds (13,14). The strong adsorption observed for polar compounds had been attributed to the formation of hydrogen bonds (5,6). (4) The dipole momentum (p). The dipole momentum is used to describe dipole-dipole interactions (10, 12). The other variables that were not found particularly useful in the regression analysis are as follows: the surface tension (cr), the heat of condensation (AHc),the first-order
molecular connectivity index (lx), the hydrogen bond and the dipolarity (T*). In Table 1,the literature donor (a), values of all variables are listed for all used compounds. The intercorrelation matrix of these variables can be seen in Table 2. Experimental Data Used for Regression Analysis. The experimental data used for the multiple regression analysis has been published earlier (5-7). In this earlier work, the heat of adsorption, AHs, of each particular substance had not shown a dependence on relative humidity and was not significantly different for different sorbents (quartz sand, different clay minerals, fresh ice). Thus, the valuesfor AHs,listed in the first column of Table 1 and used for the regression analysis, are averages of all these measurements (standard deviation 110% 1. Only the heats of adsorption for the polar substances obtained on aged ice were omitted because these were significantly lower than the corresponding values on the other adsorbents (7). The data for the parameter C (second column in Table 1)were taken from the experiments with quartz sand and Environ. Scl. Technol., Vol. 28, No. 4, 1994
641
Ca-kaolinite. The corresponding values for Ca-bentonite were significantly different, probably due to the influence of the electrical double layer of the expandable clay mineral, For A*, the values of In K obtained on quartz sand and Ca-kaolinite at 50 OC extrapolated to 100% RH were used. A comparison of the adsorption coefficients of those substances for which measurements on both adsorbents (i.e., quartz sand and Ca-kaolinite) had been carried out revealed that the results for quartz sand were about 25 % lower than the ones for Ca-kaolinite (6). This had been attributed to uncertainties associated with the determination of the surface area of the sand in the original paper (6). In the meantime, a more precise determination carried out with an automatic analyzer (Gemini 2370, Fa. Micromeritics) gave a specific surface area of 0.26 m2/g for the quartz sand instead of the previous value of 0.34 m2/g. For the calculation of A*, the results on quartz sand were recalculated with the new value of the specific surface area. Two of the tested substances were not included in the regression analysis. For methanol, absorption (Le., dissolution in the water film) was observed in addition to adsorption. The measured K values, therefore, were the result of the combination of two different processes and could not be compared with pure adsorption coefficients (5). 2,3-Benzofuran was also excluded, as sufficient literature data on the physicochemical properties used as predictors could not be found. Results and Discussion
For all three parameters, A*, AHs, and C, a linear correlation was found that explained at least 91 % of the variance with the help of two or three physicochemical parameters. Regression for the Heats of Adsorption. A good correlation was found between the heat of adsorption, A",, and two predictors: the heat of condensation, AHc, and the hydrogen-bond acceptor, 6. This result strongly supports earlier considerations: the forces governing adsorption consist of an unspecific component, which can be described by the heat of condensation, and, in the case that the molecule can provide electrons for a hydrogen bond, of a specific component accounted for by 6. However, it is often difficult to find literature data of AHc for environmentally relevant compounds. Additionally, considerable discrepancies were observed among these values given for a particular substance and temperature in different literature sources (e.g., refs 16 and 20). The high cross-correlation (0.97) between the logarithm of a substance's vapor pressure and its heat of condensation suggested that AH, could be replaced by In vp in the regression analysis. The resulting equation (eq 4) explains 91% of the variance with a relative standard error of 7.1 % between calculated and measured values (maximum deviation: 16% ): AHa= 3.20 In vp - 50.26 - 55.0
(4)
Regression for Dependence on Relative Humidity. In order to satisfactorily explain the variance of the dependence of adsorption on relative humidity (parameter C),three variables were necessary:
C = -0.0546 - 0.00070mR - 0.0041~+ 0.00061 (5) 642
Enrlron. Sci. Technol., Vol. 28, No. 4, 1994
+
t
U
m
i
a
c
ooflo.
f OflCC3! :c3c01
c3:01
coo:
301
01
nezsu-ec Y I c m ) Figure 1. Measuredadsorptloncoefficients of 30 compounds at different temperatures and relative humidities plotted against the corresponding predicted values for quartz sand and Ca- and Na-kaolinite.
