Download - [Advances in Chemistry] Aquatic Humic Substances Volume 219 (Influence on Fate and Treatment of Pollutants) || Analysis of Humic Substances Using Flow Field-Flow Fractionation

5 Analysis of Humic Substances Using Flow Field-Flow Fractionation

Ronald Beckett

Water Studies Centre, Chisholm Institute of Technology, 900 Dandenong Road, Caulfield East, Victoria 3145, Australia

James C. Bigelow, Zhang Jue, and J. Calvin Giddings

Department of Chemistry, University of Utah, Salt Lake City, UT 84112

A new method for the determination of molecular-weight distributions of humic substances using flow field-flow fractionation (flow FFF) is outlined. Fairly good agreement between the results obtained by flow FFF and other methods for some humic reference substances was achieved using poly(styrene sulfonate) molecular-weight calibration standards. The molecular-weight distributions obtained for a variety of humic samples were all fairly broad and, in contrast to the data sometimes reported for gel permeation chromatography, did not show any indication of multiple peaks. The number- and weight-average molecular weights can be estimated, and these were shown to vary considerably (Mw from about 4400 to 19,000) for humic acids extracted from different environments. The method is also capable of fractionating a humic sample. However, because it is a very small-scale separation (<1 mg of sample), quite sensitive analytical detection methods would be required to make use of this feature.

INTEREST IN HUMIC SUBSTANCES GOES BACK at least to the 19th century when the dark organic matter from soil was extracted with alkali and studied (J, 2). In recent years environmental scientists have become increasingly aware of the importance of humic substances in many geochemical processes that affect the fate of pollutants in natural aquatic systems and in water-treatment processes. This interest is evidenced by the growing number of

0065-2393/89/0219-0065$06.00/0 © 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.

66 AQUATIC HUMIC SUBSTANCES

studies being reported in the past decade, either investigating the interaction of pollutants with humic substances or attempting to elucidate the structures of these complex organic compounds.

Not only do humic substances form metal complexes of varying stability with most trace metals (3-5) but they can also bind and help solubilize nonpolar organic compounds (6-8). In addition, they are adsorbed to many mineral surfaces, and thus they affect the properties of soils, sediments, and suspended particulate matter. In particular, they control the surface charge of aquatic particles (9, 10) and substantially influence their colloid stability (11-13) and adsorption behavior (14-16). Despite much effort and considerable advances, our knowledge of the structure of humic substances is still inadequate. No doubt this lack stems largely from the fact that this very heterogeneous class of materials is defined largely by the method of extraction used to isolate its components. Certainly the introduction of better fractionation schemes is beginning to help simplify the problem of structure determination (17).

A good illustration of the dearth of reliable information on humic substances is the diversity of views held by scientists in the field on the molecular weight of these compounds. They are very commonly described as having high molecular weight, yet others dispute this claim (18). The molecular weights reported in the literature vary enormously, with values in the range of 500-200,000 being recorded (19). There appear to be several plausible reasons for this observation. Certainly, different workers have used samples extracted from various sources and by various methods. However, the question remains of whether the huge variations reported for different samples are real or artifacts of the methods and conditions used. The introduction of reference samples by the International Humic Substances Society (20) should eventually help to answer this question, and researchers should be encouraged to use such standards as reference materials in their work (21).

A number of different techniques have been used to determine the molecular weight of humic substances. Each technique is based on a different physical principle and is invariably subject to its own set of limitations and approximations. This variation may be one of the reasons for analytical discrepancies. Another factor that may account for the very high molecular weight sometimes reported is the suggestion that humic substances may aggregate under some solution conditions. Aggregation may be promoted, for example, by high solution concentration, increased ionic strength (particularly in the presence of multivalent cations), or low p H . Wershaw and co-workers (22, 23) have even suggested that humic substances may be capable of forming micellelike agglomerates that can be used to account for properties such as the ability of humic substances to solubilize nonpolar substances (e.g., pesticides, polychlorinated biphenyls [PCBs], polycyclic aromatic hydrocarbons [PAHs]). On the other hand, perhaps degradation reactions may occur under some conditions and lead to lower apparent molecular weights.

