1087
Anal. Chem. 1985, 57, 1087-1091 '
mation 4500 transient digitizer and to Jim Jones of Gould, Inc., for technical assistance given during this work.
MASS (amu) 172 174
I
LITERATURE CITED
-
6
z
(1) Lubman, D. M.; Naaman, R.; Zare, R. N. J . Chem. Phys. 1980, 72, 3034. (2) Lubman, D. M.; Kronlck, M. N. Anal. Chem. 1982, 54, 660. (3) Tembreull, R.; Lubman, D. M. Anal. Chem. 1984, 56, 1962. (4) Dletz, T. G.; Duncan, M. A.; Liverman, M. G.; Srnalley, R. E. Chem. mys. Len. 1980, 7 0 , 246. (5) Dletz, T. G.; Duncan, M. A.; Liverman, M. G.; Smalley, R. E. J . Chem. Phys. 1980, 73, 4816. (6) Boesl, U.; Neusser, H. J.; Schlag, E. W. Chem. Phys. 1981, 55, 193. (7) Zandee, L.; Bernstein, R. B. J . Chem. Phys. 1979, 70, 2574. (8) Lichtln, D. A.; Datta-Ghosh, S.; Newton, K. R.; Bernstein, R. B. Chem. Phys. Lett. 1980, 75, 214. (9) Leutwyler, S.; Even, U. Chem. Phys. Left. 1981, 81, 578. (10) Dlmopoulou-Rademann, 0.;Rademann, K.; Brutschy, B.; Baumgartei, H. Chem. Phys. Lett. 1983, 101, 485. (11) Smalley, R. E.; Wharton, L.; Levy, D. H. Acc. Chem. Res. 1977, 70, 139. (12) Anderson, J. 8.; Andres, R. P.; Fenn, J. B. Adv. Chem. Phys. 1966, 10, 275. (13) Miller, C. M.; Nogar, N. S.; Gancarz, A. J.; Shields, W. R. Anal. Chem. 1982, 54. 2377. (14) Mlller, C. M.; Nogar, N. S. Anal. Chem. 1983, 55, 1609. (15) Lubman, D. M.; Zare, R. N. Anal. Chem. 1982, 54, 2117. (16) Lubman, D. M.; Rettner, C. T.; Zare, R. N. J . Phys. Chem. 1982, 86, 1129. (17) Wlley, W. C.; McLaren, I . H. Rev. Sci. Instrum. 1955, 26, 1150. (16) S. Leutwyler, private communication, Basil, Switzerland, July 1984.
1
P v: z
0
kl
h 2
3
Figure 5. Time of flight mass spectra of p-bromophenol obtained as a function of wavelength: (A) 278.75 nm; (B) 278.77 nm; (C) 278.79 nm.
Received for review November 2,1984. Accepted January 16, 1985. We gratefully acknowledge financial support from a Cottrell Research Grant and a University of Michigan Rackham Award. Acknowledgment is also made to the donors of the Petroleum Research Fund, administered by the American Chemical Society, for support of this research.
resolution pulsed lasers even for the case of large aromatic molecules.
ACKNOWLEDGMENT Special thanks are due to Gould, Inc., for loan of a Bio-
Quantitative Analysis of Aqueous Species Using Raman Spectrometry and Equilibrium Model Calculations J. A. Sorensen and L. C. Thompson Department of Chemistry, University of Minnesota-Duluth, Duluth, Minnesota 55812 G. E. Glass* Environmental Research Laboratory-Duluth, Duluth, Minnesota 55804
U.S. Environmental Protection Agency, 6201 Congdon Boulevard,
An analytical approach of quantlfylng various chemical species, uslng Raman spectrometry In conjuncllon wlth equlllbrlum modellng, has been tested on aqueous solutlons containing Nd, Cu, and dlplcollnlc acid. Equlllbrlum modeling was used to select optlmum conditlons In slmple solutlons for the determlnatlon of concentration-Raman Intensity relationships. These relatlonshlps were then used to Interpret spectra from more complex solutions and to make comparlsons with equlllbrlum modeling results from the same systems. Peak heights were determlned through curve fitting of the spectra using nonllnear regression and were normallted uslng CI0,as an Internal standard.
