Kinetics of Heavy Metal Dissociation from Natural ... - ACS Publications

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Kinetics of Heavy Metal Dissociation from Natural Organic Matter: Roles of the Carboxylic and Phenolic Sites Zhenqing Shi,*,†,‡ Pei Wang,†,‡ Lanfang Peng,†,‡ Zhang Lin,†,‡ and Zhi Dang†,‡ †

School of Environment and Energy, South China University of Technology, Guangzhou, Guangdong 510006, People’s Republic of China ‡ The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, South China University of Technology, Guangzhou, Guangdong 510006, People’s Republic of China S Supporting Information *

ABSTRACT: We developed a unifying model for the kinetics of heavy metal dissociation from natural organic matter (NOM) in this study. The kinetics model, integrated with the equilibrium model WHAM 7, specifically considered metal ion reactions with various NOM sites formed by the carboxylic and phenolic sites. The association and dissociation rate coefficients for metal reactions with various NOM sites were constrained by WHAM predicted equilibrium distribution coefficients at specific reaction conditions. We developed the relationship for the dissociation rate coefficients among different binding sites for each metal, which was internally constrained by the metal binding constants. The model had only one fitting parameter, the dissociation rate coefficient for the metal complexes formed with two weak carboxylic sites, and all other parameters were derived from WHAM 7. The kinetic data for metal dissociation from NOM were collected from the literature, and the model was able to reproduce most of relevant data analyzed. The bidentate complexes appeared to be the predominated species controlling metal dissociation under most environmental conditions. The model can help to predict the reactivity and bioavailability of heavy metals under the impact of multiple competing ligands including NOM.

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cation exchange resin,20−28 was used to bind quickly metal ions released from metal−NOM complexes. The kinetic data were usually analyzed by assuming few dissociation sites in NOM with varying dissociation rate coefficients responsible for the observed dissociation kinetics.20,24,25 One major issue for those analyses is the lack of the mechanistic constraint for the metal distribution among NOM sites and the corresponding rate coefficients. One fundamental assumption used in those analysis is that the reassociation of metal ions with NOM was negligible due to fast uptake of metal ions by the competing ligands, but the validity of this assumption was not assessed.29 As a result, large variations of the dissociation rate coefficients were reported in various studies, some of which even cannot be reconciled by the experimental variables or the heterogeneity of NOM sites.30 Therefore, a mechanistic-based approach, which considers various NOM binding sites, varying solution chemistry, and the effect of metal reassociation reactions with NOM, is desired. We have developed a mechanistic-based model for the kinetics of heavy metal adsorption/desorption reactions with soil organic matter (SOM),31−34 by integrating the equilibrium model WHAM.3,35 Our previous results demonstrated that the

INTRODUCTION Natural organic matter (NOM) is probably the most important ligand in the environment that affects the speciation and reactivity of heavy metals. Extensive work has been done on the equilibrium of heavy metal complexation with NOM and a few predictive models have been developed.1−4 Less progress has been made for predicting the kinetics of metal association/ dissociation reactions with NOM.5−10 The release of metal ions from NOM may be slow, and the slow dissociation rates of metal−NOM complexes may limit the bioavailability of metal ions in natural environment.11,12 The quantitative understanding of the kinetics of heavy metal dissociation from various NOM binding sites is essential for accurately predicting the reactivity, bioavailability and transport of heavy metals in the environment.9 NOM contains a variety of heterogeneous sites and the carboxylic and phenolic sites are two of the most important functional groups controlling metal binding.13 Even with the success of the widely used equilibrium models for metal complexation such as WHAM (Windermere Humic Aqueous Model),3,14,15 little is known about the distribution of metal ions among various binding sites of NOM, and, especially, its impact on the rates of metal dissociation from NOM. The majority of the experimental studies on the kinetics of heavy metal dissociation from NOM employed a competing ligand exchange (CLE) method, in which a strong metal complexing ligand, either as a dissolved ligand5−7,16−19 or as a © 2016 American Chemical Society

Received: Revised: Accepted: Published: 10476

April 12, 2016 August 7, 2016 August 31, 2016 August 31, 2016 DOI: 10.1021/acs.est.6b01809 Environ. Sci. Technol. 2016, 50, 10476−10484

