Effects of Sorption on the Rejection of Trace Organic Contaminants

Understanding the removal of trace organic contaminants is critical for membrane applications in water recycling. This study investigates the relation...
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Environ. Sci. Technol. 2010, 44, 2592–2598

Effects of Sorption on the Rejection of Trace Organic Contaminants During Nanofiltration EVA STEINLE-DARLING, ERIC LITWILLER, AND MARTIN REINHARD* Department of Civil and Environmental Engineering, Stanford University, Stanford California 94305

Received September 20, 2009. Revised manuscript received February 16, 2010. Accepted February 19, 2010.

Understanding the removal of trace organic contaminants is critical for membrane applications in water recycling. This study investigates the relationship between trace contaminant sorption and their rejection by nanofiltration (NF) membranes. A mass balance is developed that quantitatively links the rejection decline over time seen with some sorbing compounds to the total mass found sorbed on the membrane. The sorbed mass of perfluorooctane sulfonamide (FOSA) and fluoxetine evaluated from the mass balance agreed to within approximately 30% of the quantity analytically determined via extraction. Static sorption experiments show that sorption takes place predominantly within the polyamide separating layer of the membrane. Finally, the relationship between the steady-state rejection and sorption tendency of ten trace organic compounds is elucidated. A greater tendency to sorb results in lower steady-state rejection, both when comparing compounds of similar size, as well as when comparing the same compound under different conditions. As a result, a major finding is that in the presence of competitive sorption, that is, the presence of other trace organic compounds in the membrane matrix, some compounds sorb less and are therefore rejected more than when these compounds are alone in the feed. At no point during experimentation was any effect on the water flux observed.

model inherently assumes that the part of the membrane that performs the separation is a homogeneous “thin film” layer, into which compounds “dissolve” or “partition” from the feed solution and then diffuse through to eventually partition into the aqueous phase on the permeate side (9). Passage and rejection of small molecules is thought to be governed by three main effects: size and geometric constraints, charge repulsion, and “solute-membrane affinity.” The latter effect is thought to depend on a variety of factors that can include size, charge, hydrophobicity, hydrogen bonding capacity, and dipole moment (10-12). There is considerably more uncertainty about the transport mechanisms at work in NF. Figure 1 illustrates that transport in NF is generally thought to be influenced by solution-diffusion processes, as well as flow through pores or “defects” on the nanometer (nm) scale (2, 9). Along with the thinner separating layer generally observed in NF membranes (13), this additional permeation mechanism likely contributes to an increased water permeability (flux per applied pressure) observed with NF membranes as opposed to RO membranes. Trace organic solutes exceeding a certain size, on the other hand, may be just big enough to be rejected via size exclusion by these membrane “defects,” while still being able to pass through the “bulk” membrane material via solution-diffusion or a similar mechanism. Recent work illustrates that sorption, one manifestation of “solute-membrane affinity,” can play a critical role in the rejection of trace organic contaminants (3, 14, 15, 17, 18). Sorption can affect rejection in several ways. First, it can cause a transient effect, resulting in temporarily higher initial rejections; once the sorption capacity of the membrane is exhausted, rejection is dominated by the mechanisms affecting diffusion through the membrane. Declining rejection over time has been observed by others for sorbing trace organic contaminants (3, 14). To quantify the amount of solute that is rejected because of the transient sorptive processes requires both data that indicate the timedependence of rejection and a mass balance evaluation providing the total mass rejected due to sorption to the membrane. Other potential consequences of trace contaminant sorption are its indirect effects on the steady-state rejection

Introduction Developing safe measures for keeping up with soaring water demand is of paramount importance in a world where highquality water resources are becoming increasingly scarce. Recycling wastewater by treating it to an acceptable standard using membrane technology, such as reverse osmosis (RO) or nanofiltration (NF), is one promising option because of the efficiency of these membranes in removing a broad range of dissolved organic contaminants (1). But results have also shown that NF and RO membranes are permeable to some degree to certain relatively small trace organic contaminants, which include, among others, some pharmaceuticals and personal care products (1-4), as well as the group of emerging contaminants known as perfluorochemicals, which are being found ubiquitously in the environment (5-8). In RO, the solution-diffusion model is generally accepted as the prevailing transport mechanism for water and solute, despite some unexplained aspects with respect to sorption and mixing behaviors, for example. The solution-diffusion * Corresponding author e-mail: [email protected]; phone: 650-723-0308; fax: 650-723-7058. 2592

