Frontal Chromatographic Concepts To Study Competitive Adsorption

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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.

C x R A N U L A R ACTIVATED CARBON (GAC) HAS RECENTLY BEEN PROPOSED by

the U . S . Environmental Protection Agency's Office of Drinking Water Qual ity 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

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


534

AQUATIC H U M I C SUBSTANCES

activity will probably be increased use of G A C for halogenated-organicsubstance 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 concentra tions and types of organic mixtures vary and most contaminants are in the nanogram- to microgram-per-liter concentration range. In water- and wastewater-treatment applications the complexity and variability of influent qual ity 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 the ory. 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).


535

Frontal Chromatographic Concepts

31. BAKER ET AL.

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


Attnbute Definable distribution coefficients Diffusion-controlled mass-transfer kinetics Theoretical plate concepts applicable Competition for adsorption sites Displacement of adsorbed compounds by others Local equilibrium maintained throughout system Constant number of theoretical plates Time to breakthrough Constant influent composition Irreversible adsorption at some sites Homogeneity of adsorption sites Homogeneity of adsorption media

Frontal Elution Water-Treatment Liquid Chromatography GAC Operations yes (isotherm points) yes (*') yes yes yes

yes yes yes

yes

yes

yes no minutes yes no preferably yes

yes no days or months no yes no 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 G A C ) , influent variability (constant for F C , variable for G A C ) , and homogeneity of the adsorbent (GAC is nonhomogeneous, most chro matographic 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) effec tively 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 G A C ) 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



536


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 distri bution 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 gra dients 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 will 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 assump tions 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 com plicate 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 In Aquatic Humic Substances; Suffet, I., et al.; Advances in Chemistry; American Chemical Society: Washington, DC, 1988.


31. BAKER ET AL.Frontal Chromatographic Concepts

537

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 ap pearance characteristic of frontal chromatography and sometimes observed in G A C loading profiles. The slowest (rate-limiting) mass-transfer steps con trol 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 con siders adsorption and desorption as potential rate-limiting mass-transfer steps. The current practice of not considering rates of adsorption and de sorption as finite in G A C modeling (5) may be an important oversight in breakthrough prediction for low-molecular-weight, rapidly diffusing com pounds. 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 com pound is shown concentrated at the column inlet, a weakly adsorbing species In Aquatic Humic Substances; Suffet, I., et al.; Advances in Chemistry; American Chemical Society: Washington, DC, 1988.


538


has its highest loading farther down the column, and there is some irre versible 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. Mobilephase 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.


31. BAKER ET AL.Frontal Chromatographic Concepts

539


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 appli cable to G A C .

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

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, what ever shape they assume can be described by statistical moments. Theoretical plate concepts are used in frontal chromatography to de scribe and predict the times of wave breakthrough. From frontal chromat ographic 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 t is the time the point of inflection reaches the column outlet and w is a constant that is a function of front diffusion. p


540


C

0


Π C. ΤΙΓΠΕ

ac aT ΤΙΓΠΕ

Figure 3. Statistical moments offronts. (Based on afigurein 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 Theory to GAC

Chromatographic

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 will 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 com pounds 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



31. BAKER ET AL.

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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 0.392-gpm flow rate; 5.0-min contact time; 4.5gpm/ft surface loading ground-water-fed reservoir, Upper Merion, PA, operated by Philadelphia Suburban Water C o . , Bryn Mawr, PA

Hydraulic parameters:

2


Water: i

Cl H 1,1-dichloroethane ( D C E )

C l - c - C-H H H Cl H

1,1,1-trichloroethane

Cl -c- C-H I Cl H

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

c

Cl Cl

=

KH /

Cl

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 concen tration 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


