Heavy metal adsorption on iron oxide and iron oxide-coated silica ...

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140data over a broad range of conditions when using a single set of model parameters.9.4 Ni and Zn CompetitionThe modeling results for single adsorbate systems (Table 9.2) indicate that the reactionconstants for Zn(II) <strong>adsorption</strong> are greater than that for Ni(II), suggesting Zn ions exhibita higher affinity than Ni ions for the goethite surface. This observation is in agreementwith other studies (Tiller et al. 1984; Crawford et al. 1993; Gupta, 1998; Dube et al.2001; Trivedi et al. 2001b; Jeon et al. 2003). Therefore, competition is expected whenboth ions are present and the site density is limited. Competition has been investigatedby many researchers. For example, Gadde and Laitinen (1974) concluded that Pb sorbedmore strongly than other ions (Zn, Cd, and Ti) on HFO and HMO surfaces; Balistrieriand Murray (1982) found that Mg(II) tends to suppress the <strong>adsorption</strong> of trace <strong>metal</strong>s(Cu, Pb, Zn, and Cd) on goethite; Christophi and Axe (2000) observed that goethite has agreater affinity for Pb than Cu; Trivedi et al. (2001b) found that Zn and Ni bind morestrongly than Ca to goethite; Bradl (2004) observed that Cd <strong>adsorption</strong> is stronglyinfluenced by the presence of competing cations, such as divalent Ca and Zn; andKanungo et al. (2004) found in a study on Co, Ni, Cu, and Zn sorption onto HMO that Niexperienced the greatest degree of displacement (Kanungo et al. 2004). However,competition between trace <strong>metal</strong>s in other studies may have been difficult to demonstrate,because site density may not have been limiting (Swallow et al. 1980; Palmqvist et al.1999).The competition experiments were performed at pH 6. Compared to singleadsorbate systems, Ni(II) <strong>adsorption</strong> decreased by approximately 23% due to presence of
141Zn(II) (Figure 9.8). With a higher affinity for goethite surfaces, Zn(II) competes withNi(II) in occupying sites available for both <strong>metal</strong>s. Ni(II) and Zn(II) competition waspredicted using both sets of parameters for Ni (pH 6.5 set) and Zn (pH 5.5 set) and resultswere within the data and model error (Figure 9.8), predictions were within the data error.Although SCMs have been employed to simulate multisolute <strong>adsorption</strong>competition, success has been mixed. Using a generalized two-layer model, Ali andDzombak (1996) predicted <strong>adsorption</strong> of sulfate and organic acids reasonably well basedon single-adsorbate data over a wide range of conditions. Underprediction for the weakeradsorbate was explained by adsorbate-specific surface site heterogeneity and/or byinaccurate representation of Coulombic effects in the model. Gao and Mucci (2001)predicted the shape of the competitive <strong>adsorption</strong> data for phosphate and arsenate ongoethite, but failed to reproduce it quantitatively. Heidmann et al. (2005) were able topredict Cu and Pb competition on kaolinite successfully using the combination of a 1-pKBasic Stern model for edge sites and an extended Basic Stern model for face sites;nevertheless the surface complexes were simply assumptions without spectroscopicsupport. Hayes and Katz (1996) pointed out that non-electrostatic, diffuse layer, andconstant capacitance models are likely to be less successful in modeling competition data,because they do not account for differences in the affinity of inner- and outer-spherecomplexes. Christi and Kretzschmar (1999) demonstrated that surface site density is akey parameter in applying SCMs to multicomponent environments and they obtained bestpredictions with site densities between 5 and 10 sites nm -2 for hematite. Palmqvist et al.(1999) showed that single-adsorbate modeling predicted <strong>adsorption</strong> competition for Cuand Zn, but underestimated Pb(II) <strong>adsorption</strong>. Both the TLM and NEM predicted Cd and
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Copyright Warning & RestrictionsThe
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ABSTRACTHEAVY METAL ADSORPTION ON I
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HEAVY METAL ADSORPTION ON IRON OXID
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APPROVAL PAGEHEAVY METAL ADSORPTION
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Fan, M.; Boonfueng, T.; Xu, Y.; Axe
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ACKNOWLEDGMENTI would like to expre
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TABLE OF CONTENTS(Continued)Chapter
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TABLE OF CONTENTS(Continued)Chapter
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LIST OF TABLES(Continued)TablePageB
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LIST OF FIGURES(Continued)FigurePag
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LIST OF FIGURES(Continued)FigurePag
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CHAPTER 1INTRODUCTIONHeavy<
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3and Sigg, 1992; Gunneriusson et al
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CHAPTER 2OXIDES AND THEIR EFFECT ON
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7et al. 1996; Green-Pedersen et al.