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FIGURE 1. Schematic of hypothesized transport paths for water and organic microconstituents through NF membranes. For the data shown in this paper, the dominant water transport path is hypothesized to be convection through pores, whereas the main transport mechanism for organic solutes, which are too large to pass through the pores, is solution-diffusion through the bulk membrane material. A fraction of those organic solutes may be sorbed in the process of passing through the membrane. 10.1021/es902846m

 2010 American Chemical Society

Published on Web 03/10/2010

TABLE 1. List of Test Compounds Useda

a Unless otherwise indicated, pKa values were obtained from SPARC (30) and log Kow values were obtained from ref 31. NA ) not applicable.*Many pKa values can exist; only the values in the neutral range are shown. †Charge ) compound charge at operating conditions of pH ) 5.6. ‡Approximately 10% present in neutral form at pH ) 5.6. §Approximately 10% present in anionic form at pH ) 5.6

of solutes. The presence of trace contaminants does not affect bulk solution characteristics, such as pH, ionic strength, and temperature, which are known to affect water flux as well as the rejection of trace organic contaminants (2, 8, 16). But sorption of trace chemicals in the membrane separating layer may still significantly affect the properties of the membrane with respect to its rejection performance (14). For example, one could imagine a Langmuirian sorption process, whereby one compound in a feed mixture might associate more strongly with the membrane material than others and thus prevent other compounds from associating with it, that is, some compounds might “outcompete” others for favorable positions via which molecules pass through the membrane, an idea that has been explored recently (19). This aspect might be particularly important when the feed contains a mixture of contaminants, such as often seen in recycled waters (20). However, the effects of a mixture of contaminants have not been explicitly studied until very recently (15, 21).

The objectives of this study were to elucidate the influence of sorption on the rejection of trace organic contaminants in several ways, (1) by developing a mass balance-derived quantitative link between the transient rejection behavior and sorption and validating it using several data sets, (2) by employing static sorption experiments to show that a model compound, fluoxetine, sorbs mainly to the polyamide separating layer of the NF270 nanofiltration membrane, and (3) by using a diverse group of trace organic contaminants, listed in Table 1, to show that while the extent of sorption of trace organic contaminants has a significant effect on their rejection, it does not affect the water flux. Specifically, the objective of these experiments was to demonstrate that the presence of other sorbing trace contaminants (i.e., “competition” for the sorptive capacity of the membrane) can cause the extent of sorption for a particular compound to be reduced, resulting in a higher steady-state rejection. Mass-Balance Approach to Calculating Sorption from Rejection Data. The declining rejection behavior described VOL. 44, NO. 7, 2010 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 2. (a) Schematic plots showing declining rejection from R0 (initial rejection) to Rss (steady-state rejection). (b) Mass balance on solute flux over a control volume of the membrane for a compound with sorptive tendencies. The arrows describe mass flux as a product of water flux (J [m3/m2d]) and feed concentration (cfeed [µg/m3]). The steady-state rejection and sorptive flux are given as Rss [-] and S˙ [µg/m2d], respectively. Asterisk (*) refers to nonsorptive rejection processes. in the Introduction is shown schematically in Figure 2a. A derivation of the quantitative relationship between rejection and sorption is based on the general mass balance shown schematically in Figure 2b; this derivation is provided in the Supporting Information (SI).

Materials and Methods Sorption-Rejection Experiments. To investigate the potential effects of sorption on rejection, the rejection and sorption of the compounds listed in Table 1 were measured in bench-scale, flat-sheet, cross-flow experiments conducted with NF270 membrane (Dow/FilmTec, Minneapolis, MN, USA). The experimental setup, which includes three membrane cells operated in parallel to obtain triplicate measurements, has been described previously (16). NF270 is a highflux thin-film composite (TFC) membrane with a piperazinebased semiaromatic polyamide (PA) separating layer (32), in contrast to fully aromatic RO membranes that are based on m-phenylenediamine chemistry. The experimental protocols and chemical analysis methods have been described previously (8). Briefly, membrane coupons were compacted with a deionized water feed at operating conditions for at least 24 h, then the trace organic compound mixtures used in each experiment were spiked into the feed tank. All rejection experiments were performed at a trans-membrane pressure of 50 psi (340 kPa) and a crossflow velocity of 10 cm/s. Feed and permeate samples were collected over time for at least 24 h. Then membrane coupons were removed from the setup and extracted in methanol as described in previous work (8), to quantify the amount sorbed on the membrane. Spike recovery tests, which are also described in previous work (8), were performed in order to verify the efficiency of the extraction process. The first set of experiments was performed with feed solutions spiked with a mixture of perfluorochemicals (PFCs), including perfluorooctane sulfonamide (FOSA), at ∼200 ng/L each, in the context of previous work (8). During one of these experiments, a simulated fouling layer was produced using sodium alginate, as described previously (8). During an additional experimental phase, two separate experiments, labeled A and B, were performed. In experiment A, the feed concentrations of caffeine, atrazine, pentoxifylline, TCEP, trimethoprim, erythromycin, and fluoxetine were spiked at 10-25 µg/L, and DEET, dilantin, and sulfamethoxazole at approximately 100 µg/L. Because method detection limits were higher than anticipated, only the rejections for DEET and caffeine could be determined. In experiment B, all compounds were spiked to approximately 100 µg/L and thus quantitative results were obtained for all but two compounds (dilantin and pentoxifylline, for which rejections 2594

