Ion exchange characteristics of Cu

Transcription

1 /06/$ # 2006 Institution of Chemical Engineers Trans IChemE, Part B, March 2006 doi: /psep Process Safety and Environmental Protection, 84(B2): A NATURAL ZEOLITE PERMEABLE REACTIVE BARRIER TO TREAT HEAVY-METAL CONTAMINATED WATERS IN ANTARCTICA Kinetic and Fixed-bed Studies A. Z. WOINARSKI 1, G. W. STEVENS 1 and I. SNAPE 2 1 Department of Chemical & Biomolecular Engineering, University of Melbourne, VIC 3010, Australia 2 Human Impacts Research, Australian Antarctic Division, Kingston, TAS 7050, Australia Ion exchange characteristics of Cu 2þ on the natural zeolite clinoptilolite at 2 and 228C are presented to facilitate the development of a permeable reactive barrier (PRB) to treat heavy-metal contaminated waters in Antarctica. A one-dimensional mass transfer transport model describing non-equilibrium sorption of Cu 2þ in fixed-bed flow reveals that saturation capacities are independent of flow rate, but mass transfer coefficients increase with water velocity. Clinoptilolite capacity in fixed-beds is approximately 50% the capacity in equivalent batch systems, and mass transfer coefficients are between two and eight times batch-estimated values. Fixed-bed performance is significantly reduced at cold temperature, with breakthrough points and saturation capacities at 28C between 60 and 65% less than operation at 228C. The detrimental effects of cold temperature on fixed-bed performance will have significant implications for the design of a natural zeolite PRB to treat heavy-metal contaminated waters in Antarctica or other cold regions. Keywords: clinoptilolite; ion exchange; copper; transport model. INTRODUCTION Permeable reactive barriers (PRBs) are an in situ passive treatment technology that removes dissolved contaminants from polluted waters through the subsurface emplacement of reactive materials (USEPA, 1998). PRB technology is currently being investigated to treat heavy-metal contaminated surface and subsurface waters from contaminated sites, such as Thala Valley and Wilkes in the Casey Station region of Antarctica, using a range of reactive materials including natural zeolites (Woinarski, 2004). Although significant work has been achieved with PRB technology in temperate climates, very few studies have investigated their use in cold regions. These studies (Snape et al., 2001; Woinarski et al., 2003) indicate that the design of a natural zeolite barrier system suitable for use in Antarctica must involve consideration of coldregion specific constraints to barrier efficacy, which include the reduction in zeolite capacity and sorption rates at low temperatures the focus of work presented in this paper. Correspondence to: Professor G. W. Stevens, Department of Chemical and Biomolecular Engineering, University of Melbourne, VIC 3010, Australia. gstevens@unimelb.edu.au The ion exchange characteristics of natural zeolites have been well studied, with metal cation sorption occurring through a combination of ion exchange, molecular sieve processes and precipitation reactions. Equilibrium behaviour has received extensive attention, showing that clinoptilolite has a high degree of selectivity towards heavy metals including Ba 2þ, Cd 2þ, Cr 2þ, Cu 2þ, Fe 3þ, Ni 2þ,Pb 2þ and Zn 2þ (Curkovic et al., 1997; Doula et al., 2002; Panayotova, 2001; Ouki and Kavannagh, 1999). The kinetics of heavy metal ion exchange on clinoptilolite, which are typically controlled by particle diffusion (Semmens et al., 1978), have been presented for Cd 2þ, Co 2þ,Cr 3þ,Cu 2þ,Fe 3þ,Ni 2þ,Pb 2þ and Zn 2þ (Ouki and Kavannagh, 1999; Malliou et al., 1994; Inglezakis et al., 2002). The equilibrium characteristics of the clinoptilolite used in this study have been presented for Cu 2þ (Woinarski et al., 2003), and Pb 2þ and Zn 2þ (Woinarski, 2004) at 2 and 228C. While the effects of increasing temperature on equilibria have been studied and show that heavy metal exchange with clinoptilolite is an endothermic process, and metal uptake increases with temperature for Cd 2þ,Co 2þ, Cs þ and Pb 2þ (Curkovic et al., 1997; Malliou et al., 1994; White et al., 1999), little work has been conducted at low temperature. However, given the importance of equilibrium 109

