Homo-Conjugation of Low Molecular Weight Organic Acids Competes

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Environmental Processes

Homo-Conjugation of Low Molecular Weight Organic Acids Competes with Their Complexation with Cu(II) Jing Zhao, Gang Chu, Bo Pan, Yuwei Zhou, Min Wu, Yang Liu, Wenyan Duan, Di Lang, Qing Zhao, and Baoshan Xing Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b05965 • Publication Date (Web): 17 Apr 2018 Downloaded from http://pubs.acs.org on April 18, 2018

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Environmental Science & Technology

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Homo-Conjugation of Low Molecular Weight Organic Acids

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Competes with Their Complexation with Cu(II)

3 4

Jing Zhao†,§, Gang Chu†, Bo Pan*†, Yuwei Zhou†, Min Wu†, Yang Liu†, Wenyan Duan†, Di

5

Lang†, Qing Zhao*‡, Baoshan Xing§

6 7

†

Faculty of Environmental Science & Engineering, Kunming University of Science & Technology,

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Kunming, Yunnan 650500, China ‡

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§

Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China

Stockbridge School of Agriculture, University of Massachusetts, Amherst, MA 01003, USA

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* Corresponding author: Dr. Pan, e-mail: [email protected];

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Dr. Zhao, e-mail: [email protected]

14 15

ABSTRACT

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Dissolved organic matter (DOM) controls the bioavailability and toxicity of heavy metals in aquatic

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environments. The observation of decreased conditional binding constants with increasing DOM

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concentration is not well documented, which may result in significant uncertainties in heavy metal

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behavior modeling and risk assessment. We used eight low molecular weight organic acids (LMOC)

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with representative structures to simulate DOM molecules. The interactions between LMOC

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molecules resulted in the decreased Cu(II)-LMOC binding with increasing LMOC concentrations,

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but higher pH values than theoretical calculation after mixing LMOC solutions of different pHs. We

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thus proposed homo-conjugation between LMOC molecules through negative charge-assisted

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H-bond ((-)CAHB). A mathematic model was developed to describe Cu(II)-LMOC complexation 1

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(KC) and LMOC homo-conjugation (KLHL). The increased competition of LMOC homo-conjugation

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over Cu(II)-LMOC complexation, as suggested by the increased ratios of KLHL/KC, resulted in the

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apparently decreased Cu(II)-LMOC binding with the increased LMOC concentration. Similar

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concentration-dependent binding was also observed for DOM. With the identified

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homo-conjugation between DOM molecules, some of the literature data with

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concentration-dependent behavior may be re-evaluated. This is the first work that quantitatively

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identified homo-conjugation among organic molecules. Both the modeling concepts and results

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provide useful information in investigating the environmental roles of DOM in mediating metal

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bioavailability and transport.

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Abstract Art

36

Cu 10

log KC (g/L)-1

(-)CAHB

+

Cu

8 6

4 2

AA CA OA TT BA PA GA TA 1 10 100 1000 LMOCs concentration (mg/L)

37 38

INTRODUCTION

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Dissolved organic matter (DOM) is widely present in the environment and interacts with

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various contaminants. The complexation between DOM and heavy metals has attracted a great deal

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of research attention, because this process alters heavy metal availability and their risks.1 Taking

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Cu(II) as an example, over 90% Cu(II) was complexed with DOM in aquatic media,2 suggesting the

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dominant role of DOM in Cu(II) speciation.3, 4 DOM contains abundant functional groups such as

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carboxyl (-COOH), phenolic hydroxyl (-OH), amino (-NH2) and thiol (-SH) groups,5-7 among

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which -COOH and -OH groups made a major contribution to Cu(II) complexation in the 2


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environment.8, 9 Two types of complexation between Cu(II) and DOM were generally discussed in

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previous studies, outer- and inner-sphere complexes.10-12 The inner-sphere complexation is strong,

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comparable to a covalent bond with electron donor-acceptor interaction. The outer-sphere

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complexation is relatively weak, similar to electrostatic interaction. The inner- and outer-sphere

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complexations occur simultaneously during Cu(II)-DOM interactions.