The importance of the chemical form(s) of compounds in aqueous solution in the interpretation of ecological impact and 0003-2700/65/0357-1087$01.50/0
.
environmental protection has been well established (1-3). However, the direct determination of complexed species in aqueous solutions is a complex problem with numerous experimental difficulties. Among the techniques that have been used are those based on electrochemicalproperties and those based on spectral properties (4). Most common among the latter are the measurements of the ultraviolet and visible spectra. Unfortunately, these are restricted to species that either have strong charge-transfer bands or give colored solutions due to d-d transitions. Moreover, with the transition elements these are not generally useful as diagnostic tools for complexes of a given class of ligands since all the spectra consist of broad bands with very little differentiation. On the other hand, vibrational spectroscopictechniques that use a distinct property of the bonds within the ligand or of the bonds between the metal and ligand could potentially be of considerable value. The most promising of these would
0 1985 American Chemlcal Society
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ANALYTICAL CHEMISTRY, VOL. 57, NO. 6, MAY 1985
appear to be Raman spectrometry since it is generally applicable to aqueous systems whereas conventional infrared spectrometry is limited to use in very narrow windows in either normal or heavy water (5). The Raman effect has been used, for example, in estimating the dissociation constants of very strong acids (6),in determining the equilibrium constants in halide systems, in identifying the major hydrolysis products of organometallic cations, and in studies involving the methylmercury(I1) ion with nucleotide bases (7). Although the earlier work of this type was carried out on relatively concentrated solutions ( ~M), 1 the advent of the laser as the exciting source as well as other advances in instrumentation have now permitted the investigation of substantially more dilute solutions. A recent communication, for example, reports the hydrolysis quotient for tribasic sodium phosphate in solutions having concentrations between 0,001 M and 0.4 M (8). When a metal ion or ions are in an aqueous solution in the presence of a molecular species that can act as a ligand, the ions may be distributed among several possible complexes. If the total concentrations and the appropriate equilibrium constants of metal and ligand are known, the distribution of the various species can be determined. In practice the computations can become very complex. Modern computer techniques have made such calculations feasible and recently an elaborate program, REDEQL-UMD(9),has been developed and is readily available to handle these, as well as other, equilibrium computations. The purpose of the work described in this paper was to combine both Raman spectrometry and equilibrium modeling as a useful approach for quantitative measurements of species concentrations in aqueous solutions. First, a series of simple solutions for each component of interest were made for calibrating the intensity of their Raman spectra and for comparison with equilibrium calculations. Next, the compositions of more complex solutions containing several components are determined through their spectra and verified using equilibrium modeling. The aqueous system chosen for testing this methodology consisted of copper(II),neodymium(III), and dipicolinic acid (pyridine-2,6-dicarboxylicacid, Dipic2-)
