Article pubs.acs.org/est

Sorption Mechanisms of Organic Compounds by Carbonaceous Materials: Site Energy Distribution Consideration Xiaofang Shen, Xiaoying Guo, Meng Zhang, Shu Tao, and Xilong Wang* Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China S Supporting Information *

ABSTRACT: Sorption of naphthalene, lindane, and atrazine on 10 kinds of carbonaceous materials which included four kinds of graphene, three kinds of graphite, two kinds of carbon nanotubes and one kind of mesoporous carbon was investigated. The approximate sorption site energy distributions were calculated based on Dubinin-Ashtakhov (DA) model. The average sorption site energy and standard deviation of the site energy distribution were deduced and applied to analyze the interaction between sorbents and sorbates, and the sorption site heterogeneity. The introduction of oxygen-containing functional groups to the sorbents caused a decrease in their average sorption energy for the studied compounds. However, relative to the decrease in average site energy, the reduction in number of sorption sites as indicated by surface area more strongly reduced their sorption capacity to the tested carbonaceous materials based on the result of the linear regression analysis. Sorption site heterogeneity of the sorbents decreased as their oxygen contents increased, which is attributed to the better dispersion of the oxygen-containing materials as indicated by their TEM images. The method proposed in this study to quantify the average sorption site energy and heterogeneity is helpful for a better understanding of the sorption mechanisms of organic pollutants to carbonaceous materials.

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INTRODUCTION Due to excellent physicochemical properties of carbon nanomaterials (CNMs), they have been attracting increasing research interests and have widely been used in numerous fields.1−3 With increasing production and use of CNMs, they will inevitably be released to the environment.4,5 Once entering into the environment, CNMs may exert adverse health effect on those exposed, such as human beings, plants, and other organisms.6,7 Meanwhile, the released CNMs would interact with the ubiquitously present organic pollutants (OPs) upon contact. Due to the large surface area and highly hydrophobic nature of CNMs, they have been proposed as a promising sorbent for removing environmental pollutants.8−10 Sorption of OPs to carbonaceous materials is an important process that may affect their transport, fate and persistence in the environment, as well as health risks.11−13 Three most popular CNMs are fullerene, graphene, and carbon nanotubes. Graphene can be viewed as the specific graphite with one-atom thick layer, and it is the basic structure of other two allotropes of carbon. Rolling of graphene is to form concentric cylinders, which are called carbon nanotubes (CNTs).14 According to the number of concentric cylinders, CNTs can be classified into two types: single-walled carbon nanotubes (SWCNTs) and multiwalled carbon nanotubes (MWCNTs). To enhance the dispersibility of CNMs and facilitate their practical applications, they were functionalized by introducing hydrophilic functional groups such as hydroxyl, carboxyl, and carbonylic groups. Much work has been done to © XXXX American Chemical Society

explore sorption characteristics of OPs on CNMs, especially SWCNTs and MWCNTs.8−11 It was shown that as the surface oxygen content of CNTs was relatively low, oxidation treatment enhanced their dispersibility such that a greater number of sites were exposed for toluene, ethylbenzene and mxylene (TEX) sorption. Hence their sorption capacity was increased.15 However, with the oxidation proceeding, sorption of CNTs for these chemicals decreased due to water cluster formation at their surfaces or tube ends, which inhibited their interactions.15 As a neotype CNM, single-layer graphene (SG) had large surface area with a theoretical value being 2630 m2/ g.16 It exhibited strong sorption for many OPs, such as phenol and bisphenol A.17,18 Based upon a comparison of the sorption characteristics of four aromatic compounds by SG and graphene oxide (GO), Pei et al.9 concluded that π−π interactions and hydrogen bonding regulated their sorption. It is hypothesized that different CNMs have dissimilar sorption characteristics for a same compound due to their physical structure and chemical composition difference, and the sorption behavior difference results from their distinct site energy distributions. In previous studies, parameters obtained from isotherm model were applied to discuss the sorption mechanisms of OPs Received: December 12, 2014 Revised: February 15, 2015 Accepted: March 19, 2015

