Using recyclable magnetic carbon nanotube to remove micropollutants from aqueous solutions

Accepted Manuscript Using recyclable magnetic carbon nanotube micropollutants from aqueous solutions

to remove

Mohammad Alizadeh Fard, Brian Barkdoll PII: DOI: Reference:

S0167-7322(17)34398-2 doi:10.1016/j.molliq.2017.11.039 MOLLIQ 8155

To appear in:

Journal of Molecular Liquids

Received date: Revised date: Accepted date:

22 September 2017 2 November 2017 4 November 2017

Please cite this article as: Mohammad Alizadeh Fard, Brian Barkdoll , Using recyclable magnetic carbon nanotube to remove micropollutants from aqueous solutions. The address for the corresponding author was captured as affiliation for all authors. Please check if appropriate. Molliq(2017), doi:10.1016/j.molliq.2017.11.039

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT Using recyclable magnetic carbon nanotube to remove micropollutants from aqueous solutions

IP

T

Mohammad Alizadeh Fard* and Brian Barkdoll

CR

Department of Civil and Environmental Engineering, Michigan Technological University,

AN

US

1400 Townsend Dr., Houghton, MI 49931, USA

*Corresponding author. Tel.: +1 906 231 3654, fax: +1 906 487 2943.

AC

CE

PT

ED

M

Email address: [email protected] (M. Alizadeh Fard)

1

ACCEPTED MANUSCRIPT Abstract Magnetic carbon nanotubes (MCNs) were synthesized using a new hydrothermal method. The new developed MCNs were evaluated for removal of Metolachlor, Bisphenol-A, Tonalide, Triclosan, Ketoprofen and Estriol from aqueous solutions. Using

IP

T

response surface methodology, a predicting removal model was developed based on solution pH, contact time, adsorbate concentration and adsorbent dose. Experimental

CR

results showed high agreement with the predicted ones at optimum conditions. In

US

addition, experimental results were modeled by Freundlich and Langmuir isotherms, which directed a better fit to the Langmuir isotherm. MCN presented good adsorption

AN

capacity in which Bisphenol-A, Ketoprofen and Tonalide were the most effectively

M

removed micropollutants, with 98, 96 and 96% removal within 47 minutes, respectively. Thermodynamic studies showed that the adsorption process was endothermic and

ED

spontaneous for the micropollutants. Adsorbate regeneration studies were done with

PT

methanol, ethanol, HCl, NaOH and hydrogen peroxide in five regenerating cycles. Methanol had the highest level of adsorbent recovery. MCN can be used as a

AC

CE

sustainable adsorbent for adsorption of the studied micropollutants.

Keywords: Emerging contaminants; Magnetic carbon nanotube; Adsorption; Adsorbent restoration.

2

ACCEPTED MANUSCRIPT 1. Introduction Over the last decades, water resources were contaminated by different organic and inorganic contaminants emanated from natural and human activities [1]. Rapid industrial development has resulted in release of several contaminants to potable water resources

IP

T

[2]. Thus, it becomes difficult to find clean water resources. The occurrence of emerging contaminants in the environment is a serious environmental issue [3, 4]. Emerging

CR

contaminants, like personal care products are present in the aquatic ecosystem at very

US

low concentrations (mostly ng/L-µg/L). Long term existence of micropollutants in water can pose serious toxicological effects on human health [5]. These compounds are

AN

generally non-biodegradable or low-biodegradable, therefore if released into the

M

environment, they are stable and persistence in both soil and water. As urban wastewater treatment plants (UWTPs) have not been designed for micropollutant

ED

removal, a majority of micropollutants can stay in the plant effluent and subsequently

PT

enter in the receiving water body [6, 7].

CE

To address the problem, different treatment methods have been studied to remove micropollutants from water. Physicochemical treatment processes have shown great

AC

capacity to remove emerging contaminants [8]. These processes mainly include adsorption, membrane technology [9], and advanced oxidation processes (AOPs) [10]. Adsorption techniques are reliable due to flexibility in design, low operation cost, and relatively high removal capacity [11]. Adsorbents like carbon nanotubes, activated carbon, polymers, ion exchange resins, and natural zeolites have been extensively used [9, 12, 13]. However, there are limitations over the application of some of them to full-

3

ACCEPTED MANUSCRIPT scale treatment plants [14]. For every adsorption method, it is necessary to separate the saturated adsorbent to achieve a free adsorbent solution. On the other hand, regeneration of the saturated granular activated carbon (GAC) through incineration is energy intensive, and cannot completely recover its adsorption

IP

T

capacity [15]. Powdered activated carbon (PAC) also has been dumped alongside the process sludge after use, which is another source of hazardous waste [16]. Therefore, it

CR

is important to find an adsorbent that could be recovered and finally regenerated to its

US

highest adsorption capacity. To achieve these objectives, magnetic adsorbents can be used to provide a free adsorbent solution and regeneration techniques can recover the

AN

adsorption capacity.

