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Bureau of Mines Information Circular/1987 
 
 MgO Filtration Research 
 
 By D. N. Tallman and J. E. Pahlman 
 
 UNITED STATES DEPARTMENT OF THE INTERIOR 
 
Information Circular 9138 
 
 // 
 
 MgO Filtration Research 
 
 By D. N. Tallman and J. E. Pahlman 
 
 UNITED STATES DEPARTMENT OF THE INTERIOR 
 
 Donald Paul Hodel, Secretary 
 
 BUREAU OF MINES 
 Robert C. Horton, Director 
 
x^ 6 
 
 Library of Congress Cataloging in Publication Data: 
 
 Tallman, Daniel N. 
 
 MgO filtration research. 
 
 (Bureau of Mines information circular; 9138) 
 
 Bibliography: p. 30. 
 
 Supt. of Docs, no.: I 28.27: 9138. 
 
 1. Filters and filtration. 2. Magnesia. 3. Mineral industries— Water-supply. 4. 
 Water— Purification— Filtration. 5. Mine drainage. I. Pahlman, J. E. (John E.). II. Title. 
 III. Series: Information circular (United States. Bureau of Mines); 9138. 
 
 IM295JJ4-^ [TN535] 
 
 622 s 
 
 [622'.5] 
 
 87-600009 
 
CONTENTS 
 
 Page 
 
 Abstract 1 
 
 Introduction 2 
 
 Background 2 
 
 Filtration mechanisms 2 
 
 Transient behavior 4 
 
 Filtration indices 5 
 
 Contact filtration of asbestos fibers 6 
 
 Granular bed filtration 7 
 
 Synthetic suspensions 8 
 
 Filtration of kaolin 8 
 
 Filtration of milled sand 10 
 
 Use of polymer f locculants. 10 
 
 Kaolin filtration 10 
 
 Filtration of metal precipitates 12 
 
 Filtration with mixed MgO-sand beds 13 
 
 Applications 13 
 
 Steel mill cooling water 13 
 
 Process water from magneite benef iciation 14 
 
 Process water from flotation of iron ore 15 
 
 Mississippi River water 15 
 
 Process water for cutting granite 15 
 
 Engineering aspects 17 
 
 Backwashing of MgO filters 17 
 
 Attrition of MgO filters during backwashing 21 
 
 Poisoning of MgO filters by heavy metals 23 
 
 Filtration parameters 24 
 
 Effect of surface charge and particle shape on filtration 24 
 
 Removal and head loss coefficients 25 
 
 pH and chemical effects 27 
 
 Scale formation and mudballing 28 
 
 Summary and conclusions 29 
 
 References 30 
 
 Appendix. — Nomenclature 31 
 
 ILLUSTRATIONS 
 
 1. Transient behavior typical of granular bed filtration 4 
 
 2. Filtration of amphibole asbestos by granular MgO and sand filters with 
 
 and without alum pretreatment 8 
 
 3. Filtration with mixed MgO-sand filters 13 
 
 4. Filtration of granite-cutting process water 16 
 
 5. Bed expansion of MgO versus flow velocity 19 
 
 6. Optimum bed porosities calculated from optium Reynolds number 21 
 
 7. Binding of MgO filters 22 
 
 8. Effects of dissolved heavy metals on MgO filtration 23 
 
 9. Cemented MgO chunks containing anthracite grains 28 
 
 TABLES 
 
 1. Dimensionless filtration parameters 3 
 
 2. Contact filtration of asbestos 7 
 
 3. Filtration of synthetic suspensions 9 
 
ii 
 
 TABLES — Continued 
 
 Page 
 
 4. Filtration with polymer f locculants 
 
 5. Filtration of steel mill cooling water 
 
 6. Filtration of iron ore processing water , 
 
 7 . Chemical analysis of process water 
 
 8. Fluidization results , 
 
 9. Durability study 
 
 10. Effects of filter medium surface charge and particle shape on kaolin 
 
 removal 
 
 11. Head loss and removal coefficients of MgO and sand filters for the 
 
 filtration of kaolin 
 
 12. Effect of influent pH on filtration of kaolin suspension flocculated 
 
 with Al 3+ and Fe 3+ salts 
 
 11 
 
 14 
 
 15 
 
 17 
 
 20 
 
 21 
 
 25 
 
 26 
 
 27 
 
 
 UNIT OF MEASURE ABBREVIATIONS 
 
 USED IN THIS 
 
 REPORT 
 
 °c 
 
 degree Celsius 
 
 L/s 
 
 liter per second 
 
 cal/(mol 
 
 deg) calorie per mol 
 per degree 
 
 m 
 
 meter 
 
 
 
 mg/L 
 
 milligram per 
 
 cm 
 
 centimeter 
 
 
 liter 
 
 cm 3 
 
 cubic centimeter 
 
 min 
 
 minute 
 
 cm H 2 
 
 centimeter water 
 (pressure) 
 
 mm 
 
 millimeter 
 
 
 
 y m 
 
 micrometer 
 
 cm 3 /g 
 
 cubic centimeter 
 
 
 
 
 per gram 
 
 ymho 
 
 micromho 
 
 cm/s 
 
 centimeter per 
 
 m/s 2 
 
 meter per second 
 
 
 second 
 
 
 per second 
 
 eV 
 
 electron volt 
 
 m 2 /s 
 
 square meter per 
 second 
 
 g 
 
 gram 
 
 
 
 
 
 mV 
 
 millivolt 
 
 g/cm 3 
 
 gram per cubic 
 
 
 
 
 centimeter 
 
 NTU 
 
 nephelometric 
 turbidity unit 
 
 h 
 
 hour 
 
 
 
 
 
 pet 
 
 percent 
 
 K 
 
 kelvin 
 
 
 
 
 
 ppm 
 
 part per million 
 
 kg/m 3 
 
 kilogram per cubic 
 
 
 
 
 meter 
 
 r/min 
 
 revolutions per 
 minute 
 
 kg/(m*s) 
 
 kilogram per meter 
 
 
 
 
 per second 
 
 s 
 
 second 
 
 L 
 
 liter 
 
 vol pet 
 
 volume percent 
 
 L/cm 2 
 
 liter per square 
 centimeter 
 
 wt pet 
 
 weight percent 
 
 
 
 yr 
 
 year 
 
 L/min 
 
 liter per minute 
 
 
 
MgO FILTRATION RESEARCH 
 
 By D. N. Tallman 1 and J. E. Pahlman 2 
 
 ABSTRACT 
 
 The Bureau of Mines has completed 4 yr of deep-bed filtration research 
 comparing the efficiencies of granular magnesium oxide (MgO) and conven- 
 tional filter sand in single- and dual-medium filters when filtering 
 mineral-processing and mine waters. Bench and field evaluation tests 
 were conducted using water types ranging from synthetic suspensions of 
 asbestos, kaolin, metal hydroxides, and milled sand to process waters 
 from magnetite benef iciation, iron ore flotation, granite cutting, and a 
 steel mill. Even though the turbidity reductions were similiar, MgO 
 filters were found to be advantageous when filtering water pretreated 
 with alum because the volume throughput before breakthrough (turbidity 
 > 1 NTU unit) was much more for the MgO filter than for the sand filter. 
 Reduced head loss owing to the greater porosity of the MgO filter beds 
 is potentially the most beneficial advantage in employing MgO as the 
 filter medium, especially when filtering water pretreated with polymer 
 flocculants. Granular MgO (periclase) is durable and can be backwashed 
 like sand. It is compatible with anthracite in a dual-medium filter and 
 apparently is not poisoned by dissolved metals in the process water. No 
 single solid-removal mechanism could be identified for the improved fil- 
 tration observed with granular MgO. 
 
 1 Research chemist, Twin Cities Research Center, Bureau of Mines, Minneapolis, MN 
 (now with Econ Laboratories, Eagan, MN). 
 
 ^Supervisory physical scientist, Twin Cities Research Center, Bureau of Mines, Min- 
 neapolis, MN. 
 
INTRODUCTION 
 
 Suspended solids are a common impurity 
 in mine water. Mines rely mainly on 
 flocculation and settling for solid re- 
 moval, but this can be unreliable owing 
 to seasonal variation in water tempera- 
 ture, runoff, and changes in the charac- 
 ter of ores being mined. Filtration is 
 often needed to provide sufficiently pure 
 water to meet mineral processing require- 
 ments and/or statutory effluent limits. 
 Although recyling decreases the volume of 
 discharge needing treatment, it can ad- 
 versely affect plant performance unless 
 the return water is treated to keep con- 
 taminants from reaching unacceptable 
 levels of concentration. 
 
 The Bureau of Mines has completed 4 yr 
 of research on improving filtration of 
 mine and mineral-processing water using 
 MgO as the filter medium in contact and 
 deep-bed filters. The initial phase of 
 work resulted from a previous study of 
 the surface charge of asbestos fibers in 
 water CO* 3 Numerous candidate materials 
 (sand, calcite, diatomaceous earth, ac- 
 idic alumina, basic alumina, microcrys- 
 talline cellulose, magnesium carbonate, 
 and activated carbon) were tested for re- 
 moving asbestos fibers from water by con- 
 tact filtration, a process that required 
 no pretreatment of the water and that 
 used shallow beds of fine filter media. 
 MgO filter media gave the best removal. 
 The superior performance of MgO was at- 
 tributed to its positive surface charge 
 (2^). The next phase of research was the 
 application of MgO to filtration of other 
 suspended solids occurring in natural 
 waters. Bench-filtration tests that 
 
 compared MgO and filter sand were per- 
 formed on synthetic suspensions and on 
 mine-water samples (_2-3)« In these tests 
 granular materials were used for practi- 
 cal reasons such as achieving adequate 
 solid-loading capacity and reducing pres- 
 sure drop through the filters. Floccula- 
 tion with alum improved filtration with 
 the granular media, and MgO generally 
 outperformed sand. Field tests were run 
 to validate bench-scale tests on mine 
 water (4^« 
 
 The remaining phase of research dealt 
 with practical engineering aspects of us- 
 ing MgO filters, such as f luidization, 
 backwashing, and durability. Attempts to 
 derive a model for MgO bed expansion were 
 unsuccessful because there appears to be 
 a transition in the expansion behavior of 
 the MgO for particles between 0.5 and 
 1.0 mm. MgO was found to be compatible 
 with anthracite but not with sand in 
 dual-medium filters as the anthracite and 
 MgO were easily restratified by backwash- 
 ing. Granular MgO possesses the neces- 
 sary durability to be a filter medium and 
 was apparently not poisoned by dissolved 
 metals in the process water. The MgO 
 filters were tolerent to moderate levels 
 of calcium hardness and carbonate alka- 
 linity, provided adequate backwashing 
 with air scour was available. Cementa- 
 tion of MgO grains with each other or 
 with anthracite grains was observed with 
 scale formation in the filters. Descrip- 
 tions of each phase of research and dis- 
 cussion of pertinent results are pre- 
 sented in this report. 
 
 BACKGROUND 
 
 FILTRATION MECHANISMS 
 
 A detailed theoretical discussion of 
 filtration mechanisms as they pertain to 
 MgO filtration is beyond the scope of 
 this paper. Reviews of the theory of 
 deep-bed filtration are available in the 
 
 3 Underlined numbers in parentheses re- 
 fer to items in the list of references 
 preceding the appendix. 
 
 literature (_5-7)« A brief examination of 
 relevant filtration mechanisms, however, 
 is helpful for understanding the filtra- 
 tion results presented herein. 
 
 In deep-bed filtration, filter pores 
 are usually large compared with the size 
 of the particles being filtered. Clear- 
 ly, forces other than straining must ac- 
 count for particle retention (_5). Trans- 
 port and attachment steps are both 
 important in the capture of small 
 
suspended particles. Flow is usually 
 laminar, so forces must act on a particle 
 to move it across streamlines into close 
 proximity with the surface of the filter 
 medium where attachment forces operate. 
 
 The main forces considered in particle 
 transport are gravitational, diffusional, 
 hydrodynamic, and inertial forces (4~5)« 
 Surface forces that affect attachment are 
 of mainly two kinds, the molecular dis- 
 persion force (London van-der-Waals 
 force) and the double-ionic-layer force, 
 which is mainly due to surface charge 
 (6_). Particle interception is really 
 neither a transport mechanism nor an at- 
 tractive force, but it is the final step 
 in particle capture in any case. The net 
 effect of all these forces will determine 
 the overall removal efficiency of the 
 filter. Contributions to particle col- 
 lection by each type of force can be 
 estimated using the dimensionless param- 
 eters given in table 1. In general, it 
 can be seen that the size of the particle 
 
 to be captured is the single most impor- 
 tant variable; increasing the parti- 
 cle size will enhance all collection 
 mechanisms except diffusion and London 
 van-der-Waals forces. For particles 
 smaller than 1 ym, surface charge, ionic 
 strength, and diffusion are dominant cap- 
 ture mechanisms, while interception 
 and/or straining becomes dominant above 
 10 to 100 ym. For particles with sizes 
 between 1 and 10 ym, mixed capture mecha- 
 nisms are observed. Overall collector 
 efficiency is at a minimum for particles 
 of about 1-ym diam; increasing particle 
 size by flocculation results in better 
 collection. Flocculation also acts to 
 decrease surface charge on the particle 
 so that surface charge effects are re- 
 duced. At high ionic strength, the 
 ionic-double-layer thickness (l/<) is 
 minimal. This also reduces surface- 
 charge effects. 
 
 Particle detachment is especially im- 
 portant in cleaning filters, but also 
 
 TABLE 1. - Dimensionless filtration parameters 
 
 Parameter Typical range 
 
 Formula 
 
 Comments 
 
 
 
 
 ATTACHMENT MECHANISMS 
 
 n dl 
 
 10°-10 5 
 
 <a D , where 
 
 Dimensionless double-layer-thick- 
 
 
 
 
 e d kT I m J Z J 
 1 
 
 1/2 
 
 ness effect of ionic strength 
 
 
 
 K = 
 
 
 versus conductivity. 
 
 n E i 
 
 10 _1 -10 3 
 
 £d<(^p 2 + ip m 2 )/12iryv 
 
 Electrokinetic group 1: elec- 
 trical versus shear forces. 
 