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Environmental Science & Technology

reaction can be constrained by the equilibrium constant. Shi et al.31 have recognized the importance of the equilibrium constraint on the reaction rates for the heterogeneous environmental ligands when studying the kinetics of metal desorption from soils, and since then have developed kinetics models based on the mechanistic-based equilibrium model WHAM.32−34 Similar concept has also been applied to some studies on metal kinetic reactions with model humic acids (HA) and fulvic acids (FA)10,37−39 or freshwater NOM.30 By assuming that the Eigen mechanism applies to the metal− NOM complexation reaction, the association rate coefficients could be computed theoretically based on the stability constant of the outer-sphere complex formation and the rate coefficient for water loss from the inner coordination sphere of the metal ion.30,39 It is still not clear how the variations of the equilibrium binding constants affect the association or dissociation rate coefficients because they are internally coupled together with the equilibrium binding constants. By analyzing the literature data, Town et al. (2012) found that the variations of metal stable constants were reflected by the dissociation rate constants whereas the association rate constants are not dependent on the metal occupation in humic acids.10,38 Considering the variations of binding strength of various binding sites in NOM and different techniques to study the kinetics of metal dissociation from NOM, more work is desired to develop the theoretical basis for constraining the reaction rate coefficients based on the mechanistic description of metal ion reactions with various NOM sites. Integration of WHAM into the Kinetics Model. WHAM is a chemical speciation model developed by Tipping and coworkers,3,14,15,40 which is capable of calculating the equilibrium of metal binding to humic substances (S1 section, Supporting Information). WHAM 7,15 the latest version of WHAM, assumes a discrete distribution of binding sites of humic substances, and there are two types of sites, A sites and B sites, that correspond to the carboxylic and phenolic sites, respectively. Metal ions can form multiple mono-, bi-, and tridentate complexes with A and/or B sites. In our previous modeling studies on the kinetics of metal adsorption/desorption on SOM,32−34 the adsorption and desorption rate coefficients for the mono-, bi-, and tridentate sites were constrained by the WHAM predicted equilibrium distribution coefficients Kpi. A similar concept can be applied to the kinetics of metal association and dissociation reactions with NOM:

mono-, bi-, and tridentate metal complexes may have different reaction rates.32,33 The kinetics model, in principle, should be able to account for the effects of solution chemistry and the heterogeneity of NOM sites on metal dissociation kinetics in the CLE reactions. However, the carboxylic and phenolic sites may form various bidentate and tridentate sites with different binding strength. The metal binding constants for the carboxylic and phenolic sites differ significantly and are interrelated through the proton binding constants of both sites.15,36 Because the reaction rate coefficients are constrained by the equilibrium distribution coefficients during the kinetic reactions,31 the carboxylic and phenolic sites may have different association/dissociation rate coefficients. How various mono-, bi-, and tridentate sites affect the kinetics of metal dissociation from NOM has not been quantitatively studied. In this study, we proposed a unifying kinetics model for heavy metal dissociation from NOM based on metal reactions with various NOM binding sites formed by the carboxylic and phenolic sites, as described by the WHAM 7 model.15 We developed the relationship for the dissociation rate coefficients among different NOM binding sites, which was internally constrained by the metal binding constants of the NOM sites. We reviewed the kinetic data published during last 3 decades, and selected and analyzed some most relevant kinetic data. We assessed how the distribution of metals among NOM sites affected the kinetic behavior of metals in the environment. We, for the first time, quantitatively elucidated the roles of both carboxylic and phenolic sites on controlling the dissociation rates of metal−NOM complexes, and assessed the effect of the metal reassociation reaction in the CLE reaction for different heavy metals.

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THEORETICAL BACKGROUND Competing Ligand Exchange Reactions for Metal− NOM Complexes. The dissociation of heavy metal ions (Me) from NOM can be described as kdi

MeLi ⇄ Me + Li kai

(1)

where MeLi is metal ions associated with the ith binding site of NOM, Li is the ith binding site, and kai (s−1) and kdi (s−1) are the association and dissociation rate coefficients for the ith binding site, respectively. When a strong competing ligand, Lc, is introduced, it drives the reaction toward forming the complex with Lc, MeLc, with a formation rate coefficient k (s−1): k

Me + Lc → MeLc

(2)