M) of the dipotassium salt of dipicolinic acid (Aldrich) was prepared from a known weight of the acid (previously assayed potentiometrically) and the required amount of standard KOH solution. The copper(I1) and neodymium(II1) solutions were standardized against EDTA using murexide and xylenol orange, respectively, as indicators. The concentrations of the desired complexes in the samples for the Raman work varied from 0.003 to 0.08 M. In addition each solution contained 0.030 M C104as an internal standard. Raman Measurements. Raman spectra were excited using the 514.5-nm line from a CR-18 argon ion laser (Coherent Inc.). Approximately 2 W of power was incident on a Ramalog spectrometer system (Spex Industries, Inc.) with about 0.5 W directed onto the sample. The Ramalog is equipped with the DPC-2 photon countingsystem and an RCA C31034 photomultipliertube mounted in a thermoelectrically cooled housing. The system is computer controlled by the SCAMP accessory that can store the resulting data as well as process it. The laser beam enters a compact monochromator to reject spurious lines before the radiation is focused onto the capillary sample cell. Slits for the double monochromator used for analyzing the scattered light were set at 2.0 cm-’ spectral band-pass. Photon counting was in 1-s periods at 0.25-~m-~ increments and multiple scans were made between 910 and 1065 cm-l. A minimum of five scans (each of 10 min duration) per analysis was chosen to provide a signal to noise ratio of about 50:l for the C104- peak. This corresponds to a detection limit of about 0.001 M for both C10, and Dipic2-. Up to 10 scans were used for those samples with very small peaks. Analysis was made by first subtracting the background Raman spectrum of water (defined by 30 scans). The resulting spectrum was then resolved into all major component peaks through curve fitting using a Cyber 171 computer. The bandwidth, height, and position of each peak along with the base line linear drift were found for the best fit of the data. The equation used to fit each peak was a Gauss-Lorentz sum function (13-15)
where I is the amplitude at position,Io is the amplitude maximum, G is the fraction Gauss component - used 0.30 (13),F = ( A t At0)/(B/2)l2, A‘V is the position of amplitude I with respect to excitation wavenumber (cm-l), A‘Vois the position of amplitude maximum with respect to excitation wavenumber (cm-l),B is the bandwidth fwhm (cm-l),and L is the fraction Lorentz component ( L = 1- G). A best fit of all parameters was obtained by using a Fortran program to perform a nonlinear regression. After supplying initial guesses, the program minimizes the sum of the squares of the residuals using the Gauss-Newton method. Resulting peak heights (lo)were then normalized to that of the C104peak height at 937 cm-’. All fits required two-componentpeaks for the C10, standard and a base line roll ( B 65 cm-’) toward the center of the scan in addition to the major peaks. REDEQL-UMD Equilibrium Model Computations. The calculations of the equilibrium concentrations of the various species in the metal ion-dipicolinic acid solutions were carried out using the equilibrium model REDEQL-UMD and the stability constants of Grenthe (IO, 11,16). These constants and their values at zero ionic strength, calculated according to Sun et al. (17),are listed in Table I. REDEQL-UMD uses equilibrium constants at zero ionic strength for the first iteration and then applies the appropriate corrections for subsequent iterations using either the equation of Sun et al. or Davies (18)at the user’s option. N
The choice of dipicolinic acid ( 1 0 , I I ) was made because (1) it forms strong soluble complexes with di- and trivalent metal ions, (2) the stability constants for many of its complexes have been carefully measured, (3) protonated metal complexes normally are not present nor are hydroxo complexes, (4)it has a “ring-breathing” vibration active in the Raman spectrum that is relatively isolated and is affected by metal complexation, and (5) the chelation sites are chemically similar to a variety of compounds found in the aquatic environment. The choice of metal ions was dictated by the requirement that they form stable, well-defined complexes with dipicolinic acid, that their effect on the “ring-breathing” vibration is substantial but different, and that their dipicolinate complexes had been previously studied in D20 by means of infrared spectrophotometry (12). EXPERIMENTAL SECTION Preparation of Solutions. Stock solutions of copper(I1) chloride (0.5 M) (Fisher), neodymium(II1)chloride (0.05 M and 0.01 M) (LindsayChemical Division), and sodium perchlorate (0.6 M) (Fisher) were prepared by dissolvingthe appropriate amount of substance in deionized distilled water. A stock solution (0.1