M

Carbon nanotubes (CNTs) have been studied extensively in water and wastewater

ED

treatment and have shown high adsorption capacity [17, 18]. However, the centrifugation separation process is difficult to perform in industrial applications.

PT

Magnetic separation is a fast separation process to address the issue. Magnetic carbon nanotubes (MCN) have been generally synthesized in two procedures. In the first

CE

method, CNTs soak in Fe3+ solution, then they are dried and calcined under inert

AC

atmospheric conditions. The produced MCNs have been studied for removal of pollutants from aqueous solutions [19]. In the second method, carbon nanotubes are added to a mixture of Fe2+ and Fe3+ with the molar ratio of 2:1. Next, addition of NaOH or NH3 to the solution causes co-precipitation of Fe2+ and Fe3+ onto the CNT surface [11]. In both these methods, magnetite production is done in the presence of carbon nanotubes. This can finally cause the formation of other iron oxide species such as maghemite [11]. 4

ACCEPTED MANUSCRIPT In this work, to prevent the formation of other species of iron oxide, synthesis of MCNs were performed separately: first, the magnetic nanoparticles were produced by a simple hydrothermal method and collected by a magnet. Then, the magnetic nanoparticles were mixed with the HNO3-treated CNTs. The synthesized MCNs were studied for

T

removing six micropollutants from water. Table S1 briefly describes physicochemical

CR

IP

properties of studied compounds.

US

2. Materials and methods

AN

2.1 Materials

Ammonium hydroxide (25%), ferric chloride (99%), ferrous chloride (99%), sodium

M

hydroxide, hydrogen peroxide (30%), sulfuric acid (98%), ethanol, and methanol were

ED

purchased from Merck Co. (Germany). Suwannee River Fulvic Acid (SRFA) was

PT

obtained from the International Humic Substances Society (IHSS). Potassium persulfate (KPS), sodium bisulfite (>95%), and micropollutants (Bisphenol-A, Tonalide, Triclosan,

CE

Ketoprofen, Metolachlor and Estriol) were obtained from Sigma-Aldrich (USA). Pristine

AC

multi-wall carbon nanotubes (PMWCNs) were purchased from Nanoshel (USA). 2.2 Synthesis of MCN 5 g of PMWCNs was added to 70 ml of HNO3 (65%) and constantly stirred for 6 h at 105°C. The acid washed PMWCNs were filtered and rinsed twice with ultrapure water. Then, it was dried in oven at 65°C for 48 h. Magnetic nanoparticles were produced using a hydrothermal method. First, 0.76 g of ferrous chloride and 1.84 g of ferric chloride were added to 250 mL ultrapure water and mixed at 85 °C for 2h. Next, 35 mL 5

ACCEPTED MANUSCRIPT of ammonium hydroxide (30%) was added to the mixture dropwise. Then, magnetic nanoparticles were separated with a neodymium disc magnet (2.0 x 1.0 inch) followed by rinsing with ultrapure water. Finally, magnetic nanoparticles were dispersed in 100 ml of ultrapure water followed by addition of 5 g of acid washed PMWCNs and was stirred

T

at 85 °C for 2h under N2 flow. As magnetic nanoparticles have a point of zero charge

IP

(PZC) of 6 and acid washed PMWCNs have a PZC value of 2, these two can attract

CR

each other in a pH range of 2 to 6 due to their opposite charges. At pH values lower than the PZC, the surface is positively charged, though it is negatively charged at pH

US

values greater than the PZC. The final products were black precipitates. To remove

AN

possible surface impurities, they were dispersed in 50 mL of 0.1 N HCl and 0.1 N NaOH solutions. The precipitates were filtered and rinsed with ultrapure water. The magnetic

ED

finally retained in a desiccator.