Generally, the experiments were conducted with a large excess of Lc and the back reaction of eq 2 was minimal. The CLE reaction following eqs 1 and 2 is known as the disjunctive pathway, in which the competing ligands do not directly react with the metal−NOM complexes. Another reaction pathway, adjunctive pathway, may exist, in which the competing ligands form intermediate complexes with the metal−NOM complexes and the dissociation of the intermediate complexes is the ratelimiting step.6 The kinetics of the disjunctive pathway provides valuable information on the stability of metal−NOM complexes and thus is more environmental relevant, because the adjunctive pathway is highly dependent on the competing ligands selected for the specific experiments.6 Thermodynamic Equilibrium Constraint of Reaction Rates. The forward and backward reaction rates for a certain

kai /kdi = K pi(Cpi , pH, I, ...) = Cpi /C ion

(3)

in which Kpi is the ratio of metal concentrations in the specific site of NOM, Cpi (M), to the ionic metal concentrations in solutions, Cion (M), and is a function of Cpi and the reaction chemistry conditions at the specific reaction time. A detailed description on integrating WHAM into the kinetics model is presented in the Supporting Information (S2 section). Note that eq 3 has general applicability to various kinetic reactions and does not require the kinetic reaction to be close to the equilibrium. It indicates that the reaction is tending toward the equilibrium dictated by the local conditions at each reaction time along the reaction path. 10477

DOI: 10.1021/acs.est.6b01809 Environ. Sci. Technol. 2016, 50, 10476−10484

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MATERIALS AND METHODS Experimental Data. The largest volume of CLE kinetic studies was conducted by Chakrabarti and co-workers,20−28 in which metal−NOM solution samples were mixed with 1% Chelex 100 resin and the total dissolved metal concentrations were continuously measured to study the kinetics of metal dissociation from NOM. The resin had a wet capacity of 0.61 mequiv g−1.24 Different from those earlier CLE kinetic studies that employed dissolved competing ligands,5−7,16−19 the Chelex resin particles did not adsorb metal−DOM complexes,20 which minimized the chance of the direct attack of the resin particles to metal−NOM complexes. Kinetic studies also suggested that the disjunctive pathway may predominate in the Chelex resin experiments.24 The data include experiments with either model FA and HA solutions or natural water samples from different origins. The ionic strength of the water samples was in the range of 3 × 10−4 − 2.4 × 10−2 M. We excluded a few data sets from experiments with very low ionic strength for the model FA/HA solutions. A description of the literature data was presented in the Supporting Information (S3 section). Based on the concentration of the Chelex resin and its wet capacity, the total binding sites of the Chelex resin were much higher than the total amount of metals in all water samples. All experimental data were digitized from the published literatures using the OriginPro 9 program. Modeling Methods. The kinetics of metal association/ dissociation reactions with NOM may be complicated by diffusion process, outer-sphere complexation and inner-sphere complexation.37,38 Here we mainly focused on the inner-sphere complexation reactions that may occur during the CLE reactions. The total dissolved metal concentrations Cw (M) equal to the sum of the concentrations of metal−NOM complexes CMeLi (M) and the ionic metal (Cion) in the solution that include all metal ions not complexed by NOM: Cw =

∑ C MeL

i

+ C ion

sites, respectively. All above binding constants are dimensionless. The bidentate complexes can be formed either through two A sites (denoted as AA) or one A and another B sites (denoted as AB), and each group can be further divided into three subgroups according to their binding strength, denoted as AAweak, AA-medium, AA-strong, AB-weak, AB-medium, and ABstrong metal complexes. The metal binding constants of these six groups of bidentate sites can be derived through the monodentate sites:3 log KAA = 2log KMA + xΔLK 2

log KAB = log KMA + log KMB + xΔLK 2

dt

log KAAB = 2log KMA + log KMB + yΔLK 2 (y = 0, 1.5, 3)

=

∑ kdiC MeL

i

(4)

i

−

∑ kaiCion − kCion

−

∑ kdiK piCion − kCion

log K i = log kac, i − log kdc, i

(11)

We assume that the metal binding constant has an equal effect on both of association or dissociation rate constants, which results in the following: log kdc, i − log kdc, j = 1/2(log Kj − log K i)

(12)

and log kac, i − log kac, j = 1/2(log K i − log Kj)

(6)