2 110 WOINARSKI et al. and kinetic processes in column operation, and the apparent influence of temperature on these characteristics, it is highly likely that cold temperature will reduce the ability of clinoptilolite columns to remove heavy metals from solution. While previous work at standard laboratory temperatures has shown that clinoptilolite columns can be successfully used to remove heavy metals from solution (Inglezakis et al., 2002; Cincotti et al., 2001; Mier et al., 2001; Inglezakis and Grigoropoulou, 2003), the only low temperature column study found was by McLaren and Farquhar (1973), who found the ability of a clinoptilolite column to treat ammonium was significantly reduced at 28C compared to performance at 128C. This study investigates the Escott clinoptilolite exchange characteristics of Cu 2þ a contaminant of concern in Thala Valley and Wilkes; at 28C (the temperature of melt waters during summer in Thala Valley) and 228C in order to allow comparisons to existing literature, characterize the effects of cold temperature on fixed-bed performance and develop a model describing solute transport to facilitate the development of a natural zeolite PRB in Antarctica. MATERIALS AND METHODS Clinoptilolite Previous work (Woinarski, 2004) revealed that a large, uniform grain size is necessary for use in cold region PRBs in order to mitigate the detrimental effects of freezing and thawing, and ensure sufficient permeability when frozen. Subsequently, Escott clinoptilolite, an Australian natural zeolite, with a grain-size distribution of mm was chosen for study. The as-received clinoptilolite was converted to a homoionic sodium form, which is well known to improve ion exchange capacities and performance (Inglezakis et al., 2001). Na-clinoptilolite was used in all tests. The total cation exchange capacity of Escott clinoptilolite is 1.19 meq g 21, and the maximum Cu 2þ capacity (q max ) is and meq g 21 at 2 and 228C, respectively (Woinarski et al., 2003). Kinetic Studies Batch kinetic tests were conducted to quantify and qualify the rate-controlling mechanism of copper uptake by clinoptilolite either diffusion of ions through the surface boundary layer (film diffusion) or diffusion of ions within the zeolite particle (particle diffusion) rather than the exchange process itself (Helfferich, 1962). Approximately 15 g of clinoptilolite was contacted with 1500 ml of a 10 meq l 21 Cu 2þ solution in a sealed Erlenmeyer flask and mechanically agitated to ensure that bulk fluid diffusion rates were not significant. Solution samples were extracted at set intervals, then filtered to,0.2 mm and acidified before being analysed for copper colorimetrically at 518 nm using a GBC 916 UV-Visible Spectrophotometer. An ICP-OES (Thermo Jarrell-Ash IRIS Plasma Spectrometer) was used to analyse approximately 10% of the copper samples for quality control and replication purposes. Results from the two methods of copper analysis corresponded to within +5%. Small sample volumes were used so that the total volume of the batch system did not change by more than 10% to minimize the influence of changing zeolite/solution ratio. Tests were carried out in triplicate at 2 and 228C. Control (copper solution but no zeolite) and blank (zeolite and distilled de-ionized water) tests were conducted but found to have no significant impact on results (,5%). Although copper exchange kinetics are likely to be dominated by particle diffusion, interruption tests were conducted in duplicate at 2 and 228C to determine the rate-controlling diffusion process. Interruption tests were carried out in the same way as kinetic tests, but after 30 min the zeolite was removed from contact with the solution for a 20 min period, before being reintroduced and continued as before. In this way, in systems where particle diffusion is dominant, zeolite particle concentration profiles relax while the zeolite is out of the copper solution and uptake occurs at a faster rate upon immersion. Conversely, if film diffusion is controlling, the interruption will have no effect. Fixed-Bed Studies Fixed-bed experiments were carried out using vertical HDPE columns of 155 mm height and 28 mm internal diameter large enough to ensure that column wall effects on flow distribution are insignificant (Helfferich, 1962). Packed clinoptilolite had a porosity of 0.42, bulk density of 1.12 g cm 23, and a saturated hydraulic conductivity of 0.09 cm s 21. A 10 meq l 21 copper solution feed was introduced using a peristaltic pump in an upflow arrangement at superficial water velocities of between and cm s 21 equivalent to flow rates between Four and 15 bed pore-volumes (PV) per hour. Water samples were taken at the column exit at appropriate intervals and analysed for copper. Conductivity and ph were also measured. Column tests were carried out in duplicate for each flow rate at 2 and 228C. Control and blank column tests were conducted, but found to cause less than a 1% change in relative effluent