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31 Frontal Chromatographic Concepts To Study Competitive Adsorption Humic Substances and Halogenated Organic Substances in Drinking Water

Ronald J. Baker and I. H . Suffet

Environmental Studies Institute, Drexel University, Philadelphia, PA 19104

Thomas L . Yohe

Philadelphia Suburban Water Company, Bryn Mawr, PA 19010

This chapter introduces the use of frontal chromatographic theory to describe the breakthrough of solutes in granular activated carbon (GAC). Depletion of adsorption sites during use of GAC contactors can be expressed in terms of changes in moving concentration profiles, or fronts. These fronts can be defined in chromatographic terms. Data from a pilot-scale carbon adsorption study are presented and used as an example of how frontal chromatographic theory can be applied. Current models for describing and predicting solute breakthrough from GAC columns cannot predict breakthrough of a wide variety of compounds under water-treatment conditions. Frontal chromatography theory, as applied in this chapter, is useful for understanding the displacement and breakthrough phenomena in carbon contactors.

CxRANULAR ACTIVATED CARBON (GAC) HAS RECENTLY BEEN PROPOSED by the U.S . Environmental Protection Agency's Office of Drinking Water Quality as the best available technology for removal of several categories of synthetic organic substances, including trihalomethanes (THM) and other halogenated organic compounds (I). One consequence of this regulatory

0065-2393/89/0219-0533$06.(X)/0 © 1989 American Chemical Society

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In Aquatic Humic Substances; Suffet, I., et al.; Advances in Chemistry; American Chemical Society: Washington, DC, 1988.

534 AQUATIC HUMIC SUBSTANCES

activity wil l probably be increased use of G A C for halogenated-organic-substance removal. However, many low-molecular-weight organic materials, including T H M and other halogenated disinfection byproducts, are not strongly adsorbed by G A C . Considering the substantial capital and operating costs involved in G A C adsorption, optimization of this process in terms of equipment required and carbon consumption will be a high priority.

Many models for describing and predicting solute breakthrough from G A C columns have been and are being developed (2-5). Although progress is being made, current models cannot predict breakthrough of a wide variety of compounds under water-treatment conditions, where influent concentrations and types of organic mixtures vary and most contaminants are in the nanogram- to microgram-per-liter concentration range. In water- and waste-water-treatment applications the complexity and variability of influent quality make it difficult to develop models to predict breakthrough of individual solutes.

Because competitive effects from humic materials are difficult to predict, they greatly complicate the process of predicting specific solute breakthrough and thus of designing effective and efficient G A C installations. Site-specific water-quality differences add to the complexity. Therefore, the National Academy of Science (NAS) has recommended that each water-treatment design for G A C be piloted at that location and that only general principles be assumed to apply between plants (6). This chapter introduces ideas that may lead to a new approach for evaluation of pilot-plant column data. The approach is based on the concepts of frontal chromatography.

Adsorption-site distribution on a G A C bed and depletion upon use of the G A C are expressed in terms of changes in moving concentration profiles, or fronts, that represent movement of specific solutes down the column. The shapes of these fronts can be defined by using frontal chromatographic theory. Data from a pilot-scale carbon adsorption study are presented and used as an example of how some aspects of frontal chromatographic theory can be applied to observed G A C behavior at specific locations. It is hoped that this concept of using pilot-plant data will enhance general understanding for the control of future full-scale operations.

Analogy: Similarities Between GAC and Frontal C hromatography Conceptually, a G A C column can be thought of as a slow, inefficient liquid chromatographic (LC) column operated in the frontal elution mode. Table I lists operational similarities and differences between the two systems. The distribution coefficient or capacity factor, k\ in chromatographic theory (7) is analogous to points on a carbon isotherm (8), where each point on the isotherm indicates the distribution between the solid and liquid phases. In both systems diffusion is thought to control the mass-transfer rate (7, 8).

