Characterization of Natural Organic Matter Using High Performance

(13) Newcombe, G.; Drikas, M.; Assemi, S.; Beckett, R. Wat. Res. 1997, 31 (5), 965-972. (14) Wershaw, R. L.; Aiken, G. R. Molecular Size and Molecular...
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Environ. Sci. Technol. 1999, 33, 2807-2813

Characterization of Natural Organic Matter Using High Performance Size Exclusion Chromatography C O S T A S P E L E K A N I , * ,† GAYLE NEWCOMBE,‡ VERNON L. SNOEYINK,† CHRIS HEPPLEWHITE,‡ SHOELEH ASSEMI,§ AND RONALD BECKETT§ Department of Civil and Environmental Engineering, University of Illinois, Newmark Civil Engineering Laboratory, 205 N. Mathews Avenue, Urbana, Illinois 61801, CRC for Water Quality and Treatment, Private Mail Bag, Salisbury, SA 5108, Australia, and CRC for Freshwater Ecology, Water Studies Center and Department of Chemistry, Monash University, Clayton, VIC, 3168, Australia

High performance size exclusion chromatography (HPSEC) was used to obtain the molecular weight distributions of natural organic matter (NOM) from two South Australian drinking water sources. The NOM was separated into five nominal molecular weight fractions (30K) using ultrafiltration membranes prior to HPSEC analysis. The use of HPSEC as a tool for NOM characterization was compared with an independent method, flow field-flow fractionation (FlFFF), which separates molecules via a different mechanism. Unlike HPSEC, which uses a porous gel with a controlled pore size distribution to separate molecules, FlFFF uses hydrodynamic and molecular diffusion principles to separate molecules on the basis of molecular size, in the absence of a porous gel. The comparison was made using the following parameters: weight-average molecular weight (Mw), numberaverage molecular weight (Mn), peak molecular weight (Mp), polydispersivity (Mw/Mn), and molecular weight range (80% confidence limits). Within the technical limitations of each method, good agreement was obtained between HPSEC and FlFFF for the different fractions. Although solutegel interactions were identified with the HPSEC system, the validation of the technique with FlFFF indicates that HPSEC can provide useful and reliable molecular weight distributions of NOM in drinking water supplies.

Introduction Natural organic matter (NOM), a complex mixture of organic compounds derived from the decay of plant and animal material, is present in all water sources. Most of these watersoluble materials are complex organic acids and are generally classified as humic substances (1-3). Characterization of the physicochemical properties of NOM is an integral part of understanding the role of NOM in an array of environmentally important processes, such as fate and transport of * Corresponding author phone: (217)333-5778; fax: (217)333-6968; e-mail: [email protected]. † University of Illinois. ‡ CRC for Water Quality and Treatment. § Monash University. 10.1021/es9901314 CCC: $18.00 Published on Web 07/14/1999