RESULTS AND DISCUSSION The first objective was to define solution concentration and obtain a working curve (relative Raman intensity vs. computed concentration) for each of the aqueous species in this study (Dipic2-, H(Dipic)-, Cu(Dipic), C ~ ( D i p i c ) ~Nd(Dipic)’, ~-, Nd(Dipic);, and Nd(Dipic):-). This is a straightforward task if simple aqueous solutions can be prepared in which the complex of interest is essentially the only one present. For those species where this is not possible the peaks arising from each complex must be well resolved. As it turns out, Nd(Dipic); is the only complex which does not satisfy either of
ANALYTICAL CHEMISTRY, VOL. 57, NO. 6, MAY 1985
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Table I. Stability Constants for the Formation of Relevant Dipicolinate Complexes
reaction
log of stability constant
H+ + Dipic2- + H(Dipic)2Ht Dipic" + H,(Dipic) Cuzt + Dipic2-6 Cu(Dipic) Cu2++ 2(Dipi@- == Cu(Dipic)lNd3++ (Dipic)2-F= Nd(Dipic)+ Nd3++ 2 ( D i p i ~ )+ ~ - Nd(Dipic)2Nd3+4- 3(Di~ic)'-+ Nd(Di~ic)?-
4.68 6.78 9.14 16.51 8.78 15.50 20.56
+
ionic strength 0.1 0.1
0.5 0.5 0.5
0.5 0.5
a,M-'
N
Dipic233.2 f 0.3 H(Dipic)35.8 f 0.3 Cu(Dipic) 25.4 f 0.2 Cu(Dipic)," 68.0 f 0.8 Nd(Dipic)+ 51.4 f 0.5 Nd(Dipic); 107.0 f 1.1 Nd(Dipic)a- 173.3 i 2.1
concn peak range, position, bandwidth, M cm-' cm-l
10 10-50 8 11 10 10 10 10
1003 1021 1046 1045 1026 1025 1025
9-37 5-23 8-16 10-20 5-20 3-9
6.2 5.8 6.1 6.3 4.0 4.1 4.1
stability constant corrected to zero ionic strength
20 20 20 20 20 20 20
5.09 7.40 10.37 17.74 10.64 18.00 22.42
1:l complex, 84% in the 2:l complex, and 7% in the 3:l complex. Regressions of relative Raman intensity vs. concentration were obtained for each of the seven species. In all cases the data are well-representedby straight line relationships of the form I = cyC where I is the relative Raman intensity, C is the complex concentration, and a is a constant for each species. The best fit values of cy are given in Table 11. The range of concentrationvalues in these systems is rather narrow because of the desire to avoid both Raman intensities near detection limit and concentrated solutions for which the ionic strength corrections would be large. No significant changes in peak shapes for a given species were detected over the concentration ranges used for this table. The results of these measurements on relatively simple solutions indicate that the equilibrium model REDEQL-UMD can satisfactorily be used to interpret Raman spectra of this type. In order to examine this approach further, a more complicated set of solutions was prepared so that both 1:l and 2:l metal complex forms were present for both copper and neodymium. The objective here was to compare the predicted concentrations of these forms with that determined experimentally from the Raman spectra. Again, a series of equilibrium model computer runs were made in order to select three different solutions (samples A, B, and C) which would be of interest. Some of these runs are summarized in Table I11 where the choices for samples A, B, and C are indicated. The pH values of these three samples are near those used by Grenthe- (11) where no protonated metal complexes were observed. If there are two dipicolinate complexes that are contributing to the intensity of one peak, it is still possible to estimate the
Table 11. Parameters Relating Relative Raman Peak Height ( I ) to Species Concentration ( e )Where Z = aC and N Is the Number of Measurements Over the Concentration Range'
species
temp, "C
f 0.6 f 0.2 f 0.3 f 0.2 f 0.1 f 0.1 f 0.1