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31. BAKER ET AL. Frontal Chromatographic Concepts 535

Table I. Comparison Between Frontal Elution Liquid Chromatography and Water-Treatment GAC Operation

Frontal Elution Water-Treatment Attnbute Liquid Chromatography GAC Operations Definable distribution coefficients yes (*') yes (isotherm points) Diffusion-controlled mass-transfer

kinetics yes yes Theoretical plate concepts applicable yes yes Competition for adsorption sites yes yes Displacement of adsorbed compounds

by others yes yes Local equilibrium maintained

throughout system yes yes Constant number of theoretical plates no no Time to breakthrough minutes days or months Constant influent composition yes no Irreversible adsorption at some sites no yes Homogeneity of adsorption sites preferably no Homogeneity of adsorption media yes no

Displacement of some solutes by others through competitive adsorption also occurs in both systems. The most significant differences between G A C and frontal chromatography (FC) are time to breakthrough (minutes for F C , months for GAC) , influent variability (constant for F C , variable for GAC) , and homogeneity of the adsorbent (GAC is nonhomogeneous, most chromatographic media are homogeneous). In both F C and G A C systems the solutes compete for adsorption sites, and less strongly adsorbed species are displaced by those more strongly adsorbed.

The humic materials that are irreversibly adsorbed onto G A C (9) effectively reduce the number of theoretical plates in the system in a nonuniform manner. It is not known what fraction ofhumic materials adsorbs irreversibly, and a priori prediction of how the humic substances as represented by nonvolatile total organic carbon (NVTOC) in a feedwater will interact with G A C is not now possible. This type of irreversible fouling would not be experienced in F C , as analysts minimize decreases in column efficiency by sample pretreatment (e.g., cleanup by base extraction (10) to remove humic substances before G C or L C analysis).

Each system (FC and GAC) can be described as a column reactor with advection, diffusion, and reaction terms as shown in equation 1. This general equation for liquid-phase concentration as it changes with time results from a mass-balance procedure (11) and has been applied to F C (12) and G A C (7)

total rate of change = advection + diffusion + reaction

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where C is solute concentration, t is time, V is flow velocity, D is diffusivity, χ is distance down the column, and r(C) is a reaction term.

The reaction term r(C) in both systems refers to rates of adsorption and desorption. Treatment of this term varies somewhat between G A C and F C , although in both cases thin-film and intraparticle mass transfer and distribution equilibrium are considered rate- and capacity-limiting. In order to define and quantify the r(C) term, most G A C models rely on estimation of mass-transfer and competitive equilibrium parameters for each solute; then aqueous and adsorbed concentrations of the solutes are calculated as gradients through the G A C particles at different bed depths through time. Although this approach has also been used in F C , another approach is to describe the front or wave of solute concentration (solid or liquid phase or both) in terms of its statistical moments, and to project how the wave wil l change with time and distance down the column. Application of this approach to G A C should be possible.

Another chromatographic approach that may be applicable to G A C is the coherence concept developed by Helfferich (13). In this approach solutes are considered to be interactive (competitive) in their movement through chromatographic columns, and multicomponent wave movement occurs in a predictable "coherent" manner. Rates of wave and solute movement are found as solutions to eigenvector problems. Application of the coherence theory to G A C in water treatment will be mathematically complex because of the constantly changing influent and because some simplifying assumptions that apply to many chromatographic systems (13) may not hold true for G A C with its nonconstant separation factors. This essentially means that relative solute retention times (time spent in the column by the solutes) are significantly affected by relative aqueous-phase concentrations in G A C . The effect of this phenomenon on the use of coherence theory for describing G A C breakthrough has yet to be seen.

Some of the physical factors responsible for front shape and adsorption site depletion in column systems are shown in Figure 1. These factors apply to both frontal chromatography and G A C adsorption. For each column in Figure 1 (I-IV) a profile of bed depth versus surface loading concentration of a compound is shown for a column taken off-line after a period of loading. Each successive column shows additional physical factors that further complicate the system and reduce the column's capacity to adsorb compounds from the mobile phase.