(13)

where eqs 12 and 13 set up the relationships for the intrinsic association or dissociation rate constants between two specific binding sites. It indicates that sites with larger metal binding constants have larger intrinsic association rate constants and smaller dissociation rate constants. Because NOM particles were usually charged and the free site concentrations changed with reaction time, we used WHAM 7 calculated equilibrium distribution coefficients to constrain the association and dissociation rate coefficients during the kinetic experiments. Consistent with our previous modeling approach,32,33 during the dissociation process the dissociation rate coefficients for each group of sites remained constant and the association rate coefficients, that virtually equal to the product of the intrinsic association rate constants

In WHAM 7, metal ions can form inner-sphere complexes through mono-, bi-, and tridentate bindings to FA and HA and outer-sphere complexes through the electrostatic attractions. The monodentate complexes can be divided into two groups, complexed with one of the four A sites or the four B sites. WHAM 7 fixed the metal binding constants of all four A sites, KMA, at the same value, and that of all four B sites, KMB, at the same value, respectively. The relationship between KMA and KMB can be described as15 log KMB = log KMA × pKB/pKA

(10)

where y = 0, 1.5, 3 corresponds to the weak, medium and strong tridentate complexes, respectively. Above formations result in total 11 groups of distinct sites for metal complexation reactions. In WHAM 7, with the known values of KMA, pKA, pKB and ΔLK2, the metal binding constants of any specific binding sites can be calculated based on eqs 7−10. For any specific site i, the intrinsic association and dissociation rate constants, kac,i (s−1) and kdc,i (s−1), are constrained by the metal binding constants described above, here denoted as Ki:

(5)

∑ kdiC MeL

(x = 0, 1, 2)

where x = 0, 1, 2 corresponds to the weak, medium, and strong bidentate complexes, respectively, and ΔLK2 is a “spread factor” for the metal binding constants used in WHAM, which accounts for the tendency of the metal to interact with N and S atoms in ligands. All tridentate complexes are formed by two A and one B sites (denoted as AAB) and, similar to the bidentate sites, can be divided into three groups, denoted as AAB-weak, AAB-medium and AAB-strong. The metal binding constants of the tridentate complexes can be calculated as

= −kdiC MeLi + kaiC ion = −kdiC MeLi + kdiK piC ion

dC ion = dt

(8)

(9)

The rates of metal dissociation from the specific NOM binding site and the change of the ionic metal concentrations can be described as dC MeLi

(x = 0, 1, 2)

(7)

where pKA and pKB are the average pK values, the negative logarithms of the proton dissociation constants, of the A and B 10478


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Figure 1. Distribution of Cu on FA binding sites predicted by WHAM 7. (a) Monodentate complexes, (b) bidentate complexes, (c) tridentate complexes, and (d−i) various bidentate complexes formed by A and B sites. Refer to the text for the definition of each bidentate site. The background electrolyte was set as 0.01 M NaNO3 and 0.001 M Ca(NO3)2.

and then calculated Kpi at each time by linear interpolation. For experimental data that demonstrated typical biphasic curves, we separated the kinetic curves into two sections and then calculated Kpi at each time for each section. An implicit finite difference numerical method was used to solve the model equations (eqs 4−6). Each data set was tabulated in a Microsoft Excel spreadsheet and, for each observation time, the square of the difference between measured and model calculated dissolved metal concentrations was calculated. The sum of the squares for each data set was calculated to obtain the total squared error. The SOLVER program in EXCEL was used to obtain the model fitting parameter, kd,AA‑W, by minimizing the total squared error for each experiment data set of each metal.

and the free ligand site concentrations, changed with time as Kpi changed with reaction time (eq 3). Therefore, we adapted the relationship described in eq 12 to constrain the dissociation rate coefficients: log kdi − log kdj = 1/2(log Kj − log K i)

(14)

As a result of eq 3 with WHAM predicted Kpi, the association rate coefficients accounted for the effects of reaction chemistry and electrostatic interactions during the kinetic reactions. As predicted by WHAM 7, the bidentate complexes predominated in most environmental conditions as shown later. Therefore, we chose the kdi value for the bidentate complexes formed with two weak carboxylic sites (AA-weak), kd,AA‑W, as the model fitting parameter, and the kdi values for all other complexes can be calculated from kd,AA‑W according to eq 14 with all other parameters derived from WHAM 7 (Table S1, Supporting Information). Under the experimental conditions analyzed in this study, the contribution of the outer-sphere complexes was negligible. For WHAM 7 calculations, the major input parameters include the solution parameters and the FA or HA concentrations. A detailed description of the WHAM 7 input parameters was presented in the Supporting Information (S1 section). On the basis of the WHAM 7 output, we calculated the equilibrium distribution coefficients Kpi for all 11 groups of mono-, bi-, and tridentate metal complexes. In principle, Kpi can be calculated by WHAM 7 at each time. However, it was not practical when multiple heavy metals were present because the exact chemistry conditions at each time were not available during the numerical calculations. To simplify the calculations, we calculated Kpi at the start and the end of the experiments