 N E 2 
 
 -1 to +1 
 
 2<Mm/(iJ'p 2 + ^ 2 ) 
 
 Electrokinetic group 2: "parity" 
 group; - = favorable, 
 + = unfavorable interaction. 
 
 n L o 
 
 io- 5 -io -2 
 
 h/9iry a p 2 v 
 
 London group: London-van-der- 
 Waals forces-shear forces. 
 
 
 
 INTERCEPTION AND STRAINING 
 
 Nr 
 
 io-Mo" 1 
 
 dp/d m 
 
 Relative-size group. 
 
 TRANSPORT MECHANISMS 
 
 
 
 
 -14 
 
 ga p 2 (p p -pf )/18yv 
 RT 
 
 Gravity group: settling velocity- 
 approach velocity, 
 dimensionless . 
 
 1/Pe 
 
 10" 
 
 8_ 10 -5 
 
 Inverse of Peclet number: ratio 
 of diffusion number to approach 
 
 3iryd p d m 
 
 
 
 
 
 velocity. 
 
 Re 
 
 
 ~1 
 
 vdpg/y = vdp/v 
 
 Reynolds number: characterizes 
 hydrodynamic; usually laminar. 
 
 Sources: Rajagopulan and Tien (7) and Ives (5) 
 
during filtration, where increases in 
 flow rate will create proportionately 
 higher shear forces that can dislodge de- 
 posited solids and cause breakthrough. 
 Beds with large filter-medium grains and 
 large porosity will have less head loss 
 and will be more resistant to scouring 
 and subsequent breakthrough (4). 
 
 TRANSIENT BEHAVIOR 
 
 To get a complete description of a fil- 
 tration process, one needs to obtain a 
 record of the pressure drop (both across 
 the bed and within the bed), filtrate 
 quality, and flow rate as they vary with 
 time. Idealized versions of typical 
 kinds of head-loss and turbidity behavior 
 are illustrated in figure 1 by curves A 
 and A' for deep-bed filtration and by 
 curves B and B' for surface straining or 
 cake filtration. Filtration is a dynamic 
 process with pressure and turbidity fluc- 
 tuating as channels become clogged with 
 deposits and reopened by scouring. As 
 filtration progresses, more material be- 
 comes lodged in the filter, the porosity 
 decreases, and as a result head loss in- 
 creases with time. This manifests itself 
 as a rise in the water level above a 
 gravity filter or as increased gauge 
 pressure in a pressure filter. At con- 
 stant loading, the deposit in the filter 
 grows at a steady rate, and the head 
 above the filter increases almost linear- 
 ly with time (curve A y fig. 1). Changes 
 in either influent flow rate or solids 
 concentration will have a corresponding 
 effect on head loss. This is the ex- 
 pected pattern in deep-bed filtration. 
 Often the suspended solids are actually 
 removed at the surface of the bed by 
 straining. As a result of this phenom- 
 enon, a cake forms and pressure begins to 
 increase exponentially, as in curve B of 
 figure 1. Filtrate turbidity will gener- 
 ally be very low, as in curve B' . Sur- 
 face or cake filtration is inefficient, 
 because designed increases in allowable 
 head loss result in diminishing gains in 
 filtrate volume before backwashing is 
 necessary. Poor design, changes in solid 
 loading, or atrrition of the medium 
 
 are the usual causes of excessive rates 
 of head loss. 
 
 In deep-bed filtration the filtrate 
 turbidity initially decreases slightly 
 and then levels out before breakthrough 
 (curve A' of figure 1). Up to a point, 
 material deposited in the filter improves 
 solid capture, but then a critical point 
 is reached where the reduction in poros- 
 ity and the resulting increased shear 
 rates cause a decrease in the efficiency 
 of solid removal. In fact, deposits are 
 often dislodged and then trapped deeper 
 in the filter. This scour-deposit mech- 
 anism was postulated by Mints (5) when he 
 observed that particles appearing in the 
 filtrate at breakthrough were larger than 
 those in the influent, leading to the 
 assumption that they were actually floes 
 of deposited material. Onset of break- 
 through may manifest itself as increased 
 fluctuation in the filtrate turbidity and 
 is most easily observed with a 
 turbidimeter-recorder setup. In Bureau 
 filtration tests, increased fluctuation 
 in the turbidity was usually observed 
 prior to consistent increases in turbid- 
 ity. This may be a reliable indicator of 
 imminent breakthrough. 
 
 FILTRATION INDICES 
 
 Efficient deep-bed filtration is the 
 result of a successful compromise between 
 filtrate quality goals and minimizing 
 head loss. The best filter achieves the 
 desired quality at the lowest pumping 
 cost. Flocculant dosage and mixing, 
 filter-grain size, flow rate, and depth 
 are all interdependent; sometimes adjust- 
 ments in one or more of these variables 
 become necessary due to variations in in- 
 fluent composition. Numerous attempts 
 have been made to describe the perfor- 
 mance of a filter quantitatively, in 
 terms of both filtrate quality and head 
 loss, with a single number or index 
 (_5, 8). One of the simpler and more com- 
 monly used indices is the f ilterability 
 index (F) given by Ives (_5): 
 
 F = (C/C )(H/vt) = (t/t )(H/V), (1) 
 
x - 
 
 en 
 
 CO 
 
 O 
 
 Q 
 
 < 
 
 LU 
 
 X 
 
 
 
 1 1 
 
 1 
 
 1 
 B. 
 
 1 1 
 
 
 
 
 - 
 
 
 
 
 
 
 A 
 
 A 1 
 
 - 
 
 - < 
 
 
 r 
 
 t 
 
 
 
 I 
 
 KEY 
 
 A, A' Deep-bed filtration 
 
 B,B' Surface straining or 
 cake filtration 
 
 i 
 
 
 
 - 
 
 
 1 1 
 
 B' 
 
 i 
 
 > 
 
 CD 
 
 or 
 
 TIME (t) 
 FIGURE 1.— Transient behavior typical of granular bed filtration. 
 
 where C = concentration, 
 
 H = increase in head loss, 
 
 v = filtration rate or approach 
 velocity, 
 
 t = time, 
 
 t = filtrate turbidity, 
 
 V = filtrate volume per unit area 
 at time t (V = vt), 
 
 and 
 
 C = influent concentration, 
 t = influent turbidity. 
 
 The f ilterability index is the product of 
 two dimensionless parameters that can be 
 represented by residual turbidity and 
 head-loss rate. Low values of F indicate 
 
 efficient filtration; effective solid re- 
 moval and/or small head loss could con- 
 tribute to a low value for F. F could be 
 used, for example, by a plant operator 
 who needs to adjust plant-water treatment 
 to seasonal variations of influent-solid 
 loading. Several options such as floccu- 
 lant dosage and flow-rate changes would 
 be tested on several small-scale filters 
 run in parallel. The parameters that re- 
 sult in the minimum value of F and still 
 meet quality goals can then be tried full 
 scale. Comparisons of filter media can 
 also be made with F; the filter giving 
 the lowest value of F is the best choice 
 for a given influent. Other indices are 
 available that are similar to F but take 
 into account operating limitations on 
 head loss and filtrate quality for a par- 
 ticular plant (8). 
 
 Higher solids concentrations will in- 
 crease H/V, but this is not accounted for 
 by F. Comparisons of tests run with 
 
different solids concentrations require a 
 different index that will normalize the 
 effect of concentration. The solid cap- 
 ture index (SC) measures the amount of 
 solid trapped in the filter per unit area 
 per unit head loss and is expressed in 
 units of concentration (g/cm 3 ). This 
 type of index was used by Bauman and 
 Cleasby (8) to compare waste water fil- 
 tration results at various treatment 
 plants and is defined by the following 
 equation: 
 
 SC = C (1-C/C )(V/H) 
 
 = C (1-t/t )(V/H). (2) 
 
 Large values of SC are desirable. 
 
 One disadvantage of using filtration 
 indices is that different values of H, V, 
 and t could give the same value for F or 
 SC. For the large number of tests per- 
 formed in this study, filtration indices 
 provide the only practical means of ana- 
 lyzing experimental data. Aside from a 
 few figures used to illustrate special 
 cases, the f ilterability index, F, and 
 solid capture index, SC, have been used 
 throughout this review. To offset the 
 ambiguity that results from relying on 
 filtration indices, the values of t/t 
 and V/H are given so that the contribu- 
 tion of each parameter can be assessed. 
 
 This is especially important when values 
 of either F or SC for two filters are al- 
 most equal. 
 
 The values of V and v are also listed 
 for further evaluation of results. Gen- 
 erally, values of F were calculated for 
 the portion of a test preceding break- 
 through. After breakthrough, F values 
 may actually improve because often there 
 is a reduction in head loss that is dis- 
 proportionate to average turbidity in- 
 crease. Comparison between a filter that 
 has broken through and one that has not 
 broken through is invalid because the 
 former no longer meets quality require- 
 ments. Excellent values of F (due to low 
 head loss) may be obtained for a filter, 
 but breakthrough may be reached so quick- 
 ly that it would be impractical to use 
 that filter. A ratio of V/v greater than 
 21.6 (run length equal to 6 h) should be 
 achieved for practical purposes; net pro- 
 duction of filtered water declines rapid- 
 ly with further decreases in run length 
 because more frequent backwashing becomes 
 necessary (_9)» In some cases, filtrate 
 quality never reaches satisfactory levels 
 or may be declining when a run is termi- 
 nated because of excessive head loss on 
 one of the filters. For these tests, F 
 values are based on the entire run, and 
 values of V for the two media being com- 
 pared should be approximately equal. 
 
 CONTACT FILTRATION OF ASBESTOS FIBERS 
 
 Contact-filtration experiments were 
 performed using a number of natural and 
 synthetic filter materials. The filters 
 were typically a 0.5- to 2.0-cm layer of 
 0.10-mm (minus 100- plus 200-mesh) Baker 4 
 reagent-grade material supported by a 
 layer of coarse sand and cotton. MgO, 
 sand, magnesium carbonate, acidic and 
 basic alumina, calcite, diatomaceous 
 earth, microcrystalline cellulose, and 
 activated carbon were all tested against 
 suspensions of amosite and crocidolite 
 asbestos in distilled water. Amphibole 
 and chrysotile asbestos samples were ob- 
 tained from the International Union 
 
 ^Reference to specific products does 
 not imply endorsement by the Bureau of 
 
 Mines. 
 
 Against Cancer (UICC). Ultrasonic and 
 mechanical agitation were used to dis- 
 perse the asbestos fibers in water. The 
 beds were washed with 50 cm 3 of distilled 
 water, 15 cm 3 of 1- to 10-ppm suspension 
 was added to the next 50-cm 3 aliquot 
 passing through the filter, and finally 
 the filter was washed with an additional 
 50 cm 3 of water. Flow velocities were 
 0.07 to 0.15 cm/s under 10- to 20-cm 
 gravity head. The entire volume of fil- 
 trate was then passed through a 0.45- 
 pm-pore-size membrane filter. Fiber 
 counts were made on sections of filter 
 membrane using a scanning electron micro- 
 scope at magnifications of x 1,000 to 
 x 5,000. 
 
 Results for the contact filtration ex- 
 periments are summarized in table 2. MgO 
 
TABLE 2. - Contact filtration of asbestos, 
 percent removed 
 
 Solid filter medium 
 
 Sand ■ 
 
 Calcite 
 
 Diatomaceous earth . 
 
 Microcrystalline cellulose. 
 
 Alumina, acidic 
 
 Alumina, basic 
 
 MgO 
 
 Carbon 
 
 Amp hi bole 
 
 Chrysotile 
 
 
 
 
 
 10 
 
 60 
 
 60 
 
 10 
 
 20 
 
 20 
 
 99 
 
 50 
 
 50 
 
 80 
 
 100 
 
 99 
 
 85 
 
 65 
 
 Source: Schiller and Khalafalla (2). 
 
 and acidic alumina were both efficient 
 for filtering amphibole asbestos, but 
 only MgO could effectively remove both 
 amphibole and chrysotile asbestos. These 
 results can be explained on the basis of 
 surface charge and pH. Surface charge 
 on particles in water is pH dependent. 
 Charge is acquired owing to selective 
 dissolution-adsorption of ions at the 
 liquid-solid interface. Amphibole asbes- 
 tos and most naturally occurring particu- 
 lates are negatively charged in water. 
 Adsorption of H + and OH" account for the 
 pH dependence; particles generally become 
 more negative at higher pH. The isoelec- 
 tric point for amphibole asbestos is 
 pH 3 to 3.5, and that of chrysotile is 
 
 approximately pH 11. Amphibole asbestos 
 has a negative zeta potential of -25 to 
 -45 mV in neutral and slightly basic wa- 
 ter. Chrysotile has a positive zeta po- 
 tential but flocculates in water at high 
 pH. MgO is basic and has a positive sur- 
 face charge below pH 12, so it is able to 
 remove the amphibole asbestos fibers by 
 electrokinetic attraction and still re- 
 move positively charged chrysotile by 
 causing it to flocculate. Acidic alumina 
 is also positively charged, but not 
 basic, so it collected amphibole asbestos 
 but passed the chrysotile because the pH 
 of the suspension was not increased 
 enough to cause f locculation. 
 
 GRANULAR BED FILTRATION 
 
 The contact filters restricted flow ex- 
 cessively and collected too few particles 
 to be directly applicable for treating 
 water. For practical reasons such as 
 solid loading, filtration rate, and 
 backwashing (filter regeneration), granu- 
 lar filters are used to filter waste 
 water. 
 
 The purpose of this phase of work was 
 to compare red flint sand and MgO as 
 granular filters for removal of asbestos 
 and other naturally occurring particu- 
 lates. Granular MgO was purchased as 
 crushed periclase from Basic Chemical and 
 Kaiser. The periclase is made by roast- 
 ing MgO (calcining) at a high enough tem- 
 perature so that it fuses and becomes in- 
 ert ("dead burning"). This product was 
 chosen because it was less friable than 
 pellets of a more active MgO material. 
 Active magnesia such as was used in the 
 
 contact filtration studies is calcined at 
 lower temperatures so that much of its 
 internal porosity is retained. Conse- 
 quently, in changing to a durable granu- 
 lar material substantially more surface 
 area was lost than would be predicted on 
 the basis of gross-particle size. 
 
