Environ. Sci. Technol. 2006, 40, 350-356
Competitive Effects of Natural Organic Matter: Parametrization and Verification of the Three-Component Adsorption Model COMPSORB LI DING, BENITO J. MARIN ˜ AS,* LANCE C. SCHIDEMAN, AND VERNON L. SNOEYINK Department of Civil & Environmental Engineering and Center of Advanced Materials for the Purification of Water with Systems, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 QILIN LI Department of Civil, Construction & Environmental Engineering, Oregon State University, Corvallis, Oregon 97331
Natural organic matter (NOM) hinders adsorption of trace organic compounds on powdered activated carbon (PAC) via two dominant mechanisms: direct site competition and pore blockage. COMPSORB, a three-component model that incorporates these two competitive mechanisms, was developed in a previous study to describe the removal of trace contaminants in continuous-flow hybrid PAC adsorption/membrane filtration systems. Synthetic solutions containing two model compounds as surrogates for NOM were used in the original study to elucidate competitive effects and to verify the model. In the present study, a quantitative method to characterize the components of NOM that are responsible for competitive adsorption effects in natural water was developed to extend the application of COMPSORB to natural water systems. Using batch adsorption data, NOM was differentiated into two fictive fractions, representing the strongly competing and pore blocking components, and each was treated as a single compound. The equilibrium and kinetic parameters for these fictive compounds were calculated using simplified adsorption models. This parametrization procedure was carried out on two different natural waters, and the model was verified with experimental data obtained for atrazine removal from natural water in a PAC/membrane system. The model predicted the system performance reasonably well and highlighted the importance of considering both direct site competition and pore blockage effects of NOM in modeling these systems.
concentrations of 0.5-12 mg/L as carbon (1), having molecular weights (MW) of several hundred to over 10 000. NOM has been shown to reduce the adsorption capacity of activated carbon for trace compounds, typically present at concentrations in the microgram- or nanogram-per-liter level, when both substances are exposed to the adsorbent at the same time, and when carbon is equilibrated with NOM prior to being exposed to the trace compound (2, 3). Carter et al. identified direct site competition and pore blockage as the two primary mechanisms of competitive adsorption between trace compounds and NOM (4). Small, strongly adsorbing NOM molecules with a size comparable to that of the target compound adsorb in the same size pores as the target compound, thus exerting direct site competition and causing a reduction in adsorption capacity for the target compound. In contrast, large NOM molecules that may not adsorb on the same sites as the target compound are capable of constricting or blocking pores, through which the trace compound travels to access final adsorption sites. This phenomenon reduces the rate of adsorption kinetics for the trace compound (5), and the extent of this effect depends on molecular weight distribution (MWD) of the NOM as well as the pore size distribution and configuration of activated carbon pores. Li et al. found evidence that the pore-blocking fraction of NOM is mostly in the MW range of 200-700 dalton (6). Powdered activated carbon (PAC) can be effectively applied to water, together with the membrane filtration process, in reactor configurations such as hybrid PAC adsorption/membrane filtration systems (7). These hybrid systems make it possible to simultaneously remove dissolved and particulate contaminants by adsorption and filtration mechanisms, and they allow for carbon contact times much longer than the reactor hydraulic retention time, which enables more efficient use of PAC adsorption capacity. However, the typical carbon retention times used in these hybrid systems (less than 2 h) are usually still inadequate to achieve adsorption equilibrium. Li et al. (8, 9) made significant progress in the study of competitive adsorption in flow-through systems by developing the three-component model COMPSORB and applying it to quantify the effects of competition between a trace target contaminant and two model compounds representing the strongly competing (SC) and pore blocking (PB) fractions of NOM. This model was able to accurately predict the rate of adsorption for all three compounds. The primary objective of this research was to develop a procedure to extend the application of the COMPSORB model to natural water systems where a variety of unknown compounds in the background NOM contribute to competitive adsorption effects by direct site competition and pore blockage. The model was then verified by comparing model predictions with experimental data obtained with a continuous-flow PAC/membrane system.