 1999 American Chemical Society

micropollutants, and its impacts on potable water treatment unit operations. Molecular weight and size distribution are two important bulk properties of NOM. Estimates of the average molecular weight of humic substances derived from soil and aquatic origin have been the subject of many studies (4-7). Literature values indicate that the molecular weight of NOM can vary from a few hundred to greater than 100000 Da and is highly polydisperse in nature. However, recent data show that molecular weights of less than 10 000 are more likely. Ultraviolet and fluorescence spectroscopy, elemental analysis, and pyrolysis-gas chromatography/mass spectrometry techniques have been used to characterize NOM in a variety of surface waters (8). It was found that the NOM was composed of pedogenic and aquagenic proteinaceous compounds (5-10%), pedogenic and aquagenic polysaccharides (10-20%), aquagenic refractory organic matter (520%), and pedogenic refractory organic matter (50-80%). It was proposed that the pedogenic refractory organic matter is the fulvic acid fraction derived from soils. These compounds have relatively low molecular weights (less than a few thousand daltons), the degree of aromaticity is relatively high and their nitrogen-to-carbon ratio is low compared with aquagenic proteinaceous compounds. The size of NOM is important in drinking water treatment processes. Numerous studies have shown that processes such as coagulation are effective in removing the high molecular weight components, while activated carbon adsorption removes a broad molecular weight spectrum (9-12). The molecular size distribution of NOM has also been found to affect the adsorption of trace micropollutants such as pesticides and taste and odor compounds. Several studies have shown that the low molecular weight NOM fractions show the greatest level of competition for adsorption sites because they can access the same pores as the contaminant (13). Molecular weight distributions (MWD) of NOM have traditionally been measured using size exclusion chromatography (SEC) or ultrafiltration (UF) (5). These techniques do not fractionate based on size alone because other factors such as charge, molecular structure, steric effects, and hydrophobicity can influence the results (14). UF is a convenient procedure for fractionating material into different size ranges. Commercial UF membranes are available with different nominal molecular weight cutoffs (MWCO) (e.g., 500, 1K, 3K, 10K, 30K, and 100K). It is important to note that UF membranes have a distribution of pore sizes and thus do not exhibit a sharply defined MWCO (5). The large nominal molecular weight cutoff membranes (i.e., >3K) are usually calibrated with proteins, while sugars and polysaccharides are used to calibrate lower nominal molecular weight cutoff membranes (Amicon Membrane Catalog, 1996). Proteins are globular in nature, while humic materials are likely to be more linear structures under typical environmental conditions of neutral pH and low ionic strength (15). As a result of the different structures, the true nominal molecular weight cutoff for humic materials will be lower because the size-to-mass ratio is larger (16). Ideally, SEC separates compounds on the basis of hydrodynamic molecular size. Samples are injected into a column containing a porous gel material. Small molecules can access more of the internal pore volume than larger molecules, which are excluded from such pores. The net result is that the large molecules elute first followed by the smaller components, as long as the surface of the porous material is nonreactive. VOL. 33, NO. 16, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 1. Schematic of the FlFFF separation mechanism. For many years, the measurement of molecular weight distributions by SEC has been criticized because of the effects of solute-gel interactions (17, 18). Adsorption due to van der Waals and electrostatic forces between the gel surface and analytes will affect the retention time in the column and hence the apparent molecular weight. Hydrophobic compounds can adsorb to reactive sites on the gel surface, resulting in transport retardation and an artificially low apparent molecular weight. Electrostatic repulsion will result in artificially high molecular weights. Old SEC columns were made of Sephadex, a silica-based gel. Silica has many reactive sites (silanol groups, SiOH), and solute-gel interactions are expected (19). The development of bonded silica and polymeric gels to minimize reactive surface sites, as well as optimization of the eluent composition, has allowed SEC to become a more reliable molecular weight distribution analysis tool. Eluent composition, particularly pH and ionic strength, can greatly impact the results of SEC analysis. The eluent will affect the surface charge characteristics of the gel, the NOM charge and structure, and the gel-NOM interactions (20, 21). The effect of eluent composition on the molecular weight distribution of aquatic humus has been studied (19). It was found that significant ionic interactions occurred when the ionic strength was low. At higher ionic strengths (greater than 0.2), ionic effects were suppressed. The presence of aromatic groups in the NOM however, resulted in adsorption and retarded elution. An important issue concerning SEC is molecular weight calibration. The calibration compounds should ideally have similar structures and solution behavior to NOM if realistic MWDs are to be obtained. Chin et al. (22) used SEC to determine the MWDs of a variety of aquatic humic substances. Polystyrene sulfonates (PSS) were used for calibration, with good agreement obtained between the SEC MWDs and those determined using techniques based on colligative properties, such as vapor pressure osmometry and smallangle X-ray scattering. PSS molecules were assumed to have a similar configuration to Suwanee River fulvic acid, an International Humic Substance Society standard, when an eluent of pH 6.8 and an ionic strength of 0.1 were used. Today, SEC is often referred to as high performance SEC, or HPSEC, because of the use of tightly packed columns consisting of small, uniform particles (typically less than 10 µm). These are operated at high pressure (>500 psi) to provide fast, high-resolution chromatograms. Flow field-flow fractionation (FlFFF) is another technique which can be used for analyzing molecular size distributions (26-28). FlFFF has not been used as widely as HPSEC for characterizing MWDs of NOM, but its use is becoming increasingly popular, in light of the criticisms of HPSEC (16, 23-25). Unlike HPSEC, FlFFF does not involve the use of a porous packing material. Figure 1 shows a schematic of the FlFFF separation mechanism. The sample is injected into a thin channel (usually less than 300 µm thick). With the cross-flow and the axial flow off, the molecules are allowed to achieve an equilibrium distribution perpendicular to the channel. 2808