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were too high to quantify permeate concentrations). Spike recoveries of the extraction process for the compounds varied between 64% and 100%; thus sorption data was normalized with respect to the spike recovery. Concentrations in feed and permeate, as well as in the membrane extracts were quantified via a liquid chromatography - tandem mass-spectrometry method (LC-MS/MS) as described by others for FOSA (33) and the other compounds listed in Table 1 in (34). The source and purity of perfluorooctane sulfonamide (FOSA) was reported previously (16). Standards for the remaining trace contaminants listed in Table 1 were obtained from Sigma-Aldrich (St. Louis, MO, USA), except fluoxetine and caffeine-d9 (an internal standard), which were obtained from Toronto Research Chemicals (North York, Ontario, Canada). Static Sorption Experiments. To confirm that the bulk of the sorption observed during cross-flow experiments was taking place within the PA separating layer of the membrane, static sorption experiments with different layers of TFC membranes were performed with fluoxetine as a model compound. Fluoxetine is a relatively hydrophilic pharmaceutical that has been found in wastewater influenced water bodies (35). First, the polyester (PET) backing layer was manually peeled off a large section of NF270 membrane, leaving the PA and polysulfone (PS) layers intact. Then, 21 coupons, each 1 in. (2.54 cm) by 3 in. (7.62 cm), were cut out of the separated PET and PA+PS layers. Since mechanical separation of the PA and PS layers was not possible, the PS layer (manually peeled off) from a Hydranautics PS membrane was used as a surrogate PS layer. The Hydranautics PS membrane was obtained as a noncommercial sample and is assumed to be comparable to those used as backing layer for polyamide-based RO membranes. Again, 21 coupons, each 1 in. by 3 in., were cut from this surrogate PS layer. All coupons were then weighed. The mass of the PA layer was estimated based on a 40 nm layer thickness (36) and a estimate of the PA layer density, 1 g/mL. The density of the PA layer is unknown but was estimated based upon the approximate density of similar materials, such as nylon. The coupons were placed in 12 beakers each containing 240 mL of 104 µg/L fluoxetine in deionized water, as follows: For each membrane layer type prepared (NF270 PET, NF270 PS+PA, Hydranautics PS, and Hydranautics PET), 3, 6, and 12 coupons were placed, respectively, into the test beakers. These were then stored at 21 ( 0. 5 °C for approximately one month, and the concentration of fluoxetine in solution before and after was measured by the LC-MS/MS method described by others (34). The amount sorbed to the various coupons was then determined by difference, on a per membrane layer coupon mass basis. The mass of fluoxetine sorbed per area PA layer was determined indirectly from the amount sorbed to the Hydranautics PS layer and the amount sorbed to the NF270 PS + PA layer. It was calculated by subtracting the corresponding values for the Hydranautics PS layer from those for the NF270 PS+PA layer, assuming a linear sorption isotherm to normalize the quantity by the ratio of specific mass of PS in each membrane type. The mass of fluoxetine sorbed per mass PA layer was then calculated using the PA layer specific mass estimated above.