Column I (isothermal) in Figure 1 shows the ideal situation for maximum adsorption of a solute in a column: a single solute (no competition) and instantaneous mass transfer. The advancing front is asymptotic because the initial influent equilibrates with carbon at the column inlet and is reduced in concentration when it contacts carbon farther down the column. This reduction results in lower surface loading at points farther down the column. Because phase equilibrium exists at each point in the front, the isotherm could be constructed from the surface loading-mobile phase concentration

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Figure 1. Front shaping mechanisms.

ratio at points in the front. Conversely, the front shape could theoretically be drawn from the isotherm.

The effect of noninstantaneous mass transfer is shown in column II (Finite Mass Transfer). Here the front has a sigmoidal or half-Gaussian appearance characteristic of frontal chromatography and sometimes observed in G A C loading profiles. The slowest (rate-limiting) mass-transfer steps control the front shape in the loading profile and the breakthrough profile. Both G A C modeling theory and chromatographic theory consider diffusion as a rate-limiting step in mass transfer. Chromatographic theory additionally considers adsorption and desorption as potential rate-limiting mass-transfer steps. The current practice of not considering rates of adsorption and desorption as finite in G A C modeling (5) may be an important oversight in breakthrough prediction for low-molecular-weight, rapidly diffusing compounds. In this case, points on the frontal curve of Column Β would not represent isotherm points because stationary and mobile phases are not in equilibrium in the frontal region.

Column III (Competition) shows the loss of adsorption capacity resulting from competition from other compounds. A more strongly adsorbing compound is shown concentrated at the column inlet, a weakly adsorbing species

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has its highest loading farther down the column, and there is some irreversible adsorption throughout the column, typical of some fractions of humic materials (13). A l l three of these generalized types of competition reduce the adsorption capacity for other compounds. The reduction results in earlier breakthrough in G A C and earlier front elution in F C .

Column IV (Variable Influent) shows the effect of varying the influents of the adsorbing species. This variable poses the greatest challenge for G A C modeling, especially when the degrees of variation are not known. Mobile-phase effluent profiles can assume virtually any shape and are difficult to describe mathematically. This is the reason that site specificity for G A C treatment of different water quality is invoked (6).

The Statistical Moment Approach Any curve can be described in terms of its statistical moments, which are mathematical descriptions of area distribution under the curve (14). The shape of a curve can be estimated and regenerated if enough moments are known. Figure 2 shows the procedure of approximating curve shape from statistical moments. If only the Oth moment is known (curve area), nothing is known about the curve shape between the boundaries. However, if the first moment is also known (center of mass), the estimated peak begins to take shape. When moments 2-4 are added, the estimated peak approaches

Figure 2. Curve description by statistical moments.

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the actual peak in shape. If an infinite number of moments were applied, the actual peak would be reproduced exactly. The Gram-Charlier series (15) (equation 2) is one function that can be used to approximate a distribution from its moments. This approach, used extensively in F C , should be applicable to G A C .

where C is concentration, which is considered a dependent variable of time; t is time; σ 2 is variance of the peak; is the fth Hermite polynomial; and C, is functions of statistical moments 3-5:

where m{ is the ith statistical moment. To apply the statistical moment approach to F C , we must convert the

elution fronts to distributions that can be described in terms of moments. Kalinichev (16) developed one approach, which is shown in Figure 3. The first derivatives of adsorption or desorption fronts are "bell-shaped" curves that have the necessary moments. It is not suggested that G A C breakthrough curves will generate Gaussian curves with this procedure. However, whatever shape they assume can be described by statistical moments.

Theoretical plate concepts are used in frontal chromatography to describe and predict the times of wave breakthrough. From frontal chromatographic plate theory, the effluent profile of a chemical can be related directly to the number of theoretical plates (n). Then η can be calculated from the statistical moments of breakthrough curves by using the method of Reilley et al. (17):

η - , (*)' ,3)

where tp is the time the point of inflection reaches the column outlet and w is a constant that is a function of front diffusion.

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C 0 Π C.

ΤΙΓΠΕ

ac aT

ΤΙΓΠΕ

Figure 3. Statistical moments of fronts. (Based on a figure in ref. 12.)