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Axial flow of the carrier liquid is initiated, causing the sample to be displaced. The channel is designed such that the axial flow profile is laminar, with a parabolic velocity profile established across the thin dimension. Retention in the FlFFF channel is achieved by forcing analyte material against one wall of a thin channel, where the axial velocity of the carrier liquid is very low. The driving force is a cross-flow carrier fluid through the accumulation wall. A semipermeable membrane at the wall allows carrier liquid to permeate but not the analyte. The increase in analyte concentration at the accumulation wall is opposed by diffusion, which is inversely proportional to the hydrodynamic diameter. Hence, smaller compounds are more effective in opposing the cross-flow; as a result, the low molecular weight compounds diffuse further toward the center of the FlFFF channel, where the axial flow is faster. Thus, the small molecules elute first, followed by the larger molecules. As a result of the open channel, FlFFF has several advantages over HPSEC. First, open channels have several orders of magnitude less surface area than packed columns, which translates into reduced opportunity for adsorption. Second, the flow through open channels is laminar and less tortuous than in packed columns. Therefore, molecular degradation of samples due to shear is minimized. Finally, the hydrodynamic molecular size can be calculated from the retention data. FlFFF does have some limitations. The main disadvantage lies in the MWCO of the semipermeable membrane, which determines the lowest molecular size that can be retained in the channel. There is evidence which suggests that loss of sample through the membrane as well as adsorptive interactions with the membrane surface may occur (16). Reducing the molecular weight cutoff of the membrane to minimize sample loss through permeation is limited by the increased pressure required to drive the cross-flow field through the membrane. With the current technology the maximum pressure that FlFFF channels can withstand before they leak is 150 psi (16). However, others have reported that most of these limitations can be minimized using cast cellulose acetate membranes, as used in this work (23). As with HPSEC, the evaluation of MWDs using FlFFF requires the use of calibration standards to convert diffusion coefficients to molecular weights. Polystyrene sulfonates (PSS) have been used by some to establish the correlation between the diffusion coefficient and molecular weight (23). The molecular weights of Suwanee River fulvic acid and soil humate and fulvate samples were measured by independent techniques (i.e. small-angle X-ray scattering) and the diffusion coefficients were calculated from FlFFF analysis. Satisfactory agreement was obtained between the NOM samples and PSS standards. Both HPSEC and FlFFF have been shown to provide useful information on the performance of water treatment processes (11, 12). HPSEC is a relatively simple technique and requires only modest analytical expertise. FlFFF involves more complex instrumentation and more skilled operators. However, it should be noted that this situation is changing with recent advances in commercially available FlFFF channels. The semipermeable FlFFF membranes most suitable for organic material are often made by the analyst and may require replacement after several months of use. Inexpensive and rapid analysis of water samples at different stages of treatment by HPSEC is thus an attractive option. The aim of this research was to utilize HPSEC and FlFFF to obtain molecular weight distributions of ultrafiltration fractions from two different Australian waters and determine if similar distributions could be obtained. The specific objectives of the study were (1) to verify that with the appropriate choice of column and eluent composition, HPSEC can provide reliable NOM molecular weight distri-

butions, comparable to those from FlFFF, (2) to identify possible methods to improve the molecular separation capabilities of HPSEC, and (3) to identify compounds that are greatly affected by adsorption and/or solute-gel interactions.