M

carbon nanotubes (MCN) were dried at 65°C for 24 h, calcinated at 115°C for 5 h, and

PT

2.3 Analysis methods

CE

Micropollutant concentrations were measured by a gas chromatography–mass spectrometry (GC/MS) equipped with a TRB-5 fused capillary column (60 m, 0.32 mm

AC

ID). The apparatus was operated under the internal ionization mode. A capillary column SGE (30 m × 0.25 mm), was used with electron energy=60 eV, scan speed of 1000 Hz, and a transfer-line temperature of 200◦C [20]. The point of zero charge (PZC) was determined using the following procedure: 0.1 M NaCl solutions at pH values 1.5 to 12.5 were prepared. Next, 0.35 g of MCN was added to 15 ml of each solution and were continuously stirred overnight at 25 oC. PZC was determined as the final solution pH that did not change after contacting with MCN [21]. 6

ACCEPTED MANUSCRIPT Surface area and pore distribution were measured by PHS 1020 surface analyzer (China) using nitrogen gas adsorption–desorption process. The XRD analysis were done with Scintag X-Ray diffractometer (XDS-2000 θ/θ powder diffractometer) using Cu Ka (k = 0.1541 nm). The Scherrer equation (Eq.1) at (311) plane was used to calculate

IP

T

the mean crystallite size:

CR

(1)

US

where t is the average crystallite size, k is 0.89 (the dimensionless shape factor for magnetite), γ is the X-ray wavelength (1.54059 Å), θ is Bragg’s angle and β is the line

AN

broadening at half the FWHM. Fourier transform infrared spectrometer (PerkinElmer

M

100) was used to characterize the functional groups of MCN surface.

ED

2.4 Statistical design of adsorption studies

Interaction effects of four independent variables and optimization of the adsorption

PT

conditions for removal of each micropollutant were performed by central composite

CE

design (CCD) [22]. The independent variables were solution pH (X1), contact time (X2), micropollutant concentration (X3), and MCN dose (X4). The actual values of the

AC

independent variables used for the experimental design are presented in Table 1. The experimental removal efficiencies were developed with quadratic (second order polynomial) model as shown in Eq. (2): (2) where y is the micropollutant removal efficiency (%), B0 is the intercept value, Bi, Bii, and Bij refer to the regression coefficient for linear, second order, and interactive effects, 7

ACCEPTED MANUSCRIPT respectively. Xi and Xj are the independent variables, and C is the error of prediction. R software (V 3.4.1, 2017-06-30) and MATLAB (R2015a) were used for analyzing the results. 2.5 Batch experiments

IP

T

Adsorption experiments were carried out in a 50-mL sealed glass vial. Sonication was

CR

performed before doing the tests to separate possible MCN clogs. All batch reactor vials were stirred at 150 rpm using a rotary agitator. All containers were wrapped with

US

aluminum foil to avoid photolysis.

AN

After performing the adsorption tests, MCN was collected by magnet in 45 minutes. To reduce analytical uncertainties, stock samples were kept under the same

M

experimental conditions except adding the adsorbent. Therefore, results were obtained

ED

by comparing the concentration of adsorbates in the stock sample to the experimental ones. All experiments were repeated at least four times and the average values are

PT

reported.

CE

To obtain adsorption isotherms, adsorbent and adsorbates were added to 50 mL sealed glass vials. The range of adsorbate concentrations was 25-250 µg/L. The

collected.

AC

containers were stirred at 25, 35, and 45 oC for 60 minutes and the adsorbent was

Regeneration studies were conducted in a 50-mL sealed glass vial. For all regeneration experiments, 0.5 mg of saturated adsorbate was mixed with 10 mg/l of the regenerating agent. The vial was placed on a rotary agitator with rotary speed of 150 rpm for five minutes. The residual hydrogen peroxide was neutralized with NaHSO3. 8

ACCEPTED MANUSCRIPT The regenerated MCN was tested again to remove the adsorbates. The regeneration studies were repeated five times.

T

3. Results and discussions

IP

3.1 Characterizations of the adsorbent

CR

Results indicated that, the PZC value of MCN was 6.8. This neutral pH value could be

MCN almost free of charge at that pH value.

US

due to the treatment of the adsorbent with NaOH and HCl which kept the surface of

AN

Fig. 1(a) shows the XRD pattern for MCN. Results indicated that, magnetite with a

M

cubic spinel structure was the dominant phase of the sample. The main crystalline phase identified as magnetite by comparing the calculated lattice parameter (8.3963 Å)

ED

of MCN with the lattice parameter of magnetite (8.3960 Å) (JCPDS 19-629). The

PT

average crystallite size of 21.2 nm was calculated by using Eq. (1).