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Various models have been proposed to describe heavy metal-DOM complexation. Early

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empirical models, such as Quasiparticle model (including Buffle, Polyelectrolyte, and Scatchard

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Models) and Random structure models (discrete and continuous models) were proposed to calculate

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heavy metal-DOM conditional binding constants in specific water chemistry conditions.13-15

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Although these models, especially the widely used Scatchard model, have been shown as useful

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tools in describing heavy metal behavior and speciation,16 they are regression tools for the obtained

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binding curves and metal-DOM binding mechanisms could not be revealed based on this model.

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Geochemical models, such as MINTEQA2, biotic ligand (BLM) and Windermere humic aqueous

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model (WHAM) 17, 18 are used to estimate heavy metal behavior. Because of the important role

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DOM played in heavy metal behavior and risks, these models have incorporated DOM as an

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individual phase. However, these models generally applied a very simple description of heavy

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metal-DOM conditional binding constants. They either took a specific value (such as BLM), or

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simply correlated the conditional binding constant to a certain functional group (such as

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MINTEQA2 as discussed by Dudal & Gerard3). A very important step forward is the proposed

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Model VI and non-ideal competitive adsorption (NICA)-Donnan Model. Although the role of

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protons was not addressed in these models,19 they considered ion competition on the heterogeneous

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sites of DOM.19, 20 Tipping et al. then improved the WHAM to Model VII to predict the

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competitions between metals and H+ with DOM. 21

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Previous studies have suggested that DOM molecules could interact with each other and thus

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aggregate. DOM aggregates play important roles in their colloidal behavior 22, soil functions 23, the

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fate of contaminant (i.e. organic pollutants,24 heavy metal 25-27 and nanoparticles 28, 29) in soil or 3



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aquatic environments. The inter- and intramolecular interactions of DOM molecules could not only

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change their mobility and property, but also alter their interactions with pollutants.30 However, how

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the negatively charged DOM molecules interact with each other, and how the intermolecular

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interactions control heavy metal-DOM interactions are seldom investigated. Conditional binding

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constants independent of DOM concentration are used in all the current models to predict heavy

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metal behavior and risk.31

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Recent investigations suggested strong interactions between negatively charged adsorbates and

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adsorbents. This interaction was facilitated by the negative charge-assisted H-bond ((-)CAHB),32

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which is a subset of the Low-Barrier H-Bonds (LBHB),33 or salt bridges similar to a cation bridge.34

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(-)CAHB is much stronger than ordinary H-bond with considerable covalent character. Based on the

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theory of (-)CAHB, the closer the pKa of the adsorbates and the pHzpc of the adsorbents, the stronger

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the (-)CAHB interaction. We thus hypothesize that homo-conjugation of DOM promoted by

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(-)CAHB competes with Cu(II) for DOM-Cu(II) binding and results in the apparently decreased

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DOM-Cu(II) binding with increasing DOM concentration. Because of the heterogeneous

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characteristics of DOM, the simultaneous presence of various functional groups with different pKas

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will make the system very complicated for any mechanistic analysis. We therefore used a series of

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model low molecular weight organic acids (LMOCs) to investigate their interactions with Cu(II). It

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was reported that carboxyl and phenolic groups primarily bind with Cu(II).35 We thus selected

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chemicals with these functional groups.

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MATERIALS AND METHODS

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Materials and reagents. Four LMOCs without benzene rings, namely, acetic acid (AA),

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oxalic acid (OA), citric acid (CA), and tartaric acid (TT), as well as four LMOCs with benzene

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rings, namely, benzoic acid (BA), phthalic acid (PA), gallic acid (GA) and tannic acid (TA) were all

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obtained from Jicang Company and with purities ≥ 99.8 %. A humic acid (HA) was extracted from

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a sediment collected from Dianchi Lake (Yunnan, China). Briefly, the collected sediment sample

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was freeze-dried, ground, and sieved through a 2-mm sieve. Plant residues were picked out 4


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manually. Mixed solution of 0.1 M NaOH and 0.1 M Na4P2O7 was mixed with the soil particles

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(50:1, v:w) to extract HA. The mixture was shaken at room temperature, after 12 h of equilibration,

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the mixture was centrifuged at 1000 g for 15 min and the supernatant was collected for acidification

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(pH= 1) with HCl to obtain the HA fraction. The HA was freeze-dried, ground gently, and stored

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until use for characterization and analysis. The selected physicochemical properties of the model

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chemicals are given in Table S1, and the elemental compositions and functional groups of HA were

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presented in Table S2 and Figure S1.