'Also shown are the spectral positions and bandwidths (fwhm). Standard deviations are listed for a and bandwidths. the above conditions. The peak positions and bandwidths listed in Table I1 show that the Raman peaks for the neodymium complexes are not resolvable (note that the copper complexes are not resolvable either). In order to obtain the working curve of Nd(Dipic)l, it was necessary to subtract the contributions of Nd(Dipic)+and Nd(Dipic),%(as determined by their working curve regressions and computed concentrations) from the measured peak hGghts for these solutions. REDEQL-UMD was used to determine the initial conditions (metal and ligand concentrations)necessary to prepare a series of solutions in which only one of the metal ion complexes would be present as the major constituent. Only in the case of the solutions containing Nd(Dipic)2-was it not possible to have at least 99.3% of the metal ion in a single complex. The worst case with Nd(Dipic); contained 9% of the metal in the
Table 111. Summary of Subset of REDEQL-UMD Runs Used for Selecting Samples A-F. some progiam results copper distributions neodymium distributions Dipic distributions (W of total) (% of total) ( % of total) free (Dipi& (Dipic)z free (Dipi& ( D i p i ~ ) ~(Dipic), free Cu Nd H
some program inputs initial concentrations, 10-3
sample Dipic
A B
c
D
E F
30.0 35.5 35.0 40.0 45.0 50.0 45.0 50.0 55.0 60.0 65.0 40.0 30.0 36.0 55.55 46.15 55.86
M
Cu
Nd
pH
10.0 10.0 10.0 10.0 10.0 10.0 10.0
10.0 13.0 15.0 15.0 15.0 15.0 20.0 20.0 20.0 20.0 20.0 15.0 10.0 18.0 11.11 7.89 12.41
4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 2.7' 2.9" 2.6' 5.3' 5.5" 5.0'
10.0 10.0 10.0 10.0 10.0 10.0 10.0 7.41 7.69 6.90
LI
0.2 0.1 0.3 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.1 0.2 0.6 0.0 0.0 0.0
Actual pH of sample when prepared.
37.5 33.5 44.4 25.6 11.6 2.9 32.2 18.9 9.1 3.0 0.9 25.6 37.5 55.5 0.0 0.0 0.0
62.4 66.4 55.3 74.3 88.3 97.1 67.6 81.1 90.8 97.1 99.1 74.3 62.4 44.0 100.0 100.0 100.0
0.4 0.3 0.6 0.1
0.0 0.0 0.4 0.1 0.0 0.0 0.0 0.2 0.4 1.2 0.0 0.0 0.0
61.7 58.4 68.9 49.5 27.4 7.4 58.3 41.1 23.1 8.0 2.1 49.6 61.8 77.4 0.0 0.0 0.0
37.7 41.1 30.4 49.8 70.8 83.2 40.9 57.9 74.3 82.6 70.3 49.6 37.7 21.3 0.2 0.2 0.4
0.2 0.3 0.1 0.5 1.7 9.4 0.3 0.8 2.5 9.4 27.5 0.5 0.2 0.1 99.8 99.8 99.6
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
54.1 47.5 44.3 43.5 41.8 39.4 37.2 36.2 0.0 34.7 0.0 32.8 0.0 30.6 0.0 43.5 0.0 54.1 0.0 39.8 10.7 26.7 14.1 33.3 5.7 24.7
45.9 52.5 55.7 56.5 58.2 60.6 62.8 63.8 65.3 67.2 69.4 56.5 45.9 60.2 60.0 50.0 66.6
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 2.7 2.6 3.0
ionic strength 0.102 0.114 0.116 0.125 0.133 0.144 0.139 0.147 0.155 0.167 0.187 1.126 0.103 0.123 0.179 0.152 0.178
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ANALYTICAL CHEMISTRY, VOL. 57, NO. 6, MAY 1985
concentration of each. First the peak height of the desired component is determined for each sample (A, B, and C) and then an excess quantity of the ligand is added sufficient to convert the metal totally into the highest order complex (2:l complex in the case of copper; 3:l complex in the case of neodymium) to form samples D, E, and F, respectively. This quantity is easily determined since once the complexation of the metal ion is complete,the Raman peak due to free Dipic2will appear. The peak heights for the metals in their highest complexed form can be converted into values of the total concentration of metal ion in the solution (dilution corrections are not necessary since peak heights are normalized to the C10, peak height). This value in conjunction with the peak heights observed in the absence of excess ligand is then used to estimate the concentrations of the two complexes using the appropriate slope values ( a )given in Table 11. The relevant equations for the copper complexes are as follows:
[Cu(Dipic)] =
I T - l! a2
- a1