This method of plate calculation relies only on the zeroth and first moments of the breakthrough curve (i.e., peak areas and mass centers, respectively). It was used for calculation of plate numbers for nonvolatile total organic carbon (NVTOC) and specific micropollutants in the study described in the next section, which will show how meaningful information for estimating remaining column capacity can be obtained.

Example: Application of Statistical Frontal Chromatographic Theory to GAC Some aspects of frontal chromatographic theory were applied to data from a pilot-scale G A C evaluation. System and operating parameters are shown in List 1 and are published in detail elsewhere (18). Many parameters and compounds were monitored during the 300-day pilot study. However, for this example only four compounds (Chart 1) and N V T O C wil l be discussed. Influent concentration variability of the four compounds discussed are shown in Table II.

Relative positions of the Freundlich isotherms (19) for four of the compounds are shown in Figure 4. To further the G A C - F C analogy, relative affinity of the solutes for the stationary phase should determine breakthrough (or elution) order; greater affinity should result in later breakthrough. This result was found to be true in the pilot study. Compounds broke through in increasing order of affinity, as defined by their isotherm positions. This effect may not hold true for compounds of widely different concentrations

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List 1. System and Operating Parameters in the Pilot-Plant Study Activated carbon: Calgon F-400, Calgon Corp, Pittsburgh, PA Column: 4-in. i .d . , 3-ft G A C bed depth, glass

construction Hydraulic parameters: 0.392-gpm flow rate; 5.0-min contact time; 4.5-

gpm/ft 2 surface loading Water: ground-water-fed reservoir, Upper Merion, PA,

operated by Philadelphia Suburban Water i Co. , Bryn Mawr, PA

Cl H 1,1-dichloroethane (DCE) C l - c - C-H

H H

Cl H

1,1,1-trichloroethane Cl -c-I

C-H Cl H

Ci H Cl 1,2,3-trichloropropane (TCP) H-C -Ç - C - H

1 H Cl H

Cl

trichloroethene (TCE) c = K trichloroethene (TCE) Cl H

Cl Cl /

tetrachloroethene (PCE) tetrachloroethene (PCE) Cl' Cl

nonvolatile T O C (NVTOC)

Chart 1. Compounds monitored.

because position on the isotherm determines affinity to some degree. Figure 5 shows the relative order of breakthrough for the four compounds (18). After 180 days 1,1-dichloroethane had reached saturation in the column and was apparently being displaced by competing compounds. Influent concentration exceeded effluent concentration much of the time after 180 days. This result is an example of the so-called chromatographic effect (20, 21), which is really a frontal chromatographic effect. The other three compounds approached saturation in reverse order of their affinities for the G A C .

The column was taken off-line and sampled after 300 days. Samples of the core were extracted with hexane, and the hexane extracts were analyzed

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Table 11. Average Weekly Organic Influent Levels ^ g / L ) Week CHCl2CH3

a CCl3CH3b TCEb PCEb T C P NVTOCc

1 1.0 1.0 4.5 0.6 1.5 600 2 1.0 1.1 5.6 0.7 1.4 640 3 1.0 1.0 5.5 0.6 2.1 560 4 1.2 0.8 8.3 0.6 2.1 540 5 1.0 0.6 9.6 0.5 1.3 570 6 1.6 0.6 11.3 0.5 1.8 660 7 1.8 1.2 13.4 0.8 4.3 690 8 2.0 1.3 14.1 0.8 2.9 610 9 2.4 1.4 15.4 0.7 5.3 660 10 3.5 1.7 12.7 0.3 8.9 500 11 2.3 1.6 12.3 0.6 6.5 660 12 2.4 2.0 18.9 0.9 8.2 530 13 2.1 2.0 17.6 0.7 7.8 600 14 1.7 2.5 19.4 1.2 8.2 760 15 3.3 1.9 17.7 1.1 9.1 800 16 2.3 3.4 22.6 1.2 8.6 700 17 2.3 2.5 19.0 1.6 5.0 670 18 1.3 3.6 15.9 2.2 4.7 — 19 1.9 3.0 13.1 1.9 3.9 700 20 1.8 3.9 14.5 2.0 3.6 1240 21 — 3.5 13.7 1.7 — — 22 2.0 3.3 12.3 1.7 3.1 620 23 1.7 3.8 13.4 1.9 4.0 1040 24 1.9 3.4 11.2 1.7 4.8 —. 25 1.5 2.8 13.9 2.1 4.1 640 "Weekly average from two to four purge-and-trap analyses of grab samples. ^Weekly average from three hexane extractions (Monday, Wednesday, and Friday) of grab samples. nonvolatile TOC (samples purged to remove C02).

