Adsorption of Beta Blockers to Environmental Surfaces

Beta-adrenergic blocking agents (beta blockers) are widely used pharmaceuticals which have been detected in the environment. Predicting the transport ...
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Environ. Sci. Technol. 2007, 41, 5349-5356

Adsorption of Beta Blockers to Environmental Surfaces TOHREN C. G. KIBBEY,* RAJIV PARUCHURI, DAVID A. SABATINI, AND LIXIA CHEN School of Civil Engineering and Environmental Science, The University of Oklahoma, Norman, Oklahoma 73019-1024

Beta-adrenergic blocking agents (beta blockers) are widely used pharmaceuticals which have been detected in the environment. Predicting the transport and ultimate fate of beta blockers in the environment requires understanding their adsorption to soils and sediments, something for which little information is currently available. The objective of this work was to examine the adsorption of three beta blockers, propranolol, metoprolol and nadolol, to a natural alluvial material, as well as to six minerals present as components of the alluvial material. Batch adsorption experiments indicate that, for most of the minerals studied, compound hydrophobicity is an important predictor of adsorption, with propranolol, the most hydrophobic compound studied, adsorbing to the greatest extent. Results further suggest that, for the minerals studied, electrostatic effects are not a good predictor of adsorption; adsorption extent was not well-predicted by either surface zeta potential or by the difference between experiment pH and point of zero charge, despite the cationic nature af the three beta blockers at experiment pH values. Experiments were conducted to examine the effect of an anionic surfactant, sodium dodecyl benzene sulfonate (SDBS), on adsorption. Results indicate that SDBS significantly increases the adsorption of propranolol to two different sorbents. This result is potentially important because surfactants such as SDBS are likely to be present in wastewater effluents with beta blockers and could influence their mobility in the environment.

Introduction A wide range of pharmaceutical compounds have been identified in the environment, and their presence has been a matter of growing concern both for human and ecological health (e.g., refs 1, 2). The ultimate fate of pharmaceutical compounds in the environment can be strongly influenced by their adsorption to soils and sediments, because adsorption can slow the migration of chemicals, potentially increasing the time for degradation, and reducing the potential for exposure. Adsorption behavior varies from compound to compound, and can be difficult to predict for pharmaceutical compounds because their behavior is often controlled by interactions with specific functional groups or complicated pH-dependent speciation. To date, only a fraction of pharmaceutical compounds have seen extensive study of their adsorption behaviors in the presence of natural soils or sediments. * Corresponding author phone: 405-325-0580; fax: 405-325-4217; e-mail: [email protected]. 10.1021/es070152v CCC: $37.00 Published on Web 06/28/2007

 2007 American Chemical Society

Beta-adrenergic blocking agents (beta blockers) are important pharmaceutical compounds for which little environmental adsorption data exists. Beta blockers are pharmaceuticals which affect the heart and circulatory system and are used to treat hypertension and a range of other conditions. Beta blockers exhibit moderately high solubilities in water (3), and have been detected in surface waters at concentrations as high as µg/L levels (e.g., ref 4). As is the case with many pharmaceuticals, many beta blocker compounds have the potential to be highly persistent (5, 6) and toxic (7, 8) in the environment. Incomplete wastewater treatment is a common source of beta blockers entering the environment (4, 5, 9). The work described in this paper examines the adsorption of three beta-blockers to a natural aquifer material and to six individual mineral subcomponents of the aquifer material. Furthermore, because anionic surfactants are widely used, and are likely to enter the environment with beta blockers through incomplete wastewater treatment, selected experiments were conducted to examine the effect of anionic surfactants on beta blocker adsorption.