in which the subscripts 1 and 2 refer to the 1:l and 2:l complexes and T refers to the results obtained in the presence of excess ligand. A similar set of equations would apply to the neodymium case. It should be noted, though, that this method is limited to solving for only two species per peak. The peak heights corresponding to Nd(Dipic):- in samples D, E, and F were corrected for the small contributions due to H(Dipic)-, calculated using the data in Tables I1 and 111. The Raman spectrum of sample A containing 0.030 M ClO,, 0.01M Cu2+,0.015 M Nd3+,and 0.040 M Dipic2-at pH 2.7 is shown in Figure 1 where the Dipic” is entirely complexed with the metal ions. The peak at 937 cm-l is due to ClO;, that at 1026 cm-l is due to the neodymium-Dipic complexes, and that at 1046 cm-’ is due to the copper-Dipic complexes. The spectrum of sample D that results when an excess of Dipic is added to sample A is shown in Figure 2. In both solutions each of the metal ions is 99.9% complexed with Dipic. However, in the first solution both copper and neodymium are present as the 1:land 21 complexes whereas, in the second solution, copper is primarily present as Cu(Dipic)22-and neodymium is primarily present as N d ( D i ~ i c ) ~This ~ - . is the source of the dramatic change in the relative intensities of the Raman bands associated with these complexes. The new peak which appears in Figure 2 at 1003 cm-l is due to the presence of the excess dipicolinate dinegative anion. The predicted and measured concentrations (each the average of two trials) along with their estimated precisions are summarized in Table IV. A comparison of the predicted values with the measured values shows that the Raman derived concentrations and precisions are consistent with the equilibrium modeling results for these “more complex” samples. An alternate method for analyzing these Raman spectra quantitatively could employ multicomponent analysis. A series of equations for the N components could be written where the ith equation would take the form N
I(>$)=
cgiJcj J=1
where I($ is the Raman intensity at frequency li,Cj is the concentration of the j t h component Gth species), and K,C1 is the intensity contribution at frequency bi due to the Jth component with K , being a constant determined through
ANALYTICAL CHEMISTRY, VOL. 57, NO. 6, MAY 1985
0
925
950
975
1000
1025
1050
1091
the appropriate constants. The methodology used here, which employs curve fitting, requires no prior knowledge of an unwanted peak (except that its shape be Raman in nature and resolvable) in order to solve for the needed concentrations. This method was selected not to solve this specific problem but rather to lay the framework for more general applications. The system studied in this work was also analyzed using peak areas. The agreement between Raman and calculated equilibrium results here was slightly poorer than that with peak heights. This was probably because peak areas depend on two fitted variables (peak height and bandwidth) rather than one. The procedure described in this paper demonstrates the utility of using chemical equilibrium modeling in conjunction with Raman spectrometery as an analytical approach. Furthermore, it suggests that the curve fitting methods employed here are workable and will provide for a variety of complex applications. Future work is planned in recognition of the need of chemical speciation (I) and reactivity information in studies defining biological availability and toxicity of polluting substances in aquatic environments.
qcm-‘
ACKNOWLEDGMENT
Figure 1. Background corrected Raman spectra of sample A (0.01 M Cu2+, 0.015 M Nd3+, 0.040 M Dipic2-,and 0.030 M CIO,-) shown by dots. Best fit using Gauss-Lorentz sum function shown by solid curve. Upper plot shows residual of best fit on same relative scale. 0-
The authors thank the ERL-D staff, especially, J. Poldoski, for constructivereview comments and T. Highland and J. Ilse for assistance in preparing this manuscript. Registry No. Cu(Dipic),69720-88-3;Cu(Dipic)?-, 16448-26-3; Nd(Dipic)+,94978-26-4; Nd(Dipi&-, 94978-27-5; Nd(Dipic)?-, 38721-35-6;Hz(Dipic),499-83-2; H(Dipic)-, 79776-53-7;Dipic2-, 17606-33-6; HzO, 7732-18-5; Nd, 7440-00-8; CU, 7440-50-8.