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zm

0 20 40 60 80 100 120 140 160 180 TIME CDAYS)

Figure 5. Relative breakthrough curves of volatile halogenated organic compounds in Upper Merion Reservoir. (Reproduced with permission from ref.

21. Copyright 1981 American Water Works Association. )

by gas chromatography (GC). This analysis provided information about the relative distribution of adsorbed solutes in the column. This relative distribution is shown in Figure 6. Compounds with lower affinity have been displaced from the column entrance, and those with greater affinity have not yet saturated lower areas of the column. This pattern of adsorption to saturation followed by competitive displacement is a typical pattern seen in frontal chromatography.

In this example cumulative mass-loading curves (e.g., Figure 7) wil l be described statistically. The moments zero and one can be used to calculate the number of theoretical plates (n) in the column relative to each compound by applying the relationships of Reilley et al. (17) and Yau (22) to the mass-loading curves. Figure 8 shows the decrease in η with time for N V T O C and 1,1-dichloroethane. First η decreases drastically between t = 0 and 90 days; then it increases slightly up to 110 days, and decreases to nearly zero at 170 days. The increasing period would be made possible by elution of competing species from the column because of a decrease in their influent concentration. The N V T O C showed a relatively stable η after an initial decline at t = 20 days. Figure 5 shows the displacement of 1,1-dichloroethane (DCE) by other compounds and an extreme chromatographic effect (effluent exceeding influent concentration) after t = 110 days. At t = 300 days (Figure 9), virtually

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Figure 6. Distribution of compounds in GAC column, Calgon F-400, Upper Menon, 300 days.

all of the D C E had been displaced from the column (i.e., fc'-»0, n—»0) and the carbon was not capable of retaining D C E . Longer column runs would have been required to observe the same type of displacement in the other micropollutants from effluent evaluation.

N V T O C was adsorbed at a relatively consistent, high rate during the first 180 days; the volatile halogenated compounds were competitively displaced during that time. Also, distributions of adsorbed solutes appear to have moved down the column in a chromatographic manner when the loading profiles at 180 days are compared to those at 300 days (Figure 9). It therefore appears likely that some of the competitive effects were from humic materials. One could also assume from Figures 5 and 6 that the more strongly adsorbed halogenated hydrocarbons are displacing the less strongly adsorbed ones.

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£ » COLUMN t CWV-G) 4. 1> Δ

Ο » COLUMN 2 <UV-G> + 5 Δ

+ » COLUMN 3 <F-408> +\Γ

+ Ο Χ Δ + ^ Δ Δ

+ Ο Δ + + * Δ

t Ο Δ Δ

Λ Ο Λ

ί Δ

i

θ 5 10 15 20 25 38 35 40 45 59

BED VOLUMES CX1083>

Figure 7. NVTOC cumulative mass loading on three GAC contactors.

Both of these assumptions may be premature, and it can only be concluded that, in general:

1. More strongly adsorbed compounds are competing effectively for sites and displacing less strongly adsorbed compounds.

2. Humic substances may be involved in the competitive displacement process.

3. Irreversible adsorption by humic materials may permanently remove sites from the competitive process.

Proposed Future Work and Summary A new approach to describing solute movement in G A C contactors has been presented, where concepts of frontal chromatography are applied. The effect of competition between solutes is expressed in terms of decreases in column efficiency (number of theoretical plates).

The micropollutants studied behaved much like solutes in a frontal chromatographic system, although the time frames are much longer (tens

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β 2Θ 40 68 88 109 120 M3 ISO 189

DAYS

Figure 8. Competition-induced reduction of equilibrium stages over time for 1,1 -dichloroethane.

or hundreds of days to breakthrough versus minutes in frontal chromatography). Other frontal chromatographic concepts may be applicable to G A C .