concentrations. Following Kawabata and Nakamura (1997), axial dispersion was determined using Na-clinoptilolite packed columns by spiking a distilled de-ionized water feed at flow rates between 4 and 25 PV h 21 with a 2 eq l 21 NaCl solution and measuring column effluent conductivity. CXTFIT, a code developed by the U.S. Agriculture Department for estimating solute transport parameters using a nonlinear least-squares parameter optimization method (Toride et al., 1999), was used to solve the inverse axialdispersion problem and quantify the axial dispersion coefficient (D l ) for each flow rate and bed porosity (n). MODEL DEVELOPMENT Particle Diffusion Assuming the rate limiting step is particle diffusion, and a spherical particle, using Nernst Plank equations the fractional attainment of equilibrium on the zeolite at time t, U(t), with infinite solution boundary conditions, is (Helfferich, 1962; Inglezakis and Grigoropoulou, 2001): U(t) ¼½1 exp (z)š 0:5 (1)

3 NATURAL ZEOLITE PRB IN HEAVY-METAL CONTAMINATED WATERS 111 with z ¼ p 2 (c 1 T þ c 2 T 2 þ c 3 T 3 ) (2) 1 ¼ 0:64 þ 0:36a 0:668 c 1 (2a) 1 ¼ 0:96 2a 0:4635 c 2 (2b) 1 ¼ 0:27 þ 0:09a 1:14 c 3 (2c) where T ¼ 4D p t=d 2 p, D p is the particle diffusion coefficient (homogeneous diffusion) and d p is the mean zeolite particle diameter. The constant a is the ratio of the self-diffusion coefficients of the exchanging cations (Cu 2þ and Na þ ) and was estimated by the ratio of molecular diffusion coefficients in solution for the ions (Inglezakis and Grigoropoulou, 2001), which equals Particle diffusion coefficients were determined from a non-linear least square minimisation technique using the model presented above. Fixed-Bed Solute Transport The one-dimensional mass conservation equation for the transport of a reactive solute through saturated, homogeneous, isotropic media with steady state flow is (Freeze and ¼ 2 r (3) where C is the dissolved copper concentration, D l the axial dispersion coefficient, x is distance, v the pore water velocity, r b the bulk density of the zeolite bed, and n the bed porosity. For non-equilibrium sorption, mass transfer processes govern the rate of exchange, which is proportional to the distance the system is from equilibrium, and assuming particle diffusion control can be described by a simple linear driving force (LDF) model (Semmens et al., 1978; ¼ 60D p ðq e ^q Þ (4) d 2 p determined for copper exchange using Escott clinoptilolite as (Woinarski et al., 2003): q e ¼ 0:198C 1 þ 0:819C q e ¼ 0:653C 1 þ 1:875C (6a) (6b) at 2 and 228C, respectively. Mathematica, a general purpose mathematical program (Wolfram, 1996), was used to solve numerically the set of partial differential equations (3) and (4) describing solute flow through a clinoptilolite fixed-bed, with the initial and boundary conditions for C(x, t) and q(x, t): C(x, 0)¼ 0 and q(x, 0)¼ 0 at x 0 (7a) C(0, t) ¼ C 0 and C(1, t) ¼ 0 at t. 0 (7b) RESULTS Batch Exchange Kinetics The characteristic jump in exchange rate immediately after the interruption seen in Figure 1 indicates that particle diffusion is the rate-controlling mechanism for Cu 2þ uptake on clinoptilolite at 2 and 228C (Helfferich, 1962). While Figure 2 shows that the Cu 2þ exchange flux is lower at 28C than 228C, when viewed in terms of fractional attainment of equilibrium there is no difference between copper exchange rates at 28C and 228C (Figure 3). Indeed, Figure 3 shows that the Nernst Plank model [Equation (1)] provides a satisfactory fit to kinetic data, and particle diffusion coefficients were determined to be 3: and 3: m 2 s 21 at 2 and 228C, respectively, with an estimated error of +15%. These particle diffusion coefficients are comparable to those presented in the literature for copper and other heavy metal cations (Inglezakis et al., 2002; Dyer and White, 1999). Fixed-Bed Performance The extensive tailing of column breakthrough curves, which is indicative of axial dispersion and non-equilibrium where ^q is the average concentration in the zeolite and q e is the zeolite loading at the particle surface that is in equilibrium with the solution. For particle diffusion control the term 60D p /d p 2 is analogous to a mass transfer coefficient (k), where k ¼ 60D p d 2 p (5) The Langmuir equation relates solution (C) and zeolite concentration (q e ) at equilibrium and is q e ¼ q maxk L C 1 þ K L C (6) where K L is a Langmuir constant and q max is the maximum copper capacity. The Langmuir equation has been Figure 1. Interruption tests showing that particle diffusion controls the uptake rate of Cu 2þ on clinoptilolite at 2 and 228C.

