Environ. Sci. Technol. 1999, 33, 2926-2933
Correlation of Aqueous-Phase Adsorption Isotherms J O H N C . C R I T T E N D E N , * ,† SOMPOP SANONGRAJ,† JOHN L. BULLOCH,† DAVID W. HAND,† TONY N. ROGERS,‡ THOMAS F. SPETH,§ AND MARKUS ULMER| Department of Civil and Environmental Engineering and Department of Chemical Engineering, Michigan Technological University, Houghton, Michigan 49931, Water Supply & Water Resources Division, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, and DVGW-Technologiezentrum Wasser, Heinrich-Sontheimer-Laboratorium, Karlsruher Strasse 84, D-76139 Karlsruhe, Germany
A correlation was developed to estimate the adsorption equilibrium capacity of various adsorbents and organic compounds using a combination of Polanyi potential theory and linear solvation energy relationships (LSERs). Polanyi theory provided the basic mathematical form for the correlation. LSERs were used to normalize the Polanyi theory based on the fundamental interaction forces between the solvent, adsorbate, and adsorbent expected in aqueousphase adsorption. The correlation was developed using 56 organic compounds and eight adsorbents. The following classes of organic compounds were used: (i) halogenated aliphatics, (ii) aromatics and halogenated aromatics, (iii) polyfunctional organic compounds and (iv) sulfonated aromatics. The adsorbents were (i) three coal-based activated carbons (F-300, F-400, and APA), (ii) one coconut shell based activated carbon (580-26), (iii) one unspecified activated carbon, and (iv) three synthetic polymeric adsorbents (XAD-4, XAD-7, and XEN-563). The proposed correlation, which considers the fundamental solventadsorbate-adsorbent interaction forces, showed a significant improvement in predicting the adsorption capacity over a correlation that considered only van der Waals forces. However, the correlations did not predict the adsorption capacities of highly soluble organic compounds such as polysulfonated aromatics and polyfunctional organic compounds.
Introduction Adsorption is one of the most extensively used technologies to remove organic contaminants from aqueous streams in water treatment (1). For preliminary design, the adsorption equilibrium capacity of an adsorbent has to be estimated. Unfortunately, there are relatively few experimental adsorption equilibrium isotherms available for the approximately * To whom correspondence should be addressed. Fax: (906) 4873010; phone: (906) 487-2798; secretary: (906) 487-2520; e-mail:
[email protected]. † Department of Civil and Environmental Engineering. ‡ Michigan Technological University. § U.S. Environmental Protection Agency. | DVGW-Technologiezentrum Wasser. 2926
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70 000 organic compounds currently in use (2). In addition, cost, time, and toxicity may prevent the development of experimental adsorption equilibrium isotherms. Consequently, a correlation capable of predicting adsorption equilibrium capacities from commonly available physical properties would be very useful. Table 1 displays some of the correlations that have been proposed. Most correlations are based either on Polanyi adsorption potential theory (3-12) or linear solvation energy relationships (LSERs) (13, 14). Previous researchers using the Polanyi theory approaches have focused on finding the most appropriate normalizing factor (5-12). Polanyi potential theory (15) assumes that there is a fixed space (adsorption space) surrounding the adsorbent surface where adsorption occurs. The net attractive forces involving the solute, solvent, and the adsorbent are assumed to be responsible for adsorption. Among these forces, van der Waals force is normally the dominant force for gases or vapors adsorbing onto a hydrophobic adsorbent (16). van der Waals forces may also be significant for adsorption from the aqueous phase. However, a correlation considering only van der Waals forces may not be applicable in cases where dipole-dipole, induced-dipole, and hydrogen-bonding donor-acceptor interactions exist, such as in aqueous solution (3-12). These forces can be important for molecules with certain functional groups. Hence, a correlation combining Polanyi potential theory with LSERs to consider the solvation effects may provide an improvement in predicting adsorption equilibrium capacities. LSERs are generalized treatments of solvation effects including nonspecific dipolarity/polarizability, hydrogen bonding, and the free energy of solute partitioning into solvent cavities (17, 18). In general, the LSER parameters include the intrinsic molar volume (Vi), the polarity/polarizability parameter (π*), the hydrogen-bonding acceptor parameter (β), and the hydrogen-bonding donor parameter (R) (14). Some attempts to utilize only LSERs to predict adsorption capacity have correlated the LSER parameters with the infinite-dilution partition coefficient between the adsorbed phase and solute (13, 14). Unfortunately, the correlation cannot describe the nonlinear isotherms that are typically observed for adsorption from aqueous solution. The Polanyi theory (15) can describe the nonlinear isotherm behavior of each compound studied because it assumes heterogeneity of adsorption energies and multiplelayer adsorption. To simultaneously correlate adsorption isotherms of several different compounds on an adsorbent, a normalizing factor representing the fundamental adsorption interaction forces must be included with the Polanyi based model. Hence, aqueous-phase adsorption correlations based on Polanyi potential theory using LSERs as a normalizing factor were proposed. The correlations were developed using single solute adsorption isotherms from several sources (11, 12, 19-22). Results of the correlations are capable of accurately predicting the adsorption capacities in aqueous solution for some chemical classes.
