BIOSORPTION OF Cu FROM FERRUGINOUS WASTEWATER BY ALGAL BIOMASS   

ABSTRACT 
        The biosorbent prepared from Sargassum algal biomass binds approximately 2.3 meq/g of metal cations from water by ion exchange. The values of ion exchange equilibrium constants showed that the affinities of metals towards the biosorbent decrease in the following order Cu>Ca>Fe. A flow-through sorption column was used to continuously and selectively remove Cu²⁺ from the feed containing Cu and Fe ions. A chromatographic effect in the column performance caused by different sorption affinities of the metal ions studied was successfully predicted by the Equilibrium Column Model. The biosorbent saturated with Cu was regenerated with 0.1M HCl. When Fe(III) was present in the mixed feed solution as suspended solids (SS) the column removed Cu²⁺ by biosorption and Fe(III) solids by in-depth filtration while producing effluent free of heavy metals from the feed containing 25 mg/L of Cu²⁺, and Fe(III) as SS in the concentration range of 15-40 mg/L. Effective copper removal/recovery from ferruginous wastewater using Sargassum biosorbent was demonstrated. 

INTRODUCTION 
        Usually, many types of aquatic pollution caused by heavy metals also contain iron as one of the elements. Recently, the biosorption equilibrium of a Cd-Fe system was studied and a methodology allowing the evaluation of interferences in biosorption was introduced (1). The main objective of this work was to investigate the interference of iron in the biosorption of copper by Sargassum biosorbent, while the second one was, to evaluate the alternatives of the biosorption process which would selectively remove Cu from ferruginous wastewater , taking into account the speciation of iron in water. 

IRON SPECIATION IN WATER 
        Iron typically enters bodies of water in the form of ferrous iron (Fe²⁺) which can be oxidized to ferric iron (Fe³⁺) by the oxygen dissolved in water according to equation (1). The rate of the oxidation reaction (1) depends primarily on the pH and on the level of dissolved oxygen (DO) in water. Consequently, due to a lack of DO, Fe²⁺ is the predominant form of iron in groundwater and in deep water reservoirs. At pH < 4 and a relatively low DO, reaction (1) is very slow (2). At pH>4, however, Fe²⁺ ions oxidize quickly to Fe³⁺ ions which then react with water according to equation (2) producing ferric hydroxide precipitate and acidity. 

THEORY OF BIOSORPTION 
        Recently, several researchers have independently concluded that the major mechanism of heavy metal uptake by algae (8 , 9), fungi (10), and peat moss (11) is ion exchange. Furthermore, it has been demonstrated that algal bisorbents, similar to ion exchange resins, can be prepared in different ionic forms such as H-form and Ca-form (12). Consequently, ion exchange models have been introduced to fit and interpret the data obtained from both equilibrium and dynamic biosorption experiments (12,13). A binary ion exchange system containing divalent metal ions A and B may be described by the following exchange reaction 

             (4)

                                                 (5)

                                 (8)

; ;                              (9)

                                     (10)

COLUMN FEED (methodology abbreviated) 
        Ca-saturated biomass of Sargassum seaweed was packed in a 50 cm long column of 2.5 cm I.D. yielding an approximate packing density of 200 g/L. Feed metal solutions of FeSO₄ and CuSO₄ and Fe₂(SO₄)₃ and CuSO₄ were fed into the sorption column at pH 4 and at the rate of 2 and 3 cm/min (0.5 and 0.75 gpm/ft²). 

RESULTS AND DISCUSSION 
        According to equation (5), the sorption equilibrium data for the two binary systems Fe-Ca and Fe-Cu were plotted as (q_A/q_B) versus (C_A/C_B), where A and B represented Fe and Ca, and Cu and Fe in the two plots, respectively. Both plots yielded straight lines passing through the origin (Fe-Ca: y = 0.3028 x; Fe-Cu: y = 6.7341 x), fitting the experimental data reasonably well (Fe-Ca: R² = 0.97; Fe-Cu: R² = 0.99). This indicated that the ion exchange model provides a relatively good description of the biosorption of the heavy metals by the algal biomass. The values of ion exchange equilibrium constants determined from the slopes of the above mentioned straight lines were K_FeCa = 0.3 and K_CuFe = 6.7 for the Fe-Ca and Fe-Cu systems, respectively. The equilibrium constants defined by equation (5) are related to Gibbs free energy of ion exchange reactions (4), and hence the values of the constants reflect the relative affinities of the metals towards the binding groups in the Sargassum biomass. Consequently, the metals can be sorted in the order of descending affinity, based on the values of the equilibrium constants, as follows : Cu>Ca>Fe. 
        Furthermore, once the equilibrium constants K_FeCa, and K_CuFe are determined, the ion exchange isotherms represented by equation (10) can be plotted for the binary systems in question using the dimensionless coordinate system [ y_A , x_A ] as shown in Figure 1. The diagonal line in Figure 1 represents the hypothetical case of an equilibrium where the composition of A in the liquid and in the sorbent are the same thereby indicating that the sorbent is not selective for either of the components of the binary system. Clearly, the sorbent is selective when it sorbs preferentially either the species A or the species B from the binary mixture. The former and the latter case are represented by equilibrium isotherms of A which pass above and below the diagonal line, respectively, in the [ y_A , x_A] coordinate system. It can be seen from Figure 1 that both Cu and Ca are sorbed preferentially from their respective binary mixtures with Fe over the entire concentration interval. Furthermore, equation (5) shows that for equimolar binary mixtures of Fe and Cu, i.e. when x_Fe = x_Cu = 0.5, the value of the equilibrium constant expresses the ratio of the metal uptakes K_CuFe = (q_Cu/q_Fe) . Hence, the Sargassum biomass equilibrated with an equimolar mixture of Fe²⁺ and Cu²⁺ is expected to bind approximately 6.7 times more of Cu than Fe. 