A

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determined by heating at 900 °C for 4 h, their O content was calculated by mass balance. As the surface elemental composition of the sorbents could be different from the bulk one due to aggregation, AXIS-Ultra X-ray Imaging Photoelectron Spectrometer (Kratos Analytical Ltd., UK) was employed to obtain their surface elemental composition. Since surface area and porosity of sorbents are important factors that may affect OP sorption, sorption−desorption isotherms of N2 by all sorbents at 77 K were obtained using an Autosorb-1-MP Surface Area Analyzer (Quantachrome Instruments, Boynton Beach, FL) after outgassing at 105 °C for 16 h. Surface area of all sorbents were derived from N2 sorption isotherms using multipoint BET method with the relative pressure P/P0 ranging from 0.05 to 0.3. The Barrett−Joyner− Halenda (BJH) model was employed to calculate their mesoand macropore volumes from the desorption isotherms. The microporosity of sorbents was obtained using Dubinin− Radushkevich (DR) model with P/P0 ≤ 0.05.19 Surface morphological information on CNMs was obtained using TEM to evaluate their structural homogeneity. To capture the TEM images of all sorbents, the suspensions containing sample particles with solid-to-solution ratios identical to the sorption experiments were ultrasonicated for 20 min, followed by dripping a droplet onto the surface of copper grid to dry out before analysis. Sorption Experiments. The batch equilibration technique was applied in the sorption experiment. According to the solidto-solution ratios obtained from our preliminary work (SI Table S2), the sorbent particles were weighed and added to the screw cap vials with aluminum foil-Teflon liners. Except for nonlabeled atrazine, which was dissolved directly in water, the 14 C-labeled and nonlabeled chemicals (naphthalene, lindane, and atrazine) were dissolved in methanol to prepare the stock solutions. The methanol content in the sorption systems was controlled below 0.1% by volume to avoid cosolvent effect. The background solution was prepared which contained 200 mg/L NaN3 to inhibit bioactivity and 0.01 M CaCl2 to maintain a constant ionic strength. The 14C-labeled and nonlabeled stock solutions of individual tested compounds were spiked to the background solution to get the test solutions with varying concentrations ranging from 0.01 to 0.85 times of the water solubility of the studied compounds. After shaking for 1 h, test solutions were added to the vials with preweighed sorbents. Since our preliminary tests showed that sorption equilibrium reached in 6 days for all sorption systems, the sealed vials were mixed for 7 days on a rotary shaker at room temperature. Then the vials were centrifuged at 3000 rpm for 30 min and put there still for 8 h, to avoid any possibility of intrusion of the precipitated sorbent particles into the supernatant. To check the goodness of the separation of solid particle and liquid phase after centrifugation, turbidity of the supernatant was measured using a Turbidity Meter 2100AN (Hach, Loveland, CO). The results showed that except for graphene, all tested sorbents were completely separated (SI Table S2). The supernatant containing incompletely separated graphene particles was filtered through 0.2 μm aluminum oxide membrane. The concentrations of 14C-labeled sorbates in the aqueous phase were determined by mixing 2 mL supernatant with 4 mL cocktail (Fisher Scientific Co.) for liquid scintillation counting with a liquid scintillation counter (Beckman Counter, LS6500). All samples including blanks were run in duplicate. Due to negligible mass loss of the tested compounds during the

to CNMs,19,20 on which little work was available from the point of view of site energy distribution. As sorption isotherm parameters correspond to the specific site energy distribution, detailed information on sorption characteristics can be obtained from isotherm model-based sorption site energy distribution. Cater et al.21 examined the effect of 1, 2, 4-trichlorobenzene preloading on sorption of trichloroethylene to activated carbon using three cases of Langmuir models by comparing the site energy distribution of the sorbent before and after preloading. It was proposed that the interaction forces between solutes and sorbents could be indicated by the mean of the site energy distribution, and the width of the site energy distribution was able to interpret the surface energy heterogeneity of sorbent.21 The common Freundlich model-based site energy distribution was applied to analyze sorption of OPs by soils and humic substance.22 The site energy analysis was found to be helpful for explaining the sorption data and demonstrating the heterogeneous sorption site distribution of the natural sorbents.22 Similarly, site energy distribution derived from Freundlich model was used to probe the displacement mechanism of pyrene by phenanthrene from soils and sediments.23 It was documented that introduction of displacer reduced energy of the sorption sites for pyrene and the energy reduction was more pronounced for the high-energy sites relative to those with low energy.23 To help better understand the interaction difference between OPs and carbonaceous materials on site energy respect, the site energy distribution analysis was conducted to probe sorption behaviors of naphthalene, lindane, and atrazine on ten sorbents with different physical structure and chemical composition. Particularly, sorbents with different surface chemistry were used to evaluate roles of hydrophilic groups introduced to their surfaces in OP sorption. The carbonaceous materials with similar elemental composition but different physical structures, such as graphene, graphite, mesoporous carbon (MC) and CNTs were chosen to better understand roles of the physical structure (e.g., surface area and pore volume) of these sorbents in their sorption for OPs.