Materials and Methods Introduction Competition between target trace compounds and natural organic matter (NOM) is common in activated carbon processes used for drinking water treatment. NOM is a complex, site-specific mixture of numerous organic compounds present in both ground and surface waters at * Corresponding author phone: +1 217 333 6961; fax: 1 217 333 6968; e-mail:
[email protected]. 350
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Water. Distilled deionized (DDI) water as organic free water (OFW) and two natural waters were used in this study. Groundwater from the Clinton Water Works (CWW), Clinton, IL, was collected before treatment and stored in a stainless steel barrel at 4 °C in a cold room. Prior to an experiment, the water was warmed to ambient temperature and passed through a nylon membrane filter with a nominal pore size of 0.45 µm (OSMONICS, Minnetonka, MN) to remove suspended solids. The dissolved organic carbon (DOC) concentration of CWW water, measured using a Phoenix 8000 10.1021/es050409u CCC: $33.50
2006 American Chemical Society Published on Web 12/02/2005
TABLE 1. Selected Characteristics of Norit SA UF Carbona property
batch A
batch B
BET surface area (m2/g) micropore surface area (m2/g) mesopore surface area (m2/g) micropore volume (cm3/g) mesopore volume (cm3/g)
1085 662 423 0.226 0.885
1112 615 421 0.214 0.844
a Discrepancies in pore surface area and volume data for PAC batches A and B might not reflect actual differences but rather they might be the result of general analytical variability.
TOC analyzer (Tekmar-Dohrmann, Cincinnati, OH), was 7.6 ( 0.2 mg/L. The second natural water was groundwater from a well located adjacent to the Newmark Civil Engineering Laboratory (NCEL) building at the University of Illinois at Urbana-Champaign, Urbana, IL. NCEL water, with a DOC of 2.6 ( 0.2 mg/L, was passed through a greensand filter to remove iron and manganese and a 0.45 µm membrane filter to remove particles before use. Adsorbent. Two batches of NORIT SA-UF PAC were used. Batch A (NORIT France, S.a.r.l., Le Blanc Mesnil Cedex, France) was used in the experiments with CWW water, and batch B (NORIT Netherlands, B.V., Amersfoort, Netherlands) was used in experiments with NCEL water. Relevant carbon properties are presented in Table 1. Prior to use, the carbon was taken out of the desiccator, oven-dried overnight at 105 °C, and placed in the desiccator for cooling. Trace Organic Compound. Atrazine, an herbicide commonly found in source waters, was chosen as the target trace compound. Carbon-14 radio-labeled atrazine (Syngenta Crop Protection, Inc., Greensboro, NC) was used. A stock solution at a concentration of about 7.5 mg/L was prepared using DDI water and kept at 4 °C until use. This stock solution was diluted to make up the test solutions. Isotherm Experiments. Atrazine isotherm tests were conducted in OFW and in natural waters using the conventional bottle-point technique (10). In the tests performed in natural waters, DOC concentration was also monitored. Samples were taken from these bottles after a 7 day contact time and analyzed as described previously (11). Adsorption Kinetic Experiments. Two types of atrazine adsorption kinetic tests were carried out: (a) adsorption on fresh carbon in OFW and (b) adsorption on carbon preloaded with NOM from natural waters. For the test in OFW, atrazine was dosed into 2 L of OFW in the container of a jar-test apparatus. The target initial atrazine concentration was 10 µg/L. At time zero, a suspension of preweighed carbon was dosed into the jar to reach a carbon concentration of 2 mg/L. The test solution was mixed by mechanical stirring at 170 rpm in a Phipps and Bird (Richmond, VA) jar tester, and samples were taken at various times. For the preloading tests, different carbon surface loadings of NOM were achieved by dosing different amounts of fresh carbon, 2, 4, 8, and 12 mg/L for CWW water, and 4, 7.5, and 10 mg/L for NCEL water, into 2 L of the test solution. The resulting suspension was continuously mixed for 4 days, at approximately 100 rpm, in order to keep the PAC uniformly dispersed. The kinetic test was started at the end of the 4 day preloading period by dosing atrazine into each jar aiming at an initial concentration of 10 µg/L and increasing the stirring speed to 170 rpm. Atrazine samples were taken at predetermined times and analyzed following procedures described previously (11). DOC adsorption kinetic tests on fresh carbon were conducted in a similar manner, using carbon doses of 15 and 30 mg/L for CWW waters and 10 and 20 mg/L for NCEL waters. Samples were taken using a polytetrafluoroethylene siphon tube in order to collect a uniform sample of water plus PAC, and thus to keep the PAC concentration inside the