CE

FT-IR spectra of acid washed CN and MCN are presented in Fig. 1(b). The broad absorbance band around 3,610 cm−1 corresponds to O-H. The band at 1,610 cm−1

AC

shows the presence of C=O. The band at region of 1,610 cm−1 mainly is assigned to C=C aromatic. The band detected at 1,460 cm−1 is assigned to carboxyl–carbonates structures. The band at 1160 cm−1 is assigned to C-C. A strong adsorption band at 480 was detected in the FT-IR spectra of MCN shows the presence of iron oxides [19]. This band is ascribed to the stretching vibrations of Fe−O. Comparison of the FTIR spectra of MCN and acid washed CN samples showed that iron oxide nanoparticles were successfully coated. 9

ACCEPTED MANUSCRIPT 3.2 Response surface methodology (RSM) analysis The individual and combined impacts of variables on micropollutants removal efficiency, were investigated using CCD. The experimental design of 42 runs along with the experimental and modeled results for adsorption of Bisphenol-A onto MCN are

IP

T

tabulated in Table 2 (results for other studied micropollutants are presented in Tables S2-5). According to the results, the adsorption capacities vary significantly depending

CR

on the values of the independent variables. Results indicated that pH did not have a

US

significant impact on Bisphenol-A adsorption onto MCN (Run # 6, 7, 8 and 10). It has been demonstrated before that the adsorption of hydrophilic compounds is impacted by

AN

pH change while hydrophobics with Log Kow> 2.5 are not [23]. All tested

M

micropollutants except Estriol, were removed better at pH 5-9. Estriol had the minimum adsorption rate at this pH range and the maximum adsorption rate at pH 11. This could

ED

be due to its high pKa value which makes it more adsorbable at high pH values. On the

PT

other hand, increasing the contact time improved removal efficiency. Runs # 6, 20, and 28, show that increasing contact time led to better removal efficiencies. The best

CE

removal efficiency happened at Run # 29 with contact time of 45 minutes, pH 7,

AC

Bisphenol-A concentration of 50 µg/L and MCN dose of 7 mg/L. Table 3. presents the regression analysis of Bisphenol-A adsorption. The impact of parameters can be explained with the Pr > |t| and p-value factors. Results indicated that, the interaction between pH and contact time (X1 × X2), pH and Bisphenol-A concentration (X1 × X3), pH and MCN dose (X1 × X4), were insignificant as their p-values were greater than 0.05 [22]. Furthermore, the most influencing parameter on the Bisphenol-A adsorption was MCN dose (which has the maximum t-value). Increasing 10

ACCEPTED MANUSCRIPT the MCN dose can provide more adsorption sites as the main adsorption driving force to enhance the removal efficiency. The equation of quadratic model, for the model, is showed at Eq. (3):

T

Bisphenol-A removal efficiency (%) = 10.04929 + 0.95821 X1 + 0.93459 X2 + 0.28767 X3

IP

+ 0.04934 X4 + 0.00228 X2 X3 + 0.04474 X2 X4 + 0.04445 X12 - 0.00870 X22 + 0.00890 X32 + 0.04972 X42

CR

Eq. (3)

US

Using Solver “add-in”, the optimal variables for Bisphenol-A removal (97.6%) are pH 7.09, contact time of 47 minutes, Bisphenol-A concentration 53.18 µg/L and MCN dose

AN

of 7.21 mg/L. At the optimal condition, the experimental removal is 96.8% indicating that the experimental results accurately confirm the optimum conditions that were optimized

M

by the model.

ED

3.3 Kinetic studies

PT

Fig. 2 depicts the effect of contact time on adsorption of micropollutants. The

CE

experiments were performed at the optimum conditions resulting from the model in section 3.2. The micropollutants were adsorped in the first 20 minutes. Then, gradual

AC

concentration reduction was observed until the system reached its equilibrium. Bisphenol-A, Ketoprofen, and Tonalide had the highest adsorption rate, with 98, 96 and 96% removal, respectively. This could be due to their lower molecular mass, and surface properties of MCN. The following phases can be expressed for the adsorption of the studied micropollutants by the adsorbent (Fig. 3). In the first few minutes, the micropollutants

11

ACCEPTED MANUSCRIPT were adsorbed on the surface of the MCN. In this step, the interactive forces between the micropollutant molecules and surface of the adsorbent took place. As the reaction proceeded, a gradual adsorption was observed. In this case, micropollutants occupied most of the reachable active sites through physisorption in which physical bonding of

T

the micropollutant molecules onto the surface of MCN took place. Finally, the adsorption

IP

equilibrium was observed between the adsorbates and the adsorbent when little or no

CR

change was observed in the aqueous phase concentration of the adsorbates.