Experimental Methods NOM Preparation. NOM was obtained from two South Australian natural water sources: the Myponga reservoir, located 60 km south of Adelaide in the Fleurieu Peninsula (agricultural region), and the Hope Valley reservoir, located 15 km northeast of Adelaide in the Adelaide Hills. The two reservoirs have different catchment areas, with different soil types and vegetation. Prior to concentration, the water was passed through a 0.45 µm cartridge filter to remove particulate matter. Samples were taken during the Australian winter (July 1996) when algal activity was low. Myponga water was highly colored with dissolved organic carbon (DOC) levels greater than 12 mg/L, with a UV-254 absorbance of 0.4-0.5. In contrast, Hope Valley water displayed little color, with less than 6 mg/L DOC. NOM was concentrated using an anionexchange resin (31). This method removed approximately 80% of NOM measured as dissolved organic carbon. The unrecovered and lost NOM most likely consisted of the low molecular weight, hydrophilic, nonhumic material. The concentrate was desalted and fractionated using ultrafiltration membranes (Diaflo, Amicon) with nominal MWCOs of 500, 3K, 10K, and 30K (32). The MWCOs were determined as the molecular weight of a globular compound whose rejection was greater than 90%. The fractionation procedure yielded five NOM fractions for each natural water. FlFFF Analysis. The channel void volume was 1.1287 mL and the channel thickness was 223 µm. A cellulose acetate membrane was used to cover the accumulation wall. The complete membrane manufacturing procedure has been published elsewhere (30). The FlFFF cross-flow membrane was made of cellulose acetate, with a MWCO rating of 100. The channel and field flow rates were maintained at 0.8 and 4 mL/min, respectively, using a Universal Fractionator Fluid Delivery Module, Model F-4000 (FFFractionation, Inc., Salt Lake City, UT). The carrier solvent was 0.05 M tris(hydroxymethyl)aminomethane (TRISMA, BDH), 0.0268 M HNO3, and 0.00308 M NaN3 with a pH of 7.9. Polystyrene sulfonate (PSS) molecular weight standards of 1430, 4500, 6500, 17 500, and 31 000 g/mol (Polysciences Inc., MA) were used to calibrate the system. The PSS standards were dissolved in the carrier solution to give concentrations of 1 mg/mL. Standards and samples were measured at three injection masses of 0.625, 1.25, and 2.5 mg to check for overloading of the channel. The data are given for the injection mass of 2.5 mg. A fixed wavelength (254 nm) UV detector (BAS UV absorbance detector UV-8) was used. Although lower wavelengths can detect more chromophores, certain inorganic species (e.g. NO3-) can interfere. On the basis of UV-254, sample recovery was greater than 90%, indicating minimal loss of NOM through the membrane. HPSEC Analysis. The operating system consisted of a Waters 501 high-pressure pump, Waters 717 autosampler, a column temperature control oven (30 °C), and a Waters 484 UV/visible detector. Three different SEC columns were utilized in this study. The Waters Protein-Pak 125 column consisted of a glycol-functionalized silica gel with a rated molecular weight range of 2000-60 000 (Waters Corp., Milford, MA). The carrier solvent consisted of a 0.02 M phosphate buffer adjusted to an ionic strength of 0.1 M with sodium chloride, with a pH of 6.8. A flow rate of 0.7 or 1.0 mL/min was used, depending on the column. The system was calibrated with PSS standards of the following molecular weights: 1.8K, 4.6K, 8K, 18K, and 35K (Polysciences Inc., MA), prepared at 1 g/L concentration. The PSS monomer

with a molecular weight of 183 was used for some of the calibrations. The column void volume was determined using blue dextran, a polysaccharide with a molecular weight of 2 000 000. The total permeation volume was determined using acetone. The PSS standards were detected at 224 nm, acetone at 280 nm, and NOM samples at 260 nm. All samples were prepared in the carrier solvent, and injection volumes of 100 or 200 µL were used. A series of organic acids and dyes were used to test for solute-gel interactions. The compounds (all reagent grade) included aurintricarboxylic acid, mellitic acid, pyromellitic acid, tetrahydrofurantetracarboxylic acid, dibenzoyl-L-tartaric acid, 9,10-anthraquinone-2,6-disulfonic acid, glycyrrhizic acid, eriochrome cyanazine RC dye, and cibacron blue 3GA dye. HPSEC Calibration. A linear equation of the form log(MW) ) a - b(t), was obtained, where MW ) the molecular weight; t ) the peak retention time. A coefficient of determination R2 > 0.99 was consistently obtained. FlFFF Calibration. The retention time is related to the diffusion coefficient (23). A linear equation of the form: log D ) a - b[log(MW)] was fitted, where D ) the diffusion coefficient. Mw, Mn, and Polydispersivity (Mw/Mn). Weight-average (Mw) and number-average (Mn) molecular weights were used for calculation purposes only, so that MWD distribution parameters from HPSEC and FlFFF could be directly compared. These are defined elsewhere (22). Polydispersivity is a measure of the sample heterogeneity. Mp and Molecular Weight Range. Mp is defined as the molecular weight corresponding to the peak maximum. The molecular weight range for each sample was defined by excluding 10% of the sample mass at each end of the molecular weight distribution curve.