4 112 WOINARSKI et al. Figure 2. Kinetic tests for the uptake of Cu 2þ on clinoptilolite at 2 and 228C. Error bars represent the 90% confidence interval. sorption processes (Worch, 2003), shows that mass transfer processes must be considered. Axial dispersion coefficients were determined using CXTFIT, which provided an excellent fit to data (coefficient of variation ¼ ), and ranged from 0: to 3: m 2 s 21, depending on flow rate (Figure 4). Column Peclet numbers were moderately low (Pe ¼ 20 to 40) and increased with flow rate, indicating that axial dispersion is a significant transport mechanism and that advective solute transport becomes increasingly dominant at high water velocities (Shackelford, 1994). For modelling purposes, the straightline equation D l ¼ 7: Re þ (Figure 4) was used to approximate the axial dispersion coefficient (in m 2 s 21 ) from the fixed-bed Reynolds number (Re). Breakthrough curves are presented for Cu 2þ in terms of relative effluent concentration (C/C 0, where C 0 is the influent concentration) at 228C (Figure 5). Table 1 shows that the time to breakthrough (taken when C/C 0 ¼ 0.1) and the corresponding fixed-bed operating capacity (determined by numerical integration of the breakthrough curves) increases with decreasing flow rate. Fixed-bed saturation capacities (q sat ) are independent of flow rate (Table 1) and approximately 50% lower than the capacity expected Figure 4. The relationship between Re (a function of temperature and water velocity) and D l at 2 and 228C. The curve ( ) represents the linear approximation to this relationship. Error bars represent the 90% confidence interval. from equilibrium studies. However, the reduction of q sat in column operations (34%) due to cold temperature is similar to the reduction of q max in batch systems (30%) (Woinarski et al., 2003) for the same clinoptilolite between 22 and 28C, and is comparable to findings from other studies using Pb 2þ (29% decrease) and Cd 2þ (33% decrease) (Curkovic et al., 1997). The detrimental effects of cold temperature on column performance are illustrated in Figure 6, which shows a steeper breakthrough curve for a set of given flow conditions and breakthrough times up to 40% earlier at 28C compared to operation at 228C. An 80% confidence interval was chosen to reflect the greater inherent variation in column work compared to batch testing, and the fact that column adsorption tests were only able to be carried out in duplicate. Contaminant Transport Modelling One-dimensional solute transport modelling was performed using batch-estimated Langmuir constants (K L and q max ) from Woinarski et al. (2003) and a mass transfer Figure 3. Modelling Cu 2þ exchange kinetics using the Nernst Plank approximation at 2 ( ) and 228C ( ). Error bars represent the 90% confidence interval. Figure 5. Copper breakthrough curves of clinoptilolite columns at 228C. Initial Cu 2þ concentration ¼ 10 meq l 21.