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Cu(II) - LMOC binding. All the model chemicals and HA were separately dissolved in

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background solution (0.01 M NaNO3) as stock solutions (1 g/L). These stock solutions were diluted

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in 100 mL vials to 6 different concentrations spanning in the range of 1 - 100 mg/L. Cu(II) solution

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(as 1 g/L Cu(NO3)2) was added drop by drop through a micro automatic injection system with a

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5-min interval and continuous stirring to ensure Cu(II)-LMOC binding equilibrium. The weight and

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pH of the solution were continuously monitored. The overall Cu(II) concentration was calculated

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based on the solution weight change. Free Cu(II) concentrations were recorded on a Cu(II) ion

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selective electrode (ISE). The overall Cu(II) concentration was in the range of 10-6 to 10-4 mol/L. It

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should be noted that other inorganic Cu species, such as CuHCO3+ and CuCO3-, could not be

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measured by ISE, and thus the difference between added and measured free Cu(II) was not the

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amount of Cu-LMOC complex. The software WHAM was applied to calculate Cu species

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(representative results are listed in Table S3), and the LMOC-bound Cu was calculated after

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excluding the inorganic Cu species.

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pH change of the mixed solutions. The stock solutions of the LMOCs were diluted to 6

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concentrations in the range of 1 - 100 mg/L. Each sample was separated into two identical vials and

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the pH values were adjusted to 4 and 6, respectively. These two identical samples with different

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pHs were then mixed. The final pH was calculated based on the initial pHs and the exact volume of

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each sample through the equation of pH calculated = -log

10− pH1 ⋅ V1 +10− pH 2 ⋅ V2 . At the same time, the V1 +V2 5



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final pH was measured using a pH electrode. The pH difference between the calculated and

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measured values provides important insights into inter-molecular interactions in addition to H+

125

dilution.

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Density functional theory computation. In this study, density functional theory (DFT)

127

computation was applied to calculate the optimized geometry, vibrational frequencies, and

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single-point energy of the different types of hydrogen bonding at B3LYP/6-31 ++G (d, p) level.32, 36

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All the calculations were performed using Gaussian 09. The interaction energies were calculated

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using the following equation:

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Eint = E A− B − E A − EB

(1)

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where Eint is the interaction energies of the calculated system. EA-B is the binding energy of the

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whole system, including Cu-LMOC complexes and the homo-conjugation of LMOCs. EA and EB

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are the individual energies of Cu(II) and LMOCs, respectively.

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RESULTS AND DISCUSSION

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The binding between Cu(II) and LMOCs. The binding curves of Cu(II) to LMOCs are

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presented in Figure 1. The complexed Cu(II) concentrations were normalized by LMOC

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concentrations. Formation Equation is widely used to fit the complexation data,37, 38 although it is

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an empirical formula and does not provide mechanistic description of the complexation. We

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provided the fitting results using the Formation Equation as a reference for the readers (Table S3).

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Before the development of a proper model to describe these binding curves, the possible binding

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mechanism should be discussed first. It is important to notice that Cu(II) binding decreased with the

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applied LMOC concentrations. Previous researchers have reported that large molecules, such as HA

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or even TA, tend to aggregate with increasing concentration,39, 40 which consequently resulted in

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decreased binding to Cu(II). However, previous studies have suggested that the aggregation of low

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molecular weight organic matter is difficult to achieve. 41 Thus, aggregation of these LMOCs is

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unlikely to occur at the investigated concentration range. Clearly, other possible mechanisms should

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be considered. 6


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log CuL/LH (mol/g)

149 -1 A -2 -3 -4 -5 -6 -7 -8 -7 -1 -2 -3 -4 -5 -6 -7

-6

-5

-1 -2 -3 -4 -5 -6 -7

-8

-7

-1 -2 -3 -4 -5 -6 -7

-6

-5

-9

-4 -11

E

-4

-1 -2 -3 -4 -5 -6 -7

B

-7

-5

F

-8

-7

-6

-5

C

-10

-8

-1 G -2 -3 -4 -5 -6 -7 -4 -8 -7

-6

-4

-1 -2 -3 -4 -5 -6 -7

D

-8

-1 -2 -3 -4 -5 -6 -7 -6

-5

-4

-7

-6

-5

-4

-7

-6

-5

-4

H

-8

log Cu(II) (mol/L) 1mg/L

5mg/L

10mg/L

20mg/L

50mg/L

100mg/L

150 151

Figure 1. Cu(II) binding with different concentrations of LMOCs in the background solution of 0.1

152

M NaNO3. Relationships between the free Cu(II) concentrations (mol/L) and LMOC-bound Cu(II)

153

concentrations were normalized by LMOC concentrations (mol/g). The x-axis represents the

154

logarithm of free Cu(II) concentrations (as measured by ISE, mol/L). Panels A-D present the

155

LMOCs without benzene rings of AA, OA, CA and TT, respectively. Panels E-H are the LMOCs

156

with benzene rings of BA, PA, GA and TA, respectively.