Materials and Methods Materials. The beta blocker compounds selected for this work were nadolol, propranolol, and metoprolol. Properties and structures of the three compounds are shown in Table 1. All three compounds are positively charged at neutral pH, with pKa values near 9.6, and are moderately hydrophilic. Of the three compounds, propranolol is the most hydrophobic, with a log Kow (neutral species) of 3.48 (Table 1), and nadolol the least hydrophobic, with a log Kow (neutral species) of 0.85 (Table 1). The Kow values of all three compounds are approximately 3 to 4 orders of magnitude lower when in the ionized (positive) form (Table 1). An interesting feature of beta blockers is that they have been reported to behave as weak cationic surfactants at neutral pH (10). As such, it was speculated that interactions with anionic surfactants in the environment could have a significant effect on their behavior, as anionic surfactants are known to have a profound influence on the solution properties of most cationic surfactants (11, 12). To test this hypothesis, selected experiments were conducted with the anionic surfactant sodium dodecyl benzene sulfonate (SDBS) in addition to the beta blocker propranolol. Technical grade SDBS was purchased from Sigma-Aldrich (St. Louis, MO), and used as received. Note that SDBS is a commercial mixture containing a number of alkylbenzene sulfonate isomers; purified SDBS is neither commercially available, nor representative of surfactant likely to enter the environment. SDBS was chosen as it is one of the most widely used anionic surfactants worldwide (13). For this work, we have studied adsorption to Canadian River Alluvium (CRA), a material collected from the alluvial channel of the Canadian River in Norman, Oklahoma. CRA is predominantly quartz sand, with a large number of additional minerals present in small quantities. Characterization of CRA was conducted by scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS) as a part of previous work (14). Analysis indicated that although the material was predominantly a quartz sand, up to a third of the grains exhibited modest iron oxide coatings. Individual grains of alkali and plagiosclase feldspars, amphiboles, cordierite, ilmenite, magnetite, and tourmaline were detected in a cumulative amount less than 1-2% of the total. To better understand adsorption to CRA, we have studied adsorption to a number of its component minerals: a high purity natural quartz sand, magnetite, ilmenite, cordierite, tourmaline, and VOL. 41, NO. 15, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 1. Beta Blocker Compounds Studied. Note that K0ow Is the Octanol-Water Partition Coefficient of the Neutral Species, and K+ ow is the Octanol-Water Partition Coefficient of the Positively Charged Species

a

From ref 21.

b

From ref 22. c From ref 23.

d

Value from ref 24 and estimated using the diff 3-4 method (16).

TABLE 2. Properties of the Seven Sorbents Studied BET surface area (m2/g)

sorbent natural alluvial material Canadian River alluvium (CRA) framework silicates F95 quartz sand NC4 feldspar G200 feldspar oxides ilmenite magnetite ring silicates tourmaline a

Measured for this work.

b

9

formula

3.5a

∼2a

0.0992a 1.21b 1.26b

2c 2-2.4c 2-2.4c

SiO2 (K,Na)[AlSi3O8] (Na>K) (K,Na)[AlSi3O8] (K>Na)

1.16a 0.5a

5.6d 6.5c

Fe2+TiO3 Fe2+(Fe3+)2O4

0.29a

6.6e c

Value provided by Feldspar, Inc. From ref 25.

two types of feldspars. Although these materials are present in very small quantities in CRA, it is possible for a very strongly adsorbing mineral or surface coating to have a significant effect on ultimate adsorption results. Properties of the sorbents selected are shown in Table 2. CRA was sieved and used in the 140-200 mesh size fraction (e.g., material that passed the 140 mesh sieve, but was retained on the 200 mesh sieve). F95 quartz sand was purchased from US Silica (Ottawa, IL) and was used as received. NC4 and G200 Feldspars were purchased in powdered form from Feldspar Corporation (Atlanta, GA) and were used as received. The remaining minerals (ilmenite, magnetite, tourmaline) were purchased from Ward’s Natural Science (Rochester, NY), and were converted to a powdered form for experiments using a jaw crusher, followed by an automatic compaction hammer, and then sieved. Ilmenite, magnetite, and tourmaline were used in the 100-200 mesh size fraction for all experiments. Surface areas of sorbents were measured using multipoint BET analyses on a Quantachrome (Boynton Beach, FL) Autosorb-1 surface area analyzer. In general, most of the materials studied had final specific surface areas on the order of 1 m2/g, with the most notable exceptions being F95 Sand which has a smaller area (0.0992 m2/g) due to its natural size distribution. To allow direct comparison between minerals, all reported adsorption measurements are normalized to surface area. Zeta potentials were measured using a Particle Sizing Systems (Santa Barbara, CA) Nicomp 380/ZLS dynamic light 5350

point of zero charge (pzc)