FIGURE 1. Atrazine isotherms in OFW and in CWW water. jars from changing with sampling. The sample was immediately passed through a 0.45 µm membrane filter; the first 20 mL was used to rinse the filter and discarded before a 40 mL aliquot was collected for DOC analysis. Molecular Weight Distribution (MWD) of NOM. The MWD of NOM was measured with a high-performance liquid chromatography (HPLC) system (HP 1090, Series II, HewlettPackard Co., Wilmington, DE) using a size exclusion chromatography (SEC) column (Protein-Pak 125, Waters Corp., Milford, MA). The details are provided elsewhere (6). Flow-Through PAC/Membrane Experiments. The experimental setup was similar to that described previously (11). The membrane reactor was a 350 mL stirred cell (Millipore, Bedford, MA) with a Nuclepor Etch-Track membrane (Whatman, Clifton, NJ) having a nominal pore size of 1 µm installed on the bottom. The cell was filled with influent water, which is made of pretreated natural water spiked with atrazine to achieve a target influent concentration of 10 µg/ L, and then a pulse input of preweighed PAC in the form of slurry made with OFW was added through the pressure relief port located in the top plate of the cell. A peristaltic pump (Masterflex, Cole Parmer, Barrington, IL) was used to maintain a constant flow rate of 10 mL/min throughout the experiment for an overall operating time of 360 min, which corresponds to the interval between two consecutive membrane backwashes. Effluent samples were collected for atrazine and DOC analyses. Two experimental runs were performed with each water to assess the effect of carbon dose. The amount of PAC added as a pulse input at the beginning of each run was 7.2 or 14.4 mg, corresponding to an equivalent dose of 2 or 4 mg per liter of treated water, respectively.
Results and Discussion Model Parametrization. Equilibrium Parameters. (a) Atrazine. Single-solute isotherms for the adsorption of atrazine in OFW on PAC batches A and B are shown in Figures 1 and 2, respectively. The Freundlich isotherm equation (eq 1) was used to fit the data sets. The resulting Freundlich constants are shown next to the corresponding fitting curves in the figures, and they are also summarized in Tables 2 and 3, respectively.
q ) KCe1/n
(1)
Isotherms for the adsorption of atrazine in CWW and NCEL waters are also presented in Figures 1 and 2, respectively. Two initial atrazine concentrations were tested for each water, 10 and 60 µg/L in CWW water, and 10 and 22 µg/L in NCEL water. The lower position of the curves in natural water compared to the curves in OFW revealed reduced atrazine adsorption capacities in natural water due to competitive effects exerted by NOM, with the reduction being more pronounced at lower initial atrazine concentrations. VOL. 40, NO. 1, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 3. Adsorption isotherm of the PB fraction of CWW and NCEL waters on Norit SA UF carbons.
FIGURE 2. Atrazine isotherms in OFW and in NCEL water.
TABLE 2. Adsorption Properties for Atrazine and the Strongly Competing and Pore-Blocking Fractions from CWW Water on Norit SA UF Carbon (Batch A)a K (µg/mg)(L/µg)(1/n) 1/n C0 (µg/L) Ds (cm2/min) a
atrazine
SC fraction
PB fraction
26.5 0.409 N/A 1.70 × 10-11
26.5 0.409 400 (200 as C) 1.70 × 10-11
7.83 × 10-6 1.94 7310 as C 2.11 × 10-10
qcr ) 79.9 mg/g; β ) 0.055.
TABLE 3. Adsorption Properties for Atrazine and the Strongly competing and Pore-Blocking Fractions from NCEL Water on Norit SA UF Carbon (Batch B)a (µg/mg)(L/µg)(1/n)
K 1/n C0 (µg/L) Ds (cm2/min) a
atrazine
SC fraction
PB fraction
25.2 0.448 N/A 1.70 × 10-11
25.2 0.448 125 (63 as C) 1.70 × 10-11
3.92 × 10-4 1.67 2540 as C 2.81 × 10-11
qcr ) 38.3 mg/g; β ) 0.058.