Theory and Approach Polanyi (15) defines the adsorption potential () as the work or free-energy change required to move a molecule from the bulk solution to the adsorption space. The adsorbed phase is assumed to be a pure phase of the adsorbate. The freeenergy change or adsorption potential varies with solution concentration according to this equation (15) 10.1021/es981082i CCC: $18.00
1999 American Chemical Society Published on Web 07/28/1999
TABLE 1. Adsorption Isotherm Models for Predicting the Adsorption of Organic Compounds onto Specific Adsorbents author
model
limitation
Dubinin (3) McGuire and Suffet (36) and Arbuckle (4)
Polanyi-Dubinin Net Adsorption Energy
based on only van der Waals forces applicable to dilute solutions less accurate in predicting the volume adsorbed at high concentrations (>1 mM/L) could not predict adsorption capacity for both linear and branched alcohols
Hansen and Fackler (5)
Hansen-Fackler modification of the Polanyi theory
the modifications are deemed appropriate only for very soluble compounds such as propanol and butanol
Manes (6), Polanyi-based model (using molar based on only van der Waals forces Manes and Hofer (7, 8), volume and a single abscissa less accurate in predicting volume adsorption Wohleber and Manes (9, 10), scale factor as a normalizing factor) capacity at high solution equilibrium and Arbuckle (4) concentration (>1 mM/L) could not predict adsorption capacity for both linear and branched alcohols Urano et al. (37)
Urano’s modified Freundlich model
does not predict adsorption capacities for monoand disubstituted benzenes
Belfort et al. (38) and Arbuckle (4)
Solvophobic model
applicable to dilute solutions and small molecular weight compounds needs additional correlations to estimate model parameters
Speth (11)
Polanyi-based model (using molar volume as a normalizing factor)
based on only van der Waals forces
Kuennen et al. (12)
Polanyi-based model (using molar volume as a normalizing factor)
based on only van der Waals forces correlation fails to describe all the chemicals of different classes
Kamlet et al. (13)
LSER model
assumes isotherms are linear at low concentrations; cannot describe the nonlinear isotherms that are typically observed for adsorption from aqueous solution
Blum et al. (39)
molecular connectivity model
assumes isotherms are linear at low concentrations; cannot describe the nonlinear isotherms that are typically observed for adsorption from aqueous solution the model does not provide a phenomenological understanding because the model parameters do not reflect specific physical properties
Luehrs et al. (14)
LSER model
assumes isotherms are linear at low concentrations; cannot describe the nonlinear isotherms that are typically observed for adsorption from aqueous solution the system for estimating the LSER parameters is not designed for organic salts
) RT ln
() Cs C
(1)
in which R is the ideal gas constant, T is the absolute temperature, Cs is the aqueous solubility of the solute, and C is the bulk liquid-phase equilibrium concentration. The free-energy change varies from a maximum value when the adsorbed volume is very low to zero when the solute concentration reaches its solubility limit and the adsorbed volume reaches a maximum. The volume of solute adsorbed (W) was related to the adsorption potential by means of the Polanyi-Dubinin adsorption model (3):
[ (N ) ]
W ) W0 exp -a
b
(2)
in which W0 is the maximum volume adsorbed, a and b are empirical constants, and N is a normalizing factor. W for a given solute was estimated by dividing the solidphase concentration (q) with the density (F) of the pure
compound at the experimental temperature (23). W0, a, and b are constants that are related only to the nature of adsorbent (3). The normalizing factor (N) was used to collapse the adsorption isotherms of different organic compounds on a given adsorbent into a single relation. Normalizing factors suggested by previous researchers include molar volume, polarizability, and parachor (3, 11, 12), which account for only van der Waals interaction forces. However, in aqueous solution, both van der Waals forces and hydrophobic interactions can be important depending upon the adsorbate. Theoretically, a good normalizing factor should adequately represent all of the interaction forces responsible for adsorption. The overall adsorption energy may consist of five components:
ET ) Eos - Ews + Eoo - Eww - Ewo
(3)
in which ET is the overall adsorption energy, Eos is the interaction energy between organic adsorbate and adsorbent, Ews is the interaction energy between water and adsorbent, Eoo is the interaction energy between adsorbed organic adsorbate molecules, Ewo is the interaction energy between VOL. 33, NO. 17, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 2. Single Solute Adsorption Isotherm Data Sources references Speth (11)
Arora (19)
Bulloch (20)
Speth and Miltner (21)
experimental method
bottle point method (powdered activated carbon)
bottle point method (powdered activated carbon)
bottle point method (powdered and granular adsorbents)
no. of organic compounds class of organic compoundsb
7
5
8
Alipha-X, Ar
Alipha-X
Alipha-X, Ar, Ar-X
3-4 weeks 7.5-8.0 13.8 coal base activated carbon (F-400)
3 weeks 6.8 13 coal base activated carbon (F-400)
equilibrium time pH temp (°C) adsorbent type
particle size
1-3 weeks 4.2-10.3a 21-23 coal base activated carbon (APA), coconut shell base activated carbon (580-26), polymeric adsorbents (XAD-4, XAD-7, XEN-563) 200-400 mesh 200-400 mesh 200-400 mesh for the activated carbon and granular as received adsorbent for the synthetic adsorbents
Kuennen et al. (12)
Ulmer (22)
bottle point (powdered activated carbon) and a 100 gallon vessel with circulating water and GAC 45
bottle point method (powdered activated carbon)
bottle point method (powdered activated carbon)
18
11
Alipha-X, Ar, Ar-X, Poly-FG
Alipha-X, Ar, Ar-X, Poly-FG, Phenols 1 week 8.5 20-21 activated carbon
Ar, Ar-Sul
3 weeks 24 coal base activated carbon (F-400)
100-200 mesh and passed through as received granular a 200 mesh activated carbon
several days 7.0 20 coal base activated carbon (F-300)
powdered activated carbon
a This pH range covers for all organic compounds and adsorbents. b Alipha-X ) halogenated aliphatic organic compounds. Ar, Ar-X, Ar-Sul ) aromatic, halogenated aromatic, and sulfonated aromatic organic compounds. Poly-FG ) polyfunctional organic compounds.
organic and water molecules, and Eww is the interaction energy between water molecules. In eq 3, the Eos and Ews terms are functions of polarizability and dipole moment of the adsorbate and water molecules, respectively. The terms Eoo, Eww, and Ewo can be related to the solubility of the organic adsorbate and the octanol-water partition coefficient (24). The five interaction energy terms can be represented with LSER parameters including the intrinsic molar volume (Vi), the polarity/polarizability parameter (π*), the hydrogen-bonding acceptor parameter (β), and the hydrogen-bonding donor parameter (R) (13, 14, 18). A correlation based on the Polanyi-Dubinin model (3) using LSER parameters as a normalizing factor is given by the following:
)] [ (100N
W ) W0 exp -
b
(4)
Vi N ) k1 + k2π* + k3β + k4R + k5 100
(5)
in which b, k1, k2, k3, k4, and k5 are empirical constants, and the 100 appearing in eq 4 is a scaling factor. Typically, the Vi term is divided by 100 to obtain a magnitude on the same order as the other three parameters (π*, β, R) (25) as shown in eq 5. Equations 4 and 5 have seven adjustable parameters (W0, b, k1, k2, k3, k4, and k5) that were determined from nonlinear regression using the Simplex method (26). The best-fit parameters were determined by minimizing the percent sample deviation. The percent sample deviation based on the relative error between experimental data and the correlation was calculated using
% sample deviation (SDEV) ) Wcorrelation - Wdata Wdata Ndata - 1
[x ( ∑
)
]
2
× 100 (6)
in which Wcorrelation and Wdata are the volume adsorbed per 2928
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gram determined from the correlation and the experimental data for various aqueous-phase concentrations, respectively, and Ndata is the number of data.