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d

Na(Fe2+)3Al6(BO3)3Si6O18(OH)4 e

From ref 26. From ref 27.

scattering (DLS) particle sizing device with zeta measurement capability. Methods. Batch adsorption experiments were conducted in 16 mL vials with PTFE-lined caps. In all experiments, 0.01 M CaCl2 was included, and a liquid volume of 8 mL was used. Solids additions were varied slightly by sorbent and compound, with higher additions used to improve adsorption measurements for low-sorbing systems; all experiments were conducted with between 3 and 7 grams of solid per sample, with most in the 3-4 g range. Solids additions were consistent within each experiment. Samples were prepared by first weighing the solid into each vial and recording the weight, and then adding CaCl2, and varying volumes of Nanopure water (Barnstead, Dubuque, IA) and beta blocker stock solution to produce the desired initial concentration and a total liquid volume of 8 mL. Initial concentrations of beta blockers added ranged from approximately 5 × 10-6 M to 8 × 10-5 M, with additional lower concentration samples prepared in selected experiments. Samples containing SDBS were prepared with an initial propranolol concentration of 1.6 × 10-5 M and an initial SDBS concentration of 2.1 × 10-5 M. Final concentrations varied widely from mineral to mineral as a result of different adsorption affinities. Samples were equilibrated on an end-over-end rotator for 48 h prior to analysis. Following equilibration, the samples were centrifuged and the supernatant removed for analysis. Although pH was not controlled in the experiments, it was monitored by analysis of a subset of the equilibrated samples

TABLE 3. Adsorption Results and Corresponding Experiment pH. Data Ranges Correspond to 95% Confidence Intervalsa

a

compound

experiment pH

propranolol KD [mL/m2]

metoprolol KD [mL/m2]

nadolol KD [mL/m2]

CRA F-95 quartz sand NC4 feldspar G200 feldspar ilmenite magnetite tourmaline

7.7 ( 0.10 7.2 ( 0.49 8.4 ( 0.09 9.0 ( 0.02 7.7 ( 0.06 7.3 ( 0.34 7.5 ( 0.43

2.82 ( 0.22 0.42( 0.17 1.10 ( 0.10 0.65 ( 0.04 6.29 ( 0.38 0.23 ( 0.03 2.28 ( 0.21

1.04 ( 0.04 0.92 ( 0.28 0.04( 0.07 0.11( 0.02 3.48 ( 0.49 0.06( 0.02 0.46( 0.06

0.18( 0.01 3.21 ( 0.23 0.16 ( 0.03 0.28 ( 0.01 0.47( 0.05 0.38 ( 0.09 0.91 ( 0.08

Bold indicates highest adsorption for a given mineral. Italic indicates lowest adsorption for a given mineral.

FIGURE 1. Adsorption isotherms of beta blocker compounds to Canadian River Alluvium (CRA). Note that log Kow values shown were calculated from eq 1 based on values in Table 1. for each mineral. Experiment pH values are listed in Table 3, along with adsorption results (discussed in the Results and Discussion section). Most experiments were conducted at near-neutral pH (∼7.2-7.7), with the exception of the experiments with the two commercial feldspars, which were conducted at higher pH values (8.4, 9). To determine concentrations, the supernatant was analyzed using the fullspectrum UV absorbance analysis method described previously by Hari, et al. (14). The method makes use of the full UV absorbance spectrum of the sample, using a nonlinear optimization method to determine the concentration of individual components. For the work described here, components included the particular beta blocker compound being studied, SDBS (for experiments conducted with SDBS), and a blank containing dispersed fines from the particular mineral. The method is able to simultaneously distinguish the concentrations of multiple chemicals, and is highly insensitive to the presence of dispersed fines (a common difficulty with UV absorbance measurements).