 Filtrate quality is often measured by 
 turbidity (light scattering) rather than 
 particle counting because this allows 
 real-time monitoring and better control 
 of the filtration process. Filtrate tur- 
 bidity was therefore used as a measure of 
 filtering efficiency in almost all of the 
 granular-bed-filtration tests. Initial- 
 ly, a comparison was made between parti- 
 cle counting with the scanning electron 
 microscope and turbidity measurement 
 (nephelometric), and the two methods were 
 found to agree within experimental error 
 of the former. Pressure and turbidity 
 
were measured at 15-min intervals over 
 runs lasting several hours or more. 
 
 It became apparent that granular MgO 
 was not nearly as effective for removal 
 of asbestos as was the more active MgO 
 used in contact filtration. Adequate re- 
 moval could be achieved only by adding 
 flocculant to the influent. Figure 2 il- 
 lustrates how removal rates of both sand 
 and MgO filters are improved by the addi- 
 tion of 1 ppm of alum (potassium aluminum 
 sulfate heptahydrate) to the suspension 
 15 min before filtration. Flow velocity 
 was 0.5 cm/s. These results indicate 
 that forces other than surface charge op- 
 erate in these filters. Although the MgO 
 gives better removal than sand in the ab- 
 sence of alum, both filters benefit by 
 the increase in particle size due to 
 f locculation. For the 0.71-mm sand and 
 MgO used in this test, bed porosities are 
 38 and 50 pet, respectively. With f loc- 
 culation the sand actually becomes the 
 more efficient filter by a small margin, 
 
 
 i i 
 / 
 
 1 1 1 1 
 
 - 
 
 1.00 
 
 / ^? ■ 
 
 .7b 
 
 KEY 
 
 - 
 
 
 
 .50 
 
 
 / Sand 
 2 MgO 
 
 - 
 
 
 rl ^^^~<^ 
 
 3 MgO with alum 
 
 
 .2b 
 
 11 4 
 
 1 1 
 
 4 Sand with alum 
 
 
 
 i I i i 
 
 
 0.5 
 
 1.0 
 
 1.5 2.0 
 
 TIME, h 
 
 2.5 
 
 3.0 
 
 3.5 
 
 FIGURE 2.— Filtration of amphibole asbestos by granular 
 MgO and sand filters with and without alum pretreatment. 
 
 owing to enhanced particle interception 
 or mechanical straining. However, the 
 increase in pressure drop (head loss) 
 across the sand filter occurs from two to 
 five times faster than that for the MgO 
 filter. In virtually all remaining tests 
 flocculant was added before filtration. 
 
 SYNTHETIC SUSPENSIONS 
 
 Standard suspensions of kaolin and 
 milled sand were used in many filtration 
 tests to achieve maximum reproducibility 
 of solution turbidity. Mine water sam- 
 ples, in contrast to standard suspen- 
 sions, are often complex mixtures of var- 
 ious dissolved chemicals and particulates 
 that may vary considerably between sam- 
 pling and testing. With consistent prep- 
 aration procedures, synthetic suspensions 
 of known concentrations and reproducible 
 turbidities were made. In-mine-water 
 sample turbidity was assumed to be pro- 
 portional to suspended-solid concentra- 
 tion, and actual suspended-solid concen- 
 trations were not measured for every 
 test. For the synthetic suspensions, it 
 was possible to calculate both filter- 
 ability (F) and solid-capture (SC) in- 
 dexes because suspended-solid concentra- 
 tions were known. Only F was determined 
 for mine-water samples, but the effect of 
 altered influent-solid loadings can be 
 estimated from head-sample turbidities. 
 The mass of flocculant was not included 
 in the calculation of SC, even though al- 
 uminum hydroxides could contribute to 
 solid loading as a result of using alum 
 for f locculation. 
 
 FILTRATION OF KAOLIN 
 
 Results for the filtration of kaolin 
 suspensions by 30-cm-deep beds of MgO and 
 sand are listed in table 3. Single- 
 medium MgO filters are better than sand 
 filters by a substantial margin; the val- 
 ue of F is about eight to nine times 
 smaller and that of SC is about four 
 times larger for MgO than for sand. Com- 
 parison of tests 1 and 2 demonstrates how 
 the effect of suspended-solid concentra- 
 tion is minimized by using SC rather than 
 F. The higher suspended-solid concentra- 
 tion causes a larger rate of head loss 
 and consequently increased the value of 
 F, but this effect is factored out in SC. 
 Using finer sized MgO decreases the ef- 
 ficiency of the filter; filtrate quality 
 is no better with 0.42-mm MgO, and head 
 loss rate is approximately doubled. 
 Since shear rates are considerably higher 
 In the 0.42-mm MgO, run length was short- 
 ened by earlier breakthrough. 
 
 Dual-medium filters were made with a 
 15-cm layer of 0.71-mm sand over 30 cm of 
 either 0.42-mm MgO or 0.42-mm garnet 
 sand. Garnet sand is sometimes used 
 as a second or even third layer in 
 
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 multiple-medium filters. The performance 
 of the two dual-medium filters is more 
 nearly equal than that of the single- 
 medium filter. Since in both filters the 
 sand (upper) layer removes most of the 
 suspended solids and consequently con- 
 tributes most to head loss, the filters 
 would be expected to be similar. The 
 sand-MgO filter is 1.5 to 3 times more 
 effcient than the sand-garnet filter. 
 
 Dual-medium filters of anthracite-MgO 
 and anthracite-garnet were tested with 
 much higher loadings of kaolin. These 
 filters were comprised of 50 pet anthra- 
 cite and either 50 pet MgO or 50 pet gar- 
 net for an overall depth of 30 cm. Al- 
 though run lengths were cut in half, a 
 large amount of solids were collected by 
 these filters. Filtering such high load- 
 ings of kaolin is probably impractical 
 because filters would be operating at 
 <80-pct availability because of the need 
 for frequent backwashing. 
 
 FILTRATION OF MILLED SAND 
 
 MgO filters were dramatically better 
 than sand filters for filtering milled 
 sand flocculated with alum (table 3). 
 MgO gives lower F values by a factor of 
 10, and SC values are seven to eight 
 times larger than for sand. Both filters 
 were 42±1 cm deep. With dual-medium fil- 
 ters the difference is much less appar- 
 ent. The dual-medium filters were 46 cm 
 deep, with the top third of the filter 
 being the sand layer. F(xl0 5 ) ranges 
 from 8.8 to 9.2 for sand-garnet filters 
 and from 4.2 to 6.4 for sand-MgO filters. 
 Although the variance between values for 
 duplicate tests is fairly large, the dif- 
 ferences between filter-medium types are 
 statistically significant. The mean val- 
 ues are 9.0 for F(xl0 5 ) and 12.4 g/cm 3 
 for SC for the sand-garnet filter versus 
 5.4 and 17.4 g/cm 3 for the sand-MgO fil- 
 ter. Filtrate volume at breakthrough for 
 the sand-garnet filter is about 60 pet 
 that of the sand-MgO filter. The sand- 
 MgO filter is 1.4 to 1.6 times better by 
 any of these criteria. 
 
 There is remarkable similarity between 
 results for the filtration of kaolin and 
 milled sand in these tests. Values for 
 SC and F are better overall for filtering 
 
 the milled sand. This is 
 particle size differences 
 suspensions and to the 
 loadings of milled sand, 
 get a high removal rate 
 influent loading. The 
 ferences between the 
 are quite consistent 
 suspensions. 
 
 probably due to 
 
 between the two 
 
 use of higher 
 
 It is easier to 
 
 with increased 
 
 relative dif- 
 
 various filters 
 
 for the two 
 
 USE OF POLYMER FLOCCULANTS 
 Kaolin Filtration 
 
 Recent trends in process-water treat- 
 ment include the use of organic polymers 
 or polyelectrolytes to improve floccula- 
 tion and increase filter-loading capaci- 
 ty. Often an inorganic salt of aluminum 
 (alum) or Fe 3+ is added to destabilize 
 colloidal dispersions and create small 
 "pin" floes. Then a polymer is added to 
 further flocculate the solid into large 
 (1- to 10-mm), fast-settling floes. Typ- 
 ical dosages of polymer are 0.1 to 
 10 ppm, and the amount required is 
 strongly dependent on the solids concen- 
 tration. Although most of the solids are 
 removed effectively by settling, a small 
 residual fraction of solids often has to 
 be removed by filtration. The choices of 
 polymer (cationic, anionic, or nonionic) 
 and dosage are usually determined by 
 settling tests. Floes created with poly- 
 mer are larger and more shear resistant 
 than alum-type floes. Coarser media, 
 deeper beds, and higher filtration veloc- 
 ities are typical of filtration with 
 polymer f locculation, and solid-loading 
 capacity is usually larger than with alum 
 f locculation. 
 
 Sand-MgO and sand-garnet filters were 
 tested with a 25-ppm kaolin suspension 
 treated with 10 ppm alum and 1.0 ppm Sep- 
 aran AP-30, an anionic polymer; the re- 
 sults are given in table 4. The best 
 filtration was with the sand-garnet fil- 
 ter and a filtration velocity of 
 0.35 cm/s. The coarser anthracite-sand 
 filter gives approximately equal SC, but 
 residual turbidity is relatively high: 
 t/t = 0.22. The best result for MgO was 
 with coarser media and a velocity of 
 0.52 cm/s, but in general it can be seen 
 that use of polymer actually diminished 
 
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12 
 
 the filterability of the MgO. Filtration 
 indexes for the sand-garnet filter are 
 about the same whether polymer or only 
 alum was used to flocculate the kaolin. 
 Head loss through the sand-MgO filter was 
 greatly increased; this occurred almost 
 entirely in the MgO (lower) layer. Usu- 
 ally the upper layer collects the greater 
 share of solids and constricts flow more 
 than the lower (finer) layer, and the 
 sand and garnet contribute little to the 
 observed head loss when they comprise the 
 lower layer. The filterability index 
 F(xl0 5 ) for MgO was increased from 9.2 
 with alum flocculation (table 3, test 9) 
 to 220 by using anionic polymer (table 4, 
 test 20). Solid capture of the sand-MgO 
 filters decreased by a factor of 21. Un- 
 der these conditions, MgO did not offer 
 any significant advantage over conven- 
 tional media. 
 
 Filtration of Metal Precipitates 
 
 Fe 3+ and other base-metal ions are com- 
 monly found in mine water. Precipitates 
 of these ions as hydrous metal oxides 
 present difficult filtration problems be- 
 cause of their fragility; they are easily 
 disrupted by the shear forces encountered 
 in conventional granular-bed filters. 
 These precipitates also settle slowly, 
 and the voluminous toxic sludge produced 
 by settling presents a serious disposal 
 problem. Polymer is often added to im- 
 prove settling and to aid in dewatering. 
 
 A series of tests were performed to see 
 if MgO offered any advantage over conven- 
 tional filter media for postsettling fil- 
 tration of metal hydroxides. Sand and 
 MgO filters were first tested on Fe(0H) 3 
 precipitates, produced by bringing a 
 100-ppm-FeCl 3 solution to pH 8.7. A 
 second test suspension was prepared that 
 had 78 ppm Fe 3+ and 10 ppm Mn 2+ as sul- 
 fate salts and 37 ppm Mn 7+ as permanga- 
 nate at pH 8.0 to 9.0. The Mn 7+ was 
 present at about 20 pet excess for oxi- 
 dizing the Fe 2+ and Mn 2+ , so the predomi- 
 nant species under these conditions were 
 Mn0 2 and Fe(0H)3. A similar suspension 
 was made by simply oxidizing 11 ppm Fe 2+ 
 with 1.7 ppm Mn(VII) at pH 7.5 to 8.5. 
 Separan AP-30, an anionic polymer, was 
 
 used to flocculate the precipitates in 
 most of the tests. These suspensions 
 were made to simulate waste water from a 
 western metal mine that contained Mn and 
 Fe at approximately these levels. Field 
 tests were later run on the actual mine 
 effluent. In the mine water treatment 
 plant, polymer was used to aid clarifica- 
 tion and also for sludge dewatering; no 
 additional polymer was added to the water 
 being pumped through the small test fil- 
 ters, since none was being added to that 
 entering the sand filters in service at 
 the plant. 
 
 Results for both laboratory and field 
 tests are summarized in table 4. Bed 
 depths for all tests were 30 cm. Neither 
 medium could filter prepared suspensions 
 of metal oxides effectively without the 
 use of polymer. Field tests and labora- 
 tory tests with flocculant were in rea- 
 sonable agreement, especially if the re- 
 duced head-sample turbidity in the field 
 tests is taken into account. During the 
 field tests plant water was cleaner than 
 normal because the mill operation had 
 been suspended and the water being 
 treated was diluted by spring runoff. 
 Reduced solid loading would result in F 
 being lower than predicted from laborato- 
 ry tests. The most efficient filtration 
 (minimum F) is with 1.7- and 1.8-mm me- 
 dia, and the MgO is slightly better than 
 equivalently sized sand. In general, 
 sand gives slightly better removal rates 
 and the MgO has smaller head losses, 
 probably owing to the larger porosity of 
 the MgO. Surface-charge forces would be 
 expected to diminish in importance when 
 the filter media and the suspended- 
 particle size are large, and because 
 flocculation has also essentially neu- 
 tralized particle surface charge. The 
 stronger and larger floes produced by the 
 polymer are retained in the filter mainly 
 by gravity or hydrodynamic forces, so the 
 two media are essentially equally effec- 
 tive. Floes were able to penetrate well 
 into both filters, so straining was not 
 the dominant removal mechanism. Filter- 
 ing of the base metal hydroxides or hy- 
 drous oxides, even with the use of pol- 
 mer, is fairly inefficient compared with 
 filtering particulates such as kaolin. 
 