The variables hydrogen-bond acceptor, molar refraction, and dipole momentum account for 91 % of the variance in C. All three parameters are related to the polarity of a substance and, therefore, show a certain degree of interdependence (tolerance = 0.53 for 6,0.50 for mR, and 0.66 for p). The relative standard error for C obtained from eq 5 is 10.8% from the experimental values (maximum deviation: 16%9. Regression for Constant A*. The constant A* was best predicted by the parameters In vp and 6. The corresponding regression equation (eq 6) explains 95 5% of the variance of A*: A* = -0.615 In vp + 7.866 - 5.80
(6)
The interdependence of these variables was low (tolerance = 0.78). The standard error in the calculated values for A* is 3.3% (maximum deviation: 8%). It should be noted again that for solid substances the vapor pressure of the subcooled liquid must be used. Mackay et al. (26) developed an empirical relationship for calculating these data from the vapor pressure of the solid and the melting point. Using the predicted values for A*, AHa,and C (eqs 4-61, Know can be calculated from eq 3. According to the error propagation law, the standard error in the predicted adsorption coefficient resulting from the combined error in A*, AHs, and C is 36 % . Comparison between Experimental and Predicted Adsorption Coefficients. The variance in the adsorption coefficients used for the statistical procedure is wellexplained by the empirical model (Figure 1). For 64% of the 586 data, the deviation between calculated and measured values is less than 30 % , For 87 % of the data, deviation is smaller than 50%. Taking into account that, for the measurements, several parameters (substances, adsorbents, temperature, relative humidity) were varied over a wide range and that the adsorption coefficients also varied over several orders of magnitude, this is a satisfying result.
Table 3. Comparison of Calculated and Measured Adsorption Coefficients K on Quartz Sand for Compounds Not Used for Regression Analysis
Table 5. Comparison of Measured (Ref 28) and Calculated Adsorption Coefficients K for Adsorption on Bulk Water Surface at 12.5 "C
K x 104 (cm)
K x 103 (cm) compound
measd
calcd
nitrobenzene 90 "C,50% RH 80 "C,50% RH 70 O C , 70% RH n-tridecane 80 "C. 70% RH
3.43 2.14 3.78
4.50 2.60 4.63
1.28
0.80
Table 4. Comparison of Measured (Ref 27) and Calculated Adsorption Coefficients K for Adsorption on Silica at 15 OC and Different Relative Humidities
K x 106 (cm) 25.7% RH
K X 106 (cm) 62.3% RH
K x 106 (cm) 88.0% RH
substance
measd
calcd
measd
calcd
measd
calcd
n-pentane n-hexane n-heptane n-octane n-nonane n-decane
3.06 8.82 25.5 70.5 200 568
2.73 8.86 27.4 84.7 248 847
1.56 4.06 10.4 26.8 67.9 173
1.47 4.29 11.7 31.7 83.7 251
0.85 2.02 4.76
0.95 2.58 6.40 15.9 39.0 107
11.2
26.7 62.4
A more demanding test of the model is to apply it to compounds that were not used in developing the correlations. A comparison of adsorption coefficients obtained on quartz sand for nitrobenzene and tridecane with the corresponding calculated values is found in Table 3. Comparison with Literature Data. A further test for the model is to compare predicted adsorption coefficients with data from the literature measured under different conditions. Unfortunately, many of these data cannot be used for comparison because either the adsorption coefficients are not normalized with respect to the specificsurface area of the adsorbent, the water content of the adsorbent is given instead of the relative humidity, or the measurements are outside the linear region of the adsorption isotherm. Dorris and Gray (27) determined adsorption coefficients for six alkanes on silica gel at 15 "C and three different relative humidities. Since silica is a silicatic material just like quartz sand and clay minerals, a comparison with the results of the present work should be possible. The data are presented in Table 4. The differences between measured and calculated values are, on the whole, below 50% and only in two cases do they slightly exceed this level. Thus, the model also performs well with independent data from the literature. Adsorption on a Bulk Water Surface. In a previous paper (61,it was suggested that the adsorption on sand and kaolinite extrapolated to 100% RH is equivalent to the adsorption on a bulk water surface. Under these conditions, the model becomes simpler because the parameter C is no longer needed and the prediction only requires the variables In vp and 0. The adsorption on a bulk water surface has been investigated for a large number of substances by Hartkopf und Karger (28) and more recently by Hoff et al. (29). Their results are listed in Tables 5 and 6 and compared to the corresponding predictions obtained from the model. All compounds except tetrachloromethane show a good or even excellent agreement. Thus, the predictive model appears to be very well-suited for predicting adsorption on a bulk water surface. Hoff et al. give a good overview of the environ-