Results and Discussion Figure 1 shows adsorption isotherms of the three beta-blocker compounds on CRA at pH 7.7. It is apparent from the figure that all three isotherms are essentially linear over the range studied, with the most hydrophobic compound, propranolol, exhibiting the greatest adsorption affinity (highest slope), and the least hydrophobic compound, nadolol, exhibiting the least sorption affinity (lowest slope). This result is not unexpected since more hydrophobic compounds tend to

adsorb to a greater extent, even to low carbon sorbents such as CRA (e.g., ref 15). Calculated log Kow values at the experiment pH (pH 7.7) are also shown in Figure 1 for all three compounds. These values were calculated from eq 1 (16), which considers the effect of speciation on partitioning. 0 (pKa-pH) + log KpH )ow ) log (Kow + Kow 10

log (1 + 10(pKa-pH)) (1) where KpH ow is the overall octanol-water partition coefficient at the desired pH, K0ow is the octanol-water partition coefficient of the neutral species (Table 1), and K+ ow is the octanol-water partition coefficient of the positively charged species (Table 1). To be clear: our use of Kow here is as an indicator of compound hydrophobicity; we do not intend to suggest that adsorption to the surfaces studied is a partitioning mechanism. Considering the calculated log Kow values in Figure 1, an interesting observation can be made. Because the experiment was conducted approximately two pH units below the pKa of each compound, the concentration of the neutral species in solution would be approximately 1/100th of the concentration of the charged species. However, because of the very strong partitioning affinity of the neutral species for octanols K0ow 3-4 orders of magnitude greater than K+ owsthe majority of observed partitioning between octanol and water at pH 7.7 is actually due to partitioning of the neutral species. For VOL. 41, NO. 15, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 2. Adsorption isotherms of beta blocker compounds to six different component minerals. example, in the case of propranolol, Kow ) 50 (i.e., 101.70 ) 50) at pH 7.7, almost ten times the partitioning expected for the charged species alone (Kow ) 6). Although hydrophobicity is only one factor influencing adsorption, and mechanisms of partitioning are often different from mechanisms of adsorption, this result highlights one of the interesting challenges in interpreting adsorption of ionizable compounds regardless of mechanism: the dominant solution species at a particular pH is not necessarily responsible for the observed adsorption behavior if other species have a strong affinity for the surface. Figure 2 shows isotherms for adsorption of the three betablocker compounds to the six component mineral surfaces evaluated in this study. Note that the scales of the vertical 5352

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axes of the plots in Figure 2 vary widely, as a result of the different adsorption affinities of the minerals. As was the case with the isotherms on CRA, with a few exceptions most of the isotherms appear to be linear or very nearly linear (although some exhibit considerable scatter due to difficulty of measuring adsorption when compounds have very low affinity for a surface). As was observed in Figure 1 for CRA, it is apparent from Figure 2 that the most hydrophobic compound, propranolol, adsorbs to the greatest extent to all but two of the minerals: F95 sand and magnetite. This trend is also apparent in Table 3, which shows measured linear adsorption coefficients (KD) for the twenty one different isotherms in Figures 1 and 2, determined from linear regression fits through the origin. Error ranges shown

