Chemosphere 53 (2003) 927–934 www.elsevier.com/locate/chemosphere Competition between alga (Pseudokirchneriella subcapitata), humic substances and EDTA for Cd and Zn control in the algal assay procedure (AAP) medium Celine Gueguen a,b,* , Brahim Koukal a, Janusz Dominik a,b , Michel Pardos a a b Institut F.-A. Forel, 10 route de Suisse, CH-1290 Versoix, Switzerland Centre d’Etudes en Sciences Naturelles de l’Environnement, University of Geneva, 10 route de Suisse, CH-1290 Versoix, Switzerland Received 21 October 2002; received in revised form 27 June 2003; accepted 15 July 2003 Abstract The chemical speciation of trace metals in natural waters has important implications for their biogeochemical behavior. Trace metals are present in natural waters as dissolved species and associated with colloids and particles. The complexation of one trace metal (Cd and Zn at 200 and 390 lg/l respectively) with a green alga Pseudokirchneriella subcapitata in colloid-free algal culture medium and in presence of colloidal humic substances (HS) is presented. The influence of the nature of colloids was also addressed using three ‘‘standard’’ HS: fulvic acid (FA) and, soil (SHA) and peat humic acids (PHA). The chemical speciation model, MINTEQA2, was used to simulate the influence of pH and standardized culture medium on metal association with humic substances. The model was successfully modified to consider the differences in the metal complexation with fulvic (FA) and humic acids (HA). The deviations of concentrations of metals associated with HS between experimental results and model predictions were within a factor of 2. The results of speciation model highlight the influence of the experimental conditions (pH, EDTA) used for alga bioassay on the behavior of Cd and Zn. The computed speciation suggests working with a pH buffered/EDTA-free mixture to avoid undesirable competition effects. The behavior of Cd and Zn in solution is more strongly influenced by HS than by alga. Metal–HS associations depend on metal and humic substance nature and concentration. Cd is complexed to a higher extent than Zn, in particular at larger HS concentration, and the complexation strength is in the order FA < HA. 2003 Elsevier Ltd. All rights reserved. Keywords: Complexation; Humic substance; Trace metal; MINTEQA2; Ultrafiltration; Bioassay; Lead; Cadmium 1. Introduction Knowledge of the chemical forms of metals is essential to understand their interaction with living organisms * Corresponding author. Present address: IARC-Frontier, University of Alaska Fairbanks, 930 Koyukuk Drive, P.O. Box 757335, Fairbanks, AK 99775-7335, USA. Tel.: +1-907-4742642; fax: +1-907-474-2643. E-mail address: celine@iarc.uaf.edu (C. Gueguen). as metal speciation controls their mobility and bioavailability (e.g. Campbell, 1995). Metals in surface water have traditionally been subdivided into two fractions: ‘‘dissolved’’ and ‘‘particulate’’ according to operationally defined limit (usually 0.45 lm) and separated by filtration. The filter passing ‘‘dissolved’’ fraction clearly does not represent the truly dissolved metal ions, but is composed of free metals, metals bound to a variety of ligands, forming molecules of various dimensions and chemical characteristics, which may further be bound to larger entities of colloidal size (Buffle and van Leeuwen, 1992). 0045-6535/$ - see front matter 2003 Elsevier Ltd. All rights reserved. doi:10.1016/S0045-6535(03)00719-7 928 C. Gueguen et al. / Chemosphere 53 (2003) 927–934 Assessing toxicity of contaminated waters with algal bioassays is one of the standard tools in environmental impact assessment. It has however been noticed that at similar metal content bioassays may show a wide range of toxic effects. Evidence exist that the total metal concentration is not a good predictor of bioavailability, toxicity and mobility of the metal (Sunda and Guillard, 1976; Sunda, 1991). The speciation of a metal is expected to greatly affect the availability of trace elements for phytoplankton and other organisms. With regards to their reactivity, metal can be associated