13 
 
 - 2 
 
 Q 
 
 OD 
 
 or 
 
 Ld 
 
 < 
 
 CC 
 
 1 1 1 1 1 
 
 1 
 
 KEY 
 
 
 i I 
 
 9 o 
 
 Sar 
 
 id 
 
 
 
 - / • 
 
 % 
 
 sand, 
 
 > 
 
 MgO 
 
 a # y a 
 
 '/ 3 
 
 sand, 
 
 % 
 
 MgO 
 
 rw / / / a 
 
 Fill II 
 
 Mg 
 1 
 
 
 
 
 l l 
 
 3 4 5 6 
 
 TIME, h 
 
 FIGURE 3.— Filtration with mixed MgO-sand filters. 
 
 Efficiency might be improved by using 
 higher filtration rates and deeper beds 
 of coarser media. 
 
 Filtration With Mixed MgO-Sand Beds 
 
 A brief investigation of the possibil- 
 ity of using mixed MgO-sand beds was un- 
 dertaken. However, as shown in figure 3, 
 this does not appear to be feasible be- 
 cause of rapid breakthrough with mixed 
 beds. The filters were 30-cm beds of 
 
 0.71-mm MgO and/or sand, and the 
 filtration velocity was 0.21 cm/s. Be- 
 cause of the poor retention of solids, 
 head loss decreased with decreasing MgO 
 fraction. Values of SC were 4.8, 5.2, 
 8.3, and 9.6 g/cm 3 in order of increasing 
 sand content, but in this case the use of 
 indexes is misleading. The most likely 
 reason for the poor retention of kaolin 
 by the mixed beds is the reduction in po- 
 rosity that results from mixing spherical 
 (sand) and angular (MgO) particles. 
 
 APPLICATIONS 
 
 MgO and sand filters were compared in 
 field tests at four mines and two 
 mineral-processing sites. In addition to 
 mine water, MgO was tested on river water 
 for its application to municipal-water 
 treatment. 
 
 STEEL MILL COOLING WATER 
 
 Large volumes of process water are used 
 in secondary production of steel. Much 
 of this water is used in the direct-spray 
 quenching of billet and becomes contami- 
 nated mainly by mill scale and tramp 
 oils. The mill scale is removed by set- 
 tling primary and secondary scale pits, 
 but residual suspended solids clog spray- 
 er nozzles and increase abrasion of plant 
 piping. Tramp oils are treated by skim- 
 ming and emulsif iction with surfactants. 
 
 The treated water passes through a cool- 
 ing tower before returning to the plant. 
 Several samples of return water were 
 filtered in laboratory tests before field 
 testing began. Results for both field 
 and laboratory tests are shown in table 
 5. The process water had high levels of 
 dissolved solids, and suspended particles 
 had weakly negative zeta potentials, but 
 these could not be measured accurately 
 owing to the high conductivity of the wa- 
 ter. Jar tests showed that 30 ppm alum 
 gave optimum settling. Results of the 
 bench tests indicated that the dual- 
 medium filters were not significantly 
 better than single-medium filters, and 
 that the MgO and anthracite-MgO filters 
 were able to filter two to three times 
 more water before breakthrough than the 
 sand or anthracite-garnet filters. 
 
14 
 
 TABLE 5. - Filtration of steel mill cooling water 
 
 Test 
 
 Filter medium (d m ) 
 
 NTU 
 
 t/t 
 
 V, 
 L/cm 2 
 
 v, 
 cm/s 
 
 V/H 
 
 F 
 (xlO 5 ) 
 
 LABORATORY TESTS 
 
 
 1. 
 
 
 1. 
 
 38 
 
 0. 
 
 
 0. 
 
 
 0. 
 
 3-mm anthracite, 0.71-mm 
 3-mm anthracite, 0.71-mm 
 
 7 1— mm MgO 
 
 7 1-mm sand 
 
 7 1 -mm MgO 
 
 sand* • • 
 MgO .... 
 
 13.3 
 
 19.3 
 
 24 
 
 27 
 
 22 
 
 0.038 
 .018 
 .015 
 .030 
 .011 
 
 3.4 
 6.7 
 7.4 
 2.4 
 6.2 
 
 0.34 
 .34 
 .34 
 .34 
 .34 
 
 106 
 91 
 
 106 
 57 
 31 
 
 36 
 20 
 14 
 53 
 35 
 
 FIELD TESTS 
 
 41, 
 
 42. 
 43. 
 44. 
 45. 
 46. 
 
 0.71-mm MgO 
 
 0. 7 1-mm sand 
 
 0.71-mm MgO 
 
 0. 7 1-mm sand 
 
 0.71-mm MgO 
 
 0. 7 1-mm sand 
 
 0.71-mm MgO 
 
 0. 7 1-mm sand 
 
 0.71-mm MgO 
 
 0. 7 1-mm sand 
 
 1.3-mm anthracite, 
 1.3-mm anthracite, 
 
 0. 7 1-mm 
 0. 7 1-mm 
 
 MgO .... 
 
 sand. • • 
 
 0.35 
 
 13 
 
 .34 
 
 3.1 
 
 .33 
 
 18 
 
 .33 
 
 8.7 
 
 .21 
 
 38 
 
 .21 
 
 42 
 
 .18 
 
 >59 
 
 .15 
 
 33 
 
 .23 
 
 30 
 
 .23 
 
 31 
 
 .24 
 
 41 
 
 .24 
 
 39 
 
 120 
 1,800 
 
 130 
 
 620 
 47 
 53 
 
 <42 
 76 
 63 
 57 
 52 
 63 
 
 Values of F(xl0 5 ) are 14 and 35 for MgO 
 and 53 for sand, while differences be- 
 tween the dual-medium filters are less 
 pronounced. 
 
 In the field mainly single-medium fil- 
 ters were tested, and flow rate was the 
 only variable that was manipulated. In 
 general, the field and laboratory tests 
 are in agreement. Filtration velocities 
 had to be reduced from 0.34 to 0.21 cm/s 
 to get F values roughly equivalent to 
 those from bench tests, but this appears 
 to be mainly due to differences in head 
 loss. Higher suspended-solid loading, 
 entrained air (possibly enhanced by use 
 of surfactant for oil breaking), and 
 other factors could be responsible. 
 Field tests were usually controlled to a 
 lesser degree and generally gave slightly 
 poorer results than laboratory tests. 
 Filtrate volume at breakthrough for the 
 MgO filter often doubled that for the 
 sand filter, and F values were lower ex- 
 cept for one test. Differences between 
 dual-medium filters probably were not 
 statistically significant, and run 
 lengths were shortened considerably by 
 early breakthrough. Although the field 
 test results were for the most part not 
 quite so good (higher F) as results from 
 
 laboratory tests, the trends in the data 
 are remarkably similar, and MgO is sub- 
 stantially more effective than sand in 
 this application. 
 
 PROCESS WATER FROM MAGNETITE 
 BENEFICIATION 
 
 Process water used in the beneficia- 
 tion of magnetite becomes laden with mod- 
 erate levels of suspended hematite. 
 Water is recycled and is treated only by 
 settling before returning to the grinding 
 circuit. As can be seen from the results 
 of bench tests given in table 6, this 
 water is easily filtered when 15 ppm alum 
 is added for f locculation. MgO filters 
 give slightly higher F values but more 
 than double the filtrate volume of sand 
 at breakthrough. Dual-medium anthracite- 
 garnet and anthracite-MgO filters are 
 nearly equivalent. Three field tests 
 were run with single-medium MgO and sand 
 filters, and the differences were even 
 more pronounced than in the laboratory 
 tests; breakthrough occurred so rapidly 
 in the sand filters that quantitative 
 comparisons were meaningless. Results 
 for the MgO filters were comparable with 
 those from bench tests. 
 
TABLE 6. - Filtration of iron ore processing water 
 
 15 
 
 Test 
 
 Filter medium (d m ) 
 
 T o» 
 NTU 
 
 t/t 
 
 V, 
 L/cm 2 
 
 v, 
 
 cm/s 
 
 V/H 
 
 F 
 (xlO 5 ) 
 
 49 
 
 50 
 
 1.3-mm anthracite, 0.71-mm MgO.... 
 1.3-mm anthracite, 0.71-mm garnet. 
 1.3-mm anthracite, 0.42-mm MgO.... 
 
 49.5 
 46.0 
 54.5 
 55.0 
 56.0 
 
 0.005 
 .003 
 .003 
 .003 
 .002 
 
 4.0 
 4.3 
 8.3 
 4.3 
 11.2 
 
 0.34 
 .34 
 .33 
 
 .34 
 .34 
 
 220 
 
 120 
 
 990 
 
 51 
 
 21 
 
 2.4 
 2.2 
 
 .26 
 5.0 
 
 51 
 
 0. 7 1-mm MgO 
 
 9.3 
 
 
 
 
 PROCESS WATER FROM FLOTATION OF IRON ORE 
 
 Process water from this flotation oper- 
 ation had almost 250 ppm of very fine 
 iron oxide and silicate particles, 11 ppm 
 Ca hardness, 110 ppm dissolved Si0 2 , 
 115 ppm P alkalinity, and 610 ppm M alka- 
 linity (as milligrams of CaC0 3 ). This 
 water is first settled in a large sedi- 
 mentation basin and then clarified with 
 alum flocculation before discharge. In 
 these tests overflow from the sedimenta- 
 tion basin was used to test the MgO and 
 sand filters. 
 
 Filteration results were extremely 
 sensitive to flocculant dosage (Separan 
 AP-30 anionic polymer), which was varied 
 between 0.62 and 2.5 ppm. In general, 
 sand outperformed MgO in field tests, 
 giving F values that were 2.5 to 5 times 
 lower than those for MgO. F(xl0 5 ) 
 ranged from 470 to 1,300 for MgO and from 
 200 to 290 for sand. These values are 
 too high (high rate of head loss) to be a 
 practical application for either filter 
 medium. The results are consistent with 
 other tests in which MgO filters became 
 plugged easily when polymer flocculants 
 were used. This type of process water 
 needs to be softened and clarified before 
 attempting filtration. 
 
 MISSISSIPPI RIVER WATER 
 
 Mississippi River water is used to sup- 
 ply potable water to a large segment of 
 the Minneapolis-St. Paul metropolitan 
 area. Municipal-water treatment involves 
 lime-softening, settling, and filtration 
 followed by disinfection. A series of 
 filtration tests were run on Mississippi 
 River water treated in a manner similar 
 to that used at the municipal water 
 treatment plant. River water was first 
 softened with 150 ppm CaO and then 
 
 flocculated with 2.0 ppm alum. The 
 decant after 15 to 30 min settling was at 
 pH 8.0±0.5 and had turbidity of 35±2 NTU. 
 More alum was mixed with the decant so 
 that final alum concentration in the fil- 
 ter influent was 26 ppm. Thirty- 
 centimeter beds of sand and MgO were 
 tested in parallel at a filtration veloc- 
 ity of 0.21 cm/s. 
 
 Three bench-scale tests were run under 
 these conditions, and in two of the three 
 tests run lengths were extended enough to 
 reach breakthrough. Values of F(xl0 5 ) 
 averaged 13±4 for the MgO and 22±12 for 
 the sand. The main difference appears to 
 be in the lower rate of head loss for the 
 MgO, which averaged 1.7 times lower than 
 for sand. The MgO filtered about 28 pet 
 more water at breakthrough, based on the 
 average of two tests. 
 
 Since the minimum run length was al- 
 ready about 11 h, both filters would 
 operate at >95 pet availability, so the 
 extra filtrate volume per cycle is proba- 
 bly not too significant. The reduced 
 head loss rate is an important advantage, 
 however. 
 
 PROCESS WATER FOR CUTTING GRANITE 
 
 The final field tests were conducted on 
 water used in cutting granite. 
 Particulate-laden water is collected from 
 all cutting and grinding stations and 
 settled in a clarifier. Polymer is used 
 to aid flocculation, but clarification is 
 poor owing to inadequate control of floc- 
 culant dosage, inadequate mixing, and 
 convection due to evolution of gases 
 caused by microbial activity. On occa- 
 sion phosphoric acid (H3PO4 ) is also 
 added to the system when a special kind 
 of finish is being applied to the gran- 
 ite. The process water is recycled with 
 minimal makeup water; consequently, 
 
16 
 
 hardness and conductivity are increased 
 and calcite scaling and corrosion are 
 serious operating problems. Zeta poten- 
 tials of the suspended particles were 
 found to be weakly negative, with values 
 ranging from -1.4 to -23 mV with a mean 
 value of -11±6 mV. The specific conduc- 
 tivity was 1,300 ymho. 
 
 These tests were intended to measure 
 the filtering capability of the MgO over 
 an extended period of time. Media attri- 
 tion and scaling effects were to be ob- 
 served directly, and their impact on fil- 
 ter performance evaluated. Laboratory 
 tests on process water samples indicated 
 that MgO, sand, and anthracite were ap- 
 proximately equal in their ability to 
 filter this water. Both alum floccula- 
 tion and softening the water by elevating 
 pH were more effective than using poly- 
 meric flocculants. 
 
 In the field tests the water was 
 treated first by softening with 6 pet 
 NaOH and settling, and then by filtration 
 through 55-cm beds of either 0. 71-mm MgO 
 or sand. The NaOH solution was metered 
 into raw process water entering a 570-L 
 settler, and the overflow was kept at 
 
 pH 9.0 to 9.8. Total flow through the 
 system was 11.4 L/min (0.19 L/s), and the 
 filtration velocity was 0.31 cm/s. Dual- 
 medium filters were also tested with 1.3- 
 mm anthracite replacing the upper 25 to 
 30 pet of the beds. 
 
