Environ. Sci. Technol. 1991, 25, 1427-1431
(38) Stumm,W.; Morgan, J. J. Aquatic Chemistry; Wiley: New York, 1981.
Received for review September 28,1990. Accepted March 4,1991. Air Force Office of Scientific This work was funded by the U.S.
Research, Grant AFOSR-88-0301. Funding was also obtained from the University of Wisconsin Sea Grant College Program under grants from the Office of Sea Grant, NOAA, U.S.Department of Commerce, and the State of Wisconsin (Federal Grant NA84AA-D-00065).
Continuous Multiligand Distribution Model Used To Predict the Stability Constant of Cu( I I ) Metal Complexation with Humic Material from Fluorescence Quenching Data Davld M. Grlmm,? Leo V. Azarraga,t Llonel A. CarreIra,***and Wlsnu Susetyo§
Technology Application, Inc., U S . Environmental Protection Agency, Athens, Georgia 306 13,Environmental Research Laboratory, U S . Environmental Protection Agency, Athens, Georgia 30613, and Department of Chemistry, university of Georgia, Athens, Georgia 30602 We report the use of a pH-dependent continuous multiligand distribution model to determine the stability constant between Cu(I1) and dissolved humic material. Fluorescence quenching of the humic material by Cu(I1) is used to produce spectral titration curves. The values from the titration curves are then fit, by use of a leastsquares fitting routine, to the calculated values produced by the model. Three titrations at pH 2.5,3.5, and 4.5 were conducted using this method, and the observed and calculated values are compared. A single stability constant for Cu(I1) with the humic material is reported. The results of these titrations are compared with the results of experiments carried out using a new technique that relies on the spectral properties of the Eu(II1) ion to probe metal binding sites in humic material.
Introduction Naturally occurring organic materials, in both terrestrial and aquatic systems, have been studied by researchers for many years. The conclusions that can be drawn from these studies are that the structure and physical properties of these organic materials, more commonly referred to as humic and fulvic substances, vary from region to region and are important in many environmental processes. Recently, particular interest in humics and fulvics has increased because of their ability to bind and transport potentially toxic metals in the environment (1-5). In an effort to understand and quantify metal humic complexation, researchers have used an assortment of techniques. The most common methods used to study the metal binding characteristics of naturally occurring dissolved organic matter (DOM) have been ultrafiltration, ion-exchange, equilibrium dialysis, and potentiometric methods (5-11). All of these techniques employ an indirect method of determining the amount of metal complexed to the humic material under study. Namely, the free metal ion concentration is measured and subtracted from the total metal added to determine the amount of metal bound. A more direct method of studying the metal binding characteristics of DOM would be to examine a property exhibited by either the humic material itself or a property of the metal to which it is complexed. In recent years, such a method was proposed by Ryan and Weber (12). Their Technology Application, Inc., U S . EPA.
* Environmental Research Laboratory, U.S. EPA. 8 University
of Georgia.