Data Sources for the Adsorption Isotherm Data and Physical/Chemical Parameters Single solute adsorption isotherm data from Speth (11), Arora (19), Bulloch (20), Kuennen et al. (12), Speth and Miltner (21), and Ulmer (22) were used to develop the correlations. Table 2 summarizes the main characteristics of these data sources. The physical/chemical properties including molecular weight (MW), solubility (Cs), density (F), molar volume (Vm) and the LSER parameters of the organic compounds used to develop the correlations were collected from several data sources (properties taken from refs 22 and 27-31 are listed in Supporting Information). The values of MW, Cs, F, and Vm at the experimental temperature were obtained from the Software to Estimate Physical Properties (StEPP) (27). StEPP is designed to predict physical and chemical properties over a wide range of temperature from a database of over 1800 organic compounds using various parameter estimation techniques (27). The values of MW, Cs, F, and Vm from the StEPP are close to reported experimental values (28-31). Some of the Cs and F values (e.g., for organics with polyfunctional groups) were either measured (22) or obtained from organic compound handbooks (28-31). The LSER parameters were calculated according to the procedure developed by Hickey and Passino-Reader (25).
Result and Discussion As a first attempt, all organic compounds were correlated together for each adsorbent. However, a good correlation could not be developed. Subsequently, the correlations were developed for different classes of compounds for each adsorbent. Basically, the organic compounds were divided into these classes: (i) halogenated aliphatics, (ii) aromatics and halogenated aromatics, (iii) sulfonated aromatics, and (iv) polyfunctional organic compounds.
TABLE 3. Results of the Regression Analysis for Eight Adsorbents data source adsorbent name type of adsorbent type of compounda no. of compounds data points concentration range temp (°C) W0 (mL/g) b k1 of Vi k2 of π* k3 of β k4 of R k5 % SDEV for Polanyi-LSER % SDEV for Polanyi-Vm data source adsorbent name type of adsorbent type of compounda no. of compound data point concentration range temp (°C) W0 (mL/g) b k1 of Vi k2 of π* k3 of β k4 of R k5 % SDEV for Polanyi-LSER % SDEV for Polanyi-Vm
ref 22 F-300 activated carbon Ar, Ar-Sul 11 84 10-7-10-1 Cs 20 0.39 1.17 40.17 0.48 -1.23 -2.59 0.64 17b
refs 11, 19, 21 F-400 activated carbon
ref 20 580-26 activated carbon
alipha-X 20 380 10-7-10-1 Cs 13 and 24 0.56 1.22 20.20 1.79 -12.77 -0.67 5.90 23
Ar, Ar-X 12 133 10-6-10-2 Cs 13 and 24 0.54 1.21 25.00 5.88 -1.89 -0.02 4.57 22
poly-FG 12 141 10-7-10-1 Cs 24 0.42 1.05 41.90 34.10 -3.19 -8.17 -55.14 23c
alipha-X 4 38 10-7-10-2 Cs 21-24 0.61 1.30 99.64 41.34 -24.82 -1.33 -51.12 16
Ar, Ar-X 4 37 10-5-10-1 Cs 21-24 0.69 1.61 30.06 11.97 -10.49 -6.33 -0.96 24
alipha-X 4 42 10-7-10-2 Cs 21-24 0.59 1.21 30.96 5.71 -7.70 -8.00 -1.18 21
Ar,Ar-X 4 42 10-7-10-1 Cs 21-24 0.62 1.28 13.44 13.74 -11.57 -7.37 6.26 28
24b
48
23
68c
44
44
33
44