(2)
A nonadsorbing fraction was not included because of the desire to simplify the model parameter determination. Consistent with previous work by Li et al. (8, 9), the SC fraction was the only fraction that affects the atrazine isotherm, and it was treated as a single compound based on the concept of the equivalent background compound model (12-15). Additional simplifying assumptions were that NOM molecules, competing with trace compounds for adsorption sites, had the same molecular weight and adsorption properties as those of the trace compound, including the Freundlich constants, K and 1/n, as well as the molecular weight of the SC fraction, and that carbon accounted for 50% of the NOM molecular weight. The ideal adsorbed solution theory (IAST) was applied to calculate equilibrium concentrations for atrazine and the SC fraction as a function of carbon dose (16) (eq 3, for bi-solute systems), where n1 and K1, and n2 and K2, are single-solute Freundlich constants (eq 1) for atrazine and the SC fraction, with n1 equal to n2 and K1 equal to K2. The unknown we need to solve for is the initial concentration of the SC fraction, C0,2, to calculate qSC (q2) with eq 4. Therefore, the two competitive isotherms obtained for atrazine in each natural water (Figures 1 and 2) were fitted to eq 3 simultaneously to search for the best fit of C0,SC (C0,2), and the 352
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)[ )[
( (
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] ]
q1 n1q1 + n2q2 q 1 + q2 n1K1
n1
q2 n1q1 + n2q2 Ce,2 ) q 1 + q2 n2K2
n2
Ce,1 )
where qi )
C0,i - Ce,i with i ) 1, 2 Cc
(3)
(4)
Cc ) carbon dose The initial concentration of the PB fraction C0,PB was then obtained by subtracting C0,SC from the total DOC, C0,DOC:
C0,PB ) C0,DOC - C0,SC
(b) NOM. NOM was divided into two fictive fractions, SC and PB, each quantified in terms of DOC. Total DOC concentration was the sum of DOC attributable to the two fractions:
CDOC ) CSC + CPB
results are given in Tables 2 and 3. The good agreement of the lines of best fit with the experimental data shown in Figures 1 and 2 supported the use of these C0,SC values, and demonstrates that assuming that the Freundlich parameters of the SC fraction were the same as those of atrazine was reasonable for modeling purposes.
(2′)
Because of the molecular size difference between the PB and SC fractions, it is reasonable to assume that they adsorb on different adsorption sites and that their isotherms can be treated as single-solute isotherms, each obeying the Freundlich isotherm equation. Aqueous-phase equilibrium concentrations for the SC fraction, Ce,SC, were first calculated using the Freundlich constants described above for the series of carbon doses that were used in the DOC isotherm test:
qSC ) KSCCe,SC1/nSC where qSC )
C0,SC - Ce,SC Cc
(1′) (4′)
Subtracting the resulting Ce,SC from the total equilibrium DOC concentration Ce,DOC yielded the aqueous-phase concentration of the PB fraction (i.e., Ce,PB ) Ce,DOC - Ce,SC), from which the equilibrium solid-phase concentration qPB at each carbon dose was calculated using eq 4′′. The resulting values were then fit with the Freundlich equation (eq 1′′) to obtain K and 1/n for the PB fraction (Figure 3). The resulting fitting of the Freundlich isotherm constants for the PB fraction is listed in Tables 2 and 3.
C0,PB - Ce,PB Cc
(4′′)
qPB ) KPBCe,PB1/nPB
(1′′)
qPB )
FIGURE 4. Atrazine adsorption kinetics in OFW on Norit SA UF carbons (Cc ) 2 mg/L). Kinetic Parameters. The (pseudo-) single-solute adsorption concept and the homogeneous surface diffusion model (HSDM) (17-20) were used to determine the surface diffusion coefficient Ds for the three components, atrazine, the SC fraction, and the PB fraction. A routine named “SEARCH”, developed by Traegner et al. (21), was used to search for the Ds values that provide the best fit of the kinetic data. (a) Atrazine. Atrazine adsorption kinetic data obtained with PAC batches A and B in OFW are shown in Figure 4. The resulting Ds values, similar for the two carbon batches, are presented