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MATERIALS AND METHODS Chemicals. Naphthalene, lindane, and atrazine are listed as persistent toxic substances (PTS) by the United Nations Environment Program (UNEP). They were selected as sorbates representing OPs with different polarizability, hydrophobicity and aromaticity, and their physicochemical properties are listed in Table S1 in the Supporting Information (SI). Both of the 14 C-labeled and nonlabeled chemicals were purchased from Sigma-Aldrich Chemical Co.. Sorbents. Ten kinds of carbonaceous materials with considerably different physical structure and chemical composition were used as sorbents. Graphene-based materials, including single-layer graphene (SG), multilayer graphene (MG), graphene oxide (GO), and COOH-functionalized graphene (CG), and the graphite-based materials, including graphite (GH), graphite oxide (GHO) and nanoscaled graphite (NGH), were purchased from Nanjing Jicang Nano Technology Co., Ltd. The pristine (SWCNT) and COOH-functionalized single-walled carbon nanotubes (CSWCNT), as well as mesoporous carbon (MC) were obtained from Chengdu Organic Chemicals Co., Ltd., Chinese Academy of Sciences. Characterization of Sorbents. The C, H and N contents of all sorbents were analyzed using a PE2400 Elemental Analyzer (Waltham, MA). With the ash content of all sorbents B

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Figure 1. Isotherms of naphthalene, lindane, and atrazine on various carbonaceous materials. The blue symbols correspond to the left Y-axis, and the red ones are labeled on the right Y-axis. Lines are data fittings of the corresponding color symbols with the DA model

sorption experiment, their sorbed amount to the solids was calculated from mass balance. Sorption Isotherm Data Fitting. Because of the strong van der Waals interactions, CNTs are prone to aggregating through forming bundles and cross-linked disordered structures.24 The heterogeneous sorption sites for OPs were developed in this process as indicated by the nonlinear sorption isotherms.8,19 The nonlinear Polanyi theory-based Dubinin-Ashtakhov (DA) model and the Freundlich one have widely been used for sorption isotherm data fitting. Since Freundlich model is the special case of Polanyi theory-based model, the latter one is more universal for diverse carbonaceous sorbents.25 Both of these two models were employed to fit the sorption isotherm data of naphthalene, lindane, and atrazine by various carbonaceous materials with dissimilar physical structures. Dubinin-Ashtakhov (DA) model: log Q e = log Q 0 − (εsw /Ed)b

MWSE =

N 2 ] ∑ [(Q measured − i − Q model − i)2 /Q measured −i i=1

(3)

where v is degree of freedom (v = N-2 for Freundlich, v = N-3 for DA model); N is the number of experimental data points; i represents a data point at a certain initial concentration; Qmeasured‑i is the ith measured sorbed concentration at equilibrium, and Q model‑i is the ith estimated sorbed concentration at equilibrium. Approximate Site Energy Distribution Function. The site energy distribution of a sorbent can be deduced from the isotherm parameters because any isotherm model is based on an assumption of a distribution of site energies.26 It has been proved to be useful for comparing sorption characteristics of OPs by different sorbents. The general integral isotherm equation based on the theory of OP sorption to the heterogeneous surfaces of sorbents can be written as below:

(1)

where Qe (mg/kg) is the sorbed amount of sorbate to sorbent; Q0 (mg/kg) is the maximum sorption capacity; εsw = RTln(Cs/ Ce) (J/mol) is the effective sorption potential; R (8.314 J/(mol· K)) is the universal gas constant; T (K) is the absolute temperature; Cs (mg/L) is the water solubility of sorbate; Ce (mg/L) is the equilibrium concentration of sorbate in liquid phase; Ed (J/mol) is the correlating divisor; and b is the fitting parameter. Freundlich model:

Q e = K f Ce n

1 ν

qe(Ce) =

∫0

+∞

qh(E , Ce)F(E)dE

(4)

where Ce is the equilibrium concentration of sorbate in liquid phase, qe(Ce) is the total sorption of solute to the sorbent, qh(E, Ce) is the isotherm over local sorption sites with sorption energy E, and F(E) is the site energy frequency distribution over a range of sites with homogeneous energies. Sorption energy E refers to the difference of sorption energies between the solute and solvent for a given sorption site.21 Due to the unknown sorption site energies, it is generally assumed that the limits of E on the integral range from zero to infinity.21,22 Although exact site energy distributions for Generalized Langmuir model and its simplifications have been derived by assuming qh(E, Ce) as a Langmuir-type and applying a Stieltjes transformation,26−29 it is still difficult to solve the above integral equation. To simplify the approach to determine the site energy distribution, the condensation approximation method proposed by Cerofolini was used and widely accepted.30 This method derived approximate site energy distributions from isotherm

(2)

where Kf [(mg/kg)/(mg/L)1/n] is the Freundlich sorption affinity coefficient, and n is the Freundlich exponential coefficient. As the number of parameters used for these two models was different, the effect of overparameterization on goodness of model fitting needs to be taken into consideration. To quantitatively compare the fitting goodness of these two models, the mean weighted square error (MWSE) as presented below was calculated. C

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Figure 2. The DA isotherm model-based site energy distributions of carbonaceous materials. The curves of MC, SG, SWCNT, and CSWCNT were labeled on the left Y-axis, and those of the others were labeled on the right Y-axis. The curves depicted in solid lines represent the site energy distributions in experimental data range and those in dotted lines refer to the site energy distributions beyond the experimental data scope.

models.26 It was used in previous studies to generate site energy distributions based upon the Freundlich models and Sips isotherm.21,22,31 Based on the condensation approximation, the equilibrium liquid phase concentration (Ce) of sorbate is related to the sorption energy (E) given by ⎛ E − Es ⎞ ⎛ − E* ⎞ ⎟ ⎟ = C exp⎜ Ce = Csexp⎜ − s ⎝ RT ⎠ ⎝ RT ⎠

carbonaceous materials using Freundlich and DA models, the MWSE values for these two models were calculated and compared. It was evident that the MWSE values for DA model were approximately 2 orders of magnitude lower than those for the Freundlich one for sorption isotherms of a given compound by all sorbents (SI Table S3), showing that DA model was able better to fit the sorption isotherm data of the tested compounds by the tested sorbents. Hence, DA model was applied in this study, and the related parameters are presented in SI Table S4. DA Model-Based Site Energy Distribution. Figure 2 shows the approximate site energy distributions for sorption of naphthalene, lindane, and atrazine to the tested carbonaceous materials based on DA model. Clearly, they were all unimodal distributions. As the site energy (E*) increased, the frequency function F(E*) increased to the apex, and then asymptotically decreased. Theoretically, the area under the curves in Figure 2 reveals the number of the available sorption sites in a specific energy range. Thus, the site energy corresponding to the position of the peak has the highest occurring frequency. Among the studied carbonaceous materials, MC exhibited much higher site energy at peak than others, although all of the peaks distributed over the low energy ranges (E* < 10 000) (Figure 2). This result can be due to the higher sorption capacity of MC than other studied sorbents for naphthalene, lindane, and atrazine. Theoretically, the range of E* can vary from zero to positive infinity, but the negative value does not have the true physical meaning. Even if the sorbent contained such low energy sites, they were not available for the sorbate as the residual solute concentration could not exceed its water solubility in the sorption systems. According to eq 5, the relationship between E* and the residual solute concentration is presented in SI Figure S1, with a hypothetical compound whose water solubility being 10 mg/kg. Practically, the solute concentration range could also be imposed by the analytical accuracy, solute volatilization and experimental error.21,22 Thus, the experimental range of E* would be even more restricted. In this study, the equilibrium concentrations of the sorbates (i.e., naphthalene, lindane, and atrazine) ranged approximately from 0.001 Cs to 0.6 Cs. Correspondingly, the E* values fell in the range from 1240 J/mol to 16800 J/mol, and the site energy curves in this region were depicted with solid lines in Figure 2. For a certain sorbate, the frequency function differed significantly among various sorbents in the low-energy range. In the low site energy range, the frequency function sharply increased with increasing site energy until reached the F(E*) peak. This suggested that as the solute concentration was high,