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5. BECKETT ET AL. Analysis Using Flow Field-Flow Fractionation 67

In this chapter we discuss the development of flow field-flow fractionation (flow F F F ) as a new method for determining the molecular-weight distributions of humic substances. The aim is to describe the experimental methodology, to outline current limitations that need to be overcome, and to contrast this technique with other methods that are currently in use. We also speculate on how the separation capabilities of flow F F F may be used in environmental studies.

Field-Flow Fractionation Field-flow fractionation refers to a series of separation techniques that are similar in operation to chromatography, but in which the separation of molecules or particles occurs in thin (0.1-0.5-mm) unpacked rectangular channels (24). In normal F F F operation the sample is introduced at one end of the channel; a driving force is then applied across the thin dimension of the channel and causes the sample to migrate toward one wall, the accumulation wall. There the sample particles form a cloud whose mean thickness (/) depends on the velocity induced by the field (U) and their difiusion coefficient (D) as follows (24):

Thus, the value of / generally depends on the particle or molecular size (or mass). When carrier flow begins, laminar flow is maintained as a consequence of the thin channel cross-section. The carrier flow is greatest in the center of the channel and decreases to zero at the two boundary walls. Indeed, the distribution of flow velocities across the channel is parabolic, as illustrated in Figure 1. As the sample clouds interact with the carrier flow distribution, the particles migrate down the channel with a velocity that depends on the value of I. Sample components wil l thus elute at characteristic retention volumes (V r). It can be shown that Vr and / are related to the key retention parameter, the retention ratio (R), by the relationship (25):

where V° is the channel void volume, λ is the dimensionless cloud thickness IIand w is the channel thickness.

Different F F F subtechniques make use of different types of applied fields. The most widely used subtechniques are gravitational or centrifugal sedimentation, thermal gradient, and crossflow methods. Electrical and magnetic fields are less commonly used. Other possibilities exist, including fluid shear induced forces (26). The general strategy of F F F is to measure Vr for the various sample components. Vr is used to calculate R and then λ or /,

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which in turn can be related to certain parameters of the particles or molecules (e.g., mass, diffusion coefficient, mobility) by equations derived for the particular field (subtechnique) being used.

Flow F F F is the subtechnique that uses a crossflow of fluid to drive the molecules to the accumulation wall (Figure 1). This "field" flow is maintained at right angles to and superimposed on the normal channel flow by constructing the channel walls from a porous frit material with semipermeable membranes at the accumulation wall to retain the sample in the channel. In this system the field-induced sample velocity (U) is simply the linear crossflow velocity. Therefore it follows from Equation 1 that (27):

Uw Vcw2

where Vc is the volumetric crossflow rate. Thus, in flow F F F the molecular diffusion coefficient can be estimated

from the measured elution volume. In addition to its usefulness for characterizing colloidal particles (28,

29), flow F F F has been shown to be effective for separating proteins (30) and water-soluble polymers (31) with good resolution, as illustrated in Figure 2. The theoretical diameter-based selectivity is unity, a value higher than that for gel permeation chromatography (32).

Experimental Details The equipment, samples, and method of operation have been described in detail elsewhere (33). In addition to the polysulfone membrane (Millipore PTGC) with a nominal molecular-weight cutoff of 10,000 daltons for globular proteins, which was used as the accumulation wall in the previous study, some experiments were run

ELUTION VOLUME (mL)

Figure 2. Flow FFF fractograms showing good resolution in the separation of (A) poly(styrene sulfonate) molecular-weight standards and (B) proteins.

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here with a cellulose membrane (Amicon, YC05) with a specified 500-dalton pore size. Most fractograms were collected with conventional UV-visible detectors and chart recorders. Several were recorded with a photodiode array detector (Varian Polychrom 9060) capable of collecting data between 190 and 367 nm. The Suwannee River fùlvic and humic acids used were the International Humic Substances Society reference stream samples, usually with 40-μί, injections of 0.25-mg/mL solution buffered at pH 7.9. The carrier solvent in all cases was 0.05 M tris(hydroxy-methyl)aminomethane (TRISMA, Aldrich), 0.0268 Μ H N 0 3 , and 0.00308 M NaN 3, and the pH was 7.9.