in Tables 2 and 3. These Ds values should be considered effective diffusion coefficients, combining both surface and pore diffusion. Although for single solutes, surface diffusion tends to predominate over pore diffusion in the intraparticle mass transport mechanism, pore diffusion might be a more accurate description for trace compounds in the presence of NOM (22, 23). For modeling purposes, the surface diffusion model was able to give a good quality of fit, and it was used for simplicity and consistency throughout the study. The atrazine adsorption kinetics on PACs preloaded with CWW and NCEL NOM are shown in Figure 5. The SEARCH routine was used to obtain Ds for each data set. The resulting Ds values (Tables 4 and 5) revealed that the rate of adsorption decreased with decreasing carbon dose. To confirm that this observation was due to a reduction in kinetics, an additional 7 day data point from the preloading curve on carbon preloaded with CWW water at 2 mg/L was taken. Its final C/C0 value of 0.63 was significantly lower than that observed after 4 h and consistent with that predicted from the equilibrium isotherm, supporting that it took significantly longer than 4 h for the preloaded carbon to reach equilibrium. Carbon surface loading of the PB fraction was quantified by using the Freundlich equation for the PB fraction together assuming that equilibrium was achieved for NOM in the 4 day preloading period (Tables 4 and 5). The effect of the PB fraction surface loading on Ds was represented by the empirical expression developed by Li et al. (8), eq 5. Fitting of the data to this expression resulted in the parameters qcr and β, summarized in Tables 2 and 3. As depicted in Figure
{
Ds q eqcr 1 ) q > qcr exp[-β(q q )] ) exp(βq )exp(-βq) Ds,0 cr cr (5)
6, qcr is the critical (threshold) carbon surface loading at which the pore blockage effect begins to occur (the intercept of the curve with x-axis), and β describes how fast Ds decreases with increasing surface loading in excess of qcr. Although the fit was not perfect, a sensitivity test and an attempt to fit the data with the logistics function revealed that the COMPSORB model prediction could not be improved much. It appeared
FIGURE 5. Atrazine adsorption kinetics on Norit SA UF carbon preloaded with natural waters (legends are carbon doses): (a) CWW water and carbon batch A; (b) NCEL water and carbon batch B.
TABLE 4. Surface Diffusion Coefficient of Atrazine vs Carbon Surface Loading of the PB Fraction from CWW Water for Norit SA UF Carbon (Batch A) Cc (mg/L) 2 4 8 12
qPB (mg/g) 235 210 175 154
Ds (cm2/min) 10-14
1.80 × 3.10 × 10-13 1.20 × 10-12 1.78 × 10-12
Ds/Ds,0 0.00106 0.0182 0.0706 0.105
TABLE 5. Surface Diffusion Coefficient of Atrazine vs Carbon Surface Loading of the PB Fraction from NCEL Water for Norit SA UF Carbon (Batch B) Cc (mg/L)
qPB (mg/g)
Ds (cm2/min)
Ds/Ds,0
4 7.5 10
130 103 85
6.91 × 10-14 7.84 × 10-13 7.98 × 10-13
0.00406 0.0461 0.0469
that factors other than the quality of parameter fit affected the output of the COMPSORB model. (b) NOM. All NOM kinetics curves featured a sharp concentration drop in the first 10 min, followed by a slower decrease. Because there was no means for direct measurement of the amount of the SC and PB fractions that adsorbed during the DOC kinetic test, it was assumed that the SC fraction had the same Ds value as atrazine, consistent with the previously made assumption that the SC fraction had the same adsorption properties as atrazine. The aqueousphase concentrations of the SC fraction at each measurement time were calculated using the HSDM model, and the resulting values were subtracted from the measured total DOC concentrations to yield the concentration of the PB fraction versus time (Figure 7), with the horizontal lines as the equilibrium values calculated from the Freundlich equations. VOL. 40, NO. 1, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 6. Surface diffusion coefficients for atrazine vs carbon surface loading of the PB fraction from CWW water and NCEL water for Norit SA UF carbons.