US

To study the adsorption kinetics of the studied micropollutants, the pseudo-second-

AN

order model was employed (Eq. 4) [24]:

M

(4)

where qt (µg/mg) is the adsorption capacity at time t (min), k (µg/mg.min) is the second-

ED

order rate constant, and qe (µg/mg) is the adsorption capacity at equilibrium condition.

PT

The adsorption kinetic results are tabulated in Table 4. According to the results, the

CE

adsorption capacities for the studied micropollutants are in a small range and all Rsquared values are greater than 0.99. The k value for Bisphenol-A, Ketoprofen, and

AC

Tonalide was a little higher than the other studied emerging contaminants. Micropollutants with polar bonds are more likely be adsorbed easily onto MCN. As Bisphenol-A, Triclosan, Ketoprofen, and Estriol have O-H bond(s) in their chemical structure that can easily bind to MCN. In addition, the π-π interaction could be one of the most significant nonhydrophobic adsorption driving forces. In fact, organic micropollutants which contain benzene rings may be strongly adsorbed onto carbon nanotubes due π-π electron donor-acceptor interactions. Another significant factor that 12

ACCEPTED MANUSCRIPT can influence the adsorption capacity could be molecular mass as Bisphenol-A and Ketoprofen had lower molecular mass than Triclosan and Estriol. The “butterfly” structure of Bisphenol-A, with two benzene rings and its relatively low molecular mass

IP

T

made it highly absorbable onto MCN.

CR

3.4 Adsorption isotherm studies

Adsorption isotherm plots describe the leading retention or release phenomenon of a

US

substance from aqueous phase to the adsorbent surface (solid phase) at constant

AN

temperature and pH. Freundlich and Langmuir models were studied to evaluate the adsorption capacity of MCN. In the Freundlich model the binding sites have different

M

free energy of sorption, and there are plenty of adsorbent sites available on the surface

ED

of the adsorbent. In this model, heterogeneous adsorption is associated with the

PT

diversity of the adsorbate free energies.

CE

The Freundlich adsorption model is expressed in Eq. (5) [25]:

(5)

AC

where K ((µg/mg) (L/µg) 1/n) is the adsorption coefficient of the Freundlich model and 1/n is the Freundlich model intensity parameter. In this case, if 1/n is less than one, the Langmuir isotherm is normal. The amount of micropollutant adsorbed per unit of MCN (qe) (µg/mg) was calculated by dividing the amount adsorbed micropollutant by the concentration of MCN. The linear form of the Freudlich isotherm is stated below in Eq. (6) [26]:

13

ACCEPTED MANUSCRIPT (6) The Freundlich and Langmuir isotherm plots of Bisphenol-A and Metolachor are shown in Fig. 4 (a) and (b), respectively. The isotherm plots for other studied micropollutants are presented in Fig. S2 and Fig. S3. Results indicated that

IP

T

experimental data for all micropollutants were well matched with the Langmuir model

CR

(R2 >0.98). Consequently, a single layer of the micropollutants was created onto the surface of the adsorbent. On the other hand, Langmuir isotherm adopts homogeneous

US

adsorption, in which each adsorbate molecule has constant adsorption activation energy and all adsorption sites available on the surface of the adsorbent have the same

AN

attraction for the adsorbate molecule [27].

M

The Langmuir adsorption model is defined by Eq. (7) [28]:

ED

(7)

PT

where Ce is the equilibrium concentration of micropollutant in the water phase (µg/L), qe

CE

is the amount of micropollutant adsorbed on MCN at equilibrium (µg/mg), qm is the maximum theoretical sorption capacity of MCN (µg/mg), and Ka is the sorption constant

AC

at equilibrium (L/µg).