(5)

where Cs is the solute solubility in the solvent, Es is the “lowest physically realizable sorption energy” corresponding to Ce = Cs,26 R is the universal gas constant, T is the absolute temperature, and E* = E − Es.21,26,30 The calculated energy E* refers to the difference of sorption energies between the solute and solvent to the sorbent surfaces based on the reference point Es. This equation can also be derived from the Polanyi theory.32 By incorporation of eq 5 into eq 4, the isotherm qe(Ce) can be written as a function of E*, expressed as qe(E*). Thus, the approximate site energy distribution F(E*) can be obtained by differentiating the isotherm qe(E*) with respect to E* as shown below: F(E*) =

−dqe(E*) (6)

dE *

Particularly, F(E*) for the DA model-based isotherm can be obtained by plugging eq 5 into eq 1 and then incorporating into eq 6. The result is presented as below: F(E*) =

ln 10 × b × Q 0 × E*(b − 1) Ed b × 10[(E

*/ Ed)b ]

(7)

Equation 7 was used to analyze the F(E*) of the carbonaceous materials with the sorption data.

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RESULTS AND DISCUSSION Sorption Isotherm Modeling. Sorption isotherms of naphthalene, lindane, and atrazine by all tested carbonaceous materials are presented in Figure 1. It was reported that Polanyi theory-based model was able to fit the sorption isotherms of OPs by CNTs well.11,19 However, in the recent studies regarding sorption of OPs by graphene-based materials, Freundlich model was widely used and it exhibited good fitness.9,17,33 It was also found that both Freundlich and Polanyi theory-based models had comparable fitting goodness for the sorption isotherms of phenanthrene and biphenyl to graphene and CNTs.33 To compare the fitting goodness for sorption isotherm data of naphthalene, lindane, and atrazine by various D

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employed to describe the surface energy heterogeneity of the sorbents.21 To get the average site energy of various carbonaceous materials (Em) for naphthalene, lindane, and atrazine, the mathematical expectation (Ep) of E* based on the site energy distribution in the range of the experimental concentrations was calculated as below.

a small fraction of solute molecules were forced to occupy the sites with very low energy, which only accounted for a very low portion of the total site number. Sorption of solute on these low-energy sites contributed a very limited percentage to its maximum sorption capacity. As the site energy was over the F(E*) peak, the frequency function steeply decreased first and then slowly dropped down to approach zero with increasing site energy. This implied that all the tested carbonaceous materials had a low fraction of sites with very high energy (e.g., > 15 000 J/mol). As the solute concentration was low, the sorbate molecules were preferentially sorbed to the high-energy sites, and sorption on these sites only contributed a very low portion to the maximum sorption capacity. Moreover, the difference in the frequency function of various carbonaceous materials for a given compound tended to be smaller with increasing site energy. This indicated that sorption amount of a specific chemical to the very high energy sites of all tested sorbents was very similar, regardless of their quite different physiochemical properties (e.g., surface area, pore size distribution and elemental composition). DA Model-Based Average Site Energy and Sorption Site Heterogeneity. Due to the relatively complicated expression of DA model, the implications of its parameters (Ed, b) become more difficult to understand. It was proposed that the correlating divisor, Ed, can be used to depict the sorption affinity of the target OPs to the sorbents because it reflects their interaction forces during the sorption process.34,35 Further analysis showed that Ed value in DA model is the critical point of site energy (EX*), from which to the positive infinity, integral of −F(E*) as shown below equals to 0.1 Q0. The details for EX* deduction are presented in SI.