Poly(styrene sulfonate) molecular-weight standards (Polysciences, Inc.) covering the range 4000-100,000 daltons were made up in water (1 g/L), as were some biological test samples of bovine serum albumin, ovalbumin, transfer RNA, and RNase.

Results and Discussion Fractograms of Humic Substances. Fractograms of the reference

Suwannee River fulvic and humic acids are shown in Figure 3A. In these plots the ordinate is the absorbanee (arbitrary units) of the sample at 254 nm; it should represent the sample concentration if the molar extinction coefficient remains constant across the molecular-weight distribution. The abscissa is the elution volume, which is related to the dhfusion coefficient through equations 2 and 3. Thus, the abscissa is not linear with respect to molecular weight.

The fractogram is a smooth single-peaked curve, unlike many of the complex chromatographs based on gel permeation chromatography (GPC). This finding was true of all the samples we have run so far, which have included aquatic, soil, peat, and coal humic substances. The consistency leads us to suspect that the multiple peaks generated by the G P C method are due to anomalous effects, such as adsorption and charge repulsion, involving the sample and gel.

To investigate whether different molecular-weight components show different U V signals, which may indicate a distinct change in chromophore, some runs were made with a photodiode array detector (Varian) capable of scanning between 190 and 367 nm. An example of the detailed information obtainable from such a fractogram is shown in the three-dimensional plot of Figure 4. However, because of the featureless spectrum of humic substances and the fact that no shift in peak maximum occurs as the molecular weight changes, a rather simple picture is obtained in this case. The diagram does indicate rather clearly the feet that 254 nm (highlighted curve) is a good choice of wavelength for recording fractograms of humic substances.

Several inherent problems could arise with the flow F F F technique, two of which are associated with the membrane used on the accumulation wall to contain the sample molecules within the channel. These problems are the permeability of the membrane, which may allow some of the sample to leak from the channel, and the possibility of sample adsorption onto the

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MOLECULAR WEIGHT 1000 10000 20000

10 15 20 ELUTION VOLUME (mL)

3 Ο

UJ >

ELUTION VOLUME (mL) 10 15 20

0.05 -

0.04 Fulvate -

0.03 -

0.02 " \ Β -

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_Humate \ v

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MOLECULAR WEIGHT

Figure 3. (A) Flow FFF fractograms of Suwannee River fulvate and humate samples at pH 7.9 with Millipore membrane. (B) Calculated molecular-weight distributions obtained with molecular-weight calibration line for PS S standards

given in Figure 6.

membrane. An indication that one or both of these may be occurring to some extent is given in Figure 5, which shows that the peak area of the eluted sample decreases as the stop flow time is increased. (The stop flow time is the time the sample is held without channel flow at the head of the channel, while being forced to the accumulation wall by crossflow. ) Presumably a longer stop flow time gives the sample a greater opportunity to be lost by these two mechanisms. In all other fractograms reported here, a stop flow time of 1.5 min was used to minimize these effects.

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TIME (min)

Figure 4. Three-dimensional fractogram for Suwannee River fulvate (pH 7.9) obtained with Varian photodiode array multiwavelength detector and Amicon

membrane.

τ 1 1 1 1 Γ

ELUTION VOLUME (mL)

Figure 5. Fractograms of Suwannee River fulvate (pH 7.9) obtained with Millipore membrane and different stop flow times.

An attempt was made to produce a mass balance on the sample injected by using two detectors to monitor the peak areas. One detector was connected to the normal channel outlet and the other to the crossflow outlet, where it would measure sample escaping through the membrane. These peak areas were compared with the area of an equivalent sample aliquot injected directly into the detector. Although only semiquantitative, the results indicate that as much as 15-20% of the sample may be lost by each of the processes (adsorption and leakage).

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Another potential interference is sample overloading effects. The standard F F F equations used require the sample to form an equilibrium cloud whose distribution is not affected by intermolecular interactions. This effect was not apparent for the concentrations of humic substances tested in this study (0.25-1.0 mg/mL), as the retention times obtained for runs with the same experimental conditions were not dependent on sample concentration. However, overloading effects were indicated with the PSS standards, as discussed later.