FIGURE 3. Effect of difference between experiment pH and solid pzc on adsorption. Values shown below mineral names are adsorption constants (KD) in units of mL/m2 for propranolol (P), metoprolol (M), and nadolol (N). correspond to 95% confidence intervals for the fits. Isotherms with greater scatter or some apparent nonlinearity (e.g., ilmenite/metoprolol) exhibit correspondingly greater error ranges. For each mineral, the highest KD value is indicated in bold, and the lowest value is indicated in italic. As was observed in Figure 2, propranolol, the most hydrophobic compound, shows the greatest adsorption for all but two of the solids (F95 sand and magnetite). However, for all solids except F95 sand and magnetite, only ilmenite follows the compound hydrophobicity trend observed in CRA for all three compounds (e.g., propranolol highest, nadolol lowest); in many cases, metoprolol exhibits the lowest adsorption. This may simply be due to the very low adsorption of both nadolol and metoprolol to most of the minerals and the corresponding difficulty measuring adsorption of low-adsorbing compounds, or it may indicate a difference in the nature of the interaction with the surfaces between the two compounds. Looking at F95 (Table 3 and Figure 2), the very high adsorption affinity of nadolol is interesting. Although CRA is largely comprised of sand, CRA exhibits much lower nadolol adsorption than F95. It thus appears that the oxide coatings on the surfaces of the sand contained in CRA are influencing adsorption behavior. In the case of magnetite, the other mineral for which propranolol is not the highest sorbing species, it is apparent from the isotherms in Figure 2 that the affinities of propranolol and nadolol are actually quite similar for magnetite, and both isotherms exhibit considerable scatter; the regression-based 95% confidence intervals in Table 3 may not be sufficiently large to account for the true range of error in the measurements where considerable scatter is observed. (The use of regression through the origin, as is done here to calculate KD values, can underestimate error if scatter causes data to have the appearance of a nonzero intercept. This can occur in low-sorbing systems where adsorption is measured by difference, as sample-tosample variability in sorbent surface area and concentration are magnified in the calculation of amount adsorbed.) Interestingly, the adsorption of metoprolol to magnetite is distinctly lower than the adsorption of the other two compounds.

Examining the relative extent of adsorption of each compound from mineral-to-mineral, it is apparent that adsorption varies widelysa range of an order of magnitude for propranolol, 2 orders of magnitude for both metoprolol and nadolol (Table 3). Interestingly, adsorption to CRA is strong relative to adsorption to many of the other compounds; only adsorption to Ilmenite exceeds adsorption to CRA for all three compounds, and then only by a factor of ∼3. Considering that all of the component minerals (excluding sand) make up less than 1-2% of the total CRA composition, this indicates that none of them are dominating the observed adsorption behavior to CRA. (A significant contribution would require at least a 2-order-of-magnitude greater mineral KD in comparison with the CRA KD). When taken together with the differences between adsorption to CRA and F95 sand (a major component of CRA), this result provides further evidence that a surface component not included in the studys likely oxide coatings on CRA surfacessis playing a significant role in adsorption to CRA. Figure 3 evaluates the extent to which electrostatic interactions are responsible for the mineral-to-mineral differences in adsorption by looking at adsorption in relation to experiment pH and mineral point of zero charge (pzc). The vertical axis in Figure 3 corresponds to the pzc of the minerals (Table 2), and the horizontal axis corresponds to the pH of the experiments (Table 3). The diagonal line indicates a 1:1 relationship between pzc and experiment pH; symbols below the line (in this case, all of them) correspond to experiments where the solid has a net negative surface charge. As distance from the 1:1 line increases, the magnitude of the surface charge would be expected to increase. Because all experiments were conducted at pH values below the pKa values of the beta-blockers (approximately 9.6; Table 1), the beta-blocker species are present in solution primarily in positively charged form. G200 feldspar experiments (pH 9.0) were approximately a half pH unit below the pKa values, so they would correspond to approximately 75% solution species in positive form. The NC4 feldspar experiments (pH 8.4) were approximately one pH unit below the pKa values (∼90% positive). All other experiments were VOL. 41, NO. 15, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 4. Effect of zeta potential (in the absence of beta blockers) on adsorption. Values below mineral names are measured zeta potential at experiment pH. approximately two full pH unit below the compound pKa values (∼99% positive). As such, if electrostatic interactions were the primary driving force for adsorption, minerals below the 1:1 line would be expected to exhibit increasing adsorption with increasing distance from the line. Examination of Figure 3 shows that this is, in general, not the case. Within the subset of iron-containing minerals (magnetite, tourmaline, ilmenite) increasing adsorption is observed with increasing distance from the line for both propranolol and metoprolol. However, comparison between ilmenite (two pH units above its pzc) and the feldspars (NC4 and G200; 6-7 pH units above their pzcs), for example, shows that adsorption to ilmenite is considerably stronger. If electrostatic interactions were dominant, adsorption to F95, CRA, NC4, and G200 would all be expected to be much greater than adsorption to the other compounds. This result is further illustrated by Figure 4, which shows the observed adsorption of each compound (Table 2) as a function of measured zeta potentials for each mineral at the experiment pH, in the absence of beta blockers. Note that the order of minerals in Figure 4 differs slightly from the order of distances between pH and pzc in Figure 3, likely as a result of different surface charge densities. In any case, it is clear from Figure 4 that there is no general relationship between adsorption and surface charge. The results of Figures 3 and 4 indicate that the interactions between the compounds and the various minerals results from mineral-specific surface interactions. While adsorption appears to be influenced by compound hydrophobicity, particularly for the most hydrophobic compound, propranolol, it is likely that surface complexes are occurring with iron in the iron-containing minerals (magnetite, tourmaline, ilmenite) and CRA, which contains small quantities of each, as well as iron oxide coatings. Adsorption to the iron containing minerals may in some cases be analogous to the strong complexation expected by oxine (8-hydroxyquinoline), a strong chelating agent (e.g., refs 17-19) with oxygen and nitrogen atoms positioned similarly to those in the three beta blockers. This interaction might be expected to be stronger for the neutral beta blocker species. As previously 5354