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RESULTS AND DISCUSSION Metal Binding to Various NOM Sites. The initial distribution of heavy metals among NOM sites is key information for predicting metal dissociation kinetics. Different from previous studies to obtain this information with model fitting, we employed WHAM 7 to calculate heavy metal binding to various NOM sites for all water samples before the CLE reactions. Here we showed the results in typical conditions of natural water using the contour plots. For all five metals (Cu, Cd, Ni, Pb, and Zn), the bidentate complexes predominated in most conditions (Figure 1, Figures S1−S4, Supporting Information). At low pH the contribution of monodentate may not be negligible, and, at high pH, the tridentate complexes may play an important role. The roles of both carboxylic and phenolic sites on controlling metal binding can be assessed based on the distribution of

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Figure 2. Kinetics of (a) Cu, (b) Cd, (c) and (d) Ni, (e) Pb, and (f) Zn dissociation from NOM in natural water or model FA samples. The experimental data are from Chakrabarti et al. (1994),20 Mandal et al. (2000),22 Mandal et al. (2002),23 Sekaly et al. (2003),24 Fasfous et al. (2004),25 and Yacipi et al. (2008).28 The major experimental variables were shown in the legend. For clarity, only 50% of data points are shown in plots a, b, e, and f.

ments,43 highlighting the importance of both the carboxylic and phenolic sites. Analysis of Metal Dissociation Kinetics. The kinetics of heavy metal dissociation from NOM samples, as shown by the percent of metal remaining in solutions (including both metal complexed by NOM and ionic forms of metal), differed significantly depending on the metals, pH, competing cations, and NOM samples (Figure 2). Additional results are shown in the Supporting Information (Figures S5−S7). For natural water samples, generally a gradual slow Cu decrease of dissolved Cu in solutions was observed (Figures 2a). For most of Cd, Ni, Pb, and Zn samples, however, a typical rapid decline of dissolved metals in solutions in the first a few minutes was observed and, after that, a similar gradual slow metal release followed (Figure 2b,c,e,f). For the model FA and HA solutions, it is interesting to observe that the release of Ni was extremely slow under low cation competition conditions (Figure 2d and Figure S6, Supporting Information). The difference of the kinetic behavior has been attributed to the properties of cations such as the ligand field stabilization energy and dehydration rates.24,38

metals among the six groups of bidentate sites. For Cu, all six sites may bind significant amount of Cu depending on the pH and Cu concentrations in NOM (Figure 1d−i). Both the AAmedium and AB-medium sites appeared to play the most important roles whereas the AA-weak sites bound the least amount of Cu. This Cu binding behavior can be attributed to the large values of both KMA and ΔLK2. The importance of both carboxylic and phenolic sites for metal binding was also observed for Cd, Ni, Pb, and Zn, with the relative importance of each bidentate site differing among different metals due to the different KMA and ΔLK2 values (Figures S1−S4, Table S1, Supporting Information). Generally, little has been done experimentally on verifying the metal distributions among NOM sites at the environmental relevant conditions, although spectroscopic techniques have been used to study the mechanisms of metal reactions with humic substances.41−43 At high metal concentrations, the formation of bidentate complexes of Pb with both the carboxylic and phenolic sites of humic substances has been verified with the X-ray absorption spectroscopy measure10480


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controlling metal dissociation rates. The variations of kd values among sites with varying binding strength are consistent with the concept by Town et al. (2012),38 in which the distribution in metal stability constant is reflected in that of the dissociation rate constant. Roles of Metal Reassociation, Competing Ligands, and NOM Binding Sites. Using the model developed in this study, we evaluated how reassociation reactions affected the overall metal release from NOM samples. For Cu, the reassociation reaction significantly inhibited the overall Cu release from NOM within a range of kd,AA‑W values that may provide reasonable model fits to the experimental data (Figure 4a). When the kd,AA‑W value was unrealistically low that cannot