Results and Discussion HPSEC Calibration and Evaluation of Solute-Gel Interactions. To assess the importance of analyte-HPSEC gel interactions, a series of organic acids and dyes with different levels of aromaticity and carboxylic acidity and with molecular weights less than 1000 were used. The results for each compound were plotted on the PSS-acetone calibration curve to determine whether good agreement could be attained. The basic criteria for selection of compounds was similarity of chemical character to NOM. Specific criteria included presence of carboxylic acid functional groups, UVabsorbance and water solubility. Sample elution earlier than that predicted by the PSS calibration curve was taken as an indication of electrostatic repulsion effects, while delayed elution was considered evidence for adsorption, electrostatic attraction, and/or hydrogen-bonding interactions. However, molecular conformation may also be a factor influencing the retention of organic compounds in HPSEC. Figure 2 illustrates the structural formula of the compounds tested. The HPSEC column was first tested to evaluate whether linear and consistent calibration results could be obtained with the polystyrene sulfonate standards (PSS). The Waters Protein-Pak 125 column showed a high degree of linearity. Figure 3 shows a representative molecular weight calibration plot using the Waters Protein-Pak 125 column. Regression analysis yielded the following correlation: log(MW) ) -0.4184t + 7.527; R2 ) 0.993. Although this column is rated from 2000 to 60 000, an excellent correlation was obtained with the PSS standards and acetone. Since this column is calibrated by the manufacturer using globular proteins whose structures are different from NOM, the rated linear molecular weight range is expected to be lower for humic materials because of their higher size-to-mass ratio (16, 23). Also shown in Figure 3 are the elution results obtained for the selected organic acids. 9,10-anthraquinone-2,6disulfonic acid was the only compound which demonstrated VOL. 33, NO. 16, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 2. Structural formulas of organic acids tested. 2810

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good agreement with the PSS-acetone calibration. This could be due to the presence of the sulfonic acid groups, which are characteristic of the PSS standards. Aurintricarboxylic acid, mellitic acid, pyromellitic acid, and tetrahydrofurantetracarboxylic acid all eluted much earlier than expected (1-1.5 min). Dibenzoyl-L-tartaric acid, glycyrrhizic acid, and eriochrome cyanazine RC consistently eluted later than expected (1-2 min). The only clear and consistent trend observed from these is that the compounds with the highest molecular densities of carboxylic acid groups (mellitic acid, pyromellitic acid, and tetrahydrofurantetracarboxylic acid) showed substantial electrostatic repulsion effects on the bonded silica gel column. This is most likely due to the high charge density of these compounds at the pH used in the analysis (pH 6.8). No acid ionization data were available to confirm this. Even the relatively high ionic strength of 0.1 did not appear to effectively screen and depress electrostatic interactions for these relatively small molecules. The early elution of aurintricarboxylic acid relative to the other multicarboxylic acids was unexpected. There are several possible explanations for this observed behavior. Aurintricarboxylic acid is a larger compound with a different structure and a negative charge. It is not known what the charge is or how it compares with the other multicarboxylic acids. It is a multicarboxylate with groups that may be more easily ionized, as they are more separated than the others (greater distance between the carboxyl functional groups, thus more easily ionized). Structurally, it has a triphenylmethane configuration, which is quite different from the other multicarboxylate compounds tested. It is known that the aromatic rings of the ions of the triphenylmethane compounds do not lie in a single plane as a consequence of steric hindrance (33). It is possible that, on the basis of the shape of aurintricarboxylic acid, it will not be able to access the same pores that another molecule of the same molecular weight but with a planar structure could. Therefore both the spatial distribution of the carboxylate functional groups and the molecular structure relative to the calibration standards, as well as solute-gel interactions, can affect the elution profile. Of the molecules tested, glycyrrhizic acid has a pronounced aliphatic hydrophobic region. Such moieties can show adsorptive interactions with the gel surface, which is clearly the case here. It is important to point out that although only small compounds were tested, it is possible for larger compounds to also exhibit some form of solute-gel interaction. Small molecules, however, can access more pores, resulting in larger surface area contact and thus greater opportunity for adsorption and/or electrostatic interactions. Cibacron Blue 3GA, a dye with a high nitrogen content, was also tested. This dye showed significant retardation with the retention time approaching twice the complete permeation time of acetone (i.e. dye retention time of 26 min). Poor recovery was obtained, clearly indicating strong adsorption. Significant desorption of this dye was only achieved by elution with methanol. HPSEC Analysis of Myponga and Hope Valley NOM Fractions. The above results have established that solutegel interactions are possible, even with the highly advanced bonded stationary phases used in current HPSEC columns. With this knowledge, the molecular weight distributions of different NOM fractions were evaluated. Anion-exchange concentrated NOM from Myponga and Hope Valley reservoirs in South Australia were fractionated into different size ranges using ultrafiltration membranes with different nominal molecular weight cutoffs, operated in batch-stirred mode. Five fractions were obtained for Myponga, but due to limited quantities only four were used for molecular weight characterization (30K). Five fractions were obtained for Hope Valley (30K).

FIGURE 3. Elution behavior of selected organic compounds on HPSEC column.