with particles (e.g. alga), colloids (e.g. humic substances, HS) and dissolved species (e.g. EDTA). Free metal ions are thought to be the most available and toxic (e.g. Campbell, 1995 and therein references). In natural waters, only a small fraction of dissolved metal may be present as free hydrated cations because of the presence of a large variety of inorganic and organic ligands. Humic substances, which are one of the main constituents of the natural aquatic colloids (Raspor, 1980; Linnik, 2000; Gueguen and Dominik, 2003), play a dominant role in the metal ion distribution and affect the metal bioavailability. The effects of metal speciation on toxic effects are addressed in the companion paper (Koukal et al., this volume). The metal partitioning between particulate, colloidal and truly dissolved fractions was examined in solutions constituted by a trace metal (Me: Cd, Zn), humic substance (HS), alga and standardized culture medium (AAP medium; USEPA, 1994). The presence of EDTA in AAP medium, the effects of pH and the influence of nature and contents of HS on metal complexation were also studied by chemical speciation modeling. The MINTEQA2 model is a speciation model containing a default database on metal–DOM complexation and was extensively used in aqueous systems (e.g., Christensen and Christensen, 1999; Kocaoba and Akcin, 2002). In order to evaluate the role of alga and HS in metal complexation, the distribution coefficients between particulate and truly dissolved, colloidal and truly dissolved, and particulate and total dissolved fractions were calculated as Kp , Kc , Kd respectively. Laboratoryderived Kp , Kc , Kd values have advantages over those determined in natural environments in that individual species can be singled out. Thus there is control over the algal species and the organic matter quality. 2. Materials and methods 2.1. Preparation of solutions Experiments were performed on three different humic substances (HS) types purchased from International Humic Acid Society (IHAS). Their nature, origin and molecular weight are different: (1) fulvic acid (FA) from Suwannee River has smaller molecular weight (103 kDa, Aiken et al., 1985) than (2) humic acid from soil (SHA) and (3) humic acid from peat (PHA) which has the highest molecular weight (104 –105 , Aiken et al., 1985). Detailed composition of HS has been reported in the companion paper (Koukal et al., this volume). All HS stock solutions were daily prepared at 250 mg/l with ultrapure water (Millipore system, >18 MX). They were diluted to a final HS concentrations of 1 and 5 mg HS/l. For each HS contents, one metal (Cd or Zn) was added. Cd and Zn were added to a final concentration of 200 and 390 lg/l respectively. Although these concentrations are not representative of the levels encountered in natural aquatic environments, except of extremely polluted streams, they correspond to the EC50 calculated for the studied green alga in a short-term (1 h) bioassay (Koukal et al., this volume). The EC50 means the effective concentration of metal needed to induce the 50% inhibition of the [14 C] assimilation by algae. The experiments were made in the algal assay procedure medium (AAP) (USEPA, 1994). In addition to nutrients, iron and EDTA used keep iron in solution (Lewin and Chen, 1971; Anderson and Morel, 1982; Hughes and Poole, 1991) are present. The detailed chemical composition of AAP medium is described in Koukal et al. (this volume). Each solution (Me + HS) was stored in the dark at ambient temperature. After 24 h equilibration time, the stock culture of the green alga, Pseudokirchneriella subcapitata (formerly named Selenastrum capricornutum) was directly inoculated in the solution. The culture was harvested at a cell density of 105 cells/ml and then incubated during 1 h at 24 C under 5000–6000 Lux light (USEPA, 1994). All experiments were made in algal medium (AAP medium; USEPA, 1994) at pH ¼ 8.5 0.1 using 1% of CH3 COOH/CH3 COONH4 mixture (2 mmol/l). 