FIGURE 7. Adsorption kinetics of the PB fractions from natural waters on Norit SA UF carbon: (a) CWW water and carbon batch A; (b) NCEL water and carbon batch B. The data sets at the lower PAC dose in each figure were fitted with the HSDM in order to obtain Ds, and the results are presented in Tables 2 and 3. The Ds values were then used to predict the kinetic curves at the higher PAC doses. The predictions represented the data reasonably well. It is interesting to notice that the Ds of the PB fraction is higher than that of atrazine despite the PB fraction having a larger molecular size. The following explanation is proposed to address this observation. Based on the HSDM assumption of homogeneity inside carbon particles, the PB fraction diffuses to the center of the PAC particle until a uniform concentration inside the carbon is achieved. However, the PB fraction may access only large pores, which are most likely close to the outer surface of a carbon particle. If so, the PB fraction may only need to travel a short distance to reach adsorption sites on the outer part of a PAC particle, thus rapidly inducing pore blockage effects. If the fitting model were changed to more accurately represent the actual length of the diffusion path, the Ds of the PB fraction would decrease, but unfortunately the actual length could not be easily determined. A sensitivity analysis on the effect of diffusion 354
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FIGURE 8. Molecular weight distribution of NOM in CWW and NCEL waters. path length on the values of Ds,PB revealed that path length had a tradeoff effect on Ds,PB but no effect on the quality of model fit. The HSDM was not changed because the model should accurately predict the rate of approaching equilibrium, even though it would not accurately predict the distribution of the PB fraction within a carbon particle. Comparison of the Two Natural Waters. The two natural waters shared certain similarities. The SC fraction accounted for a small portion of the total DOC in both waters (2.7% for CWW water and 2.4% for NCEL water). Consequently, the PB fraction becomes the majority of the NOM, which is more of a modeling approach than physically representing the true components of NOM. The surface diffusion coefficients of the PB fraction for the two waters were both greater than that of atrazine (and the SC fraction), which cannot be taken at face value and interpreted as faster kinetics. A difference was observed in the effect of the PB fraction. Although the β values were approximately the same for both waters, the critical PB fraction loading qcr for CWW water was approximately twice that for NCEL water. The NOM MWD shown in Figure 8, gave the weight-averaged MW (Mw) calculated according to the equations presented by Chin and Aiken (24) for CWW and NCEL waters to be 346 and 936 Da, respectively. Previous research has shown that the removal of NOM with different molecular weights is nearly uniform over the whole range, so the MWD can represent what fraction of molecular weight is adsorbed onto activated carbon (6). Larger molecules that can access the outer carbon pores are expected to be more effective in blocking pores and reducing the adsorption kinetics of trace compounds, and thus NCEL groundwater shows earlier pore blockage than CWW. Model Verification. Results obtained for the flow-through experiments performed with CWW and NCEL waters at an influent atrazine concentration of 10.5 and 11.1 µg/L are presented in Figures 9 and 10, respectively. The average atrazine concentration in the effluent from the cell decreased from 8.3 to 6.4 µg/L for CWW water and from 6.8 to 5.6 µg/L for NCEL water when the carbon mass was increased from 7.2 to 14.4 mg/L. Higher carbon doses or shorter filtration run times could have been used to produce water with lower concentrations. For example, the atrazine maximum contaminant level of 3 µg/L, specified in U.S. regulations, could have been met if the filtration run time would have been cut to 15 and 60 min (CWW water) and 60 and 90 min (NCEL water) for the PAC mass of 7.2 and 14.4 mg, respectively. The NOM in CWW water exerted stronger competitive effects on atrazine removal than the NOM in NCEL water, with the difference resulting from a combination of SC and PB effects, and could not be readily estimated from equilibrium data only. The batch equilibrium data used for the parametrization process revealed that the SC fraction in CWW water competed more strongly for adsorption sites than did the SC fraction in NCEL water due to the higher concentration
FIGURE 9. Experimental results and model predictions of atrazine removal by the continuous-flow PAC/membrane system using Norit SA UF batch A PAC and CWW water. Cin,atrazine ) 10.5 µg/L, membrane backwash interval ) 360 min, permeate flowrate ) 0.01 L/min, stirred cell volume ) 300 mL, (a) carbon dose ) 7.2 mg; (b) carbon dose ) 14.4 mg. in CWW water, yet the reduction of atrazine adsorption kinetics caused by the PB fraction of NOM in NCEL water occurred earlier than in CWW water. Normalized atrazine effluent concentrations predicted with the COMPSORB model are compared to the experimental data sets in Figures 9 and 10. Predicted atrazine removals were initially greater than those observed with the CWW water. A possible explanation for the early stage discrepancies is that lumping all the direct competition effects into a single fictive fraction is a fairly bold assumption. A more accurate representation of the heterogeneity in direct competition effects with more than one fictive compound of different adsorbabilities could improve the agreement between measured and predicted atrazine concentrations. However, it was decided not to pursue this possibility at this time in order to retain the simplicity of the modeling approach. Another possible explanation could arise from the assumption that the pore blockage effects on the SC fraction kinetics are equivalent to that on atrazine. In reality, the SC fraction might actually be affected by pore blockage to a lesser degree, because the so-called SC fraction and PB fraction are based on the separation of competitive effects instead of physical separation. They could be the same molecules exerting competition on both capacity and kinetics, and without reduced kinetics due to adsorption of itself. Therefore the SC fraction could diffuse faster than atrazine, which may result in fewer adsorption sites available to atrazine. As run time increased, the surface coverage with the PB fraction increased to the point that it decreased the diffusion coefficient of atrazine. This caused the effluent concentration of atrazine to increase rapidly. While the agreement of the predicted curve with the data in this region is reasonable in the case of the CWW water, some of the differences observed were possibly attributable to kinetic effects not taken into