FIGURE 4. Molecular weight distributions of Myponga NOM fractions: (a) HPSEC and (b) FlFFF. Figures 4 and 5 illustrate the molecular weight distributions for the Myponga and Hope Valley NOM fractions, respectively. The results show a consistent shift in the distribution to larger molecular sizes with increasing UF membrane size range. As a point of comparison, the FlFFF fractograms are also shown. The FlFFF data display the same trend as the HPSEC results. The HPSEC peak molecular weights for both sets of fractions generally increased with increasing UF size fraction. For Myponga, these were 1120, 1565, 2390, and 2730 g/mol as PSS. For Hope Valley, these were 810, 1040, 1510, 1930, and 1635. All the NOM showed molecular weights less than 10 000, with the Hope Valley fractions displaying consistently lower molecular weights than the Myponga fractions. The distributions became narrower with decreasing pore size of the membranes. There is considerable overlap of all the fractions for both the Myponga and Hope Valley NOM, which is likely to be due to the wide distribution of pore sizes present in the ultrafiltration membranes. The 10K and 30K membranes are calibrated with proteins, while the 500, 1K, and 3K membranes are calibrated with sugars. This explains why the larger pore size membranes yield peak HPSEC molecular weights well below their MWCOs. The smaller pore size membranes show better agreement with the HPSEC results, indicating that the NOM behaves more similarly to the sugars used to calibrate these membranes. However, as a general rule, the

FIGURE 5. Molecular weight distributions of Hope Valley NOM fractions: (a) HPSEC and (b) FlFFF. nominal molecular weight cutoffs of ultrafiltration membranes cannot be taken to reflect the true molecular weight of NOM. It is also possible that adsorption of NOM, especially the larger molecules, decreased the membrane pore size, and consequently, smaller molecules than expected were retained, particularly for the larger size fractions (10-30K and >30K). Charge repulsion could also play an important role in this mechanism. Experiments were also performed with an alternative HPSEC operating system. Two columns with different molecular weight range ratings, one targeting the low molecular weight region and the other targeting the high molecular weight compounds, were placed in series. The aim was to improve the NOM separation capability. The results showed evidence of band broadening, which is consistent with the longer contact time of samples in the columns. The results were difficult to interpret and therefore were not considered further. It is possible that parallel operation could provide more information than a single column with a broad molecular weight separation range. For example, a high molecular weight range column could be used to provide high resolution information about the large NOM material, and a low molecular weight range HPSEC column could be used to provide more detailed information VOL. 33, NO. 16, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 1. Percent Carbon in Each Functional Group (13C NMR) functional group NOM Fraction

carbonyl

(30K)

1.6 2.7 2.7 1.6

(30K)

5.0 2.9 2.8 3.0 3.6

carboxyl

aromatic

O-alkyl

alkyl

Myponga 13.4 17.4 14.6 12.0

16.6 17.2 16.0 13.0

24.2 35.4 43.0 50.0

43.1 26.4 22.4 22.4

Hope Valley 14.2 17.7 14.5 13.4 14.0

19.9 14.4 17.8 16.9 15.8

29.3 32.5 33.6 38.2 41.2

31.6 30.6 30.0 27.3 24.7

about the low molecular weight NOM compounds. This method could potentially provide more useful data than is currently possible with a single column with a broad molecular weight range column, which would have lower resolution. Both sets of NOM fractions were previously characterized by 13C solid-state nuclear magnetic resonance spectroscopy (13C NMR) (32). Table 1 summarizes the percentage of carbon in the following functional groups: carbonyl, carboxyl, aromatic, O-alkyl, and alkyl. The data show that each fraction contained 15-20% of carboxyl carbon, 30-45% alkyl carbon, and 30-50% O-alkyl carbon. A gradual transformation from highly colored, highly branched, higher carbohydrate structures to compounds with long chain aliphatic carbon and much lower carbohydrate content and color was identified as the molecular weight distribution of the NOM ultrafiltration fractions shifted to smaller values. The fractions from the two sources were similar, although the percentages of carbon within each functional group type (except for the carboxyl) differed slightly. This analysis showed that most of the NOM in the two South Australia waters tested is composed primarily of complex carbohydrates with carboxylic acid and aromatic moieties and negligible quantities of proteinaceous material. The structural information provided by 13C NMR provides additional information to support the similarities between the NOM and the simple sugars used to calibrate the low molecular weight cutoff UF membranes and the differences with the proteins used to calibrate the large molecular weight cutoff membranes. Comparison of Waters HPSEC with FlFFF. To provide evidence that HPSEC is a reliable molecular weight distribution characterization technique, the Myponga and Hope Valley fractions were characterized using FlFFF. It is important to highlight that the mode of separation in FlFFF is quite different from that in HPSEC. In FlFFF, there are no gel or pores. This results in significantly less surface area on which adsorptive or electrostatic interactions can take place. Furthermore, the small molecules elute first in FlFFF, while the large molecules elute first in HPSEC. FlFFF is currently limited to analysis of compounds with molecular weights greater than 300-400. To simplify interpretation of the results for the two sets of fractions with the two different techniques, the results for Mw, Mn and Mp are shown graphically in Figure 6, while the polydispersivities and molecular weight ranges are summarized in Table 2. The Mw of Hope Valley samples measured by FlFFF is higher than HPSEC, and the Mp of the Myponga samples is lower when measured by FlFFF than HPSEC. There are no strong or consistent trends otherwise. If the Mw for the Myponga 500-3000 fraction (by FlFFF) is incorrect, then in general, albeit with several exceptions, the HPSEC results for the Myponga fractions are higher than the FlFFF results, whereas the Hope Valley results are lower. 2812