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9identify components, distribution,
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11oxides. Because extraction method
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13Table 2.2 Some Coating Work and C
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15increasing the sorbate concentrat
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17mole Cu g-1 goethite (-1-7% of th
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19Overall, macroscopic adso
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21hematite (up to 9.9 limo' Pb ril-
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23concentration in their system was
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25Surface complexation modeling (SC
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27Overall, surface complexation mod
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29Spectroscopic techniques, especia
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31• Understand the effect of comp
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33existing in almost all soils and
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CHAPTER 4EXPERIMENTAL METHODSIn thi
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37included coating temperature (T),
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39generated at 45 kV and 40 mA, sca
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41PZC include electrophoretic mobil
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43Lin-edge, from 8,133 to 8,884 eV
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CHAPTER 5CHARACTERIZATION OF IRON O
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47measured by potentiometric titrat
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Table 5.2 XRD Data of Alfa Aesar (A
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51Table 5.3 XRF Results for Alfa Ae
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Figure 5.4 Particle size distributi
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55Figure 5.5 ESEM micrograph for Al
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585.2.5 Surface Charge Distribution
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Figure 5.10 Potentiometric titratio
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CHAPTER 6SYNTHESIS AND CHARACTERIZA
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Figure 6.1 Comparison between Fecon
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Figure 6.2 XRD patterns for goethit
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68iron oxide coatings at 60 °C, go
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70substrate diameter of 0.2 mm, an
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72goethite and silica results in on
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Figure 6.7 ESEM micrograph (9000x)
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76Furthermore, because discrete goe
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78Table 6.2 Surface Area and Porosi
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Figure 6.10 Surface charge distribu
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Figure 6.11 Ni adsorption</
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84that for pure silica, and the goe
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Table 7.1 Sample Preparation Condit
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Figure 7.2 EXAFS spectra of Pb/HFO
Page 112 and 113: Figure 7.3 Fourier transform and fi
Page 114 and 115: Figure 7.4 Fourier transform and fi
Page 116 and 117: Table 7.3 EXAFS Results of Pb/HFO S
Page 118 and 119: 967.2 Fe XAS of Iron Oxides and Pb/
Page 120 and 121: Figure 7.7 EXAFS spectra of iron ox
Page 122 and 123: 100and Venturelli, 1999). Overall t
Page 124 and 125: 102(hematite, goethite, akaganeite,
Page 126 and 127: 104adsorption proc
Page 128 and 129: 106of pH, ionic strength, Pb loadin
Page 130 and 131: Figure 8.1 Ni adsorption</s
Page 132 and 133: 110high metal load
Page 134 and 135: Figure 8.3 x(k)•k3 spectra and Fo
Page 136 and 137: Figure 8.4 (k)•k3 spectra of Ni-H
Page 138 and 139: Figure 8.5 Fourier transforms (magn
Page 140 and 141: 118be fit using either Fe or Ni ato
Page 142 and 143: 1208.3 EXAFS Analysis of FeThe x(k)
Page 144 and 145: Table 8.4 EXAFS Results of HFO and
Page 146 and 147: CHAPTER 9SURFACE COMPLEXATION MODEL
Page 148 and 149: Figure 9.1 Potentiometric titration
Page 150 and 151: 128Table 9.1 Surface Reactions and
Page 154 and 155: 132Table 9.2 Model Parameters for N
Page 158 and 159: 1369.3 Zn Adsorption on GoethiteReg
Page 160 and 161: Figure 9.6 Zn adsorption</s
Page 164 and 165: 142Figure 9.8 Ni adsorption
Page 166 and 167: 144oxide-coated silica. Ni and Zn s
Page 168 and 169: Figure 10.1 Ni adsorption</
Page 170 and 171: Figure 10.2 Zn adsorption</
Page 172 and 173: Figure 10.4 Ni adsorption</
Page 174 and 175: 152one for GACS (2.77x10 -6 mole si
Page 176 and 177: Figure 10.6 Zn adsorption</
Page 178 and 179: CHAPTER 11CONCLUSIONS AND FUTURE WO
Page 180 and 181: 158surfaces are needed for successf
Page 182 and 183: Figure A.2 Ni speciation in 1x10 -5
Page 184 and 185: Figure A.4 Pb speciation in 5x10 -8
Page 186 and 187: Figure A.6 Zn speciation in 1x10 -5
Page 188 and 189: 166Table B.2 Potentiometric Titrati
Page 190 and 191: 168Table BA Potentiometric Titratio
Page 192 and 193: 170Table C.3 Zn Adsorption Edges on
Page 194 and 195: APPENDIX DADSORPTION STUDIES ON SIL
Page 196 and 197: 174Table D.5 Zn Adsorption Isotherm
Page 198 and 199: 176Table E.3 Pb CBC Study on 0.3 g
Page 200 and 201: APPENDIX GINTRAPARTICLE DIFFUSION M
Page 202 and 203: 180DofA = flier ^ 2fA = Exp(-fD * f
Page 204 and 205: REFERENCES1. Adamson A. W. (1982) P
Page 206 and 207: 18426. Blake R. L., Hessevick R. E.
Page 208 and 209: 18650. Combes J. M., Manceau A. and
Page 210 and 211: 18876. Elzinga E. J. and Sparks D.
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190102. Gupta V. K. (1998) Equilibr
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192126. Joshi A. and Chaudhuri M. (
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194150. Liu C. and Huang P. M. (200
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196175. Muller B. and Sigg L. (1992
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200. Perry R. H. and Green D. W. (1
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200226. Scheinost A. C., Kretzschma
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202252. Swallow C. K., Hume D. N. a
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204278. Villalobos M., Trotz M. A.
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304. Zhong Z. Y., Prozorov T., Feln
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