Em = Ep(E*) 16800

=

∫1240 E* × F(E*)dE* 16800

∫1240 F(E*)dE* 16800 (E * /Ed)b

∫1240

=

16800

∫1240

dE * b]

Ed b × 10[(E * /Ed)

dE *

Heterogeneous sorption sites were formed on carbonaceous materials due to structure and chemical composition heterogeneity.36,37 As the site energy distribution curve describes the occurring frequency of the available sorption sites with specific energy, sorbent site energy heterogeneity can be described with standard deviation (σe*). According to the relationship between variance and standard deviation and the mathematical expectation theory, σe* was calculated from the following equations in the experimental concentration range. 16800

*2

Ep(E ) =

∫1240 E*2 × F(E*)dE* 16800

∫1240 F(E*)dE* 16800

+∞

∫E*

b]

10[(E * /Ed) E*(b − 1)

−F(E*)dE* = 0.1Q 0

=

x

∫1240 E*2 ×

ln 10 × b × Q 0 × E*(b − 1) Ed b × 10[(E

16800 ln 10 × b × Q 0 × E*(b − 1)

∫1240

b]

Ed b × 10[(E * /Ed) 16800 (E * /Ed)b × E *

Based on the site energy distribution analysis, it was clear that EX* can only cover the high-energy site area and sorption to these sites only accounted for 10% of the maximum sorption capacity. It was unable to describe the average site energy of various carbonaceous materials for the tested compounds under study. Yang and Xing proposed that the parameter “b” in the DA model can be used as an index to describe the site energy heterogeneity of sorbents.25 To quantitatively analyze the relationship between the sorption characters (i.e., heterogeneity and average site energy) and the isotherm parameters (i.e., Ed and b), the DA model-based approximate site energy distributions with variations in Ed and b were plotted (SI Figure S2). The Q0 value was fixed at 10 000 mg/kg, which approximated to the average value among the sorption results, and Ed and b values were applied according to the isothermfitting result ranges in this study. When b was fixed at 1.5 but Ed was varied from 5000, 10 000 to 15 000 J/mol, both the shape and mean of the distribution changed (SI Figure S2, a). Same thing happened as Ed value was fixed at 10 000, but b was varied through 1.0, 1.5 to 2.0 (SI Figure S2, b). It was evident that both mean and shape of the distribution simultaneously changed as either Ed or b was modulated, which implied that b could not represent the site energy heterogeneity of the sorption sites in the tested sorbents. To help understand the average site energy and the surface energy heterogeneity of the tested sorbents, it was proposed that the mean of the site energy distribution can be used to depict the interaction forces between solute molecules and sorbents, and the width of the site energy distribution can be

=

∫1240

16800

∫1240 σe* =

*/ Ed)b ]

dE *

dE *

dE *

b]

10[(E * /Ed) E*(b − 1)

b]

Ed b × 10[(E * /Ed)

Ep(E*2) − Ep(E*)2 =

dE * Ep(E*2) − Em 2

Average Site Energy. The average site energy differed significantly (p < 0.01, Friedman test) among different carbonaceous materials (SI Figure S3). As reported, the aromatic and alkyl carbon components in black carbon and CNTs were dominant sorption domains for OPs.19,38 Difference in the average site energies of the studied sorbents could result from their diverse chemical composition. It was observed that for a given compound, the average energy of the effective sorption sites on carbonaceous materials (Em) significantly decreased as their bulk and surface oxygen contents increased (Figure 3). The average site energy reduction of various carbonaceous materials induced by the introduced oxygencontaining functional groups can result from the following mechanisms. The oxygen-containing functional groups on SG, GO, CG, and GHO enhanced their hydrophilicity, thereby enhancing competition of water with sorbate molecules. A previous study using molecular simulation method revealed that, as hydrophilicity of activated carbons was increased, the water cluster formation was enhanced and the sorbed water molecules blocked a fraction of pores in these sorbents.39 The water cluster formed at the sorbent surfaces decreased the E