Equilibrium parameter (RL) can also be evaluated as an indicator of the Langmuir isotherm, which is defined by Eq. (8) [29]: (8)

14

ACCEPTED MANUSCRIPT where RL indicates the shape of the model in which values between 0-1 show favorable adsorption, while RL = 0, RL = 1, and RL > 1, show irreversible, linear, and unfavorable, sorption isotherms, respectively and C0 is the initial concentration of the micropollutant. Table 5 lists the adsorption isotherm results for all tested micropollutants. According to

IP

T

the results, the values of 1/n for Freundlich model were lower than one and RL values for Langmuir model were between 0-1, which show favorable sorption by MCN [30].

CR

Bisphenol-A had the maximum Langmuir’s adsorption capacity (qm) (28.55 µg/mg) in

US

comparison to the other studied compounds. It has the smallest molecular size among all studied micropollutants. Smaller molecules are more likely to be adsorbed on the

AN

surface of MCN.

M

3.5 Adsorption thermodynamics

ED

To study the nature of the adsorption reaction, the thermodynamic parameters were determined. The thermodynamic parameters for three different temperatures (25, 35

PT

and 45 oC) are presented in Table 6.

CE

According to the results, all R2 values are greater than 0.96, demonstrating that

AC

Langmuir model is in good agreement with the experimental results. Results showed that greater qm values were achieved when the temperature increased. Thus, it could be deduced that the sorption of the studied micropollutants onto MCN is endothermic. Thermodynamic parameters like the change in free energy (ΔG°), entropy (ΔS°), and enthalpy (ΔH°), were calculated for the sorption of each micropollutant onto MCN using the following equations [24, 31]: (9) 15

ACCEPTED MANUSCRIPT (10) (11) where Kc is the adsorption equilibrium constant, Cs and Ce are the concentrations of the micropollutant remained in the water phase and adsorbed by MCN (µg/L) at equilibrium

T

(µg/L), respectively. R is the universal gas constant (8.314 J/mol K), and T is

Fig. S4 and S5 present Van’t Hoff plots for

CR

vs. 1/T (Van’t Hoff plot (Fig. 5(a))).

IP

temperature (K). ΔS° and ΔH° can be calculated from the intercept and slope of ln Kc

US

adsorption of other studied compounds. Table 7 lists all calculated thermodynamic parameters. Negative ΔG° values indicate spontaneous adsorption and the degree of

AN

spontaneity enhanced at higher temperatures. Positive ΔS° values show the affinity of

M

all studied micropollutants and increasing randomness at the liquid-solid interface during the adsorption process [3, 25, 32, 33]. In addition, all the studied micropollutants

ED

had positive ΔH° values demonstrating endothermic adsorptions.

PT

3.6 The effect of competing dissolved organic matter

CE

Dissolved organic matter (DOM) usually exists in natural water bodies. Micropollutants usually coexist with DOM when entering wastewater treatment plants [34]. Therefore, it

AC

is necessary to study possible competition between DOM and mghadiriicropollutants when performing an adsorption study on micropollutants. To evaluate the effect of DOM on adsorption of the micropollutants by MCN, adsorption experiments were performed for both SRFA-added water (DOM = 8 mg-Carbon/L) and distilled water [35]. Table 8 compares the adsorption efficiency of MCN for SRFA-added and ultrapure water samples at 20 and 90 minutes of reaction time.

16

ACCEPTED MANUSCRIPT Results indicated that MCN was not able to effectively remove the micropollutants in the first 20 minutes when SRFA was added to the sample. This indicates that SRFA became dominant in the water-solid phase interface. The removal efficiencies increased slightly at the end of 90 minutes. In another study, Kim et al. [36] found 60% of DOM in

T

Han river water samples as hydrophobic and realized low adsorption of hydrophobic

IP

micropollutants due to the presence of DOM.

CR

The following steps can describe adsorption of the studied micropollutants coexistent

US

with SRFA. First, at the beginning of the experiment SRFA is competing with the micropollutants. Consequently, it occupied most reachable/active sites because of its

AN

hydrophobicity. Next, higher adsorption of micropollutants was achieved in the order of

M

their hydrophobicity characteristic (Log Kow>2.5). In this case Tonalide had the maximum removal efficiency, while Estriol had the minimum. No other tangible

ED

relationship was observed among the adsorbent, SRFA, and the micropollutants

PT

physicochemical properties to support this behavior.