Results and Discussion Evaluating Sorption from Time-Dependent Rejection Data. Figure 3 shows a decline in the rejection of FOSA over five days from 100% to 93%. Similar behavior was observed in preliminary experiments with other nanofiltration membranes as well (data not shown). It is also very similar to that observed previously (3, 14), where the rejection appears to decline exponentially over time to a constant value. This

FIGURE 3. Rejection of FOSA over time. Optimal fitting of the data to eq 7 in the Supporting Information results in the following parameters: Rss ) 91.7%, R0 ) 100%, and b ) 0.68 d-1, where b is the rate constant for the exponential decline. Data points and error bars shown are the averages and standard deviations of rejections calculated from two feed and six permeate concentration measurements, respectively, for each point in time. behavior was attributed to a sorption process, which the previous researchers confirmed using membrane coupons that had been presoaked in solution containing their compounds of interest (3). The data shown in Figure 3 was fit to a linearized form of the exponential decline equation provided in the SI (eq 7). During the rejection experiments, water flux was constant to within (2%, but a strong decline in feed concentration, shown in Figure S1 of the SI, was observed over the course of the multiday experiments. This loss of solute in the system (calculated by multiplying the total system volume by the difference between the initial and final feed concentrations) cannot be explained simply by sorption to the membrane coupon. In fact, the quantities of FOSA extracted from the membrane coupons show that the sorption to membrane coupons accounts for less than 6% of the overall loss in the system. This is not surprising given the tendency of PFCs to partition to interfaces and the availability of ample surface area within the membrane setup on which to do so. This calculation highlights the importance of using a direct measure of the amount sorbed on the membrane, as opposed to calculating it from an overall mass balance using the feed concentration data. Doing the latter in this case would have overestimated the sorption on the membrane by a factor of 17. Because the feed concentration declined significantly during the course of the experiment, it is necessary to use the more complex form of the equation for the total amount sorbed, eq 13 in the SI. For the experiment in deionized water, both the feed concentration and rejection decline of FOSA can be approximated by the exponential decay equations developed in the SI. In this case, the value predicted from eq 13 with the FOSA rejection data is 10. 0 µg sorbed /m2 membrane area (where J ) 1.37 m/d, R0 ) 100%, Rss ) 0 ss ) 215 ng/L, cfeed ) 58 ng/L, a ) 1.09 d-1, and b 91.7%, cfeed ) 0.68 d-1). For comparison, the amount of FOSA sorbed measured via extraction after the rejection experiment was 11 ( 1 µg/m2. Thus the calculated and measured amounts of sorbed FOSA agree to within experimental error. The close agreement between the predicted and measured values supports the assumptions underlying the hypothesis that the initially higher rejection is caused by sorption and that there is a direct, quantitative link between this decline in rejection and the extent of sorption. Similar calculations were made for the results of an additional experiment with FOSA (in the presence of a fouling layer), as well one other trace contaminant (fluoxetine) for which declining rejection was also observed. In the case with

FIGURE 4. Comparison of measured and calculated values of mass sorbed for FOSA and fluoxetine. The latter are calculated from the feed, permeate and flux (i.e., rejection decline) data over time in rejection experiments, while the measurements are those obtained from membrane coupon extractions after those same rejection tests were completed. Error bars show the standard deviation of six replicates (obtained by extraction of two 1-in. diameter discs each punched from the membrane coupons removed postexperiment from the three membrane cells, respectively). fluoxetine, rejection started at a 100% and began to decline only after 6.5 h (see Figure S2 of the SI). Thus the calculation was modified to include a constant 100%-rejection term until 6.5 h and an exponential decline thereafter. This modified calculation can also be found in the SI. The delayed breakthrough of the strongly sorbing but poorly rejected fluoxetine suggests sorption occurs during transport (through a pore or by diffusion) across the membrane, as suggested in Figure 1 and by others (15). The observed behavior appears consistent with an advection-diffusion-sorption model but more data are required to verify this hypothesis. The correspondence between the measured and calculated methods of determining the sorbed amount for FOSA and fluoxetine are shown in Figure 4. The left-most pair of bars show the data explicitly calculated above, while the other two pairs show the comparison for FOSA in the presence of a fouling layer and fluoxetine in a mixture of the compounds listed in Table 1. The calculated and directly measured values for sorbed material were within 10% for FOSA and 30% for fluoxetine under nonfouled conditions, and within a factor of 2.5 for the fouled FOSA case. The results presented here for FOSA and fluoxetine show that the proposed sorption-rejection mass balance correlation can successfully describe the rejection behavior of a sorbing solute: An exponential decline in rejection is quantitatively linked to the mass sorbed to the membrane at the end of an experiment. While variations in conditions, such as membrane type, pH, and fouling, can influence rejection and sorption behavior, this mass-balance approach has been shown to adequately describe FOSA’s behavior under fouled conditions as well. Static Sorption Results. Table 2 shows the results of the static sorption experiments. For all measurements shown, the original concentration of fluoxetine in solution was 104 µg/L. After equilibrating the solution with one to four 1 × 3-in. coupons, the largest decreases in aqueous concentration were observed in the experiments with the NF270 PS+PA layer (95%-99%); decreases were much smaller in tests of Hydranautics PS (29%-43%) and PET (43%-63%). Table 2 shows the specific masses (i.e., mass per unit area) of each membrane layer (1) and the mass of fluoxetine sorbed during static soption experiments on a per unit membrane area (2) and per unit membrane layer specific mass (3) basis for the following membrane layers: NF270 PET, Hydranautics PS, NF270 PS+PA, and the calculated values for the NF270 PA layer. VOL. 44, NO. 7, 2010 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 2. Results of Static Sorption Experiments: (1) Specific Mass of Membrane Layer and Mass of Fluoxetine Sorbed Normalized with Respect to Aqueous Fluoxetine Concentration and (2) Membrane Area or (3) Mass of Membrane Layera membrane layer PET PS PS + PA PA