2.2. Filtration/ultrafiltration After incubation, the mixture (AAP + Me + HS + alga) was filtered with an acid-washed 1 lm polycarbonate Nuclepore filter to remove the particles (here constituted by algae). The filter was dried in acid-washed plastic boxes and the weight of material retained on filter determined. The filtered solution was further ultrafiltered through a 1 kDa regenerated cellulose cartridge (Prepscale, Millipore) to isolate colloidal from the truly dissolved fraction. The ultrafiltration protocol has been described previously (Gueguen et al., 2002). Briefly, the ultrafiltration cartridge was thoroughly cleaned with 0.5 N superpure HCl, ultrapure water until pH 6 is reached in the permeate and retentate, and 0.1 N superpure NaOH. Finally, the system was flushed with a large volume of Milli-Q water until the permeate and C. Gueguen et al. / Chemosphere 53 (2003) 927–934 retentate were free of noticeable residual organic carbon. Before ultrafiltration, the cartridge was preconditioning with the sample. The applied concentration factor for ultrafiltration process was about 2 for all solutions. Bulk, filtered, colloidal and truly dissolved fractions were collected and acidified to pH < 2 with superpure HNO3 to prevent the metals from adsorbing to the container material or precipitating. They were stored in darkness at 4 C until metal analysis. 2.3. Measurements pH and conductivity were measured before and after equilibration time. The pH after equilibration did not change by more than 0.05 pH-unit and conductivity increased from 340 to 500 lS/cm for all experiments. Concentrations of organic carbon (Corg) were determined by absorbance measurements at 254 nm (Spectronic 1201, Milton Roy Company) immediately after sampling. A calibration curve for the absorbance of fulvic acid, peat and soil humic acid solutions was prepared by diluting the appropriate stock solution to the concentration range encountered in the colloidal and truly dissolved fractions. The samples were mineralized in HNO3 /H2 O2 mixture prior to metal analysis by inductively coupled plasma mass spectrometry (ICPMS) (Agilent HP4500). Rhodium was used as an internal standard for all measurements. The accuracy of the metal determinations was checked on a regular basis using the 1643d standard (National Institute of Standards and Technology). Mass balance of the ultrafiltration process was acceptable for Cd (89 4%, n ¼ 7), Zn (95 5%, n ¼ 12) and Corg (101 4%, n ¼ 19). 929 complex material consisting of many different types of monoprotic acid sites. This is a composite ligand model with a Gaussian affinity distribution (Dobbs et al., 1989; Susetyo et al., 1991; Allison and Perdue, 1994). The electrostatic interactions are not taken into account explicitly. The concentration of the binding sites is normally distributed with respect to their log K values for proton or metal binding. A database available for proton and metal interaction with Suwannee River DOM and their mean log K values is included (i.e. log K ¼ 3:3 and 3.5 for Cd–DOM and Zn–DOM respectively). The composite ligand component DOM represents a complex mixture of ligands without distinction between humic and fulvic fractions. Metal binding to humic substances can occur at two different types of binding sites, type A site (associated with carboxylic groups) and type B (associated with phenolic type group) (Buffle, 1988 and references therein). Despite the binding sites are represented only by one type of site (carboxylic) in MINTEQA2 model, the predictions of metal complexation by DOM can be reasonable (Christensen and Christensen, 1999). 3. Results and discussion Table 1 shows the partitioning of organic carbon between colloidal (>1 kDa) and truly dissolved (<1 kDa) fractions. Although fulvic acids have the molecular weight close to the nominal cut-off of the membrane, organic carbon was nearly totally found in the colloidal fraction (>92%). This suggests a considerable coagulation of fulvic acids in the AAP medium. As expected, humic acids were almost entirely retained in the colloidal fraction. 