0013-936X/91/0925-1427$02.50/0
method utilizes the well-documented (12-14) ability of the Cu(I1) ion to quench the naturally occurring fluorescence of humic material. Ryan and Weber’s work included the development of a model that uses this quenching property of Cu(1I) to determine copper’s stability constants with humic material (12). The major assumption made in employing this fluorescence quenching technique is that the quenching varies linearly with bound copper. The models developed, from both indirect and direct binding studies, and the binding parameters determined from the fluorescence as well as the other previously mentioned techniques all have one thing in common: they yield conditional constants that are functions of ligand or proton concentrations. These methods normally produce conditional binding constants that often vary greatly with ionic strength and particularly with pH. An example is a paper by Ryan and Weber (12)that reports the binding constant of Cu(I1) to vary by a factor of 6 as the pH changed from 5 to 7. These models are of limited utility for predicting the metal binding properties of DOM over a wide range of environmental conditions. In the last few years, however, a new technique that yields thermodynamic values for metal-humic interaction has proven useful as a predictive tool in determining metal-organic speciation. This method, developed by Dobbs et al. (15), uses the fluorescence properties of the Eu(II1) ion to probe metal binding sites in DOM. The technique utilizes the fluorescence spectrum of the Eu(II1) ion, which is sensitive to ligation with humic material, to produce spectral titration curves. This method is unique in its ability to simultaneously measure both the free and bound europium concentrations. The spectral data from this technique are fitted by using a continuous multiligand distribution model (16)to determine the number of metal binding sites in the system and to examine the effect of competition between protons and other metals of interest with that of the probe metal for the available DOM sites (17). This model is unique in its ability to determine binding constants for metal ions with humic material that are not conditional constants that depend on ligand concentration or changing pH conditions. This method has been used to measure the binding constants of several metals as a function of pH and ionic strength (17). While using this technique to study the competition for binding sites between Eu(II1) and Cu(II), we observed very strong fluorescence quenching of both the Eu(II1) and DOM. The quenching was strong enough to interfere with the signal being monitored from the bound Eu ion at concentrations below M Eu(II1). Although a reasonable fit to the
0 1991 American Chemical Society
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titration curve above M Eu(II1) could be made, we felt it necessary to confirm our results with another method. In this paper, we report the use of the continuous multiligand distribution model to evaluate the fluorescence quenching effect on DOM by the Cu(I1) ion. These titrations were conducted at three different pH values and the data from the titrations were then fit by use of a modified version of the continuous multiligand distribution model, which takes into account ionic strength effects as well as proton competition for binding sites. This paper will also try to address the assumptions used in modeling the fluorescence quenching experiments recently criticized and defended in the literature (18, 19). E x p e r i m e n t a l Section
Instrumentation. The experimental setup for the fluorescence quenching experiment is virtually the same as that used in the lanthanide ion probe technique described by Dobbs et al. (20). Some modifications were made to the system, however; so a brief outline of the system configuration will be presented here. A Lambda Physik EMG 101 MSC excimer laser with a power output of 1.3 J at 308 nm was used to pump a FL3002 tunable dye laser. The laser dye (QUI) provided the excitation wavelength of 394 nm. The beam was focused with a 200-mm lens and directed vertically through a 1-cm disposable UV cuvette. The fluorescence emission was collected 90" off axis to minimize stray radiation. Two lenses were used to collect, collimate, and focus the fluorescence onto the monochromator slits. A GCA/Mcpherson 0.5-m double monochromator was used to disperse the fluorescence emission and a gated RCA C31034A02 photomultiplier tube (PMT) was used for fluorescence detection. A Stanford Research Systems Model SR535 digital delay/ pulse generator was used to control the timing of the experiment. The timing sequence and data collection method for this experiment are virtually the same as for the experiment outlined by Dobbs et al. (20). The only modifications were to change the delay time to zero in this experiment and to add a circuit that utilized the toggle mode on the boxcars (Model 510 Stanford Research Systems) to eliminate any background drift. The circuit allowed the pulse generator to operate at twice the pulse rate of the laser, to take a sample between pulses, and to subtract this dark count from the actual sample signal. This technique helped reduce electronic noise as well as any base-line drift from the PMT. The beam from the dye laser was monitored by splitting a small fraction of the beam onto a photodiode, and this signal was used as a reference to reduce the effect of fluctuations in the laser power output. The measurements were taken as a ratio of fluorescence signal over reference signal. Reagents and Sample Preparations. The DOM used in this experiment was obtained from the Suwannee River in southern Georgia by Serkiz and Perdue (21) in May 1987. Reverse osmosis was used to extract and concentrate the DOM from the river water; the DOM was then further processed with XAD resins (21). A concentrated solution of the DOM was prepared by dissolving 0.55 g of the dry organic material in 50 mL of deionized water to give an 11 g/L solution with a pH