5 NATURAL ZEOLITE PRB IN HEAVY-METAL CONTAMINATED WATERS 113 Table 1. Fixed-bed breakthrough points and capacities. Breakthrough is taken when C/C 0 ¼ 0.1 and saturation when C/C 0 ¼ Batch-estimated maximum capacities are and meq g 21 at 2 and 228C, respectively (Woinarski et al., 2003). Assuming particle diffusion control, the batch-estimated mass transfer coefficient is s 21 and is independent of flow rate. Flow (PV h 21 ) Breakthrough point (PV) Saturation point (PV) q op (meq g 21 ) q sat (meq g 21 ) N (s 21 ) 228C C coefficient (k) based on the batch-estimated particle diffusion coefficient presented earlier. However, Figure 7 shows that the transport model using the batch-estimated parameters fails to predict the breakthrough point and effluent curve shape. By using a maximum capacity (q max ) based on the column-estimated saturation capacity (q sat ) instead of batch tests, and a particle diffusion coefficient evaluated by fitting the model to experimental data, the solute transport model satisfactorily describes experimental breakthrough curves (Figure 7). The use of column-measured capacities, as opposed to batch-estimated values, and evaluating mass transfer coefficients by fitting the model to breakthrough data, is commonly carried out in modelling studies (e.g., Inglezakis and Grigoropoulou, 2003; Worch, 2003). Particle diffusion coefficients, and corresponding mass transfer coefficients, are dependent on temperature and flow rate; and are between 2.2 and 7.6 times greater than the value determined from batch kinetic tests (Table 1). Errors in determining q sat (based on the 80% confidence interval) are approximately +10% and +15% for operation at 28C and 228C, respectively, which correspond to significantly larger errors for fitted mass transfer coefficients of +15% and +30% for operation at 28C and 228C, respectively. Hence, when considering errors from kinetic tests and fixed-bed modelling, there is no significant difference between evaluated mass transfer coefficients at 28C and 228C which corresponds to the predicted relationship for particle diffusion coefficients. However, the increase in evaluated mass transfer coefficients with flow rate is significant. DISCUSSION Batch Exchange Kinetics Discrepancies between experimental data and the model presented here can be attributed to the relatively simplistic modelling approach which treats the zeolite particle as a spherical homogeneous solid [when actual mineral particles are closer to angular oblate spheroids composed of zeolite crystals, other amorphous materials and binders (Depaoli and Perona, 1996)], and uses a single effective particle diffusion coefficient to represent the macroscopic average of the large number of ions and pores of different characteristics. Additionally, pore clogging caused by mineral dust fines can inhibit cation uptake and alter exchange kinetics (Inglezakis et al., 1999). Heterogenous diffusion models have been developed that take into account the different components of particle diffusion (e.g., Depaoli and Perona, 1996) or incorporate both film and particle diffusion (e.g., Cincotti et al., 2001; Worch, 2003). However, in each case use of these models requires the introduction of further fitting parameters with limited improvement on the fit. Figure 6. Copper breakthrough curves of clinoptilolite columns with a flow rate of 5 PV h 21 at 2 and 228C. Initial Cu 2þ concentration ¼ 10 meq l 21. Error bars represent the 80% confidence interval. Figure 7. An example of the fit of the solute transport model to copper breakthrough curves for operation at 28C and 5 PV h 21. The transport model using batch-estimated parameters fails to predict the breakthrough curve ( ), while the model using a column-estimated capacity value and evaluated mass-transfer coefficient provides an excellent fit to experimental data ( ). Initial Cu 2þ concentration ¼ 10 meq l 21. Error bars represent the 80% confidence interval.

6 114 WOINARSKI et al. Cold Temperature Effects The lack of change in diffusion coefficients with temperature is surprising. According to Helferrich (1962), cold temperature will decrease heavy-metal particle diffusion coefficients due to stronger electrostatic interactions and increased cation solvation at lower temperatures for example, cations with hydrated ionic diameters approaching the size of zeolite micropores are less mobile due to retarding pore-wall and steric effects. However, if the assumption of particle diffusion is incorrect, and considering that the diffusion of cations in zeolite micropores may be similar to Knudsen diffusion (see Cussler, 2001), the effect of cold temperature will be minimal as Knudsen diffusion at 28C is approximately 0.95 times diffusion at 228C for a given exchange system. Nevertheless, previous studies suggest that the influence of temperature on exchange kinetics using clinoptilolite is specific to the individual exchange system. For example, Malliou et al. (1994) found that particle diffusion coefficients for Pb 2þ and Cd 2þ on Na-clinoptilolite decrease by 40 to 50% between exchange at 50 and 258C, whereas other studies have found that Cu 2þ exchange kinetics with Na-clinoptilolite slightly increased with lower temperature (Panayotova, 2001). However, Panayotova (2001) also found that copper exchange rates increased with temperature for unmodified clinoptilolite. The independence of diffusion coefficients with respect to temperature indicates that cold temperature has no apparent effect on the mobility of the exchanging cations in zeolite macropores and framework