Molecu la r -Weigh t Ca l ib ra t ion . Separation of components in flow F F F is achieved because of differences in their diffusion coefficients (D). Because the relationship between D and the molecular weight (M) of a macromolecule depends on several parameters such as its molecular conformation (shape) and flexibility, the conversion from elution volume to molecular weight generally wil l require the use of calibration standards. For many polymers the relationship is of the form:

where A and b are constants for a particular sample type and carrier solution (34). The exponent b is usually in the range 0.33-1.0, depending on whether the molecules are globular, random coil, rodlike, etc.

In this study two sets of molecular-weight standards were tested: poly(styrene sulfonate) (PSS) samples, which are linear random-coil molecules subject to charge repulsion effects, and some more rigid proteins and RNase. For the PSS samples, the peaks shifted to slightly lower relative elution volumes as the applied field increased. This trend resulted in the £>max values decreasing by up to 15% in the range tested (crossflow = 1-4 mL/min). This result could have been caused by either intermolecular interactions or membrane adsorption effects, both of which would be expected to be more pronounced as the field increased and the sample became more compressed against the accumulation wall.

To minimize the influence of this effect on the molecular-weight determination, the diffusion coefficients plotted on the calibration graph were those corresponding to about the same λ value (0.08) as attained in the humic-substance runs. This correspondence was achieved by plotting D m a x

versus λ for the data obtained at different crossflows and reading off the diffusion coefficient (Dom) at λ = 0.08 for each PSS standard. The resulting calibration curves (log D versus log M) are shown in Figure 6. Both curves are linear, but with different slopes; the random-coil PSS molecules are displaced to lower diffusion coefficient, as would be expected.

To test which of these curves may be best suited for the estimation of molecular weight of the humic substances, a few reference fulvic and humic substances were obtained whose molecular weights had been determined

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UJ U

LU Ο Ο

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ο Humic substances * Biological standards

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3.0 3.5 4.0 4.5 5.0 LOG (MOLECULAR WEIGHT)

Figure 6. Calibration lines obtained with either polystyrene sulfonate) or protein molecular-weight standards (solid symbols) with Millipore membrane. Aho plotted are points (open circles) corresponding to the reference Suwannee

River and Mattole soil fulvic and humic acid samples.

by a number of different methods (R. Malcolm, U.S. Geological Survey, Denver, C O , personal communication). The points corresponding to the diffusion coefficients at the F F F peak maximum and the molecular weight determined independently for these humic substances are also plotted on the calibration graph. Because these points fall satisfactorily on the PSS calibration line, it was chosen for use in all the work involving the Millipore 10,000-dalton polysulfone membrane, yielding A = 7.05 Χ 10" 5 and b = 0.422 (with D expressed in square centimeters per second) for the constants in equation 4. Somewhat different calibration constants (A = 2.58 X 10 " 5 , b = 0.320) were obtained subsequently when the Amieon 500-dalton cellulose membrane was installed.

Molecular-Weight Distributions. The fractograms were digitized (150 points) and the abscissa transformed from elution volume (V r) to molecular weight by using a calibration equation obtained as already described. Because the conversion between V and M is nonlinear, the ordinate must also be modified in order that the area under the curve is proportional to the mass of sample (m) between given molecular-weight limits (35). The ordinate of the molecular-weight distribution should represent dm/dM> whereas in the case of the original fractogram, the ordinate represents the detector signal, which is proportional to dm I dV. Because dm I dM = dm/dV - dVldM, the required transformation is achieved by multiplying the amplitude values of the digitized fractogram by AV/ΔΜ, where A V is the difference between the elution volume for consecutive points and ΔΜ is the difference in the molecular weight for the same points.

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The molecular-weight distributions were also normalized so that the total area under the curve was 100. Thus, the area between any two molecular-weight limits is the percentage by weight of the sample in that range. The minimum measurable molecular weight on these distributions is determined by interference from the void volume peak and the deteriorating resolution as R increases toward unity. For the conditions used here, the lower limit is about 300 daltons.