 Laboratory tests varied considerably 
 but generally indicated that F(xl0 5 ) 
 values of around 30 could be expected in 
 the field tests. Unfortunately, field 
 test results varied even more than the 
 laboratory tests. In some cases tur- 
 bidity removal was excellent for both 
 filters, and in other tests neither 
 filter would perform efficiently. No 
 trend could be discerned that would in- 
 dicate that attrition was impairing MgO 
 performance or that either sand or MgO 
 was the better filter. Figure 4 illus- 
 trates the wide variations in filtrate 
 quality for tests with dual-medium 
 filters. Curve 3 is a fairly typical 
 plot for a good filtration run, in this 
 case with the anthracite-MgO filter. 
 Filtrate turbidity decreases below 1.0 
 NTU within 1 h and remains low for a 
 reasonable length of time. The anthra- 
 cite-sand filter (curve 4) also achieved 
 
 100.00 
 
 CD 
 
 => 
 I- 
 
 .10 
 
 .01 
 
 1 
 
 i 
 
 1 
 
 i 
 
 i 
 
 i 
 
 i i 
 
 
 ~ //^--^SP^o. 
 
 \^L 
 
 
 
 / 
 
 KEY 
 d Anthracite-MgO 
 Anthracite-sand 
 — * Samples taken 
 
 - 
 
 \. 
 
 <? 
 
 
 
 
 - 
 
 < X. 
 
 ^^L, 
 
 
 i 
 
 
 
 
 
 
 
 
 
 ■Q--c>-^ t:> __ T3 __ a __ D J 
 
 
 1 
 
 i 
 
 i 
 
 i 
 
 i 
 
 i i 
 
 
 4 
 TIME, h 
 
 FIGURE 4.— Filtration of granite-cutting process water. 
 
excellent turbidity removal after a 
 longer delay. 
 
 The arrows in figure 4 correspond to 
 sampling for chemical analysis at the 
 times shown. From the results given in 
 table 7, it appears that good filtration 
 resulted when P (probably as orthophos- 
 phate) and Fe both were present in the 
 process water. On the day that test 1 
 was run both P and Fe levels were low and 
 the anthracite-sand filtrate was turbid. 
 After 5 h flow was switched to the 
 anthracite-MgO filter, and turbidity re- 
 moval was poor in the initial stages. 
 Toward the end of the run, filtrate re- 
 moval was improved and P and Fe were 
 again both present at measurable levels. 
 It is noteworthy that the MgO removes 
 P and the sand does not. The MgO also 
 adds small but significant amounts of Ca 
 and Mg to that in the influent. (CaO is 
 
 17 
 
 an impurity in the periclase, present at 
 1 to 3 wt pet. ) 
 
 TABLE 7. - Chemical analysis of process 
 water 
 
 Stream 
 
 pH 
 
 Concentration, rc 
 
 ig/L 
 
 
 Ca 
 
 Mg 
 
 S 
 
 P 
 
 Fe 
 
 Test 1: 
 
 
 
 
 
 
 
 Influent. . 
 
 9.3 
 
 77 
 
 57 
 
 54 
 
 <1.0 
 
 1.7 
 
 Filtrate. . 
 
 9.3 
 
 68 
 
 55 
 
 56 
 
 <1.0 
 
 <.2 
 
 Test 2: 
 
 
 
 
 
 
 
 Influent. . 
 
 9.3 
 
 71 
 
 55 
 
 60 
 
 1.6 
 
 3.0 
 
 Filtrate. . 
 
 9.4 
 
 79 
 
 66 
 
 60 
 
 <1.0 
 
 <.2 
 
 Test 3: 
 
 
 
 
 
 
 
 Influent. . 
 
 9.4 
 
 64 
 
 64 
 
 69 
 
 1.3 
 
 2.3 
 
 Filtrate.. 
 
 9.5 
 
 70 
 
 71 
 
 65 
 
 <1.0 
 
 <.2 
 
 Test 4: 
 
 
 
 
 
 
 
 Influent. . 
 
 9.3 
 
 69 
 
 63 
 
 66 
 
 1.7 
 
 .24 
 
 Filtrate.. 
 
 9.3 
 
 65 
 
 62 
 
 56 
 
 1.3 
 
 3.1 
 
 ENGINEERING ASPECTS 
 
 BACKWASHING OF MgO FILTERS 
 
 Filters are cleaned by backwashing with 
 an upward flow of water, which fluidizes 
 the bed and removes deposited solids 
 mainly by hydraulic shearing forces. Of- 
 ten air scouring is used to increase the 
 backwash efficiency and reduce both the 
 flow rate and flow volume required to 
 clean the filter. The air bubbles in- 
 crease abrasion between filter grains and 
 give high shear rates owing to the in- 
 creased turbulence in the bed. After 
 dual-medium filters are backwashed with 
 air scouring, a high-rate backwash is re- 
 quired to restratify the media mixed by 
 the vigorous cleaning action. Under- 
 standing and being able to predict bed 
 expansion are important for both the de- 
 sign and operation of deep-bed filters. 
 Ideally, it would be possible to calcu- 
 late bed expansion for any flow velocity 
 knowing only the basic properties of the 
 filter medium and the fluid. In practice 
 bed expansion can only be predicted from 
 correlations derived from experimental 
 data. It is also important to predict 
 optimal backwash rates and to determine 
 whether a desired combination of filter 
 
 materials can be restratified by back- 
 washing when used together in dual-medium 
 filters. 
 
 A filter bed becomes fluidized when the 
 flow velocity is increased to the point 
 where the head loss across the medium is 
 equal to the weight of the grains in wa- 
 ter. Further increases in flow velocity 
 do not increase head loss across the bed; 
 the bed expands and the increase in po- 
 rosity offsets the higher velocity. A 
 mass balance on the medium requires that 
 
 h b (l- e ) = hb (l-e ), (3) 
 
 where h b = bed depth, 
 
 e = porosity, 
 
 h bo = unfluidized bed depth, 
 
 and e = unfluidized bed porosity. 
 
 Bed porosity is observed to increase log- 
 arithmically as a function of flow velo- 
 city. In dimensionless form this is 
 expressed as 
 
 log Re = n log e + log Re| , (4) 
 
18 
 
 where Re = 
 
 Reynolds number, 
 Re = (v d m /v), 
 
 v = the fluid velocity, 
 
 d m = the filter medium grain 
 size, 
 
 v = the kinematic viscosity of 
 the fluid, 
 
 and Re | = the Reynolds number corre- 
 sponding to the unhindered 
 settling velocity of the 
 filter grains. 
 
 As this velocity is approached, the me- 
 dium is entrained in the fluid and the 
 porosity becomes unity. Maximum shear 
 rates occur at porosities between 0.68 
 and 0.71 O0). 
 
 The parameters n and Re | are obtained 
 by measuring the initial-bed porosity or 
 bulk density; for an arbitrarily chosen 
 starting depth of medium, expanded bed 
 height is measured at several flow veloc- 
 ities. Expanded-bed porosity is calcu- 
 lated from equation 3, and linear regres- 
 sion or graphical methods are used to 
 find the slope and intercept of plots of 
 log e versus log v. This is repeated for 
 various sizes of each medium. 
 
 Both n and Re| are dependent on the 
 fundamental dimensionless group known as 
 the Archimedes or Galileo number: 
 
 Ar = g d m 5 [(S.G.) m 
 
 ( S ' G -)f 1 , ( 5 ) 
 
 where Ar = ratio of buoyant to viscous 
 drag forces acting on a 
 particle, 
 
 (S.G.) f 
 (S.G.) m 
 
 g " 
 
 d m = 
 
 specific gravity of the 
 fluid, 
 
 specific gravity of the 
 medium, 
 
 the acceleration owing to 
 gravity (9.8 m/s 2 ), 
 
 the diameter of the grains 
 of medium, 
 
 and v = the kinematic velocity 
 (m 2 /s). 
 
 Ar incorporates only properties intrinsic 
 to the medium and fluid. Values of Ar 
 range from 10 2 to 10 5 for conventional 
 deep-bed filters. 
 
 Normal backwashing spans a transition 
 region between laminar and turbulent 
 flow, with Rej ranging from less than 10 
 to approximately 500. One approach to 
 modeling bed expansion is to use power- 
 log correlations between n, Re] , and Ar 
 for each medium: 
 
 log n = ailog Re ( + bj (a^ <0) (6) 
 
 log Rej = a2log Ar + b2« (7) 
 
 This is successful if done within suffi- 
 ciently narrow limits of Ar. For laminar 
 or Stokes settling (Re <1), this simpli- 
 fies to 
 
 Re I = (const)Ar, 
 
 (8) 
 
 and for fully turbulent flow (Re >100), 
 a] becomes very small and n approaches a 
 constant value. Although accurate models 
 can be obtained in this manner for a 
 specific filter medium, attempts to make 
 a more general model fail because there 
 is no meaningful measure of particle 
 shape and its effect on drag coefficient 
 
 OO-n). 
 
 A simple correlation was given by Bohm 
 (12) for predicting the flow rate corre- 
 sponding to maximum mass transfer rate in 
 a fluidized bed: 
 
 Re op+ = 0.072 Ar - 614 . 
 
 (9) 
 
 High shear rates enhance mass transfer by 
 reducing the boundary layer thickness 
 around the particles. Because large 
 shear rates are also needed for cleaning 
 deep-bed filters, this correlation may be 
 useful for predicting optimum backwashing 
 velocities. 
 
 Fluidization curves for six sizes of 
 MgO are shown in figure 5. Similar 
 curves were obtained for sand and 
 
19 
 
 10.00 
 
 FIGURE 5 
 
 0.60 0.70 
 
 POROSITY U) 
 
 —Bed expansion of MgO versus flow velocity. 
 
 0.80 
 
 olivine. Values of n and Re | were deter- 
 mined by linear regression of the log e 
 versus log v plots. Literature values 
 for the viscosity and density of water 
 were used to calculate Ar and Re at the 
 temperatures measured during each test. 
 
 Test results are summarized in table 8. 
 Also included are values given by Gun- 
 asingham (10) for anthracite, ballotini, 
 polystyrene, and sand. ^ e pt was calcu- 
 lated from equation 9 and then substi- 
 tuted for Re in equation 4 to get E op -(-. 
 
 Attempts to derive a specific model for 
 the expansion of MgO were unsuccessful 
 owing to the nonlinearity of plots of log 
 n versus log Re j and log Re| versus log 
 Ar. At grain sizes of 1 mm and greater, 
 n varies much less than at the smaller 
 sizes. Apparently there is a transition 
 in the expansion behavior of MgO parti- 
 cles between 0.5 and 1.0 mm. Data for 
 sand also displayed nonlinear character- 
 istics, but values for n agree fairly 
 well with those of Gunasingham (10), con- 
 sidering probable differences in particle 
 shape and size distribution not taken in- 
 to account. Because of these uncertain- 
 ties, this type of correlation seems of 
 limited value for design purposes. 
 
 Calculated optimum bed porosities fall 
 between 0.56 and 0.68 for particle sizes 
 greater than 0.5 mm (fig. 6). Neglecting 
 the lower e op ^ porosity values for ballo- 
 tini and sand, the values for MgO, poly- 
 styrene, and anthracite are between 0.65 
 and 0.68, which is in good agreement with 
 the predicted porosity range needed to 
 produce maximum hydraulic shear (10). 
 Ballotini and sand have smaller optimum 
 porosities because they are more spheri- 
 cal and have smaller initial porosities 
 than MgO, anthracite, and polystyrene. 
 Below 0. 5-mm grain size the optimum bed 
 porosity is substantially greater than 
 the predicted range for maximum shear. 
 This is consistent with the data given 
 by Bohm (12), which showed that, for 
 Ar <10 3 , Re opt values begin to lie well 
 below the correlation given by equation 
 9. For nonspherical particles larger 
 than 0.5 mm, the simpler correlation suc- 
 cessfully predicts the optimum backwash 
 velocity needed to achieve maximum shear 
 rates. 
 
 Determining the compatability of var- 
 ious media for use in multimedium filters 
 can be complicated. Intuitively it may 
 be obvious that a separation will be 
 
20 
 
 TABLE 8. - Fluidization results 
 
 Sand: 
 
 1. 54-mm 
 
 1.00-mm 
 
 . 71— mm 
 
 .50-mm 
 
 MgO: 
 
 1. 54-mm 
 
 1.30-mm 
 
 1.00-mm 
 
 .50-mm 
 
 . 42-mm 
 
 . 25-mm 
 
 Olivine: 
 
 0. 50-mm 
 
 •35-mm 
 
 . 25-mm 
 
 Sand 00): 
 
 0. 84-mm 
 
 .65-mm 
 
 . 42-mm 
 
 Ballotini (10): 
 
 2. 38-mm 
 
 1. 30-mm 
 
 . 92-mm 
 
 • 78-mm 
 
 Anthracite (10): 
 
 2. 59-mm 
 
 2. 38-mm 
 
 1. 84-mm , 
 
 1. 30-mm 
 
 Polystyrene (10) 
 
 3. 67-mm 
 
 3.08-mm 
 
 2. 59-mm , 
 
 2. 18-mm 
 
 Ar 
 
 53,530 
 
 15,497 
 
 5,486 
 
 4,727 
 
 98,460 
 
 58,690 
 
 25,816 
 
 3,218 
 
 1,908 
 
 402.5 
 
 4,727 
 
 1,667 
 
 562 
 
 7,935 
 4,524 
 1,184 
 
 111,332 
 
 25,659 
 
 7,313 
 
 5,221 
 
 35,414 
 
 21,418 
 
 14,771 
 
 4,948 
 
 18,920 
 
 14,724 
 
 10,483 
 
 7,409 
 
 Re 
 
 306 
 
 178 
 79.4 
 50.4 
 
 457 
 
 332 
 
 210 
 77.7 
 38.2 
 11.0 
 
 72.5 
 38.7 
 16.7 
 
 95.7 
 63.4 
 27.1 
 
 288 
 
 134 
 69.9 
 56.1 
 
 174.4 
 
 133.7 
 
 107.6 
 
 60.2 
 
 116.8 
 
 102.9 
 
 84.5 
 
 69.1 
 
 Re 
 
 opt 
 
 57.6 
 26.9 
 14.2 
 13.0 
 
 83.4 
 61.0 
 36.8 
 10.3 
 7.44 
 2.86 
 
 13.0 
 6.85 
 3.50 
 
 17.9 
 12.6 
 5.55 
 
 90.4 
 36.7 
 17.0 
 13.8 
 
 44.7 
 32.8 
 26.1 
 13.4 
 
 30.4 
 26.1 
 21.2 
 17.1 
 
 : opt 
 
 0.56 
 .56 
 .57 
 .69 
 
 .65 
 .65 
 .65 
 .67 
 .74 
 .79 
 
 .74 
 .82 
 .83 
 
 .65 
 .67 
 .68 
 
 .59 
 .59 
 .58 
 .58 
 
 .66 
 .66 
 .68 
 .67 
 
 .65 
 .65 
 .66 
 .66 
 
 2.885 
 3.220 
 3.051 
 3.607 
 
 3.899 
 3.875 
 4.030 
 5.057 
 5.421 
 5.645 
 
 5.676 
 8.098 
 8.751 
 
 3.873 
 4.041 
 4.162 
 
 2.230 
 2.429 
 2.596 
 2.611 
 
 3.242 
 3.417 
 3.719 
 3.795 
 
 3.117 
 3.180 
 3.301 
 3.420 
 
 possible only if Re | of the upper medium 
 is smaller than that of the lower layer. 
 Re | also increases as a function of Ar, 
 so it should be possible to predict sep- 
 aration based on the size of Ar. In 
 practice, however, this becomes compli- 
 cated by differences in particle shapes 
 and the fact that some intermixing of 
 layers may be desirable. For convention- 
 al filtration systems that operate with a 
 downward flow, it is desirable to have 
 the coarsest medium in the uppermost 
 layer to achieve any benefit over 
 single-medium filters. From this stand- 
 point, a combination of MgO and sand is 
 not a practical dual-medium filter. 
 