channels. The decrease in copper exchange flux, rather than diffusion coefficient, can be explained by considering that the exchange process is controlled by particle diffusion, and for a given system, the rate of uptake will be dependant on the concentration gradient between the particle surface and centre. Cold temperature decreases the equilibrium capacity of clinoptilolite (Woinarski, 2003), thereby reducing the concentration gradient and lowering the exchange flux. Considering that clinoptilolite equilibrium behaviour is arguably the most influential aspect of fixed-bed performance (Inglezakis et al., 2002), and that mass transfer coefficients are relatively independent of temperature, it is likely that reduced zeolite capacity is the main cause for lower column performance at 28C compared to 228C. The similar magnitude of cold temperature effects suggests that even though there are differences between batch- and columnestimated parameters, the mechanisms by which cold temperature affects the exchange systems will be the same. Therefore, considering the calculated small effect of temperature on exchange thermodynamics, the decreased fixed-bed performance at cold temperature may be caused by increased retarding electrostatic interactions on exchanging cations, and changes in hydrated cation radii and hydration energies of the metal cation the mechanisms of which involve larger changes in enthalpy and are more likely to be influenced by temperature than the ion exchange process itself (Inglezakis et al., 2002; Helfferich, 1962). Fixed-Bed Exchange Characteristics Theoretically there should be no difference between equilibrium and kinetic exchange parameters determined from batch and column studies (Helfferich, 1962). However, column-estimated copper capacities of Escott clinoptilolite are approximately 50% lower than batchestimated values, which is commensurate with work by Inglezakis et al. (2002) who found that the copper capacity of clinoptilolite in column systems was between 20 and 32% of the maximum exchange capacity determined from batch experiments. Similar differences using clinoptilolite have been presented for Cs þ,pb 2þ,Zn 2þ,Co 2þ and Ni 2þ (Inglezakis et al., 2002; Abusafa and Yucel, 2002). The fundamental issue of why the Langmuir constant q max (which is essentially a thermodynamic parameter and should remain constant) is lower in fixed-bed systems is best approached by considering the conditions in batch and column systems. In batch systems there are initially high solute concentrations, which then decrease to reach equilibrium conditions, causing an uptake overshoot that results in higher apparent loadings if the exchange process is slow and not completely reversible (Weber and Wang, 1987). Conversely, column-estimated values may be lower than the real saturation capacity because of the low concentration gradients, and possible continual slow diffusion into the particles after apparent fixed-bed saturation has been reached (Weber and Wang, 1987). The measured column capacity may also be reduced due to the formation of hydraulic dead zones from channelling and preferential flow (not to be confused with dispersion processes) which physically limits the ability of solute cations to reach exchange sites on a portion of zeolite particles (Hlavay et al., 1982). Flow conditions also influence exchange characteristics in columns; for example, zeolite capacities and particle diffusion coefficients in columns are commonly found to vary with flow rate (Inglezakis and Grigoropoulou, 2003; Lehmann et al., 2001). However, flow conditions are unlikely to explain the reduced capacity of fixed-beds in this study because q sat is independent of flow rate. Dissimilarities in local equilibrium conditions may account for the difference between batch and column capacities. The high solution-to-zeolite mass ratios (100 : 1) in batch tests mean that as Cu 2þ is exchanged, Na þ concentrations in solution remain insignificant. Conversely, the fixed-bed solution-to-zeolite ratio is much lower, and local Na þ concentrations in the pore space will be much higher, albeit temporarily. Previous work has shown that increasing sodium concentrations inhibit copper uptake for example, copper uptake is reduced by 32% in the presence of 10 meq l 21 Na þ (Woinarski et al., 2003). Therefore, part of the difference between batch and column-estimated capacities may be due to increased local Na þ concentrations in the pore liquid. While mass transfer processes in packed columns are well studied (e.g., Helfferich, 1962; Worch, 2003; Treybal, 1981), it is commonly assumed that the controlling mass transfer process will be the same in batch and column systems. While the difference between particle diffusion coefficients was found to be insignificant, particle diffusion coefficients determined from batch kinetic tests are commonly found to differ from values determined by column studies for natural zeolites (Inglezakis and Grigoropoulou, 2003). Furthermore, the dependence of evaluated mass transfer coefficients on flow rate in this study suggests that film diffusion may be a significant mass transfer