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dependent on their average site energy. The average site energy of MG, GH, and NGH for a given compound was comparable to that of SG, SWCNT and CSWCNT, whereas they gave much lower Q0 value than the latter ones (Figure 4). It was mostly because of the much lower surface area and pore volume of MG, GH, and NGH than those of SG, SWCNT and CSWCNT (SI Table S5). An introduction of O-containing functionalities to the carbonaceous materials significantly decreased their average site energy (Figure 3), which in turn reduced Q0 value of the tested compounds by these sorbents (Figure 4). However, no correlation between Q0 values of carbonaceous materials and their oxygen contents was found (SI Figure S4 and S5). This further supported that relative to the bulk and surface oxygen contents, the average site energy of the carbonaceous materials in question more directly influenced sorption capacity of naphthalene, lindane, and atrazine (Figure 4). It was documented that surface area and porosity were of importance for sorption of OPs by the carbonaceous materials such as graphite, carbon nanotubes and activated carbon.19,43 For our case, Q0 value of naphthalene, lindane, and atrazine by various carbonaceous materials significantly increased with an increase in their surface area and porosity (p < 0.01) (SI Figure S6 and S7), implying that the effective sorption site numbers played an important role in their sorption. Furthermore, to compare the relative importance of the average site energy of various carbonaceous materials and their total available sorption site number in sorption of three chemicals, linear regression analysis was performed and the method is detailed in SI. Because a significantly positive correlation between surface area and porosity of all sorbents was observed (SI Figure S8), only surface area was used to represent sorption site number and conduct the regression analysis. The regression results revealed that the contribution of surface area was higher than that of average site energy for a specific compound (SI Table S6). This implied that sorption capacity of naphthalene, lindane, and atrazine by the carbonaceous materials was more closely dependent on their surface area over average site energy. Similarly, it was reported that sorption of a specific compound by mesoporous carbon and nonporous graphite on unit surface area basis was almost identical,44,45 reflecting the importance of surface area-based sorption site number of carbonaceous materials in the sorption process. Besides, Wang et al.19 demonstrated that a sum of meso- and macropore volumes of MWCNTs played an important role in sorption of phenanthrene, lindane and atrazine by MWCNTs of varying outer diameters. Sorption Site Heterogeneity. Almost all carbonaceous materials exhibited strong site energy heterogeneity for the studied compounds, as evidenced by the nonlinear sorption

Figure 3. Effect of bulk and surface oxygen contents of carbonaceous materials on the average sorption site energy for the tested compounds: naphthalene (◊), lindane (□), and atrazine (△).

accessibility of organic molecules (i.e., naphthalene, lindane, and atrazine) to approach the hydrophobic domains in the tested sorbents, thus weakening their interactions. The negative effect of the abundance of the O-containing moieties as indicated by the bulk and surface oxygen contents on average site energy of various carbonaceous materials for the two aromatic compounds (i.e., naphthalene and atrazine) was practically comparable, but less pronounced than the aliphatic compound lindane as reflected by their lower slope (Figure 3). The difference in effect of the average site energy of various carbonaceous materials for sorption of lindane and two aromatics was due to the facts as follows. All these three chemicals were able to interact with their hydrophobic carbon domains through van de Waals force. Both naphthalene and atrazine could additionally interact with their aromatic components via π−π interaction where both naphthalene and atrazine acted as electron donors and the aromatic components in the carbonaceous materials served as electron acceptors. The π−π interaction between the aromatic components in carbonaceous materials and the aromatics has been proved by the microscopic and spectroscopic analysis results, and it was stronger than the van de Waals force.40−42 The introduced Ocontaining functional groups to the carbonaceous materials more strongly decreased the availability of their hydrophobic (a sum of alkyl and aromatic) carbon domains than the aromatic ones for OP sorption. As a result, the average sorption energy of naphthalene and atrazine was less affected by the decreased hydrophobicity of the sorbents than that of lindane (Figure 3). It was further found that Q0 value of a given compound by various carbonaceous materials significantly decreased with decreasing average site energy at a significance level of 0.05 (Figure 4). If the sorbents MG, GH and NGH as marked in blue color were excluded, the correlation was significantly enhanced (p < 0.01). This suggested that Q0 value of a specific compound by various carbonaceous materials was closely

Figure 4. Relationship between average sorption site energy of carbonaceous materials and their sorption capacity for naphthalene, lindane, and atrazine. The three red circles represent SG, SWCNT, and CSWCNT, and the three blue ones represent MG, GH, and NGH, and the others refer to the rest sorbents. F