 Attempts to backwash a filter with the 
 upper layer of 0.71-mm sand and the lower 
 layer of 0.5-mm MgO resulted in almost 
 total intermixing of both layers. The 
 corresponding values of Ar and Rej are 
 very close (table 8). To get adequate 
 differences in Re| would require either 
 substantially finer MgO or at best equiv- 
 alently sized sand as the upper layer, 
 neither of which is desirable. 
 
 MgO worked well with anthracite. Dual- 
 medium filters of 0.71-mm MgO and 1.3-mm 
 anthracite were easily restratified by 
 backwashing. A sharp interface was pro- 
 duced between the two media after 15 min 
 of backwashing at flow velocities of 
 
21 
 
 1.0 
 
 .9 - 
 
 .8 - 
 
 00 
 
 o 
 
 JE .7 
 o 
 
 0_ 
 
 .6 - 
 
 - 
 
 T ▼ 
 
 • 
 
 • T 
 
 1 
 
 
 
 1 
 
 Elements 
 
 1 
 KEY 
 
 Bureau of Mines 
 
 Literature 
 
 
 - 
 
 MgO 
 
 Sand 
 
 Olivine 
 
 Ballotini 
 
 Polystyrene 
 
 Anthracite 
 
 • 
 
 A 
 ▼ 
 
 NA 
 NA 
 NA 
 
 NA 
 
 NA 
 a 
 
 O 
 
 - 
 
 ▲ 
 
 
 
 
 
 
 
 - 
 
 - 
 
 • 
 
 A D O 
 
 1 
 
 5 " 
 
 • 
 
 □ 
 
 • 
 ▲ 
 
 I 
 
 o o 
 a 
 
 
 
 - 
 
 I 2 3 
 
 FILTER GRAIN SIZE, mm 
 
 FIGURE 6.— Optimum bed porosities calculated from optimum Reynolds number. NA = Not available. 
 
 around 4 cm/s. Decreasing the velocity 
 or duration of the backwash resulted in 
 more intermixing of the two layers. An 
 equivalently sized sand-anthracite filter 
 was adequately but not so cleanly sepa- 
 rated as the MgO-anthracite filter. 
 
 ATTRITION OF MgO FILTERS DURING 
 BACKWASHING 
 
 Backwashing with air scour creates a 
 significant amount of interparticle abra- 
 sion in the filter medium. Although this 
 is an effective backwashing technique, it 
 does increase attrition of the filter me- 
 dium. The rubbing action of the grains 
 of filter medium produces fines that can 
 clog the bed in subsequent filtrations 
 and also reduce the effective size of the 
 medium. High attrition rates can result 
 in noticeable changes in filter perfor- 
 mance; head-loss rates can increase 
 enough to drastically reduce production 
 of filtered water. Angular particles 
 such as anthracite or MgO would be ex- 
 pected to experience greater attrition 
 than a spherical filter medium like sand. 
 
 Forty-eight filtration cycles were made 
 on a 61-cm bed of 0.71-mm MgO to test the 
 resistance of the MgO filter grains to 
 attrition. A standard suspension of 25 
 ppm kaolin and 25 ppm milled sand, floc- 
 culated with 10 ppm alum, and a filtra- 
 tion velocity of 0.21 cm/s were used 
 throughout. Each cycle consisted of a 
 6-h filtration run followed by 1 h of 
 
 backwashing. The backwashing proce- 
 dure consisted of a few minutes of fluid- 
 ization, followed by about 30 min of air- 
 water scouring and then by 30 min of 
 high-rate backwashing at 50-pct bed ex- 
 pansion. This latter step was employed 
 to remove fines and dislodge air bubbles. 
 This backwashing procedure was actually 
 more intense and longer in duration than 
 that normally used in commercial prac- 
 tice, since an air scour lasting 3 to 5 
 min and a 10- to 15-min fluidization at 
 20- to 50-pct bed expansion is usually 
 sufficient to clean the bed (_9)» Total 
 elapsed time for the 48 cycles to be com- 
 pleted was about 6 months. The MgO fil- 
 ter grains were kept under water in the 
 filter column between cycles. 
 
 Data from the initial, final, and every 
 fifth intermediate run are listed in 
 table 9. Cycle 39 was used in place of 
 
 TABLE 9. - Durability study 
 
 Cycle 
 
 t/t q 
 
 V/H 
 
 F(xl0 5 ) 
 
 SC, g/cm 3 
 
 
 0.048 
 
 190 
 
 26 
 
 9.0 
 
 
 .081 
 
 440 
 
 19 
 
 20 
 
 
 .081 
 
 590 
 
 13 
 
 27 
 
 15 
 
 .042 
 
 640 
 
 6.5 
 
 31 
 
 20 
 
 .038 
 
 440 
 
 8.8 
 
 21 
 
 
 .046 
 
 440 
 
 11 
 
 21 
 
 
 .042 
 
 341 
 
 12 
 
 16 
 
 35 
 
 .042 
 
 296 
 
 13 
 
 14 
 
 
 .042 
 
 281 
 
 15 
 
 13 
 
 
 .040 
 
 326 
 
 12 
 
 16 
 
 48 
 
 .031 
 
 297 
 
 11 
 
 14 
 
22 
 
 cycle 40 because the latter had an unusu- 
 ally large increase in head loss owing to 
 air blinding of the filter. Variations 
 in head loss rate account for most of the 
 variation in the values of the filtration 
 indexes. 
 
 The solid-capture index, SC, is plotted 
 versus the number of cycles in figure 7. 
 Filter performance initially improves, 
 then decreases gradually until a fairly 
 stable value of SC is reached in the vi- 
 cinity of the 40th cycle. Experimental 
 uncertainty exists because low pressures 
 and small pressure differences are dif- 
 ficult to measure. Small pressure drops 
 (head loss) for a bed result in high val- 
 ues of SC. The uncertainity in measuring 
 these small pressure drops leads to the 
 large error brackets for SC values. In 
 spite of the large uncertainty bracketing 
 each point, the trend shown in figure 7 
 appears to have statistical significance, 
 and the value of SC near the end of 
 the test has stabilized around 12 to 
 15 g/cm 5 . The behavior of the filter- 
 ability index [F(xl0 5 )] essentially mir- 
 rors that of SC, and a stable level be- 
 tween 10 and 15 is reached about halfway 
 into the test. Values for F and SC com- 
 pare quite favorably with those given in 
 table 3 for filtration of kaolin and 
 milled sand. 
 
 Forty-eight backwash cycles is equiva- 
 lent to a few weeks to several months of 
 
 20 30 
 FILTRATION CYCLES 
 
 FIGURE 7.— Binding of MgO filters. 
 
 operation, depending on the application. 
 The intensity and duration of the air 
 scour, which is largely responsible for 
 filter grain attrition, is equivalent to 
 a period of normal commercial operation 
 perhaps 6 to 10 times longer. Since fil- 
 tration performance of the MgO has stabi- 
 lized at an acceptable value during these 
 tests, attrition of MgO does not seem to 
 be a significant problem. Media losses 
 to attrition and entrainment in conven- 
 tional media can be as high as 5 to 15 
 wt pet in the first year of service 
 (lower value for sand and higher value 
 for anthracite). MgO losses are within 
 this range; no significant decrease in 
 bed depth was evident at the end of this 
 test. 
 
 MgO durability was also evaluated by a 
 standard friability test used to evaluate 
 filter media (13). Friability is deter- 
 mined by calculating the fraction of sam- 
 ple by weight that remains larger than 
 the effective grain diameter (d e ff) after 
 milling. Samples are milled by steel 
 balls in a metal cylinder which is tum- 
 bled end over end at 25 r/min for 15- and 
 30-min intervals. The milled samples are 
 sieved, and the weight in each size frac- 
 tion is compared to initial weights in 
 those size fractions. Losses of 6 to 
 10 wt pet or less at 15-min milling and 
 15 to 20 wt pet or less at 30-min milling 
 of the filter material larger than d e ff 
 indicate that the filter material has 
 good durability. Attrition losses of 10 
 to 15 wt pet and 15 to 25 wt pet for the 
 two time intervals are tolerable for con- 
 ventional filter media. A candidate fil- 
 ter material is rejected if losses are 
 >20 wt pet or >35 wt pet, respectively, 
 for the two time intervals (13). MgO 
 passed the standard friability test 
 easily. A sample with an original d eff 
 of 0.61 mm had losses of 4.0 wt pet and 
 4.5 wt pet for the 15- and 30-min mill- 
 ing. A second sample with d eff equal 
 to 0.47 mm showed losses of 5.5 and 
 7.0 wt pet for the two intervals. Both 
 tests demonstrated very good durability 
 for MgO. 
 
23 
 
 POISONING OF MgO FILTERS BY HEAVY METALS 
 
 Dissolved heavy metals present in the 
 influent will encounter an increase in pH 
 and may precipitate as they pass through 
 an MgO filter. Previous experience in- 
 dicated that these precipitates adhere 
 quite strongly to MgO granules. This 
 could spoil the desirable surface proper- 
 ties of the MgO if the metal deposits are 
 not removed by routine backwashing. If 
 this were the case, it would become nec- 
 essary to chemically strip the metals, 
 most likely by adding either dilute acids 
 or chelating agents at some stage in the 
 backwashing. 
 
 In this study a 46-cm bed of 0.5-mm MgO 
 was tested using 25 ppm suspensions of 
 kaolin, both with and without dissolved 
 heavy metals being present. Influent pH 
 was adjusted to 7.0±0.1 for all tests. 
 The filter was put through a series of 
 tests in which alternate filtrations were 
 spiked with 5.0 ppm each of Cd 2+ , Mn 2 + , 
 
 Ni 
 
 2 + 
 
 and 
 
 Zn 2 \ 
 
 all of which are 
 
 soluble at neutral pH at this level of 
 concentration. Between tests the filter 
 was backwashed with air-water scouring, 
 followed by fluidization at high flow 
 velocity. Filtration velocity was 
 0.34 cm/s. 
 
 Plots of filtrate turbidity, pH, and 
 pressure for these tests are plotted 
 versus time in figure 8. In the first 
 test cycle no metals were added and fil- 
 trate pH remained fairly constant at 10.2 
 to 10.3 for the 6-h test cycle. Head 
 loss was small, and an average of 90 pet 
 of the turbidity was removed. In the 
 second test cycle heavy metals were in 
 the influent. Turbidity was decreased by 
 99 pet, but head loss increased dramati- 
 cally. Coating of the MgO with precipi- 
 tated metal hydroxides is indicated dur- 
 ing this cycle by the steadily declining 
 filtrate pH. Subsequent filtration with- 
 out metals in the third test cycle showed 
 a slight increase in the removal of tur- 
 bidity and slightly lower filtrate pH 
 than in the first test cycle. In the 
 
 o 4 
 
 2 E 
 
 >- V) 
 
 - o ° 
 
 Q _J 
 
 ^ UJ 
 
 ■Cycle 
 
 f\ 
 
 \ 
 \ 
 
 \ 
 
 \ 
 
 V 
 
 ■Cycle 2- 
 
 f^ 
 
 -Cycle 3- 
 
 KEY 
 — pH 
 
 Head loss 
 
 Turbidity 
 
 A 
 
 \ 
 
 \ 
 
 \ 
 
 < Cycle 5- 
 
 _L 
 
 10 
 
 5 10 15 20 25 
 
 TIME, h 
 
 FIGURE 8.— Effects of dissolved heavy metals on MgO filtration. 
 
 i 
 
 Q. 
 UJ 
 
 1- 
 < 
 or 
 
 30 
 
24 
 
 fourth test cycle the dissolved metals 
 were passed through the filter without 
 the presence of kaolin. In this cycle 
 the pH declined until it was only one 
 unit higher than that of the influent, 
 indicating that the reactive surface area 
 of the MgO was virtually saturated with 
 deposited precipitates of metal hydrox- 
 ides. Head loss was large in this cycle, 
 indicating that the precipitated metal 
 hydroxides rather than flocculation of 
 the kaolin were responsible for the in- 
 creased resistance to flow observed in 
 the second test cycle. In previous 
 tests, flocculation was not observed in 
 the reservoir containing the dissolved 
 metals and kaolin suspension. In the 
 fifth test cycle solid capture was again 
 improved over that in the initial test; 
 in fact, performance as measured by 
 
 filtration indexes actually improved 
 steadily with increased exposure to heavy 
 metals. Values of F(xl0 5 ) for the first, 
 third, and fifth runs were 28, 14, and 
 3.0, and corresponding values for SC were 
 7.8, 12, and 24 g/cm 3 . For the second 
 test cycle, which had both metals and ka- 
 olin present, F(xl0 5 ) was 60 and SC was 
 3.5 g/cm 3 . It is concluded that heavy 
 metals present in water to be filtered 
 will be precipitated as hydroxides and 
 will be bound to the MgO filter grains. 
 These precipitated hydroxides are only 
 partially removed by backwashing; how- 
 ever, their presence on the MgO filter 
 grains does not reduce the f ilterability 
 of the MgO. Too high a level of heavy 
 metals in the turbid water to be filtered 
 will result in accelerated increases in 
 head loss. 
 