Metal speciation calculations with WHAM 7 for the original water samples showed that the majority of Cu (93%−99%) was complexed by NOM but, for Cd, Ni, Pb, and Zn, a significant amount of metals was present as the ionic forms for some samples. The uptake of metal ions by the Chelex resin was rapid,20 which may explain the observed quick decline of metals in solutions at the beginning of the experiments for some samples (Figure 2b,c,e,f). After that, the overall rates of slow metal release from NOM were controlled by the combination of both eqs 1 and 2. Generally, the model can describe the kinetics of metal release from various NOM samples in a wide range of experimental conditions (Figure 2). More deviations between the model calculations and data were observed at the beginning of the experiments, which suggests that various ionic metals may have different rates of the uptake by the Chelex resin. All the variations of reaction chemistry were handled by WHAM 7, including metal distribution among various NOM sites in the original samples (Figure 1, Figures S1−S4, Supporting Information) and the equilibrium distribution coefficient for each site. The dissociation rate coefficients obtained in this study are presented in Figure 3 for natural water samples and in Figure

Figure 4. Model simulations of the kinetics of Cu and Ni dissociation from NOM samples: (a) model simulations for Cu with varying kd,AA‑W (k = 0.033 s−1); (b) model simulations for Ni with varying kd,AA‑W (k = 0.04 s−1). Symbols are experimental data. Solid lines are model calculations and dashed lines are model calculations without considering the reassociation reactions. The experimental data and conditions for calculations are from Sekaly et al. (2003)24 for Cu and from Mandal et al. (2002)23 for Ni.

Figure 3. Metal dissociation rate coefficients of various NOM binding sites, kd (s−1), for five heavy metals in the natural water samples. (a) Monodentate complexes, (b) bidentate complexes, (c) tridentate complexes, and (d−i) various bidentate complexes formed by A and B sites. Refer to the text for the definition of each bidentate site.

provide a reasonable model fit, the reassociation reaction was insignificant due to the low reassociation rate coefficients (eq 3). Therefore, for Cu the reassociation reactions can effectively compete with the binding by the Chelex resin during the CLE reactions. In comparison, the reassociation reactions had little impact on Ni release and the variations of kd,AA‑W values dominated the overall reaction rates (Figure 4b), which can be explained by both lower values of KMA and kd,AA‑W for Ni than that for Cu. Similarly, because both Cd and Zn had low KMA and kd,AA‑W values, the reassociation reactions were insignificant in most conditions. For Pb, which has a similar KMA to Cu but smaller kd,AA‑W values, the impact of the reassociation reactions was moderate compared with Cu and Ni (Figure S9, Supporting Information).

S8 (Supporting Information) for model FA/HA solutions. For each binding site, the dissociation rate coefficients varied among samples for each metal. For the natural water samples, the dissociation rate coefficients of different binding sites for each metal spread a wide range from very low values (10−3 s−1) for those abundant but weak bidentate and monodentate complexes (Figure 3). For the model FA/HA solutions, the kd values of Ni were much smaller when lack of the cation competition (Figure S8, Supporting Information) than those of natural water samples. This highlights the importance of the competing cations on 10481