        The natural selectivity of the biomass for Cu over Fe is well reflected in the results obtained using the flow-through biosorption column. Figure 2 displays the concentrations of Fe²⁺ and Cu²⁺ in the column effluent as a function of time for the sorption experiment during which the column packed with Sargassum biosorbent in Ca-form was fed with an equimolar mixture of Cu²⁺ and Fe²⁺. As can be seen in Figure 2, Fe²⁺, due to its low affinity, broke through the column much faster than Cu²⁺. At approximately the 35 bed volume mark, the concentration of Fe²⁺ in the column effluent plotted in Figure 2 reached the level of Fe²⁺ in the feed, i.e. (C/C₀) = 1. Hence, thereafter, Fe²⁺ was no longer uptaken by the biosorbent and trickled down the packed-bed as an inert. 

Exit Concentration Overshoot 
        Normally, when the breakthrough of a column is complete, the exit concentration(s) will equal the feed concentration(s), i.e. the column does not sorb any more, it is totally saturated. The fact that C/C₀ for Fe²⁺ continued rising above 1 after 35 bed volumes in Figure 2 may be explained by the ion exchange between Cu and Fe whereby Cu²⁺ from the solution was displacing Fe already bound to the biosorbent. Since no more Fe²⁺ was being sorbed from the liquid beyond 35 bed volumes, the released Fe²⁺ increased the overall concentration of Fe²⁺ in the liquid above the level present in the column influent. Different affinities of the two metals cause the "chromatographic effect" seen at the column exit. 
        Tit is highly desirable to predict the time and the magnitude of the exit concentration . This can be done by using the EC Mathematical Model, by solving equations (5) - (14), introduced earlier, for A, B, and C being Cu, Ca, and Fe, respectively. This particular model has a limitation in its assumption of negligible mass transfer resistance which explains why the model curve in Figure 2 is steeper than the experimental breakthrough curve for Fe²⁺ (in more detail in the full paper version) 
        A more sophisticated column sorption model (14 ) used successfully in the recent continuous-flow copper biosorption study (12) could accommodate the process mass transfer aspects. However, the applicability of its present form is limited to binary sorption systems. While its adaptation for three- and multi-component sorption systems is possible, it requires the mass transfer coefficients for the metal ions in the biosorption system. Such work is demonstrated for Cd in the following pre-print posted here (Yang and Volesky, 1998). 

Desorption 
        Desorption of the metals deposited in the biosorbent is not only possible (12) but the determination of its dynamics represents a crucial information for biosorption process design and for metal recovery feasibility assessment. Figure 3 shows the elution peaks of Cu and Fe obtained during desorption carried out with 0.1M HCl. The peak of Fe is much smaller than the peak of Cu which is in agreement with the higher selectivity of the biomass for Cu. The desorption of copper was approximately nine times faster than the process of the column saturation. 

Effect of Fe on Cu biosorption 
        Owing to competitive sorption, the uptake of a species from a multicomponent mixture is lower than the uptake of the same species from the single component system. Figure 4 summarizes the effect of the increasing concentration of Fe²⁺ on the uptake of Cu by Sargassum biosorbent. The curves in Figure 4, calculated using equation (5), show the equilibrium uptake of Cu expressed as the fraction of the maximum Cu uptake plotted against the equilibrium concentration of Fe²⁺ in the liquid at equilibrium Cu²⁺ concentrations of 0.25, 1, and 4 meq/L (8, 33, and 120 mg/L). The lower the Cu concentration in the liquid, the greater the overall reduction of Cu uptake caused by Fe²⁺, and the lower the amount of Fe²⁺ needed to decrease the Cu uptake by a fixed percentage. 
        Ferruginous wastewater with a relatively high level of DO and a pH > 3 is likely to contain most of the iron in the form of Fe³⁺ suspended solids (SS). The biosorption column can effectively sorb Cu from the feed while functioning as a filter for the Fe³⁺ solids at the SS level of 15 and 40 mg/L. Furthermore, a linear pressure drop build-up due to the in-depth retention of solids into the packed-bed (15) was relatively slow, hence allowing the operation of the column to continue until the breakthrough of Cu. However, the Cu breakthrough occurred earlier as the level of SS in the feed increased due to the physical blockage of sorption sites in the biomass. The fact that the pressure drop across the column increased approximately linearly with time provides an indication that most of the solids penetrated deeply into the bed. 
        As long as all of the iron present in the water is in the form of either Fe³⁺ SS, or Fe²⁺, the oxidation of the biosorbent by Fe³⁺ is prevented. The reductive dissolution of Fe³⁺ SS by soluble organic matter leaching from the biosorbent may occur. However, the dissolution of the Fe³⁺ SS would not substantially interfere with Cu removal considering the time scale of one biosorption cycle and the fact that the dissolution according to equation (3) is known to be a very slow process (5, 6 ). 