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Environmental Science & Technology

hydrophobic interaction between the graphite layers decreased, and the graphite sheets were better dispersed, leading to fewer overlapped layers (SI Figure S9, f, g, and h). This noted that dispersibility of the carbonaceous materials induced by oxidation played an important role in their sorption site heterogeneity. To further evaluate the effect of other sorbent properties on standard deviation, the relationship between stand deviation and physical structural properties of sorbents was analyzed, and the results are presented in SI Table S7. No significant correlation between stand deviation with micropore volume or a sum of the meso- and macropore volumes of the studied sorbents was observed (p > 0.05). Environmental Implications. In previous studies, parameters derived from isotherm models were used to analyze the sorption mechanisms of carbonaceous materials for OPs. In this work, site energy distribution was introduced and utilized to calculate the average site energy and standard deviation to describe the interaction strength and heterogeneity of sorbents. It was observed that oxygen contents played an important role in determining the average site energy of sorbent, which was significantly and positively correlated with the sorption capacity of the studied compounds by the sorbents. However, surface area and pore volume of the carbonaceous materials exerted relatively greater effect on sorption capacity of the target compounds based on the result of linear regression analysis. Sorption site heterogeneity of the carbonaceous materials decreased as their oxygen content increased, regardless of their distinct different physical structures. The better dispersibility of the sorbents with higher oxygen-containing moieties, as shown by TEM images, could be the reason for their more homogeneous sorption site energy distribution. These findings are critical for better understanding of the sorption mechanisms of OPs to carbonaceous materials.

isotherms (Figure 1). For the carbonaceous sorbents without grafted functional groups, their heterogeneous sorption sites could stem from the defect structures, as well as the crosslinking and disordered arrangement of various carbon structures (SI Figure S9, a). These carbonaceous materials generally exhibited the evident site energy heterogeneity. Likewise, it was reported that the networked, porous structure (size and shape) of graphitized carbons in the geologically matured anthracite also provided heterogeneous sorption sites, leading to significantly nonlinear sorption for OPs.36,46,47 However, for the carbonaceous sorbents with abundant Ocontaining functional groups, their heterogeneous surfaces were reported to result from their chemical composition heterogeneity.37 If following this finding, site energy heterogeneity of the carbonaceous materials should be more pronounced with increasing oxygen content. However, our observation showed that as the low-oxygen containing materials were processed and got higher bulk and surface oxygen contents (>10%, i.e., GO, CG, and GHO as compared to MG, GH, and NGH), their σe* values decreased, illustrating more homogeneous sorption sites (SI Figure S10). It was notable that although SG contained certain amount of oxygen resulting from incomplete reduction of GO, it gave heterogeneous sorption surfaces. It was mainly due to its two-dimensional thin film structure, which tends to crimp and stack, forming sorption sites with varying site energies (SI Figure S9, b). The existence of ripples on the graphene surface was also confirmed by Monte Carlo simulations.48 Taking all the tested carbonaceous materials together, the site energy heterogeneity of all samples for a given compound significantly decreased with an increase in their surface oxygen contents (Figure 5). It was because the introduced O-

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ASSOCIATED CONTENT

S Supporting Information *

Some supplementary data and correlation relationships related to this article. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Phone: 86-10-62757822; fax: 86-10-62767921; e-mail: [email protected].

Figure 5. Relationship between sorption site energy heterogeneity index (σe*) and bulk and surface oxygen contents of carbonaceous materials for naphthalene (◊), lindane (□), and atrazine (△).

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This study was supported by the 973 Program (2014CB441101), National Natural Science Foundation of China (41271461, 41328003, 41390240 and 41130754), The National Key Project of Science and Technology (2012ZX07503-003-004), and 111 Program (B14001).

containing moieties led to more hydrophilic particle surfaces, which facilitated water cluster formation. The water cluster coverage made the surfaces of the carbonaceous materials more homogeneous. Also, dispersion of the carbonaceous materials would be enhanced as the abundance of the O-containing functionalities increased.49,50 It can be supported by the fact that the colloidal stability of functionalized MWCNTs was highly enhanced due to the introduced oxygen-containing functional groups.51 For the graphite- and graphene-based sorbents with low oxygen content, such as GH, NGH, and MG, the randomly overlapped layers and irregularly arranged edge and interspaces were formed as graphite layers tended to attract each other through van der Waals force and π−π interactions, resulting in heterogeneous sorption site energies (SI Figure S9, c, d, and e). As the oxygen contents were increased, the

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