ref 20 XAD-4 synthetic resin alipha-X Ar, Ar-X 4 4 41 31 10-7-10-1 10-5-10-1 Cs Cs 21-24 21-24 0.31 0.27 1.53 1.66 55.19 25.71 25.60 15.25 -26.15 -26.83 -1.36 -2.23 -20.06 2.58 12 24
ref 20 XAD-7 synthetic resin Ar, Ar-X 4 37 10-5-10-2 Cs 21-24 0.17 1.35 7.13 9.41 -6.6 -4.15 4.56 21
ref 20 XEN-563 synthetic resin Ar, Ar-X 4 32 10-6-10-2 Cs 21-24 0.24 1.71 18.33 30.61 -15.98 -9.97 10.68 19
57
55
36
53
ref 20 APA activated carbon
alipha-X 9 54 10-6-10-3 Cs 20-21 0.61 1.06 22.07 4.02 -9.95 -0.99 1.01 26
ref 12 unspecified activated carbon Ar, Ar-X poly-FG 4 3 24 18 10-7-10-4 10-6-10-3 Cs Cs 20-23 20-21 0.59 0.62 1.13 1.06 12.8 15.06 9.08 21.99 -0.69 -4.56 -1.18 -9.97 7.19 -6.23 24 12
phenols 2 10 10-7-10-4 Cs 20 0.59 1.17 59.36 57.70 -74.25 -22.75 -20.52 16
45
40
42
20
a Ar, Ar-Sul ) Aromatic and sulfonated aromatic organic compounds. Alipha-X ) halogenated aliphatic organic compounds. Ar, Ar-X ) Aromatic and halogenated aromatic organic compounds. Poly-FG ) Poly-functional organic compounds. b This sample deviation value was obtained from optimization analysis without including di- and trisulfonate compounds, which have high solubilities. c This sample deviation value was obtained from optimization analysis without including high-solubility compounds such as oxamyl.
Table 3 lists the regression analysis results for eight adsorbents and the corresponding percent sample deviations. It appears that the maximum volume adsorbed per gram (W0) (which may represent the total pore volume) and the exponent (b) depend mainly on the type of adsorbent. Similarly, Dubinin (3) found that W0 and b were related only to the nature of the adsorbent. The experimental total pore volumes per gram values for F-400 and XEN-563 were previously reported as 0.61 mL/g and 0.59 mL/g, respectively (32). W0 for F-400 is close to the experimental total pore volume per gram but W0 for XEN-563 is approximately half the experimental total pore volume per gram. The range of W0 values for the activated carbons (0.4-0.7 mL/g) is higher than the synthetic adsorbents (0.2-0.3 mL/g). Likewise, the range of b values for the activated carbons (1.1-1.3 excluding aromatics and halogenated aromatics for 580-26) is generally lower than the synthetic adsorbents (1.4-1.7). A sensitivity analysis was performed to determine if all the parameters in the normalizing factor were significant. To perform the sensitivity analysis, the best-fit parameters were altered (10% one at a time (while keeping all other fit parameters constant) to evaluate the sensitivity of the dependent variable (Wcorrelation) to the fit parameters. Table 4 shows sensitivity analysis results for the correlation of the aliphatic group on F-400. These results are typical of the correlations. The results of the sensitivity analysis for all the adsorbents and compound classes demonstrated that the k1Vi term is the dominant factor. This implies that molecular
TABLE 4. Impact of Changing Each Parameter by (10% for the Correlation of Aliphatic Compounds on F-400 % SDEV obtaineda the varied term
+1% change (%)
-10% change (%)
k1Vi/100 k2π* k3β k4R k5
50 24 24 24 36
40 24 24 24 32
a The original % SDEV for the correlation of aliphatic group on F-400 is 23%.