 FILTRATION PARAMETERS 
 
 EFFECT OF SURFACE CHARGE AND PARTICLE 
 SHAPE ON FILTRATION 
 
 It has never been fully demonstrated to 
 what effect the positive surface charge 
 of the MgO contributes to its ability to 
 remove particulate, although this has 
 been previously suggested as a primary 
 factor (_2~\3)« In early contact filtra- 
 tion test studies, which used fine-mesh 
 active MgO, surface charge interactions 
 undoubtedly contributed greatly to the 
 filtration of unf locculated asbestos fi- 
 bers. But in applying this concept to 
 practical deep-bed filtration, both sur- 
 face area and activity were greatly re- 
 duced in the transition. Deeper beds of 
 coarse, dead-burned (fused) periclase 
 were used instead of active (porous) MgO; 
 furthermore, flocculation with aluminum 
 salts was necessary to achieve efficient 
 particulate removal. This would all tend 
 to minimize any surface charge effect. 
 
 The ultimate removal efficiency of a 
 sand filter is equal to and sometimes 
 slightly better than that of MgO, but the 
 amount of material that can be collected 
 (run length) of the MgO is often double 
 that of sand. This can be partially ex- 
 plained by the greater porosity of the 
 MgO; more material can be deposited be- 
 fore critical shear stresses are reached. 
 
 Increased porosity means increased aver- 
 age pore diameter, as would be the case 
 in using a coarser filter medium. Cap- 
 ture efficiency, however, usually de- 
 creases as pore diameter increases. Some 
 extra compensating mechanism allows the 
 MgO to achieve removal rates nearly 
 equivalent to those for sand. Surface 
 charge and particle shape (altered hydro- 
 dynamics) are two possible mechanisms. 
 
 A factorial study was performed to 
 qualitatively evaluate the effect of sur- 
 face charge and grain shape on particle 
 removal. Four combinations of medium 
 shape and charge were tested using a 
 standard pH 7.0 suspension of 50 ppm ka- 
 olin with no flocculant. Shallow beds 
 (15.2 cm) of 0.5-mm filter media were 
 tested during 2-h runs. The size of the 
 media tested is toward the small end of 
 the sizes used in deep-bed filters. 
 
 The four filter media were MgO (+, an- 
 gular), sand (-, spherical), quartzite 
 (-, angular), and MgO-coated sand 
 (+, spherical). Zeta potentials were de- 
 termined for crushed samples of media 
 suspended in distilled water. The zeta 
 potential of kaolin in distilled water 
 was also measured and found to be -27±5 
 mV. First-order removal coefficients 
 were calculated from the ratio of influ- 
 ent and filtrate turbidities: 
 
25 
 
 TABLE 10. - Effects of filter medium surface charge and particle 
 shape on kaolin removal 
 
 Medium 
 
 Zeta potential, 
 mV 
 
 No. of 
 trials 
 
 Removal coefficient, m" 1 
 
 
 Xo 
 
 Xf 
 
 Angular shape: 
 MgO 
 
 Quartzite 
 
 Spherical shape: 
 MgO-coated sand 
 
 20±7 
 -28±3 
 
 (+) 
 
 -15±6 
 
 4 
 3 
 
 ! 3 
 
 4 
 
 7.5±0.6 
 5.4±1.1 
 
 7.9±1.8 
 3.0± .6 
 
 6.5±0.4 
 11 ±1.5 
 
 9.211.9 
 
 8.4±1.3 
 
 'The last trial was deleted because MgO coating was being lost. 
 Values for X were much lower than for the other 3 trials. 
 
 . _ In (t/tq) 
 
 X " 1 
 
 (10) 
 
 Results are given in table 10. The 
 clean-bed coefficient (X ) is based on 
 the filtrate turbidities taken at 1 and 
 15 min into the test, while the final 
 turbidity (2 h) is used to calculate Xf . 
 
 In the initial stages of filtration 
 there was little deposited particulate, 
 so particle-to-medium interactions should 
 be at their maximum. Here MgO, whether 
 as a spherical or an angular grain, is 
 the most efficient filter by a substan- 
 tial margin. The negatively charged 
 media, whether angular or spherical, had 
 lower removal efficiencies, but the mag- 
 nitude of the (-) zeta potentials makes 
 less difference than the shape of the 
 medium; the more negative and angular 
 quartzite is more effective than spheri- 
 cal sand. The negative media exhibited 
 increasing filtration efficiency with 
 time; values of Xf are approximately 
 double those of X . The MgO efficiency 
 declines very slightly in this time; the 
 MgO-coated sand efficiency increases, but 
 with less than experimental uncertainty. 
 Negatively charged media actually become 
 the more efficient filters as deposits 
 form in the filter owing to enhanced hy- 
 drodynamic and mechanical interception 
 mechanisms. Surface charge interactions 
 were more important than shape for en- 
 hancing clean-bed-particle collection. 
 It is also of interest that head loss 
 rates were lower for the positively 
 charged media, averaging 3.5, 0, 5.3, and 
 8.4 cm H 2 for the MgO, MgO-sand, sand, 
 and quartzite, respectively. Unfortu- 
 nately, the experimental uncertainty in 
 
 pressure readings is at least 3.5 cm H 2 0, 
 but it would seem that particle shape 
 (hence bed porosity) alone is not totally 
 responsible for observed head loss be- 
 havior. It may be that different modes 
 of particle deposition can significantly 
 alter the development of head loss. Most 
 deep-bed filters have coarser media, and 
 flocculant is used to neutralize particle 
 charge and increase particle size, so the 
 surface charge of the medium is probably 
 of little practical importance in operat- 
 ing conventional deep-bed filters. 
 
 REMOVAL AND HEAD LOSS COEFFICIENTS 
 
 Empirical models have been used to de- 
 scribe the head loss and filtrate quality 
 as functions of time and filter-bed 
 depth. The clean bed head loss can be 
 calculated from the Kozeny-Carmen equa- 
 tion (5): 
 
 6H 
 61 
 
 5vV(l-e) 2 /6_\ 2 
 
 
 
 ge 
 
 (11) 
 
 where 
 
 H = head loss, 
 
 1 = the filter depth, 
 
 v = the kinetic viscosity, 
 
 g = the gravitational 
 acceleration, 
 
 e = the bed porosity, 
 
 v = the filtration velocity, 
 
26 
 
 and d m = the grain size of the filter 
 bed. 
 
 A good filtration run exhibits a nearly 
 linear increase in head loss with respect 
 to time, which is closely approximated by 
 
 H = H, + k H vC t, (12) 
 
 where H = head loss, 
 
 Hj = initial head loss, 
 
 C Q = the influent concentration 
 of suspended solids, 
 
 t = the elapsed time, 
 
 and kn = the head loss coefficient 
 (cm 3 /g). 
 
 This assumes particle removal rates of 
 >99 pet. The head-loss coefficient is 
 very similar to the SC index of equation 
 2. The concentration profile with re- 
 spect to depth has been modeled as a 
 first-order process: 
 
 $£- -AC 
 61 XL > 
 
 (13) 
 
 where X is the removal coefficient (_5)» 
 Concentration decreases logarithmically 
 with depth as given in equation 10. A 
 variety of other more complicated models 
 are available for detailed analysis of 
 deep-bed filters (6~_7)» To date, it has 
 not been possible to predict these engi- 
 neering parameters, which are useful in 
 filter design, and thus they must be ob- 
 tained, at least in part, by experiment 
 (5-6). 
 
 Beds of 0.5-mm sand and MgO were tested 
 against 12.5-ppm kaolin suspensions at pH 
 7.0±0.5. Flocculant was not used. Bed 
 depths were varied between approximately 
 5 and 50 cm. A water manometer was used 
 rather than the usual pressure gauges to 
 improve sensitivity and accuracy. (Pres- 
 sure could be measured to ±2 mm H2O. ) 
 For shallow beds, a known weight of fil- 
 ter medium was used rather than attempt- 
 ing to fill filter columns to a particu- 
 lar depth, since variations in packing 
 lead to relatively large changes in bed 
 
 depth. Turbidity was used to calculate 
 removal rate, and clean-bed-filter coef- 
 ficients were calculated from the first 
 two turbidity readings. Results are pre- 
 sented in table 11. 
 
 Attemtps to fit In (t/t ) as a linear 
 function of depth were unsuccessful; al- 
 though removal decreased with increasing 
 depth, there was considerable random 
 scatter around any type of linear plot. 
 For this reason, values of X Q were merely 
 tabulated and an average value given. 
 Since turbidity removal was less than 
 99 pet, SC was calculated rather than kg 
 for head loss rate data. 
 
 In general, the MgO filter gave slight- 
 ly better removal rates and slightly low- 
 er head loss rates than the sand filter. 
 Results varied widely; the standard devi- 
 ation of duplicate tests is 20 to 50 pet 
 of mean values. It appears that SC val- 
 ues improve for sand with increased bed 
 depth, while values for MgO fluctuate 
 randomly. Measurement uncertainties for 
 turbidity and pressure are much smaller 
 than the variation in results. Prepara- 
 tion of suspensions is also carefully 
 controlled, so it would seem that a fair 
 amount of randomness is intrinsic to the 
 process of deep-bed filtration. Packing 
 irregularities may also be partially re- 
 sponsible for the variability of results. 
 Although these results are not quantita- 
 tively precise, it can be seen that MgO 
 does perform slightly better than sand 
 without the intervening variable of 
 
 TABLE 11. - Head loss and removal co- 
 efficients of MgO and sand filters 
 for the filtration of kaolin 
 
 Bed depth 
 
 A > 
 
 F 
 
 SC, 
 
 
 cm" ' 
 
 (xlO 5 ) 
 
 g/cm 3 
 
 MgO: 
 
 
 
 
 9.2 cm. 
 
 0.003 
 
 44 
 
 6.3 
 
 18 cm. . 
 
 .048 
 
 18 
 
 18 
 
 36 cm. • 
 
 1 .024 
 
 134 
 
 1 9.1 
 
 46 cm. . 
 
 .035 
 
 29 
 
 7.8 
 
 Mean. . 
 
 .03510.18 
 
 36110.5 
 
 9.414.6 
 
 Sand: 
 
 
 
 
 10 cm. . 
 
 .017 
 
 50 
 
 3.3 
 
 20 cm. . 
 
 '.014 
 
 1 56 
 
 U.4 
 
 40 cm. . 
 
 .028 
 
 34 
 
 7.5 
 
 Mean. . 
 
 .01810.005 
 
 491 8.3 
 
 4.911.5 
 
 'Average of 2 test values. 
 
27 
 
 f locculation. These results are in qual- 
 itative agreement with the bulk of the 
 experimental data presented in this 
 paper. 
 
 pH AND CHEMICAL EFFECTS 
 
 The major filtration characteristic of 
 MgO, other than its positive surface 
 charge, is its basicity. Unbuffered 
 water passing over a bed of MgO will ex- 
 perience an increase in pH of several un- 
 its. At filtration velocities of 0.2 to 
 0.3 cm/s, water entering a typical bed of 
 periclase (inert MgO) at neutral pH will 
 exit at pH 10 to 10.5. Salts of Al 3+ and 
 Fe 3+ are amphoteric; consequently, a 
 shift in pH could be expected to signifi- 
 cantly alter their solubility. Both Al 3 + 
 and Fe 3+ salts are common coagulants 
 and/or flocculants used in water treat- 
 ment to destabilize colloidal dispersions 
 by neutralizing surface charge. Often 
 relatively large quantities of Al 3 + or 
 Fe 3+ are added to produce A1(0H) 3 or 
 Fe(0H)3 floes that further clarify water 
 by enmeshing particulates. Alum f loccu- 
 lation was used in the majority of the 
 filtration tests, and while this would 
 tend to decrease favorable surface-charge 
 interactions between particulates and 
 MgO, the effect of pH could conceivably 
 be important. Effects of pH generally 
 were not investigated during previous 
 filtration tests. 
 
 A series of tests were run with 24-ppm 
 kaolin suspensions in the presence of 
 either 15 ppm Al 3+ as alum or 30 ppm Fe 3 + 
 as FeCl3. This concentration of Al 3 + is 
 about 5 to 20 times greater than those 
 used in previous tests. (Concentrations 
 
 were previously reported as ppm alum; 
 formula weight is 474. ) Influent pH was 
 varied between 4.5 and 7.0, and filtra- 
 tion velocities were 0.33 to 0.35 cm/s. 
 Results are given in table 12. A strong 
 pH effect is evident for the Al 3+ -treated 
 suspension, as turbidity removal is ob- 
 served to be much poorer at higher in- 
 fluent pH. At pH 6.9, removal is so poor 
 that head loss is almost negligible; 
 hence value of F is low. Fe 3+ removal is 
 poor regardless of pH. Filtrate pH de- 
 creases considerably throughout the test 
 if alum is present, but changes very lit- 
 tle with FeCl 3 . 
 
 The differences in filtration results 
 are probably due to the differences in 
 solubility of the two salts. Al 3+ read- 
 ily forms soluble hydroxy complexes, and 
 the region of minimum solubility where 
 A1(0H)3 formation predominates spans a 
 fairly narrow pH range of 2 pH units cen- 
 tered around pH 5. The solubility dia- 
 gram of Fe 3+ is somewhat similar, though 
 Fe(0H) 3 remains more insoluble over a 
 much wider pH range; soluble hydroxy com- 
 plexes are not formed appreciably between 
 pH 3.5 and 13. Typical applications in 
 water treatment use Al 3+ at pH 5 to 9 and 
 Fe 3+ at pH 3 to 8 (L4). 
 