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FIGURE 6. Comparison of Mw, Mn, and Mp of NOM fractions by HPSEC and FlFFF.

TABLE 2. NOM Polydispersivities and Molecular Weight Ranges (HPSEC vs FlFFF) HPSEC

FlFFF

NOM fraction

Mw/Mn

HPSEC range

Mw/Mn

FlFFF range

30K

1.35 1.16 1.22 1.63

Myponga 467-1960 1010-2450 1370-3420 1375-5410

1.56 2.35 1.59 1.75

400-2770 350-3100 550-3340 830-5820

30K

1.32 1.14 1.24 1.32 1.56

Hope Valley 356-1170 631-1470 851-2310 837-2970 851-3750

1.58 1.46 1.60 1.72 1.80

400-2880 400-2460 660-4090 770-5060 830-6140

The only significant trends when comparing HPSEC and FlFFF is the higher polydispersivity and wider separation range for FlFFF. Comparing Hope Valley and Myponga fractions, results for the two sets of fractions are similar when measured by FlFFF, whereas Hope Valley fractions appear to be significantly smaller (Mw, Mn, Mp) than the Myponga fractions as measured by HPSEC. This could be explained by the generally higher alkyl content of Hope Valley water, except for the 10 000) is probably better on FlFFF than HPSEC. This could result in the Mw data being more accurate for FlFFF than HPSEC, and could explain the inconsistencies in the trends observed when HPSEC is compared with FlFFF. It is also possible that the different solvents used in HPSEC and FlFFF could affect the conformation of NOM in solution, thus influencing the resulting molecular weight distributions. Furthermore, FlFFF is not immune from solute-membrane repulsion and adsorption, which have the effect of decreasing and increasing the apparent molecular weight, respectively. Within the technical limitations of each molecular weight characterization method, the overall agreement between the Waters HPSEC and FlFFF is good, regardless of any potential solute-gel or membrane interactions in the HPSEC columns and FlFFF channels. This is in agreement with the results of others who showed that HPSEC molecular weight distributions of a variety of natural waters agreed well with measurements by independent techniques which are not susceptible to adsorption, electrostatic, or hydrogen-bonding interactions, such as small-angle X-ray scattering and vapor pressure osmometry (22). Similarly, previous studies showed FlFFF results were consistent with those obtained using other methods (23). Overall, this study demonstrated that HPSEC is not immune to solute-gel interactions, even with the current state-of-the-art functionalized bonded stationary phases. Ultrafiltration fractions of anion exchange concentrated NOM from two Australian water supplies were used to compare molecular weight distributions using HPSEC and FlFFF. These two techniques separate molecules using independent approaches. By using several molecular weight characterization parameters, relatively good agreement was obtained. The techniques showed that the NOM in these water sources have molecular weights less than 10 000 (g/mol as PSS). The validation of the HPSEC technique as a tool for characterization of NOM molecular weight distributions by an independent method which separates molecules via a completely different mechanism, namely FlFFF, is important. This is particularly true, in light of the fact that HPSEC is now more routinely used for such applications. It is a simple and relatively fast technique which, along with structural information, such as that which can be obtained by 13C NMR, can provide useful information on the physicochemical character of NOM.