size is the dominant factor for all adsorbents and indicates that a molecule’s hydrophobicity and van der Waals forces predominate since they are related to molecular size. Routine statistical analyses were not performed because this is a nonlinear regression and the 95% confidence limits are really skewed surfaces in hyperspace (33). These surfaces are difficult to visualize and comprehend. However, if we assume that the 95% confidence limits are boxes which contain the actual limits, the sample deviation that corresponds to the 95% confidence limits can be calculated using the F table. This sample deviation is 23.4% for the aliphatic group on the F-400 carbon. Consequently, based on the sensitivity analysis, (10% of the model parameters are well within the 95% confidence limits. This is also true for all the VOL. 33, NO. 17, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 1. Correlation of aqueous adsorption isotherm data for halogenated aliphatic organic compounds on F-400 using the LSER parameters as a normalizing factor. Correlation from eq 4, (0, black) bromodichloromethane (24 °C), (0, blue) bromoform (24 °C), (0, magenta) carbon tetrachloride (24 °C), (0, green) chloroform (24 °C), (], black) dibromochloromethane (24 °C), (], blue) dibromomethane (24 °C), (], magenta) 1,1-dichloroethane (24 °C), (], green) 1,2 dichloroethane (24 °C), (+, black) 1,2-dichloropropane (24 °C), (+, blue) 1,3-dichloropropane (24 °C), (+, magenta) methylene chloride (24 °C), (+, green) 1,1,1,2-tetrachloroethane (24 °C), (4, black) 1,1,1-trichloroethane (24 °C), (4, blue) 1,1,2-trichloroethane (24 °C), (4, magenta) 1,2,3-trichloropropane (24 °C), (4, green) 1,2-dibromoethane (24 °C), (-, black) 1,1-dichloroethene (24 °C), (-, blue) cis-1,2-dichloroethene (24 °C), (-, magenta) tetrachloroethene (24 °C), (-, green) trichloroethene (24 °C), (O, black) chloroform (13 °C), (O, blue) dibromochloromethane (13 °C), (O, magenta) 1,2-dibromoethane (13 °C), (O, green) trichloroethene (13 °C), (×, black) tetrachloroethene (13 °C), (×, blue), cis-1,2-dichloroethene (13.8 °C), (×, magenta) trichloroethene (13.8 °C), (×, green) tetrachloroethene (13.8 °C).
FIGURE 2. Correlation of aqueous adsorption isotherm data for halogenated aliphatic organic compounds on F-400 using molar volume as a normalizing factor. Correlation from eq 4, (0, black) bromodichloromethane (24 °C), (0, blue) bromoform (24 °C), (0, magenta) carbon tetrachloride (24 °C), (0, green) chloroform (24 °C), (], black) dibromochloromethane (24 °C), (], blue) dibromomethane (24 °C), (], magenta) 1,1-dichloroethane (24 °C), (], green) 1,2 dichloroethane (24 °C), (+, black) 1,2-dichloropropane (24 °C), (+, blue) 1,3-dichloropropane (24 °C), (+, magenta) methylene chloride (24 °C), (+, green) 1,1,1,2-tetrachloroethane (24 °C), (4, black) 1,1,1-trichloroethane (24 °C), (4, blue) 1,1,2-trichloroethane (24 °C), (4, magenta) 1,2,3-trichloropropane (24 °C), (4, green) 1,2-dibromoethane (24 °C), (-, black) 1,1-dichloroethene (24 °C), (-, blue) cis-1,2-dichloroethene (24 °C), (-, magenta) tetrachloroethene (24 °C), (-, green) trichloroethene (24 °C), (O, black) chloroform (13 °C), (O, blue) dibromochloromethane (13 °C), (O, magenta) 1,2-dibromoethane (13 °C), (O, green) trichloroethene (13 °C), (×, black) tetrachloroethene (13 °C), (×, blue), cis-1,2-dichloroethene (13.8 °C), (×, magenta) trichloroethene (13.8 °C), (×, green) tetrachloroethene (13.8 °C). parameters that are reported in Table 3. According to eqs 4 and 5, a larger normalizing factor (N) implies that a compound has a higher adsorption capacity at a given adsorption potential. The LSER parameters used 2930
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in the correlations are on the same order of magnitude since the Vi term is divided by a factor of 100. Hence, the values of k1, k2, k3, and k4 in Table 3 can be compared to evaluate their relative importance to the correlation.
FIGURE 3. Correlation of aqueous adsorption isotherm data for halogenated aromatic and aromatic organic compounds on F-400 using the LSER parameters as a normalizing factor. Correlation from eq 4, (0, black) o-dichlorobenzene (24 °C), (0, blue) p-dichlorobenzene (24 °C), (0, magenta) ethylbenzene (24 °C), (0, green) styrene (24 °C), (], black) toluene (24 °C), (], blue) p-xylene (24 °C), (], magenta) benzene (24 °C), (], green) bromobenzene (24 °C), (+, black) chlorobenzene (24 °C), (+, blue) 2,4-dinitrotoluene (24 °C), (+, magenta) toluene (13.8 °C), (+, green) ethylbenzene (13.8 °C), (4, black) m-xylene (13.8 °C), (4, blue) o-xylene (13.8 °C).