2.4. Chemical speciation model MINTEQA2 (Allison et al., 1991) is a speciation model extensively used for calculating the inorganic aqueous species. In the version 3.11, it includes a submodel for computing the complexation of various metal cations with dissolved organic matter (DOM) (Dobbs et al., 1989; Allison et al., 1991; Allison and Perdue, 1994; Serkiz et al., 1996). This submodel is based on the work of Dobbs et al. (1989) who considered DOM as a 4. Simulation by the computer speciation model: MINTEQA2 4.1. Influence of pH Complexation of metal with HS liberates protons inducing pH modification in a closed laboratory system. To evaluate the pH impact on metal speciation, a diagram showing the relative proportion of each metallic Table 1 Repartition (%) of organic carbon between colloidal and truly dissolved after ultrafiltration of studied solutions containing AAP and 1 or 5 mg/l of HS FA (river) Colloids Truly dissolved SHA (soil) PHA (peat) 1 mg/l 5 mg/l 1 mg/l 5 mg/l 1 mg/l 5 mg/l 92 8 98 2 95 5 95 5 99 1 95 5 930 C. Gueguen et al. / Chemosphere 53 (2003) 927–934 100 100 HS 1mg/l HS 1mg/l 75 Zn (%) Cd (%) 75 50 50 25 25 0 0 6 7 pH 8 6 9 7 8 100 100 HS 5mg/l HS 5mg/l 75 Zn (%) 75 Cd (%) 9 pH 50 50 25 25 0 0 6 7 8 pH 9 6 7 8 9 pH Fig. 1. Speciation of Cd(II) and Zn(II) in modified AAP (model calculation). (}) Me2þ , (j) Me–HS, (N) MeCO3 , (M) Me(CO3 )2 2 . species in water as a function of pH is developed (Fig. 1). According to the MINTEQA2 calculations, free metal ion is the dominant form at pH < 7 and 1 mg/l HS for both metals. The calculation shows the tendency of CO2 to form complex in solution with metal in the 3 natural pH range (7 < pH < 9). Thus the change of pH in the range from 6 to 9 may strongly influence metal complexation. The use of buffer maintaining the pH at 8.5 appears necessary. Such pH is desirable to simulate conditions typical for lake epilimnion during a high productivity period. Ammonium acetate buffer was chosen for several reasons: it does not disturb significantly organic carbon measurements, it is not toxic for alga at concentration used it does not contain a noticeable amount of metals (<10 ng/l). In addition, our preliminary modeling showed that it did not constitute a significant ligand for studied metals. 4.2. Influence of culture medium AAP The standard culture medium contains high concentration of EDTA (0.8 lM), a strong ligand, and Fe3þ (0.59 lM) that is maintained in solution by EDTA. The model simulation of two Me + HS solutions with standard AAP and modified AAP (without EDTA and Fe3þ ) was performed at pH ¼ 8.5 (Table 2). The model suggests that Me–HS complexation is notably influenced by the presence of EDTA especially for cadmium. The predictions of the effects of metal complexation by HS in normal AAP were lower than in EDTA-free AAP (1.7– 5.6% and 13.2–45.0% for Cd, respectively). HS and EDTA can be therefore in competition for metal complexation. Moreover, the predicted proportion of free ionic Cd2þ would be less important in the presence of EDTA (10%) than in EDTA-free medium (80%). The competition with EDTA has minor influence on formation of Zn–HS complex and on the proportion of Zn2þ . EDTA in a standard AAP medium recommended by USEPA (1994) is necessary in long-term tests to maintain Fe in solution, an important oligoelement for alga. The presence of EDTA however influences the proportion of Me associated with HS and decreases the free metal ion contents (particularly for Cd). Thus, the ‘‘true’’ toxicity of sample may be underestimated using the standard AAP. C. Gueguen et al. / Chemosphere 53 (2003) 927–934 Table 2 Formation of Me–DOM complexes (%) in standard and modified (EDTA-free) culture medium AAP at 1 and 5 mg/l HS (model calculation, pH ¼ 8.5). The experimental data (n ¼ 9) (in parenthesis) was averaged over all HS types Normal AAP EDTA-free AAP 1 mg/l HS 5 mg/l HS 1 mg/l HS 5 mg/l HS Zn2þ Zn–EDTA Zn–DOM Zn(OH)2 Zn(OH)þ 26 16 1 44 10 20 16 23 32 8 31 24 6 (29 5) 40 10 26 (53 12) 39 9 Cd2þ Cd–EDTA Cd–DOM 10 87 2 6 87 6 80 51 13 (25 11) 45 (54 23) Log K (Me–EDTA) ¼ 16.27 and 16.53 for Cd and Zn respectively. Modeling calculations show that culture medium constituents and pH