157 158

Generally, the pH values decreased with increasing Cu(II) concentration and this pH reduction

159

was more dramatic at higher LMOC concentrations (Figure S2). However, for AA and BA, Cu(II)

160

addition did not obviously decrease pH, although significant binding was observed (Figure 1). It

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should be noted that the initial addition of Cu(II), up to the binding concentrations of 10-4 mol/g, did

162

not result in significant pH decrease. In addition, the pH decrease was more obvious for systems

163

with higher DOM concentrations. These results are useful information for the later modeling.

7



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As listed in Table S1 for their pKa values, most LMOC solutions dominated by negatively

165

charged molecules. The following interactions between Cu(II) and LMOCs could be proposed:

166

Cu2+ + 2L- = L-Cu+ + L- = Cu-(L)2

(2)

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Cu2+ + 2L = (Cu-L)+ + L + H+ = Cu-(L)2 + 2H+

(3)

168

Because of the ubiquitous electrostatic interactions, Reaction (2) may occur at relatively low Cu(II)

169

concentrations without obvious pH change. Reaction (3) will result in pH decrease. However,

170

Reaction (3) could not explain the LMOC-concentration dependent pH change. It is possible that

171

the coordination number changes with Cu(II)/LMOC ratios.42, 43 However, more obvious pH change

172

should be observed at lower Cu(II)/LMOC ratios, because of the abundance of LMOCs. Clearly,

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this is not the case in this work as presented in Figure S2.

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To further investigate the potential homo-conjugation of LMOC molecules, solution pH

175

changes were compared between the theoretical and measured ones. LMOC solutions at pH 4 and

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pH 6 but with the same concentration were mixed at the same volume. The theoretical pH change

177

was calculated according to H+ concentrations, while the pH values were directly measured in the

178

solution after well-mixing. As presented in Figure S3, the measured pH of the mixture was always

179

higher than the theoretical pH. Because no other molecules were involved in the system, the

180

increased pH, or the decreased H+ concentration should be related to inter-molecular interactions.

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This observation is consistent with the previously reported (-)CAHB.33

182

The pH change of LMOC mixtures at different concentrations was generally observed (Figure

183

S3), suggesting the ubiquity of (-)CAHB. On the other hand, Cu(II) addition will result in pH

184

decrease because of Reaction (3). However, the introduction of Cu(II) in LMOC solutions

185

decreased the apparent pH to various extent, or did not always decrease the apparent pH. We thus

186

proposed that the strength of (-)CAHB varied in different systems when compared to Cu(II)-LMOC

187

complexation. The following modeling was proposed to obtain the conditional binding constants of

188

different processes.

189 8


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The mathematical modeling of Cu(II)-LMOC interactions. According to the above

191

discussions, at relatively low Cu(II) concentrations, Cu(II) primarily complexed with the

192

dissociated organic acids, and thus the pH change was not apparent. Their interactions could be

193

described by the following equations:

194

L- +Cu 2+ ↔ L-Cu + ;

KC =

CCu-L CL CCu

(4)

195

where L-: represents the dissociated LMOC molecules, g/L; L-Cu+: represents Cu-LMOC

196

complexes, mol/L; KC: represents the conditional binding constant of Cu(II)-LMOC complexation,

197

(g/L)-1; CCu: represents free Cu(II) concentrations (as measured by ISE), mol/L.

198

LH ↔ L- +H + ;

K a,LH =

C L {H + } CLH

(5)

199

where LH: represents the un-dissociated LMOC molecules, mg/L; Ka,LH: represents the acid

200

dissociation constant. {H+}: represents the chemical activity of H+ (as measured by pH electrode),

201

mol/L.

202 203 204

205

In this current study, CT = CCu-L + CL + CLH. Because CCu-L

Homo-Conjugation of Low Molecular Weight Organic Acids Competes

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