(1) specific mass of membrane layer (g/m2)

(2) area-normalized sorbed mass (µg/m2)/(µg/L)

(3) mass-normalized sorbed mass (µg/g)/(µg/L)

78.9 20.6 20.9 0.04b

52 ( 13 23; 25 3,200 ( 700 3,200 (700

0.67 ( 0.17 1.0; 1.3 160 ( 40 81,000 ( 21,000

a Values shown in (2) and (3) are the mean ( the standard deviation of three samples (except for PS, where one sample was lost, and therefore the two individual results are shown), each with a different membrane area, and therefore a different final aqueous concentration b Layer mass estimated assuming 40 nm thickness and 1 g/mL density. Sorbed concentration found by subtracting PS from PS + PA data.

TABLE 3. Summary of Sorption and Rejection Dataa sorption in µg/m2 compound (experiment)

SS rejection (%)

MW [g/mol]

initial feed concentration

average

STD

average

STD

sorption observed: caffeine (A) DEET (A) FOSA (alone) FOSA (mix) FOSA (mix, fouled) fluoxetine (B) TCEP (B) atrazine (B) trimethoprim (B)

194.2 191.3 499.0 499.0 499.0 209.3 285.5 215.7 290.3

10-25 µg/L 100 µg/L 250 ng/L 250 ng/L 250 ng/L 100 µg/L 100 µg/L 100 µg/L 100 µg/L

85 5,400 540 11 150 4,500 130 110 71

53 4,300 110 1.0 19 1,600 28 36 25

66 84 80 92 42 91 74 83 88

6 3 2 NA 4 NA 7 5 3

no sorption observed: caffeine (B) DEET (B) pentoxifylline (B) dilantin (B) sulfamethoxazole (A)

194.2 191.3 278.3 252.3 253.3

100 µg/L 100 µg/L 100 µg/L 100 µg/L 100 µg/L

ND ND ND ND ND

NA NA NA NA NA

77 87 94 89 87

5 4 1 3 5

a Sorption data shown are averages and standard deviations of six replicates each. Rejection data shown are averages and standard deviations of the rejection calculated from six permeate and two feed concentration replicates each. STD ) standard deviation, NA ) not applicable, ND ) not detected.

These results are consistent with the 4500 ( 1600 µg/m2 fluoxetine extracted from the NF270 membranes after crossflow experiments discussed below (see Table 3). Direct comparison is complicated because (1) aqueous concentration in cross-flow experiments averaged approximately 60 µg/L, whereas the final aqueous concentrations in the static experiments were 1-5 µg/L in the three PS + PA samples above, and (2) in static sorption experiments, fluoxetine had access to both membrane surfaces, while in cross-flow experiments, PS and PET layers were shielded by the PA separating layer. Regardless, Table 2 shows that essentially all fluoxetine sorbed by the membrane is sorbed in the PA layer, the same layer that is known to be responsible for the rejection behavior of the membrane (despite the fact that the membrane is only approximately 0.04% PA by mass). It is therefore a reasonable approach to use the total extracted mass as a surrogate for the amount sorbed to the PA layer in the sorption-rejection experiments, at least for strongly sorbing compounds, such as fluoxetine and the other similar compounds discussed in this study. Effects of Sorption on the Steady-State Rejection of Trace Organics. Table 3 provides a summary of the sorption and rejection data obtained; these data are also shown graphically in Figures S3 and S4 of the SI. Table 3 shows that several compounds sorb, notably DEET (A), fluoxetine (B), and FOSA, and to a lesser extent caffeine (A), TCEP (B), trimethoprim (B) and atrazine (B). The remaining compounds were not found in the membrane extract above the extraction method quantification limits of between 50 and 150 µg/m2. Steady2596