LITERATURE CITED (1) Stumm, W.; Morgan, J. J. “Aauatlc Chemistry”; 2nd ed.; Wlley: New
I
I
925
I
#
950
975
A
1000
I
1025
4
1050
Gcrn-‘
Figure 2. Background corrected Raman spectra of sample D (Dipic excess was added to sample A shown in Figure 1). calibration of the j t h component. All concentrations could then be determined by linearly regressing 1(3J against the N predictors Kil, Ki2,... KiN The advantage of this technique is ita simplicity and would seem to be the method of choice for the aqueous solutions presented here. However, a major disadvantage exists requiring that all Kij values be known for every component. Industrial and environmental applications, for example, may in general give rise to unwanted and unrelated components where it may not be practical or possible to determine all of
(13) (14) (15)
(16)
(17) (18)
York, 1981; 780-pp. Hoover, T. B. “Inorganlc Species In Water: Ecological Significance and Analytical Needs”; EPA-600/3-78-064, July 1978, 100 pp. Glass, G. E. Anal. N . Y . Aced. Scl. 1977, 298. 31-46. Rossottl, F. J. C.; Rossottl, H. “The Determlnatlon of Stablllty Constants”; McGraw-HIII: New York, 1961. Tobias, R. S. “The Raman Effect”; Anderson, A,, Ed.; Marcel Dekker: New York, 1973; Vol. 2, p 405. Covlngton, A. K.; Thompson, R. J. Solut. Chem. 1974, 3 , 603. Mansy, S.; Tobias, R. S. J. Am. Chem. SOC. 1974, 96, 6874. Miller, A. 0.; Macklin, J. W. Anal. Chem. 1983, 55, 684. Harriss, D. K.; Ingle, S. E.; Taylor, D. K.; Magnuson, V. R. “Generalization of Water Quallty Crlterla Using Chemical Models: Development of The REDEQL-UMD System of Computer Programs for Aqueous Equlllbrla”; EPA-600/S3-84-007, Feb 1984, NTIS: PB 84135506 and 64-135516; Sprlngflekl, VA. Anderegg, 0. Helv. Chim. Acta 1960, 43, 414. Grenthe, I. J. Am. Chem. SOC. 1961, 8 3 , 360. Thompson, L. C.; Mannila, K. D. J. Inorg. Nucl. Chem. 1968, 30, 1109. Spex Industrles Technlcal Note No. 52, Metuchen, NJ, 1960. Lundeen, J. W.; Koehler. W. H. J. Phys. Chem. 1975, 79, 2957. Downey, J. R., Jr.; Janz, 0. J. “Advances in Infrared and Raman Spectroscopy”; Clark, R. J. H., Ed.; Hayden: London, 1975; Vol. 1, p 29. Grenthe, I.Acta Chem. Scand. 1963, 17, 2487. Sun, M.; Harriss, D.; Magnuson, V. Can. J. Chem. 1979, 58, 1253. Davies, C. W. “Ion Assoclatlon”; Butterworths: Washington, DC, 1962; p 41.
RECEIVED for review September 4, 1984. Accepted January 14, 1985. The research described in this article has been funded in part by the U.S. Environmental Protection Agency through Cooperative Agreement CR809412 to the University of Minnesota-Duluth and was conducted primarily at the U.S. EPA Environmental Research Laboratory-Duluth. Manufacturers and trade names are given for product identification only and no endorsement is intended or should be inferred.