The traditional approach to G A C research is to develop methods to predict breakthrough on the basis of chemical, physical, and engineering parameters. Then the predictive value of the procedure is tested against actual data. The frontal chromatographic concepts developed in this chapter could be applied in a different way. For example, pilot-plant data could be described in chromatographic terms employing a statistical moment or coherence approach; then this chromatographic data base could be used to describe the adsorption and breakthrough characteristics of the source water evaluated on a pilot scale. This information could then be used for scaling up the process to the plant scale. However, complexities from influent variability will make comprehensive modeling in real water systems difficult, a situation already familiar to those working with models based on other adsorption and mass-transfer criteria.

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Figure 9. Distribution of compounds in GAC column, Upper Merion, 176 and 300 days.

References 1. American Water Works Association. Mainstream 1986, September, pp 5 and

10. 2. Weber, W. J., Jr.; Pirbazari, M. J. Am. Water Works Assoc. 1982, 74, 203-209. 3. Peel, R. G.; Benedek, A. J. Environ. Eng. Div. (Am. Soc. Civ. Eng.) 1980,

106(EE2), 797-813. 4. Narbaitz, R. M. Ph.D. Thesis, McMaster University, 1985. 5. Crittenden, J. C.; Hand, D. W.; Berrigan, J. K. J. Water Pollut. Control Fed.

1986, 58, 312-319. 6. Drinking Water and Health, National Academy of Science, Safe Drinking Water

Committee; National Research Council: Washington, DC, 1980; Vol. 2. 7. Karger, B. L.; Snyder, L. R.; Horvath, C. An Introduction to Separation Science,

Wiley: New York, 1972; Chapters 1-5 and 13.

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8. Weber, W. J., Jr. Physicochemical Processes for Water Quality Control; Wiley: New York, 1972; Chapter 5.

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Toxicity Testing; Suffet, I. H.; Malaiyandi, M., Eds.; Advances in Chemistry 214; American Chemical Society: Washington, DC, 1986; Chapter 19.

11. Bird, R. B.; Stewart, W. E.; Lightfoot, Ε. N. Transport Phenomena; Wiley: New York, 1962.

12. Kalinichev, A. I.; Pronin, A. Y.; Zolotarev, P. P.; Goryacheva, Ν. Α.; Chmutov, Κ. V.; Filimonov, V. Y. J. Chromatogr. 1976, 120, 249-256.

13. Helfferich, F. In Adsorption from Aqueous Solution; Weber, Walter J.; Matijevic, E., Eds.; Advances in Chemistry 79; American Chemical Society: Washington, DC, 1968.

14. Snedecor, G. W.; Cochran, W. G. Statistical Methods, 6th ed.; Iowa State University: Ames, 1967.

15. Grushka, E. J. Phys. Chem. 1972, 16, 2586-2593. 16. Kalinichev, A. I.; Pronin. A. Y; Chmutov, Κ. V.; Goryacheva, N. A. J. Chro

matogr. 1978, 152, 311-322. 17. Reilley, C. N. ; Hildebrand, G. P.; Ashley, J. W ., Jr. Anal. Chem. 1962, 34,

1198-1223. 18. Suffet, I. H.; Gibs, J.; Chrobak, R. S.; Coyle, J. Α.; Yohe, T. L. J. Am. Water

Works Assoc. 1985, 77, 65-72. 19. Dobbs, R. Α.; Cohen, J. M. Carbon Adsorption Isotherms for Toxic Organics;

Environmental Protection Agency: Cincinnati, 1980; ΕPA-600/8-80-023. 20. McGuire, M. J.; Suffet, I. H. J. Am. Water Works Assoc. 1977, 69, 621-636. 21. Yohe, T. L.; Suffet, I. H.; Cairo, P. P. J. Am. Water Works Assoc. 1981, 73,

402-410. 22. Yau, W. W. Anal. Chem. 1977, 49, 395-398.

RECEIVED for review January 13, 1988. ACCEPTED for publication May 27, 1988.

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