The effect of this molecular-weight transformation is illustrated in Figure 3B. The procedure heavily weights the points occurring at lower elution volumes; thus, the maximum in the fractogram is almost eliminated in the molecular-weight distribution. The result is a fairly broad molecular-weight distribution that decreases smoothly with increasing molecular weight, without any indication of multiple peaks, and tails off toward 10,000 daltons or beyond.

From these distributions it is possible to calculate both number (M n) and weight ( M J average molecular weights of the sample. However, a number of factors wil l restrict the accuracy of these parameters. The lower molecular-weight limit of 300 will particularly affect M n , whereas uncertainties in the higher molecular-weight values will mainly affect M w . Contributions to errors in the latter will be the difficulty in establishing the exact baseline in the long tail of the distribution and uncertainties in the calibration.

Comparison with Other Methods

Various methods have been used to measure molecular size or weight of humic substances, primarily ultrafiltration, gel permeation chromatography (GPC), low-angle X-ray scattering (LAXRS), colligative properties, ultracen-trifugation, and viscosity. A l l techniques have limitations, and the results must always be treated cautiously. Excellent critical appraisals of these methods can be found in the recent reviews by Wershaw and Aiken (18) and Thurman (19).

One common problem with many of the available methods, including flow F F F , is the need to find an appropriate set of standards on which the molecular-weight determination can be based. Only colligative properties are free of this problem; unfortunately, they yield only the number average molecular weight, with no indication of the polydispersity of the sample. The work reported here showed that a random-coiled polyelectrolyte (PSS) could be used to give molecular-weight results for some reference fulvic and humic acids that were more consistent with data from other methods (ultracentrifuge, L A X R S , vapor pressure osmometry) than when proteins are used as standards. This finding is not surprising, considering the likely structure of humic substances, which would be expected to behave more like the PSS molecules than the more rigid proteins. Nonetheless, proteins have been commonly used as molecular-weight standards in the past, particularly

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for ultrafilters and in G P C . Despite the apparent success obtained in using PSS standards, it is likely that even better reference materials could be found, as the humic molecules are probably somewhat more branched than the linear PSS molecules.

The most comprehensive molecular-weight studies have been done using the International Humic Substances Society Suwannee River fulvic acid reference material. The results obtained with several methods are shown in Table I. The satisfactory agreement between the flow F F F results and the other methods (36) is evidence for the validity of the technique despite some of the potential difficulties, which still need further development to overcome.

Commercially available humic acids (e.g., Aldrich, Fluka) are commonly used in laboratory experiments on humic substances, although it is doubtful that they are a particularly good model, especially for aquatic humic substances (37). We can compare the results of flow F F F and G P C for Aldrich humic acid by using data of El-Rehaili and Weber (38). The raw fractionation output is given for each method in Figure 7A. The G P C elution volume was converted to molecular weight by using protein standards, whereas in the F F F determination, PSS standards were used. Of course, with G P C the molecular weight decreases with increasing elution volume. We have plotted it from right to left to be more comparable with the F F F fractogram. The most noticeable difference is the occurrence of two peaks in the G P C trace.

The G P C curve was transposed to a molecular-weight distribution by using the same procedure as described for the F F F fractogram. This transformation has rarely been attempted with the G P C results reported in the literature. The two molecular-weight distributions are compared in Figure 7B. The major difference is the occurrence of a quite sharp peak in the G P C curve. This peak was close to the column volume (77 mL) and is outside the range covered by the calibration standards. It probably does not accurately represent the true molecular-weight distribution in this region, and for this reason we show it as a dotted line in Figure 7B. F F F is generally characterized by higher selectivity and resolution than G P C (39), so it is likely that this peak would also be resolved by flow F F F unless some nonideal phenomenon (e.g., intermolecular interaction) was occurring with these humic samples.