CONCLUSIONS 
        The options for a biosorption process utilizing Sargassum biosorbent to remove and recover copper from ferruginous water are summarized below for the two extreme cases of water containing only ferrous form iron and water containing exclusively ferric form of iron. 
I. Water with a low level of DO and all of the iron in ferrous (Fe²⁺) form 
        Using [C(Cu²⁺), C(Fe²⁺)] coordinates, the regions of high, intermediate, and negligible interference of Fe²⁺ in the sorption of Cu²⁺ were constructed in Figure 5. In the regions of high and negligible interference, iron lowers the uptake of copper by more than 40%, and by less than 5%, respectively, as compared to the copper uptake from water containing only Cu²⁺. The borders between the regions in Figure 5 were calculated using equation (8) and fixed values of q(Cu)/Q of 0.6 and 0.95, respectively. It is clear that the removal /recovery of Cu from ferruginous water by biosorption can be considered effective only if the metal content of water falls into the ranges of either low or intermediate interference. 

II. Water containing only ferric iron in the form of Fe(III) suspended solids 
        Figure 6 summarizes the interference of Fe³⁺ SS in the removal of Cu²⁺ by biosorption. Water containing less than 40 mg/L Fe³⁺ SS may be directly fed into biosorption columns. If the level of SS in the water exceeds 40 mg/L, a partial removal of SS in a pond and/or a clarifier is necessary prior to biosorption of copper in columns. Depending on Cu/Fe molar ratio and pH, however, a portion of the overall Cu content may sorb on the Fe³⁺ precipitate during settling. The lines indicating the percentage of the overall Cu content sorbing on Fe³⁺ SS in Figure 6 were calculated from data previously published by Gutzman et al. (7 ) 

SYMBOLS 
A, B      divalent metal species 
C(M)     concentration of metal M in the liquid [ meq/L ] 
C₀(M)     concentration of metal M in the feed to a flow-through column [meq/L] 
C(M)/C₀(M)     relative concentration in column effluent [-] 
K_AB     equilibrium ion exchange constant defined by equation (5) [-] 
q(M)    equilibrium uptake of metal M by the biosorbent [ meq/g ] 
Q         concentration of metal binding sites in the biosorbent [ meq/g ] 
x_A        equilibrium equivalent fraction of species A in the liquid [-] 
y_A        equilibrium equivalent fraction of species B in the sorbent [-] 
T          dimensionless time in the ECM model [-] 

REFERENCES 
(1) Figueira, M.M.; Volesky, B.; Ciminelli, V.S.T. Biotechnol. Bioeng. 
          1997, 54, 344-350. 
(2) Stumm, W.; Morgan, J.J. Aquatic Chemistry, Wiley Interscience: 
         New York, 1981, pp 779-781. 
(3) Dudeney, A.W.L.; Ball, S.; Monhemius, A.J. Treatment Processes for Ferruginous 
           Discharges from Disused Coal Workings, R&D Note 243, National River 
          Authority: Bristol,UK, 1994. 
(4) Gazea, B.; Adam, K.; Kontopoulos, A. Minerals Engineering 1996, 9, 23-42. 
(5) Vile, M.A.; Wieder, K.R. Water, Air, and Soil Pollution 1993, 69, 425-441. 
(6) Deng, Y.; Stumm, W. Aquatic Sciences 1993, 55, 1015-1621. 
(7) Gutzman, D.W.; Langford, C.H. Environ. Sci. Technol. 1993, 27, 1388-1393. 
(8) Crist, R.H.; Martin, J.R.; Guptill, P.W.; Eslinger, J.M.; Crist, D.R. 
          Environ. Sci. Technol. 1990, 24, 337-342. 
(9) Kratochvil, D.; Fourest, E.; Volesky, B. Biotechnol. Lett. 1995, 17, 777-782. 
(10) Fourest, E.; Roux, J.C. FEMS Microbiol. Rev. 1994, 14, 325-332. 
(11) Spinti, M.; Zhuang, H.; Trujillo, E.M. Water Environ. Res. 1995, 67, 943-952. 
(12) Kratochvil, D.; Volesky, B.; Demopoulos, G. Water Res. 1997, 31, 2327-2339. 
(13) Schiewer, S.; Volesky, B. Environ. Sci. Technol. 1997, 31, 2478-2485. 
(14) Tan, H.K.S.; Spinner, I.H. Can. J. Chem. Eng. 1994, 72, 330-341. 
(15) Cleasby, J.L.; Baumann, E.R. Jour. AWWA 1962, 54, 579-592. 

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