FIGURE 10. Experimental results and model predictions of atrazine removal by the continuous-flow PAC/membrane system using Norit SA UF batch B PAC and NCEL water. Cin,atrazine ) 11.1 µg/L, membrane backwash interval ) 360 min, permeate flowrate ) 0.01 L/min, stirred cell volume ) 300 mL, (a) carbon dose ) 7.2 mg; (b) carbon dose ) 14.4 mg. account in the model. First of all, the correlation between Ds of atrazine and PB surface loading was not perfectly described by the empirical equation (eq 5 and Figure 6); more importantly, the correlation between surface loading of the PB fraction and atrazine diffusivity was obtained from batch experiments in which PAC was allowed to preequilibrate with the PB fraction of NOM for a total period of 4 days. In contrast, the surface loading of PAC with the PB fraction in the flowthrough tests occurred concurrently to the adsorption of atrazine within a period of 6 h. Although NOM adsorption kinetic data showed that adsorption equilibrium of the PB fraction was almost reached within an hour, rearrangement and relocation of the PB molecules may occur over time without changes in its solid-phase concentration. Therefore, the empirical equation that was used to describe the effect of the PB fraction on pore blockage, based on 4 day preloading, may not be entirely accurate during the relatively short time of the experimental runs. Greater discrepancy was observed between model predictions and experimental data for NCEL water. However, the model predicted the atrazine effluent concentration more accurately for the first 20 min with this water, mainly because minimal pore blockage took place and thus the competitive adsorption between atrazine and the SC fraction was accurately described by the IAST (eqs 3 and 4), since the diffusivity of the PB fraction (2.81 × 10-11 cm2/min) in NCEL water was only 13% of that of the PB fraction (2.11 × 10-10 cm2/min) in CWW water. Despite these discrepancies, the modeling approach used in the present study is a significant advance compared to previous modeling efforts in which trace compound adsorpVOL. 40, NO. 1, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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tion from natural waters on PAC was modeled by accounting only for direct competition (13, 25-27). As discussed in more detail later, the general features and trends in the experimental data are much better represented by the modeling approach used in the present study that incorporates both direct site competition and pore blockage. Three additional sets of model simulations were performed to further illustrate and assess the effects of strong competition and pore blockage by NOM on atrazine removal efficiency. They were obtained by neglecting one or two competition effects. The curves labeled as “no competition” in Figures 9 and 10 depicted atrazine removal in the absence of NOM. The effluent concentration of atrazine would have decreased relatively quickly to normalized concentrations below 1% for periods of time much longer than the 6 h duration of the filtration runs. This comparison supports the fact that most of the competitive effects exerted by the two NOM fractions have been reasonably represented with the model. The other two curves are model simulations with one of the competitive effects absent. A comparison of the curves affected by only the PB fraction with those for OFW revealed that predicted pore blocking effects started to be noticeable after an operation time of about 30 min in the case of the CWW water, and after more than 60 min in the case of the NCEL water, both estimated at the low carbon dose studied. These differences in the triggering of pore blocking effects are generally consistent with the difference in the initial concentration and surface diffusivity of the PB fractions of the CWW and NCEL waters. In turn, comparison of the curves showing the effect of only the SC fraction with those for OFW or the natural water revealed, as discussed previously, that although direct competition by the SC fraction was the main effect early in the filtration run, pore blockage effects dominated in the later part of the run. These simulations highlight the importance of incorporating pore blockage effects into adsorption models for flow-through reactors that have long carbon retention times including PAC/membrane systems, floc-blanket reactors, slurry recirculation reactors, and granular activated carbon contactors. Incorporating pore blockage effects will significantly reduce the over-prediction of trace compound removal in these systems.
Acknowledgments This work was partially supported by The WaterCAMPWS, a Science and Technology Center of Advanced Materials for the Purification of Water with Systems under the National Science Foundation agreement number CTS-0120978. The authors would like to thank George Tang and Patrick Schwer, both of the University of Illinois Urbana-Champaign, for their respective assistance in modeling and experimental tasks.
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Received for review February 27, 2005. Revised manuscript received October 15, 2005. Accepted October 17, 2005. ES050409U