The G P C molecular-weight distribution still contains, in addition, a high-molecular-weight peak that is absent in the F F F distribution. This peak

Table I. Molecular-Weight Studies for the Suwannee River Fulvic Acid Sample

Method M„ Reference Flow FFF 1150 1910 33 Ultracentrifuge 655 1335 36 VP osmometry 823 — 36

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RETENTION VOLUME FOR GPC (mL) 90 80 70 60 50 40 30

0 10 20 30 40 50 60 70 RETENTION VOLUME FOR FFF (mL)

0.030

g 0.025

ζ 0.020 U. £ 0.015 ζ IAJ

3 0.010

S £ 0.005

1 I ! 1

Β - {{ GPC -

τ ! I Flow FFF

1— ι ι

-

0 5000 10000 15000 20000 25000 MOLECULAR WEIGHT

Figure 7. Comparison of flow FFF (from ref 33) and GPC (from ref 38) data for Aldrich humic acid sample. (A) Flow FFF fractogram and GPC chroma-togram. Volume scales are different. (B) Calculated molecular-weight distributions. The dotted portion of the GPC distribution is subject to considerable

uncertainty, as discussed in text.

is much less pronounced than the first. Possibly this peak, which would correspond to a fairly high apparent molecular weight, is due to low-molecular-weight components that have been excluded from the gel by charge repulsion. Alternatively, this peak may be missing in the F F F fractogram due to adsorption or aggregation phenomena. The presence of multiple peaks in G P C analysis of humic substances is a common occurrence that we believe may be an artifact of the method. However, further work is required before this matter can be resolved completely. We also stress that the plots of the raw output from fractionation techniques such as these can be rather mis-

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leading and may be a poor representation of the true molecular-weight distribution.

Potential Applications of Flow FFF Flow F F F offers the potential to provide molecular-weight distributions of humic substances. It could thus become a valuable additional tool in the quest to understand the origin, nature, and behavior of this important class of naturally occurring organic compounds. In combination with other analytical methods, it should be of help in unraveling the biogeochemical changes that occur in these materials, both in the short term in aquatic systems and in the longer term in ground water, soils, and sediments.

We previously (33) reported the molecular-weight distributions of humic substances from a number of aquatic and terrestrial sources. Some of the data reproduced in Table II demonstrate a distinct trend toward increased molecular weights as we progress from stream, soil, and peat to coal humate types. Of course, this information alone wil l not answer the many questions that remain, and a multidisciplinary approach to these problems is most desirable.

Preliminary experiments have indicated a shift to higher molecular weight as the solution p H is decreased or if calcium salts are added. The relatively high p H of 7.9 was used in this study in an attempt to repress any tendency of the humic substances to aggregate and thus to obtain estimates of the primary particle molecular weight. This possible aggregation of humic substances would have important consequences in their behavior in natural systems and their role in affecting the fate of pollutants. Certainly more work is warranted in this area of environmental research.

The fact that flow F F F is also a fractionation technique should make it useful to study the interactions of humic substances with environmental pollutants. The small scale of the separation, which usually involves much less than 1 mg of sample, would be a limitation here. However, with the use of ultratrace analytical methods, a very powerful method for investigating the importance of different size fractions of humic substances responsible for binding pollutants could be developed. Radiotracer techniques and mass spectrometry are examples of methods that would provide detection systems sensitive enough for such experiments.

Table II. Molecular Weights of Humate Samples as Determined by Flow F F F Data

Sample M n Μ„/Μ„

Suwannee stream humate 1,580 4,390 2.78 Mattole soil humate 1,940 6,140 3.16 Washington peat humate 3,020 17,800 5.89 Leonardite coal humate 3,730 18,700 5.01 NOTE: Data are from ref. 33.

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Summary

Flow F F F is capable of yielding the molecular-weight distributions of humic substances, thus providing more detailed molecular-weight information than any other method, with the possible exception of G P C . Flow F F F should be less prone to anomalous sample interaction effects than G P C , because with this method the separation is carried out in unpacked channels of low surface area. However, indications are that some sample interaction with the membrane on the accumulation wall of the F F F channel does still occur. We hope that further work will find membrane materials and solution conditions that eliminate these undesirable effects.

The availability of a quick and reliable method for molecular-weight determination should provide a useful addition to the tools available to assist with humic-substances research. Furthermore, the fractionating ability of flow F F F could be used to provide valuable information on the interaction of pollutants with humic substances.

Acknowledgments

This work was supported by the Australian Research Grant Scheme and the Department of Science in Australia and Department of Energy Grant DE-FG02-86ER60431 in the United States.

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RECEIVED for review November 3, 1987. ACCEPTED for publication February 29, 1988.

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