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discussed, a sufficiently strong interaction with the surface can mean that the nondominant solution species (in this case the neutral species) can have a dominant effect on adsorption. Comparison With Other Compounds. From a purely practical standpoint, it is important to consider not only the differences between adsorption of the three beta blockers, but also the significance of the absolute magnitude of the adsorption for transport in the subsurface. On a mass basis, KD values for adsorption to CRA by propranolol, metoprolol, and nadolol are 9.78, 3.64, and 0.63 mL/g, respectively. These values correspond to retardation factors (R ) 1 + FbKD/n, where Fb is the bulk density of the porous medium, and n is the porosity) ranging from approximately 42 for propranolol to 3.6 for nadolol; these values are likely to significantly slow the dissolved transport of the compounds through packed CRA. (Calculations of retardation factors were based on n ) 0.39, and a solid density, Fs ) Fb/(1 - n), of 2.65 cm3/g; variations in packing would change actual values.) For comparison, previous work by the authors (14) examining adsorption of other pharmaceutical compounds to a slightly coarser fraction of CRA (80-140 mesh) found the quinolone antibiotics norfloxacin and nalidixic acid exhibited KD values of 31.1 and 1.82, mL/g respectively at pH 7.7; these values have a magnitude similar to the beta blockers. (With pKa values in the neutral range, the quinolone antibiotics are strongly pH sensitive). As mentioned in the Materials section, beta blockers are known to behave as weak cationic surfactants (10). Although this means they are capable of forming micelles and are weakly surface active, it does not necessarily imply that adsorption as strong as that produced by true surfactants would be expected. For example, the adsorption of the cationic surfactant cetylpyridinium chloride (CPC) to 80140 mesh CRA (14) exhibits a KD value of approximately 1300 mL/g at low concentrations, which is 2 orders of magnitude higher than propranolol. Because the surface area of the 80-140 mesh CRA used in the previous work was not measured, it is not possible to directly compare KD values from that work with those