influence Me–HS formation. Consequently, a modified AAP and the use of buffer are recommended to study the Me–HS interactions during the short-term (1-h test) biotests, especially for Cd. It should, however, be noticed that providing sufficient amount of Fe is essential in long-term test, which is not assured without the presence of EDTA. 4.3. Effects of HS complexation: comparison of experimental results and model predictions • Metal contents. The total concentrations of Cd and Zn used in this study were chosen at the EC50 level for the studied alga after 1 h exposure. They were 200 and 390 lg/l for Cd and Zn respectively (Koukal et al., this volume). It can be noticed that these high concentration may not be relevant for natural aquatic environments. Speciation calculation was performed to evaluate the impact of HS on the behavior of each metal at the same metal contents. The increase of Cd concentration from 200 to 390 lg/l did not influence its complexation with HS (data not 931 shown). Thus the differences observed in the experiments were not due to metal concentration effects. • Content of HS. Effects of raising the HS contents from 1 to 5 mg/l on metal sorption, while maintaining a constant metal concentration are illustrated in Fig. 2. As the HS concentration increased, a larger proportion of metals were complexed by the HS. The Me–HS complexation increased by a factor of about 2 for the three studied HS for both test metals (Table 2). At the same time, the metal contents in the truly dissolved fraction decreased. The results obtained by modeling generally underestimated the HS complexed fraction as compared to the experimental data. The deviations of the metal associated with HS between experimental results and model predictions were within a factor of 2. Considering the uncertainties usually associated with thermodynamic data on complexation reactions, the experimental data and model predictions were not unacceptable (Christensen and Christensen, 1999). • Nature of HS. At the same concentration of organic colloids, a larger fraction of Cd was complexed with HA than with FA (Fig. 2). This difference is less pronounced for Zn. The proportion of Zn associated with FA was larger than those of Cd. That can be explained by the abundance of carboxylic functional groups in FA favoring the complexation of type-A metal such as Zn over a type-B metal, Cd. For PHA, especially at the concentration of 5 mg/l, Cd is complexed in a much larger proportion than Zn. This may be explained by preferences of a type-B metal for nitrogen ligands. 4.4. Modification of the MINTEQA2-model In the MINTEQA2-model, there is no distinction between HA and FA. However, the experimental data showed that trace metals were more or less complexed depending on the nature of HS. The model should therefore be modified to take into account these differences. Specific metal binding properties for HS were derived from the literature (Buffle, 1988; Allison and Perdue, 1994; Tipping, 1994) under the assumption that 80 Cd Zn % Me-HS 60 40 20 0 FA SHA PHA FA SHA PHA Fig. 2. Percent of metal associated with FA, SHA and PHA at 1 mg/l HS (black) and 5 mg/l HS (white) in the dissolved fraction, determined with 1 kDa membrane ultrafiltration. 932 C. Gueguen et al. / Chemosphere 53 (2003) 927–934 ments, 9 3% of metal were associated with algal cells. No significant competition between alga and HS were noted for metal sorption. 80 line 1:1 Modeling (% Me-HS) 60 4.6. Environmental implications 2 3 1 As shown above, the association Me–HS depends on the nature and the concentration of HS, as well as on the metal. The distribution coefficients (Kd , Kp and Kc ) for metals associated with alga, colloids (here HS) and present as truly dissolved species (aqua ions, small inorganic and organic complexes) can be calculated as follows: 40 2 1 20 3 2 1 1 3 23 0 0 20 40 60 80 Experiment (% Me-HS) Fig. 3. Experimental results compared with model predictions for () Cd and ( ) Zn associated with 1 FA, 2 SHA, 3 PHA at 1 mg/l (filled) and 5 mg/l (open). Modelling parameters: Ka : 3.3 and 4.82 