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state rejections ranged from 65% (for caffeine (A)) to above 95% (for pentoxifylline, detection limit shown). No significant trend is seen in the increase of rejection as a function of molecular weight (see also Figure S4 in the SI). The compounds, however, can be divided into two groups, based on their sorption tendency, as done in Table 3, where nonsorbing compounds are defined as those whose concentration in the membrane extract was below the detection limit. Once this grouping has been completed, linear fits can be made to both data sets. While the fits (not shown) are still poor overall, a trend is observed that indicates nonsorbing compounds are generally rejected more for their size than those that sorb, as has been shown previously for single compounds (15). An interesting additional observation can be made about the sorption behavior FOSA: When it is alone in solution, it sorbs nearly 2 orders of magnitude more than when it is present in a mixture of other PFCs (which also sorb to a certain extent (8)). A similar result is found for the sorption behavior of DEET and caffeine, which is strikingly different between experiments A and B. Both sorb to a significant extent in A and do not sorb measurably in B; this is despite the the initial feed concentration of caffeine in A being less than a quarter of that in B. The difference in all three cases is likely caused by competitive sorption processes. As explained above, in experiment A, many of the compounds were present at much lower levels than in experiment B. Thus, a possible explanation is that in experiment B, potential sorption sites for caffeine and DEET were occupied by other compounds, preventing any significant degree of sorption

by caffeine and DEET, as described, for example in the simple competitive adsorption model developed by Braeken et al. (19). A similar case can be made for the difference in FOSA sorption behavior. The effect of the decreased sorption tendency in FOSA, DEET and caffeine on their rejections can also be seen in Table 3: In all three cases steady-state rejection is lower where sorption is higher. A mere “dissolution” or “partitioning” model does not explain these results, because those compounds for which steady-state rejection is reached more slowly are also those for which rejection is lower and more material accumulates in the membrane matrix, that is, more sorption takes place. If it were merely a quicker diffusive process that allowed the solutes to pass through more quickly, therefore resulting in a lower rejection, breakthrough, and the attainment of steadystate rejection, should be much faster than for the nonsorbing compounds which exhibit higher rejection. Since the results presented herein illustrate that this is clearly not the case, thehomogeneityassumptionimplicitinthesolution-diffusion model must be inaccurate, and an updated model is necessary to account for the effects of inhomogeneity with respect to sorptive processes. Effects on Water Flux. According to the solution-diffusion theory, the transport of water and solutes through the membrane occurs by the same mechanism, as described briefly in the introduction. Therefore one might expect factors that influence the transport of one to also influence the transport of the other. Interestingly, while the accumulation of organic compounds within the membrane had a significant effect on the sorption and rejection of other such contaminants, this did not affect the flow of water, as evidenced by the stable water flux observed throughout all experiments (all run at constant pressure). In fact, no significant differences in water flux were observed between operation with pure deionized water feed and operation with the experimental solutions. Although more research is needed, the data presented here suggest that the predominant (though perhaps not exclusive) transport paths of trace contaminants through NF membranes, i.e. solution-diffusion, may be different from those of water, that is, small-scale pore-flow. This hypothesis would provide an explanation for why the sorption of these contaminants has such a significant effect on the rejection of other organic contaminants while leaving the water flux unchanged.

Acknowledgments Funding for this work was provided by the Santa Clara Valley Water District (Agreement A2727A), the Metropolitan Water District (Agreement 41808), the California Department of Water Resources, the WateReuse Foundation (WRF-06-020), and a joint National Water Research Institute/American Membrane Technology Association Graduate Fellowship awarded to Eva Steinle-Darling. Thanks to Dow/FilmTec and Hydranautics for providing membrane samples, and to Jennifer Dougherty for help with analytical measurements.

Supporting Information Available Derivations of the mass balance eqs 1-19, as well as Figures S1-S4. This material is available free of charge via the Internet at http://pubs.acs.org.

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