542


Week

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25


Table 11. Average Weekly Organic Influent Levels ^ g / L ) PCE TCP CHCl CH TCE CCl CH 1.5 1.0 1.0 0.6 4.5 1.4 1.0 0.7 1.1 5.6 2.1 1.0 1.0 0.6 5.5 2.1 1.2 0.6 8.3 0.8 1.0 1.3 0.5 0.6 9.6 1.8 1.6 0.5 11.3 0.6 4.3 1.8 0.8 13.4 1.2 2.9 2.0 0.8 1.3 14.1 5.3 2.4 15.4 0.7 1.4 8.9 3.5 0.3 12.7 1.7 6.5 2.3 0.6 12.3 1.6 2.4 0.9 8.2 18.9 2.0 7.8 2.1 0.7 2.0 17.6 8.2 1.7 19.4 1.2 2.5 9.1 3.3 1.1 1.9 17.7 8.6 2.3 1.2 3.4 22.6 5.0 2.3 19.0 1.6 2.5 4.7 2.2 1.3 15.9 3.6 3.9 1.9 1.9 3.0 13.1 3.6 1.8 2.0 3.9 14.5 — — 1.7 13.7 3.5 3.1 2.0 1.7 12.3 3.3 4.0 1.7 1.9 13.4 3.8 4.8 1.9 1.7 11.2 3.4 4.1 1.5 13.9 2.1 2.8 2

a

3

3

b

b

3

b

NVTOC

c

600 640 560 540 570 660 690 610 660 500 660 530 600 760 800 700 670 — 700 1240 — 620 1040 —. 640

"Weekly averagefromtwo 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 C0 ). 2


543

31. BAKER ET AL. Frontal Chromatographic Concepts


zm

0

20

40

60

80

100

120

140

160

180

TIME CDAYS)

Figure 5. Relative breakthrough curves of volatile halogenated organic com pounds 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 distri bution 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) will 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 massloading 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 in fluent concentration) after t = 110 days. At t = 300 days (Figure 9), virtually



544


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 dis placed 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.



545

31. BAKER ET AL. £

» COLUMN t CWV-G)

4. 1> Δ

Ο

» COLUMN 2

+

» COLUMN 3

+ 5


+ Ο + ^ Δ + Ο Δ

+

Λ

ί

Δ

+\Γ

+ *

t Ο Δ Ο Λ

ΧΔ Δ

Δ

Δ

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 dis placement 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



546


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 chromatog raphy). 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 co herence 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 var iability will make comprehensive modeling in real water systems difficult, a situation already familiar to those working with models based on other ad sorption and mass-transfer criteria.



31.

BAKER E T AL.


547

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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AQUATIC HUMIC SUBSTANCES

8. Weber, W. J., Jr. Physicochemical Processes for Water Quality Control; Wiley:

New York, 1972; Chapter 5. 9. Keinath, T .M.Environ. Sci. Technol. 1985, 19, 690-694.

10. Gibs, J.; Suffet, I. H. In Organic Pollutants in Water: Sampling, Analysis, and

11.


12. 13. 14. 15. 16. 17. 18.

Toxicity Testing; Suffet, I. H.; Malaiyandi, M., Eds.; Advances in Chemistry 214; American Chemical Society: Washington, DC, 1986; Chapter 19. Bird, R. B.; Stewart, W. E.; Lightfoot, Ε. N. Transport Phenomena; Wiley: New York, 1962. Kalinichev, A. I.; Pronin, A. Y.; Zolotarev, P. P.; Goryacheva, Ν. Α.; Chmutov, Κ. V.; Filimonov, V. Y. J. Chromatogr. 1976, 120, 249-256. Helfferich, F. In Adsorption from Aqueous Solution; Weber, Walter J.; Matijevic, E., Eds.; Advances in Chemistry 79; American Chemical Society: Washington, DC, 1968. Snedecor, G. W.; Cochran, W. G. Statistical Methods, 6th ed.; Iowa State University: Ames, 1967. Grushka, E. J. Phys. Chem. 1972, 16, 2586-2593. Kalinichev, A. I.; Pronin. A. Y; Chmutov, Κ. V.; Goryacheva, N. A. J. Chro matogr. 1978, 152, 311-322. Reilley, C. N. Hildebrand, G. P.; Ashley, J. W., Jr. Anal. Chem. 1962, 34, 1198-1223. 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.


Frontal Chromatographic Concepts To Study Competitive Adsorption

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