FIGURE 4. Correlation of aqueous adsorption isotherm data for polyfunctional organic compounds F-400 using the LSER parameters as a normalizing factor. Correlation from eq 4, (0, black) alachlor (24 °C), (0, blue) aldicarb (24 °C), (0, magenta) atrazine (24 °C), (0, green) dinoseb (24 °C), (], black) pentachlorophenol (24 °C), (], blue) hexachlorocyclopentadiene (24 °C), (], magenta) lindane (24 °C), (], green) metolachlor (24 °C), (+, black) metribuzin (24 °C), (+, blue) oxamyl (24 °C), (+, magenta) simazine (13.8 °C), (+, green) 2,4,5-T (13.8 °C). (**) This sample deviation value was obtained from optimization analysis without including high solubility compounds such as oxamyl. The value of the k2π* term for a synthetic adsorbent was higher than that for an activated carbon, and this implies that dipole-dipole and dipole-induced dipole interactions play a more important role in case of a synthetic adsorbent than an activated carbon. Negative values of k3 and k4 indicate that hydrogenbonding terms have an inhibitive effect on the adsorption capacity. This is reasonable since larger values of the k3β and k4R terms imply stronger hydrogen bonding between water and the adsorbates, thus decreasing the adsorbate’s affinity for the adsorbent. As shown in Table 3, the correlations using the LSER parameters as a normalizing factor provide lower percent
sample deviations than the correlations using Vm for all compound classes and adsorbents. Figures 1 and 2 show the Polanyi correlation for halogenated aliphatic organic compounds on F-400 using the LSER parameters and Vm as normalizing factors, respectively. If the correlation was perfect, all of the data points would lie directly on the correlation line. Figure 2 shows more scattering of the experimental data than Figure 1, and as shown in Table 3, the percent sample deviation for the Vm normalized correlation is about twice the value for the LSER normalized correlation. In Figure 1, all organic compounds have a good correlation except for some experimental data points of 1,1dichloroethene and trichloroethene at low concentrations VOL. 33, NO. 17, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 5. Correlation of aqueous adsorption isotherm data for aromatic and sulfonated aromatic organic compounds on F-300 using the LSER parameters as a normalizing factor. Correlation from eq 4, (0, black) naphthalene (20 °C), (], black) 3-nitro-1-benzenesulfonate (20 °C), (], blue) 1-naphthalenesulfonate (20 °C), (], magenta) 6-hydroxy-2-naphthalenesulfonate (20 °C), (], green) 2-anthraquinonesulfonate (20 °C), (+, black) 1,5-naphthalenedisulfonate (20 °C), (+, blue) 2,6-naphthalenedisulfonate (20 °C), (+, magenta) 4-hydroxy-2,7naphthalenedisulfonate (20 °C), (+, green) 2,6-anthraquinonedisulfonate (20 °C), (+, red) 4,4′-dinitro-2,2′-stilbenedisulfonate (20 °C), (4, black) 1,3,6-naphthalenetrisulfonate (20 °C). (**) This sample deviation value was obtained from optimization analysis without including di- and trisulfonated compounds, which have high solubilities. (these appear as outliers in Figure 1). Consequently, these data were ignored in the development of this correlation. The 1,1-dichloroethene and trichloroethene data points made up about 4% of all data points for the halogenated aliphatics. Figure 3 shows the Polanyi correlation normalized with LSER parameters for aromatic and halogenated aromatic organic compounds on F-400. A good description of the experimental data was obtained for all compounds except for styrene. The styrene data displays more adsorbability and this may be due to the polymerization of styrene on the surface of the adsorbent, which is reportedly catalyzed by oxygen (34). Figure 4 shows the Polanyi correlation normalized with LSER parameters for polyfunctional organic compounds on F-400. The correlation tends to be applicable for polyfunctional organic compounds that have relatively low solubilities (