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Environmental Science & Technology We further assessed the significance of the formation rate coefficient, k, for metal ion complexation with the Chelex resin. The k values may be affected by the concentrations of the Chelex resin and reaction conditions.28,29 It was reported that the k values for typical heavy metals were in the order of magnitude of 10−2 s−1 when the concentration of the Chelex 100 resin was 1%,20,24,25 but little was known on how k changed with pH and metal concentrations. Our model analysis showed that the overall CLE reaction rates for Cu were sensitive to k values (Figure S10a, Supporting Information). This indicates that both eqs 1 and 2 had comparable reactions rates for Cu and affected the overall CLE reaction rates, contrary to the assumption used by previous CLE studies. In comparison, the variations of k values had little impact on the overall CLE reaction rates for Ni (Figure S10b, Supporting Information). This suggests that the dissociation of Ni from NOM (eq 1) was the rate-limiting step for the CLE reactions. Although metal ions may distribute among all 11 groups of specific binding sites, only a few of them, mostly weak bidentate sites and monodentate sites, were kinetically labile under specific experimental conditions (Figures 1 and 3). For Cu, it was the weak bidentate sites that were responsible for Cu dissociation observed under those experimental conditions, and the tridentate sites and strong AB bidentate sites were virtually inert due to the low kd values and large ka values arising from the large equilibrium distribution coefficients. For Cd, Ni, and Zn, because reassociation reactions were minimal in most conditions, the lability of metals in various sites can be assessed based on the dissociation rate coefficients. Because both tridentate and strong AB bidentate complexes only accounted for a small percent of total metal complexes, most metal−NOM complexes formed with the carboxylic or/and phenolic sites could be kinetically labile in typical environmental conditions. Model Assessment and Implications. The accuracy of WHAM 7 predictions is essential for the performance of the kinetics model. The ability of WHAM 7 to predict the equilibrium of metal partitioning between NOM and water has been extensively studied.44−48 WHAM 7 predicted predominated bidentate complex formation in most conditions. It appears the model can reproduce the observed metal dissociation kinetics appropriately under a wide range of environmental conditions, supporting the validity of the WHAM 7 based kinetics model. Our current model only considered the overall kinetic rates of metal reactions with NOM when the formation of outer-sphere complexes was minimal, whereas in natural environment the reactions may involve multiple processes/steps, such as ion diffusion, formation of outer-sphere complexes and then inner-sphere complexes, etc.,10 which may be affected by the reaction conditions and the types of cations. The uncertainties of the dissociation rate coefficients obtained in this study were not assessed. For Cu, the previously reported kd values in the Chelex resin CLE studies varied in the order of magnitude of 10−4−10−5 s−1,24,25 which Warnken et al.30 have pointed out to be unrealistically too low for freshwater samples. Our study has demonstrated that the kd values of Cu may spread to a wide range for different sites but most bidentate sites had kd values larger than 10−4 s−1 (Figure 3). The spread of kd values reflected the varying binding strength of NOM sites and was internally constrained by the metal binding constants, which is a fundamental improvement from the previous studies that obtained variable kd values purely from the model fitting.20−27 For each metal, the variations of kd

values among different samples may arise from the difference of the chemical properties of NOM samples, which was not characterized in original studies. A accurate determination of the kd values will require further work including accurate determination of the k values, the Kpi values during the kinetic reactions, and the “active” portion of NOM.48 A few chemical speciation models, such as NICA-Nonnan,49 WHAM14 and the Stockholm Humic Model,4 have shown success for simulating metal equilibrium binding to NOM, but less is known about how metal ions distribute to various NOM binding sites, which might differ for model predictions among these speciation model.4,40,43 It may make little practical difference in term of predicting equilibrium distribution within certain environmental conditions, but may significantly affect the prediction of the kinetic behavior of metal ions because binding to various sites may result in different metal dissociation rates. To predict more accurately the dynamic behavior of metals in the environment, mechanistic understanding of metal binding to various NOM sites and its kinetic effect at the molecular level needs to be further studied. Our model has significance in predicting the bioavailability and toxicity of metal ions in the presence of NOM because faster metal dissociation from NOM may result in more metal bioavailability.50 The large variations of kd values among NOM binding sites suggest that the rates of supply of metal ions from NOM sites differ for a few order of magnitude, and the correspondent time scales of the dissociation reactions for the bidentate sites range from a few seconds to several days. This information should be carefully considered when predicting the metal bioavailability in natural environment when NOM is present, and our model provides a quantitative tool in this aspect.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.6b01809. (1) Description of WHAM and model calculations, (2) integrating WHAM into CLE kinetics model, (3) description of the literature data, (4) calculations of kd values for each site, and (5) additional figures (PDF)

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AUTHOR INFORMATION

Corresponding Author

*Z. Shi. email: [email protected], phone: 86-20-39380503, fax: 86-20-39380508. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank Dr. Dominic Di Toro for his advice and Dr. Stephen Lofts for providing the customized version of WHAM 7. Funding was provided by the National Science Foundation of China (Project number: 41573090) and the Thousand Talent Program for Young Outstanding Scientists of China.

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REFERENCES

(1) Warnken, K. W.; Lawlor, A. J.; Lofts, S.; Tipping, E.; Davison, W.; Zhang, H. In situ speciation measurements of trace metals in headwater streams. Environ. Sci. Technol. 2009, 43, 7230−7236. (2) Benedetti, M. F.; Milne, C. J.; Kinniburgh, D. G.; van Riemsdijk, W. H.; Koopal, L. K. Metal-ion binding to humic substances -

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