Literature Cited (1) Gjessing, E. T. Physical and Chemical Characteristics of Aquatic Humus; Ann Arbor Science Publishers: Ann Arbor, Michigan, 1976. (2) Schnitzer, M.; Khan S. U. Humic Substances in the Environment; Marcel Dekker: New York, 1972; p 327. (3) Thurman, E. M. Organic Geochemistry of Natural Waters, 2nd ed.; Martinus Nijhoff/Dr. W. Junk Publishers: The Netherlands, 1986. (4) Ghassemi, M.; Christman, R. F. Limnol. Oceanogr. 1968, 13, 583-597. (5) Amy, G. L.; Collins, M. R.; Kuo, C. J.; King, P. H. J. Am. Wat. Works Assoc. 1987, 79 (1), 43-49. (6) Wagoner, D. B.; Christman, R. F.; Cauchon, G.; Paulson, R. Environ. Sci. Technol. 1997, 31, 937-941. (7) Thurman, E. M.; Wershaw, R. L.; Malcolm, R. L.; Pinckney, D. J. Org. Geochem. 1982, 4, 27-35. (8) Krasner, S. W.; Croue´, J. P.; Buffle, J.; Perdue, E. M. J. Am. Wat. Works Assoc. 1996, 88 (6), 66-79. (9) Chadik, P. A.; Amy, G. L. J. Environ. Engng. 1987, 113 (6), 12341248. (10) El-Rehaili, A. M.; Weber Jr., W. J. Wat. Res. 1987, 21 (5), 573582. (11) Newcombe, G.; Pelekani, C.; Hepplewhite, C.; Nguyen, K. J. Australian Water and Wastewater Assoc. 1998, 25 (6), 16-20. (12) Dixon, D.; Wood, F.; Beckett, R. Environ. Technol. 1992, 13, 1117-1127. (13) Newcombe, G.; Drikas, M.; Assemi, S.; Beckett, R. Wat. Res. 1997, 31 (5), 965-972. (14) Wershaw, R. L.; Aiken, G. R. Molecular Size and Molecular Weight Measurements of Humic Substances. In Humic Substances in Soil, Sediment, and Water; Wiley-Interscience: New York, 1985. (15) Ghosh, K.; Schnitzer, M. J. Soil Sci. 1980, 129 (5), 266-276. (16) Schimpf, M. E.; Petteys, M. P. Colloids Surf. A: Physicochem. Eng. Aspects 1997, 120, 87-100. (17) Hine, P. T.; Bursill, D. B. Wat. Res. 1984, 18, 1461-1465. (18) Chin, Y. P.; Gschwend, P. M. Geochim. Cosmochim. Acta 1991, 55, 1309-1317. (19) Miles, C.; Brezonik, P. L. J. Chromatogr. 1983, 259, 499-503. (20) Swift, R. S.; Posner, A. M. J. Soil Sci. 1971, 22, 237-249. (21) Gloor, R.; Leidner, H.; Wuhrmann, K.; Fleischmann, Th. Wat. Res. 1981, 15, 457-462. (22) Chin, Y. P.; Aiken, G.; O′Loughlin, E. Environ. Sci. Technol. 1994, 28, 8(11), 1853-1858. (23) Beckett, R.; Jue, Z.; Giddings, J. C. Environ. Sci. Technol. 1987, 21, 289-295. (24) Dycus, P. J. M.; Healy, K.; Stearman, G. K.; Wells, M. Separa. Sci. Technol. 1995, 30 (7-9), 1435-1453. (25) Hassellov, M.; Hulthe, G.; Lyven, B.; Stenhagen, G. J. Liq. Chromatogr. Relat. Technol. 1997, 20, 2843-2856. (26) Giddings, J. C. Separa. Sci. 1966, 1 (1), 123-125. (27) Giddings, J. C. Separa. Sci. Technol. 1984, 19 (11), 831-847. (28) Schettler, P. D. LC-GC, 1996, 14 (10), 852-859. (29) Giddings, J. C. J. Chromato. 1989, 470, 327-335. (30) Beckett, R.; Wood, F. J.; Dixon, D. R. Environ. Technol. 1992, 13, 1129-1140. (31) Morran, J. Y.; Bursill, D. B.; Drikas, M.; Nguyen, H. Proc. AWWA WaterTECH Conference, Sydney, May 1996, pp 428-432. (32) Newcombe, G.; Hepplewhite, C.; Pelekani, C.; Drikas, M.; Snoeyink, V. L. Proc. IHSS, Wroclaw, Poland, September 1996. Drozd, J., Gonet, S. S., Senesi, N. Eds.; 629-634. (33) Mamchenko, A. V.; Martich, V. E.; Yakimova, T. I. Russ. J. Phys. Chem. 1983, 57(6), 883-885.

Received for review February 5, 1999. Revised manuscript received June 1, 1999. Accepted June 7, 1999. ES9901314

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