7 NATURAL ZEOLITE PRB IN HEAVY-METAL CONTAMINATED WATERS 115 process in fixed-bed operation. Film diffusion may become controlling in column systems because of the different hydrodynamic conditions than in batch systems. Indeed, Weber and Smith (1987) found that in the initial stage of breakthrough using small columns, film mass transfer is thought to dominate, irrespective of the mass transfer processes that occur later. PRB Design Implications The reduced performance of fixed-beds at 28C indicates that the performance and lifetime of a PRB in Antarctica will be significantly less than that of an equivalent temperate climate barrier system. The detrimental effects of cold temperature will have significant design implications; for example, a cold region barrier will need to be over 35% thicker to allow for reduced performance. This will significantly increase material and installation costs, and also add to the high costs associated with transportation to remote cold region sites. While laboratory studies show that clinoptilolite fixed-beds can successfully treat copper contaminated waters, and the transport model can be used to describe column performance, the apparent disparity between batch and column tests indicates that care is needed when applying laboratory results to the field. Hydrogeological conditions in a PRB installation in Antarctica will be highly dynamic and variable compared to laboratory columns. Freezing and thawing cycles in cold regions promote particle sorting, ice lens formation and preferential flow channels in porous media. In a PRB this will result in increased axial dispersion, reduce the effective capacity and lifetime of the barrier, and increase the risk of barrier hydraulic failure. During periods when there is no surface or subsurface water flow and sediments are unfrozen, advective and dispersive solute transport will cease, and diffusion will be the dominant transport process. Studies have found that exchange fluxes increase and diffusion coefficients decrease with smaller particle sizes (Malliou et al., 1994; Inglezakis et al., 1999). Therefore, PRB performance will be affected as the particle size distribution of zeolite in a cold region barrier changes due to material break-up, loss of fines and particle sorting. While it would be difficult to model a barrier with a changing particle size distribution over time, it should still be considered in cold region PRB design. The 2Na þ Cu 2þ exchange system used in this study is relatively simple compared to natural waters in coastal contaminated sites such as Thala Valley that contain a wide range of heavy metal cations, very high concentrations of cations associated with sea spray, anionic complexes and high levels of iron. Competition from heavy metals and interference from other cations will decrease the uptake of copper (Woinarski et al., 2003). Field copper concentrations are also significantly lower than that used in this study, for example Thala Valley groundwater contains ca meq l 21 Cu 2þ. While the transport model should theoretically be applicable at field concentrations, further kinetic and fixed-bed studies will be necessary to describe solute transport in complex multi-component systems typical of waste disposal sites in Antarctica. CONCLUSIONS This study shows that cold temperature detrimentally affects the removal of Cu 2þ from solution in fixed-beds and that low temperature will have a significant influence on the design of a natural zeolite PRB to treat heavymetal contaminated waters in cold regions. Kinetic studies show that while the flux of copper into zeolite particles is lower at 28C than 228C, diffusion coefficients do not vary significantly with temperature. Fixed-bed breakthrough points and saturation capacities at 28C are ca. 65% of those at 228C. Saturation capacities are independent of flow rate, but mass transfer coefficients increase with water velocity. Fixed-bed exchange parameters are significantly different to batch-estimated values; with the capacity of clinoptilolite in fixed-beds approximately 50% the capacity in equivalent batch systems, and mass transfer coefficients between two and eight times batch-estimated values. A solute transport model, developed for nonequilibrium sorption controlled by mass transfer processes, successfully describes fixed-bed performance. However, further work investigating the uptake of heavy metals on clinoptilolite in multi-component systems under field conditions will be necessary before application of the model to facilitate the development of a cold region clinoptilolite PRB is possible. NOMENCLATURE ADRE advection-dispersion-reaction solute transport equation C solute concentration, meq l 21 d p (mass-weighted) mean particle diameter, m D l axial dispersion coefficient, m 2 s 21 D p effective particle diffusion coefficient, m 2 s 21 K L Langmuir constant, l meq 21 LDF linear driving force N mass transfer coefficient, s 21 Pe Peclet number PV pore volume, L ^q average cation concentration in the zeolite particle, meq g 21 q e equilibrium cation concentration in the zeolite particle, meq g 21 q max maximum zeolite capacity, meq g 21 q op fixed-bed operating capacity, meq g 21 q sat fixed-bed saturation capacity, meq g 21 Re Reynolds number t time, s U(t) fractional attainment of equilibrium, q/q max x distance, m REFERENCES Abusafa, A. and Yucel, H., 2002, Removal of 137Cs from aqueous solutions using different cationic forms of a natural zeolite: clinoptilolite, Separation and Purification Technology, 28: Cincotti, A., Lai, N., Orru, R. and Cao, G., 2001, Sardinian natural clinoptilolites for heavy metals and ammonium removal: experimental and modeling, Chem Eng J, 84: Curkovic, L., Cerjan-Stefanovic, S. and Filipan, T., 1997, Metal ion exchange by natural and modified zeolites, Water Research, 31(6): Cussler, E.L., 2001, Diffusion: Mass Transfer in Fluid Systems (Cambridge University Press, London, UK). 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