for FA and HA respectively; site density: 16.6 and 13 meq/g for FA and HA respectively. SHA and PHA have the same complexing capacity and affinity for metals as HA (see legend Fig. 3). Ka and site density of HS are the parameters whose values have a significant impact on the results. The model gave excellent prediction of metal complexation to FA (Fig. 3) but slightly underestimated the complexation with SHA and PHA. On the other hand, the complexation increase due to the changes in HS content was well reflected by model predictions. However, more studies are needed to apply this model to natural aquatic environments where lower metal concentrations are expected. 4.5. Metal associated with alga The type and contents of HS did not influence highly the metal associated with alga (Fig. 4). In all experi- Kd ðl=kgÞ ¼ mass of particulate metal=mass solids mass of total dissolved metal=volume of water Kp ðl=kgÞ ¼ mass of particulate metal=mass solids mass of truly dissolved metal=volume of water Kc ðl=kgÞ ¼ mass of colloidal metal=mass colloids mass of truly dissolved metal=volume of water They characterize the metal affinity for each phase. While the distribution coefficients between particulate and total dissolved fractions (<1.2 lm) have been extensively studied (e.g. Radovanovic and Koelmans, 1998; Gueguen et al., 2000; Paulson and Gendron, 2001), the data on the partitioning between particles and colloids, and colloids and truly dissolved (<1 kDa) are still scarce (Admiraal et al., 1995; Sa~ nudo-Wilhelmy et al., 1996; Wen et al., 1999; Gueguen and Dominik, 2003). The partitioning coefficients calculated from experimental data (Table 3) give some information on the role of HS in metal complexation. For each metal, the values of Kp are larger than those of Kd , which indicates the important role of HS during % Cd associated with algae 25 Cd Zn 20 15 10 5 0 FA SHA PHA FA SHA PHA Fig. 4. Percent of metal associated with alga in presence of FA, SHA and PHA at 1 mg/l (black) and 5 mg/l (white). Except for Cd with FA, the % of metal associated with alga were not significantly different when HS contents increased. C. Gueguen et al. / Chemosphere 53 (2003) 927–934 933 Table 3 Distribution coefficients (l/kg) determined in the studied solutions (modified AAP + alga + HS + Me) [HS] (mg/l Kd (104 l/kg) Kp (104 l/kg) Kc (104 l/kg) Mean 3r Mean Mean 3r Cd + FA Cd + PHA Cd + SHA Zn + FA Zn + PHA Zn + SHA 1 1 1 1 1 1 2.3 3.5 2.4 2.6 2.0 1.7 0.3 0.3 0.2 0.1 0.1 0.3 3.0 5.7 4.0 3.6 2.8 3.0 0.4 0.4 0.3 0.2 0.2 0.5 23.0 47.0 26.0 48.0 54.0 59.0 0.5 0.9 0.2 0.6 0.5 15.0 Cd + FA Cd + PHA Cd + SHA Zn + FA Zn + PHA Zn + SHA 5 5 5 5 5 5 7.2 3.3 4.7 2.7 4.0 1.3 0.3 0.6 0.3 0.1 0.3 0.2 12.0 16.0 14.0 5.1 8.4 4.2 0.5 28.0 0.9 0.2 0.5 0.5 15.0 80.0 41.0 30.0 23.0 44.0 0.4 1.1 0.3 0.2 0.1 0.8 the metal partitioning. The values of Kc are much higher than those of Kp , which means that the complexation capacity of HS (colloids) is greater than that of the alga (particles) (Wen, 1996). The partition coefficients Kd calculated in this study were compared with those found in natural environments during an algal bloom. In our experiments, the average Kd was 3.9 1.9 104 l/kg for Cd and 2.4 0.9104 l/kg for Zn. In a phytoplanktonic bloom, partitioning coefficient Kd of Cd and Zn were 8.3 104 and 7.9 104 l/kg respectively, in the Rhine River (Admiraal et al., 1995) and 0.7–5.1 104 and 0.1–3.8 104 l/kg respectively in the Lake Geneva (Gueguen, 2001). Despite the high contents of trace metals and different matrix used in the lab experiments, a similar partitioning between particle/water was found in the lab and in situ measurements. 5. Conclusion The calculation of chemical speciation modeling performed on MINTEQA2 showed that to study metal complexation in the presence of alga and humic substances (HS), the algal culture medium must be modified to not underestimate the Me–HS formation and that the use of a buffer is needed to avoid the pH fluctuation occurring during the equilibration time, affecting the HS complexation. 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