compound
measd calcd
n-pentane 0.09 0.083 0.2 0.22 n-hexane n-heptane 0.4 0.53 1.0 1.29 n-octane 2.3 3.10 n-nonane n-decane 5.3 8.28 1.00 2-methylheptane 0.9 0.7 0.74 2,4-dimethylhexane 2,2,4-trimethyl0.6 0.51 pentane cycloheptane 0.5 0.95 n-propyl ether 36.3 44.4
KX compound
lo4
(cm)
measd calcd
dichloromethane trichloromethane tetrachloromethane l,2-dichloroethane benzene toluene ethylbenzene fluorobenzene chlorobenzene methyl formate
0.4 0.7 0.3
0.27 0.51 0.74
1.7
0.93
0.9 2.5 5.8 1.1 2.6 4.7
0.85 2.37 6.30 0.74 3.12 3.81
Table 6. Comparison of Measured (Ref 29) and Calculated Adsorption Coefficients K for Adsorption on Bulk Water Surface at 25 "C compound n-pentane n-hexane n-heptane n-decane cyclohexane benzene toluene ethyl benzene chlorobenzene 1,3-dichlorobenzene dichloromethane
K X lo4 (cm) measd calcd 0.052 0.109 0.233 2.26 0.107 0.443 1.12 2.35 1.23 2.72
K X l(r (cm) compound
measd
calcd
0.059 0.146 0.331 4.20 0.193 0.504 1.30 3.21 1.68 3.75
trichloromethane 0.347 0.310 tetrachloro0.149 0.446 methane l,l,l-trichloro0.292 0.418 ethane trichloroethene 0.264 0.375 1,2-dichloro0.691 0.548 ethane ethyl ether 5.32 4.80 methyl formate 1.93 1.94 ethyl acetate 27.5 15.1 0.186 0.170 acetone 18.3 10.7
mental implications of vapor adsorption on the air-water interface (29). Applicability of the Model. On the basis of the experimental data used for the development of the model and other adsorption data from the literature discussed above, the following conclusions for the applicability of the model can be drawn: The good agreement between measured adsorption coefficients from the literature and calculated values indicates that the model is probably applicable for all organic compounds. With respect to the temperature, there is also no restriction of the applicability. The adsorption data for different relative humidities had shown that no exponential relationship exists between K and RH when the sorbent is not covered by at least one monolayer of water. On mineral sorbents, this monolayer is typically completed at a relative humidity between 20 and 30%. Therefore, the model should only be applied for relative humidities above 30%. It has been shown that the model is still valid at 100% RH and that this interesting special case corresponds to the adsorption on a bulk water surface. At relative humidities above 100% RH condensation of water occurs, leading to an unlimited increase in the water film. In this case, adsorption on the water film is equivalent to that on a bulk water surface. However, absorption in the water film becomes more and more important with increasing thickness of the water layer and must be considered for the overall sorption process. Unfortunately, there are some restrictions and uncertainties concerning the kind of sorbent for which the model Envlron. Scl. Technol., Vol. 28,
No. 4, 1994 648
may be applied. First of all, the model cannot be used for nonpolar sorbents that are not covered by an adsorbed water film under environmental conditions. The model can be applied for quartz sand, silica, kaolinite, and a bulk water surface. The applicability for ice and snow remains unclear until there are exact, experimental, surface area related adsorption coefficients for a comparison. For bentonite, only the heat of adsorption can be predicted while the dependence on relative humidity (parameter C) and thus K cannot be calculated with the model presented here. This difference between bentonite and the other polar sorbents has been attributed to the electrical double layer of bentonite. Experimental data for the vapor adsorption on other mineral surfaces which allow comparison with the presented model have not yet been found. Additional work must be done to clarify and expand the applicability of the model with respect to the kind of sorbent. Comparison of the Developed Predictive Model with Approaches from Literature. For the adsorption of gaseous substances on atmospheric particles, the equation of Yamasaki (30) or, equivalently, the equation of Junge (31) is used to calculate K: log K = b 4- m/T where T is the absolute temperature, b is a parameter dependent on the specific surface area of the adsorbent and on the vapor pressure of the substance, and m is a parameter associated with the heat of condensation of the substance (9, 32). This equation is used to predict the gaslparticle partitioning of organic compounds (33). Comparing this model with the results of the present work and the results published earlier, it is clear that the former is not able to explain adsorption processes on polar adsorbents, because neither the influence of the relative humidity nor the possibility of hydrogen bonding are accounted for. Nevertheless, the equation of Junge or Yamasaki seems to be useful for the description of gaseous adsorption on aerosols (34). The reason for this probably lies in the fact that the particles investigated were essentially of urban origin, with the hydrophobic soot fraction prevailing. In this case, no water film is expected to cover the surface of the particles. Thus, neither relative humidity nor hydrogen bonding will exhibit any influence on the adsorption. Cotham and Bidleman (35)found that relative humidity was of no importance for the adsorption on aerosols and attributed their observation to the high content of organic material in the urban particulate matter they investigated. This finding is further corroborated by the heats of adsorption measured for the gadparticle distribution: for the nonpolar substances they were higher than the corresponding heats of condensation (35),a result that was also found for the adsorption on graphite (36, 11). Storey and Pankow (37)also found a good agreement between the adsorption on graphite and on urban particles. On the other hand, nonpolar organics adsorbed on polar surfaces exhibit heats of adsorption that are lower than the corresponding heats of condensation (5, 6 , 1 2 , 27). Thoms and Lion (13)made use of a multiple regression analysis in order to describe the gaseous adsorption of organic substances on aluminum oxide. However, they did not discriminate between the separate influences of temperature and relative humidity, using K as the dependent variable instead, In agreement with the regression analysis presented here, they also found the 644
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hydrogen bond acceptor to be of considerable importance. On the whole, however, their regression did not lead to a useful prediction model. Valsaraj and co-workers (38,39)proposed amodel, based on the octanollwater partition coefficient, for the prediction of the adsorption of hydrophobic compounds on a bulk water surface. However, this model fails for the more polar molecules. Hoff et al. recently published a model for the adsorption on a bulk water surface that is based mainly on surface tension data and gives good results also for polar compounds (29). Unfortunately, it is not always possible to find the required surface tension data in the literature. Thus, the model has not yet been tested for a large variety of compounds, and it is not clear whether it can be applied for different temperatures. An extensive comparison between the model of Hoff et al. and that presented here with respect to the different theoretical approach, the applicability, and the quality of the results will be interesting. Acknowledgments
I thank M. Hinkel and M. S. McLachlan for critical revision of the manuscript and the referees for helpful comments. This work was supported by the Deutsche Forschungsgemeinschaft. Literature Cited (1) Valsaraj, K. T.; Thibodeaux, L. J. J.Hazard. Mater. 1988, 19,79-99. (2) Spencer, W. F.; Cliath, M. M.; Jury, W. A.; Zhang, L A . J. Environ. Qual. 1988,17, 504-509. (3) Pennell, K. D.; Rhue, R. D.; Rao, P. S. C.; Johnston, C. T. Environ. Sei. Technol. 1992, 26, 756-763. (4) Ong, S. K.; Lion, L. W. Water Res. 1991,25, 29-36. (5) GOSS, K.-U. Environ. Sei. Technol. 1992, 26, 2287-2294. (6) GOSS, K.-U. Environ. Sei. Technol. 1993, 27, 2127-2132. (7) Goss, K.-U. Environ. Sei. Technol. 1993, 27, 2826-2830. (8) Martin, R. L. Anal. Chem. 1961,33, 347-352. (9) Pankow, J. F. Atmos. Environ. 1987,21, 2275-2283. (10) Okamura, J. P.; Sawyer, D. T. Anal. Chem. 1971,43,17301733. (11) Ludwig, S.; Schmidt, H.-D. J. Chromatogr. 1990,520,6974. (12) Okamura, J. P.;Sawyer, D.T.Ana1. Chem. 1973,45,80-84. (13) Thomas, S. R.; Lion, L. W. Environ. Toxicol. Chem. 1992, 11, 1377-1388. (14) Kamlet, M. J.; Doherty, R. M.; Abraham, M. H.; Marcus, Y.; Taft, R. W. J. Phys. Chem. 1988,92,5244-5255. (15) Rippen, G. Handbuch Umweltchemikalien;Ecomed Landsberg, 1991. (16) Weast, R. C.; Lide, D. R.; Astle, M. J.; Beyer, W. H., Eds. CRC Handbook of Chemistryand Physics;CRC Press: Boca Raton, FL, 1989. (17) Sabbljic, A. Environ. Sci. Technol. 1987,21, 358-366. (18) Water-Related Environmental Fate of 129 Priority Pollutants Vol. ZI; U S . Environmental Protection Agency: Washington, DC, 1979; EPA-44014-79-029b. (19) Sicherheit im Labor: Losungsmittel; Merck: Darmstadt, 1988. (20) Smith, B. D.; Srivastava, R. Thermodynamic data for pure compounds; Elsevier: Amsterdam, 1986. (21) Howard, P. H., Ed. Handbook of Environmental Exposure Data; Lewis: Chelsea, MI, 1990; Vol. I. (22) Verschueren, K., Ed. Handbook for Environmental Data on Organic Chemicals,2nd ed.; Van Nostrand New York, 1983;p 870. (23) D'Ans Lax. Taschenbuch fur Chemiker und Physiker; Springer: Berlin, 1967.
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Received for review June 15, 1993. Revised manuscript received November 24, 1993. Accepted January 4, 1994." e Abstract published in Advance ACSAbstracts,February 1,1994.
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