FIGURE 5. Effect of sodium dodecyl benzene sulfonate (SDBS) anionic surfactant on propranolol adsorption. measured in this paper. However, calculations from early preliminary adsorption measurements with other compounds on both size fractions suggest that the KD values of norfloxacin, nalidixic acid, and CPC likely would be 1.5-4 times higher on the finer material used for this work than the values listed above for the coarser material. Effect of Anionic Surfactant. Figure 5 shows the effect of the anionic surfactant sodium dodecyl benzene sulfonate (SDBS) on the adsorption of propranolol to two different sorbents, CRA and G200 feldspar. Anionic surfactants like SDBS are widely used and are likely to be present in waters containing wastewater effluents. Because surfactants are widely used, it is likely that concentrations of surfactants would be at least comparable to those of pharmaceutical compounds, and likely much higher. From Figure 5, it is apparent that the presence of SDBS significantly increases propranolol adsorption to both sorbentssa 48% increase in the case of CRA and a 75% increase in the case of G200. This result suggests that the presence of anionic surfactants and other anionic amphiphiles may be expected to further reduce the mobility of beta blockers in the environment. The reason for the effect of SDBS on propranolol adsorption is likely the result of a complexation, ion-pairing interaction between the molecules, similar to the effect that is observed in mixtures of anionic surfactants like SDBS and traditional cationic surfactants. When anionic and cationic surfactants are mixed in solution, the solubility of the two can be drastically decreased, and adsorption to solid surfaces can be increased, due to increased apparent hydrophobicity of the surfactants (11). The effect of surfactants on adsorption of oppositely charged pharmaceutical compounds is likely to be observed for other compounds besides beta blockers. For example, previous work by Hari, et al. (14) found that the negatively charged species of nalidixic acid, a quinolone antibiotic, was increased by a factor of 4 by the presence of the cationic surfactant cetylpyradinium chloride (CPC). However, that work also found that adsorption of the negatively charged species of norfloxacin, a strongly adsorbing fluoroquinolone antibiotic, was essentially unchanged by the presence of CPC. Interestingly, as might be expected, the beta blockers also are found to increase the adsorption of SDBS to the two sorbents. In the case of CRA, where very little SDBS adsorption occurs in the absence of propranolol, the addition of propranolol increased SDBS adsorption by more than 150% (from 0.15 to 0.39 mL/m2). In contrast, SDBS adsorbed very strongly to G200 feldspar in the absence of propranolol, so the addition of propranolol increased SDBS adsorption by only 31% (from 2.3 to 3.0 mL/m2). Although transport of SDBS itself is not likely to be of as much concern as transport of propranolol, the presence of a surfactant surface coating

could influence the transport of other compounds (e.g., ref 20). Implications for the Environmental Transport of BetaBlockers. Results of this work indicate that hydrophobicity is an important predictor of beta blocker adsorption: propranolol, the most hydrophobic beta blocker studied, adsorbed to the greatest extent to six of the eight sorbents studied. As such, of the three compounds studied, propranolol might be expected to be the least mobile in the environment. Adsorption to different mineral surfaces varied by 1-2 orders of magnitude for the three beta blockers studied, and was not well-predicted by electrostatic differences, which suggests that specific interactions with some transition metals (e.g., iron) in environmental sorbents may play an important role in beta blocker adsorption and transport. In terms of overall adsorption magnitude, adsorption of the three beta blockers was found to be high enough to measurably reduce the rate of transport. Finally, the presence of the anionic surfactant SDBS was found to further increase adsorption, suggesting that similar anionic amphiphiles present in the environment with beta blockers could significantly slow their transport.

Acknowledgments We thank James Hoggan, Natee Singhaputtangkul, Ian Toohey, and Rex Richard for their assistance with solids preparation and specific experimental measurements in the early stages of this work. Funding for this work has been provided through the United States Environmental Protection Agency Science to Achieve Results (STAR) program, through grant no. R829005. Although the research described in this article has been funded by the United States Environmental Protection Agency, it has not been subjected to the Agency’s required peer and policy review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.

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Received for review January 19, 2007. Revised manuscript received May 10, 2007. Accepted May 21, 2007. ES070152V