 Apparently, efficient removal of the 
 kaolin-Al suspension requires a certain 
 amount of soluble Al to interact with the 
 MgO surface. Sufficient soluble Fe is 
 not available at these pH levels; conse- 
 quently, bonding is poor and little 
 kaolin-Fe suspension is retained. MgO is 
 not likely to be used to collect Fe 3+ - 
 flocculated suspensions in practice 
 because dissolution of the MgO will 
 
 TABLE 12. - Effect of influent pH on filtration of kaolin 
 suspension flocculated with Al 3+ and Fe 3+ salts 
 
 to. 
 
 NTU 
 
 t/t 
 
 v, 
 cm/s 
 
 V, 
 L/cm 2 
 
 V/H 
 
 F 
 (xlO 5 ) 
 
 Influent 
 pH 
 
 WITH 15 ppm Al 
 
 35 
 
 0.043 
 .347 
 .180 
 .012 
 
 0.340 
 .347 
 .330 
 .349 
 
 3.67 
 2.50 
 4.75 
 5.02 
 
 32.6 
 1,010 
 25.5 
 14.9 
 
 130 
 34 
 
 700 
 82 
 
 4.5 
 
 23 
 
 6.9 
 
 27 
 
 5.6 
 
 
 4.5 
 
 WITH 30 ppm Fe 
 
 25 
 
 0.221 
 .370 
 
 0.353 
 .350 
 
 1.27 
 1.26 
 
 36 
 60 
 
 610 
 620 
 
 6.7 
 
 
 4.6 
 
28 
 
 probably be excessive at pH levels much 
 below 5.0. 
 
 The mechanisms of these interactions 
 are complex and further complicated by 
 the fact that pH levels at the MgO sur- 
 face are likely to be considerably higher 
 than those of the bulk solution. The 
 effect of pH on particle- and medium-sur- 
 face charge would also have to be con- 
 sidered. What effect pH had on filtra- 
 tion tests with much smaller amounts of 
 the Al is unclear, but it is probably at 
 least as important as surface charge 
 effects. 
 
 SCALE FORMATION AND MUDBALLING 
 
 scale-forming tendencies in the process 
 water is recommended. 
 
 Another type of cementation was ob- 
 served in later tests at the same plant. 
 Chunks of cemented MgO were again ob- 
 served at the bottom of the filter bed. 
 These were removed for inspection and are 
 shown in figure 9. Their most interest- 
 ing feature is the presence of grains of 
 anthracite adhering to one side of the 
 cemented chunks. Evidently these chunks 
 formed at the MgO-anthracite interface 
 and worked their way to the bottom of the 
 filter during backwashing. These were 
 probably formed as a result of com- 
 pression of deposited solids at the 
 
 Another consequence of the basicity of 
 the MgO is scale formation. Water with 
 appreciable calcium hardness and carbon- 
 ate or phosphate alkalinity will form in- 
 soluble calcium compounds due to the in- 
 crease in pH. Cementation of MgO filters 
 was observed in tests with several water 
 samples. During backwashing, the medium 
 tended to lift as a plug rather than 
 fluidizing. Usually, air scour was 
 enough to break up the scale and clean 
 the filter. Formation of scale did not 
 seem to seriously impair removal rates or 
 cause excessively high head-loss rates 
 during most filtration runs. 
 
 Mudballing is one problem that can re- 
 sult from scale formation in MgO filters. 
 In conventional filter media, mudballing 
 results from the compression of floccu- 
 lated solids into a cake at the surface 
 of the filter. The relatively large 
 chunks of cake are not entrained in back- 
 wash at practical fluidization rates. 
 Depending on their size and density, 
 these will either stay at the surface or 
 sink to the bottom of the bed. In the 
 field tests with the process water used 
 for cutting granite, mudballing mani- 
 fested itself differently. Cementation 
 of the MgO was evident in the lower part 
 of the filter, and although the bed was 
 fluidized for the most part during back- 
 washing, a rim of the cemented material 
 remained along the outer edge at the bot- 
 tom of the filter. This probably would 
 be avoided if backwash air and water were 
 better distributed at the bottom 
 of the filter. However, control of 
 
 FIGURE 9.— Cemented MgO chunks containing anthracite 
 grains. 
 
29 
 
 MgO-anthracite interface, but scale for- apparently 
 mation may also be responsible. Sand tests, 
 filters and sand-anthracite filters 
 
 were not affected in these 
 
 SUMMARY AND CONCLUSIONS 
 
 Under the right circumstances MgO fil- 
 ters offer significant advantages over 
 similar conventional sand filters. Bu- 
 reau results suggests that 0.5- to 0.71- 
 mm MgO will filter water pretreated with 
 alum better than equivalently sized par- 
 ticles of conventional filter sand. Par- 
 ticulate removal was approximately equal 
 for the two media under these conditions, 
 but much more water could be passed 
 through the MgO filters before break- 
 through. The porosity of the MgO filter 
 bed is about 1.3 times greater than that 
 of the sand filter bed, which probably 
 accounts for its smaller rate of head 
 loss and large run lengths before 
 breakthrough. 
 
 Current trends in conventional water 
 treatment include the use of coarser me- 
 dia in conjunction with polymer floccu- 
 lants to increase solid-loading capacity. 
 The floes created by polymer addition are 
 more resistant to higher shear rates than 
 alum floes; consequently, higher filtra- 
 tion velocities are used. Excessive head 
 loss rather than high turbidity tends to 
 limit run length. Under these conditions 
 MgO apparently offers little advantage 
 over sand other than a slight reduction 
 in head loss rate. 
 
 In tests of recycled process water, 
 elevated levels of dissolved solids usu- 
 ally were found. The MgO filters were 
 tolerant to moderate levels of calcium 
 hardness and carbonate alkalinity, pro- 
 vided adequate backwashing with air scour 
 was available. 
 
 No single solid removal mechanism can 
 be definitively identified as the one re- 
 sponsible for the improved filtration ob- 
 served with granular MgO. In contact 
 filtration of asbestos fibers, surface 
 charge effects were almost certainly pre- 
 dominant, but in shifting to granular MgO 
 filters the specific surface area was 
 greatly reduced and alum flocculation was 
 necessary to achieve efficient solid re- 
 moval. Both factors tend to indicate 
 decreased importance of surface charge 
 
 effects in comparison with mechanical ef- 
 fects. pH-chemical effects may also be 
 important. 
 
 Granular MgO (periclase) possesses the 
 necessary durability to be a filter me- 
 dium; no drastic attrition effects were 
 noticed in field tests or in laboratory 
 longevity studies. MgO is also compat- 
 ible with anthracite as a dual-medium 
 filter, whereas sand-MgO filters are not 
 likely to stratify in a workable manner 
 except possibly in upflow filters. Bed 
 poisoning by dissolved metals apparently 
 is not a problem. 
 
 Filtration is just one step in the 
 overall water-treatment process. Optimi- 
 zation of the clarification process will 
 most likely outweigh optimization of the 
 filtration process, since the former re- 
 moves by far the larger amount of solids. 
 In instances where mine and mineral- 
 processing water is only moderately con- 
 taminated by suspended solids, direct 
 filtration of the mine water without 
 clarification may be an attractive alter- 
 native. A filter that can effectively 
 remove suspended solids without pretreat- 
 ment would be desirable. Comparison of 
 filtration tests where 0.5-mm MgO is used 
 to filter untreated kaolin and 0.71-mm 
 MgO is used to filter alum-treated kaolin 
 are encouraging. Solid capture indexes 
 (SC) and f ilterability indexes (F) were 
 better by almost an order of magnitude 
 when no flocculant was added. Flocculant 
 evidently adds considerable bulk to the 
 suspended solids and contributes heavily 
 to head loss. Reduced head loss is po- 
 tentially the most beneficial advantage 
 in employing MgO filtration. Rather than 
 concentrating on comparing MgO and other 
 media as conventional water filters, fu- 
 ture research could explore the use of 
 novel materials in novel filtration meth- 
 ods. Various grades of MgO with interme- 
 diate activity and hardness should be 
 evaluated as filter media to determine 
 whether the surface properties of MgO can 
 be better utilized. 
 
30 
 
 REFERENCES 
 
 1. Schiller, J. E., and S. L. Payne. 
 Surface Charge Measurements of Amphibole 
 Cleavage Fragments and Fibers. BuMines 
 RI 8483, 1980, 23 pp. 
 
 2. Schiller J. E., and S. E. Khala- 
 falla. Filtration of Asbestos and Other 
 Solids With Magnesium Oxide. Min. Eng. 
 (Littleton, CO), v. 35, No. 3, 1983, 
 p. 237. 
 
 3. Schiller, J. E., D. N. Tallman, 
 and S. E. Khalafalla. Mineral Processing 
 Water Treatment Using Magnesium Oxide. 
 Environ. Progr. , v. 3, No. 2, 1984, 
 pp. 136-141. 
 
 4. Tallman, D. N. , and J. E. Shiller. 
 Field Evaluations of Magnesium Oxide in 
 Deep-Bed Filtration. BuMines RI 8936, 
 1985, 11 pp. 
 
 5. Ives, K. J. Deep Bed Filtration: 
 Theory and Practice. Filtr. and Sep. , v. 
 17, 1980, pp. 157-166. 
 
 6. Tien, C, and A. C. Payatakes. 
 Advances in Deep Bed Filtration. AIChE 
 J., v. 25, No. 5, 1979, pp. 737-757. 
 
 7. Rajagopulan, R. , and C. Tien. The 
 Theory of Deep Bed Filtration. Ch. in 
 Progress in Filtration and Separation, 
 ed. by R. J. Wakeman. Elsevier, 1979, 
 pp. 179-269. 
 
 8. Lekkas, T. D. A Modified Filter- 
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 Filters. Filtr. and Sep., v. 18, 1981, 
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 9. Baumann, E. R. , and J. L. Cleasby. 
 Waste Water Filtration Design Considera- 
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 Publ. EPA-624/4-74-007a, July 1974, 
 36 pp. 
 
 10. Gunasingham, K. , T. D. Lekkas, and 
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 11. Wakeman, R. J. Backwashing of 
 Granular Filters. Ch. in Filtration 
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 1975, pp 138-145. 
 
 12. Bohm, U. Maximum Mass Transfer to 
 the Wall or Immersed Objects in Liquid 
 Fluidized Beds. Ind. and Eng. Chem. Pro- 
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 13. Degremont Co. Methods of Anal- 
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 14. Johnson, P. N. , and A. Aminthara- 
 jah. Ferric Chloride and Alum as Single 
 and Dual Coagulants. J. Am. Water Works 
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31 
 
 APPENDIX. —NOMENCLATURE 
 SYMBOLS 
 
 a p radius of suspended particle, mm 
 
 A r ratio of buoyant to viscous drag forces acting on a particle, dimensionless 
 
 C suspended solids concentration in filtrate, mg/L 
 
 C Q influent suspended solids concentration, mg/L 
 
 d ef f effective grain diameter, mm 
 
 d m diameter of the filter medium granules, mm 
 
 dp diameter of particulate being filtered, mm 
 
 e charge on an electron, eV 
 
 F filterability index, dimensionless 
 
 f subscript denoting fluid 
 
 g acceleration due to gravity, 9.8 m/s 2 
 
 H head loss, cm H 2 
 
 h constant in London group, N l q5 dimensionless 
 
 h b bed depth, m 
 
 h bo bed depth of unfluidized bed, m 
 
 Hj initial head loss, cm H2O 
 
 k Boltzman's constant, cal/(mol*deg) 
 
 k-H loss coefficient, cm 3 /g 
 
 1 filter depth, m 
 
 M represents metal 
 
 m medium property 
 
 m. molality of jth ion 
 
 N DL double-layer filtration parameter 
 
 N E i electronic group 1 filtration parameter 
 
 N E 2 electronic group 2 filtration parameter 
 
 N L0 London group filtration parameter 
 
 250 87 &><* 
 
32 
 
 Nr 
 
 n g 
 
 n 
 
 P 
 
 P e 
 
 P 
 
 R 
 
 Re 
 
 Re, 
 
 Re 
 
 opt 
 
 SC 
 
 S.G. 
 
 T 
 
 t 
 
 V 
 
 e opt 
 
 Ed 
 
 SYMBOLS — Continued 
 
 relative size group filtration parameter 
 
 gravity group filtration parameter 
 
 parameter in Reynolds number determinations, dimensionless 
 
 element symbol for phosphorus 
 
 Pec let number 
 
 particle property 
 
 ideal gas law constant, 1.987 cal/(mol*deg) 
 
 Reynolds number, dimensionless 
 
 Reynolds number corresponding to unhindered settling of filter grains, 
 dimensionless 
 
 optimum Reynolds number, dimensionless 
 
 solid capture index, g/cm 3 
 
 specific gravity, g/cm 3 
 
 absolute temperature, K 
 
 time, h or s 
 
 filtrate volume per unit area, L/cm 2 
 
 filtration velocity, cm/s 
 
 valence of jth ion 
 
 differential notation 
 
 porosity, dimensionless 
 
 porosity of unfluidized bed, 
 dimensionless 
 
 optimum porosity, dimensionless 
 
 dielectric constant of fluid, 
 dimensionless 
 
 inverse double-layer thickness, 
 
 GREEK LETTERS 
 v 
 
 ir 
 
 Pf 
 Pp 
 
 m 
 
 -1 
 
 To 
 
 removal coefficient, cm -1 
 viscosity, kg/(m*s) 
 
 kinematic viscosity, u/p or m 2 /s 
 
 constant, 3.1416 
 
 density of fluid, kg/m 3 or g/cm 3 
 
 density of particulate, kg/m 3 
 or g/cm 3 
 
 turbidity, NTU 
 
 initial turbidity, NTU 
 
 surface potential of filter 
 medium, mV 
 
 surface potential of 
 particulate, mV 
 
 US GOVERNMENT PRINTING OFFICE: 1987 605017/60052 
 
 INT.-BU.OF MINES,PGH.,PA. 28502 
 
U.S. Department of the Interior 
 Bureau of Mines— Prod, and Distr. 
 Cochrans Mill Road 
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 Pittsburgh, Pa. 15236 
 
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