CE

3.7 Adsorbent regeneration studies The disposal of saturated adsorbents is usually considered to be hazardous solid

AC

waste and sometimes is prohibited by law. Chemical regeneration methods have received much attention because they are rapid and effective [37]. In this study one base (NaOH), one acid (HCl), two organic solvents (methanol and ethanol), and one redox (H2O2) agent were evaluated to regenerate the adsorption capacity of MCN. Average adsorption efficiency of all chemical regenerants for five consecutive cycles is presented in Fig. 6. According to the results, the average removal efficiency slightly

17

ACCEPTED MANUSCRIPT decreased for ethanol, and was used though the methanol regeneration method. It was able to keep the average adsorption efficiency almost the same for all five cycles. Organic micropollutants are more soluble in alcohols because alcohols have hydroxyl groups. Filippa et al. [38] reported the solubility of Ketrophen in methanol, ethanol, and

IP

T

water 1.75, 1.85, and 6.27×10-4 mol/L, respectively. Therefore, ethanol and methanol are able to desorb the studied organic micropollutants.

In addition, decreasing

CR

molecular weight in alcohols can improve their desorption efficiency. As methanol’s

US

restoration capacity (MW = 32) is higher than ethanol’s (MW = 46). In fact smaller regenerant molecules can penetrate into the micropores of MCN more easily and finally

AN

detach the micropollutant molecule more effectively.

M

Next, NaOH and HCl were evaluated to restore the adsorption efficiency of MCN.

ED

Results indicated that HCl and NaOH could not effectively desorb micropollutants from the surface of MCN. Although HCl showed some desorbing capacities for Ketoprofen,

PT

its overall performance was not effective. This could be due to the low pka value of

CE

ketoprofen, in which it desorbs from MCN surface more easily in acidic solutions. NaOH desorbing efficiencies were trivial for all micropollutants and it could not restore the

AC

adsorbent.

Alternatively, adsorbent regeneration by hydrogen peroxide was evaluated as the method does not leave any waste at the end of the regeneration process. This process can mineralize organic micropollutants into water and carbon dioxide. According to the results, the average removal efficiency was 89.2% for the first cycle, however subsequently declined in the next cycles. It seems that hydrogen peroxide can destroy the adsorbed micropollutants and magnetic nanoparticles simultaneously. This could be 18

ACCEPTED MANUSCRIPT due to the non-selectivity nature of advanced oxidation processes (AOPs) to oxidize organic and inorganic matters. The reactive radicals were able to reach micropores of MCN and degrade iron oxide coatings as well as the adsorbed micropollutant molecules. Further experiments on regeneration of carbon nanotubes indicated that the

T

hydrogen peroxide was not able to recover the average removal efficiency more that

IP

39% (data are not shown). This indicates that the coated iron oxide on the surface of

CR

MCN is important in regeneration of MCN by hydrogen peroxide. This could be due to the in situ Fenton oxidation process on the surface of MCN as H2O2 reacts with Fe2+

US

and generate hydroxyl radical (•OH). Eq. 12 and 13 could describe the possible

ED

M

AN

reactions occurring on the surface of MCN [39, 40]:

The in situ Fenton process can produce reactive radicals and possibly improve

PT

degradation of the adsorbates. Although, this ends in the destruction of MCN to produce

AC

adversely.

CE

enough Fe2+ required for Fenton process. This finally affected the removal of MCN

Conclusions

Magnetic carbon nanotubes (MCN) were successfully synthesized as an effective sorbent to remove six micropollutants from water. A new hydrothermal method was developed to produce the adsorbent. MCN could successfully remove Metolachlor, Bisphenol-A, Triclosan, Tonalide, Ketoprofen and Estriol from aqueous solutions. The 19

ACCEPTED MANUSCRIPT optimum conditions recognized by the proposed quadratic model were:

pH 7.09,

contact time of 47 minutes, adsorbate concentration of 53.18 µg/L and adsorbent dose of 7.21 mg/L. The MCN dosage, contact time, temperature, and dissolved organic matter, all significantly affected the adsorption removal. The maximum adsorption

T

capacities of Bisphenol-A, Tonalide and Ketoprofen on the adsorbent was 28.55, 27.32,

IP

and 26.67 µg/mg at 25 oC, respectively. The thermodynamic analysis of the adsorption

CR

of the studied micropollutants indicated that the adsorption was endothermic and spontaneous. Hydrogen peroxide regeneration studies disclosed that in situ Fenton

US

reaction occurs on the surface of MCN and this can finally decrease the adsorption

AN

capacity. On the other hand, methanol regeneration experiments showed that the

ED

M

adsorbent could be regenerated with a minor loss in its adsorption capacity.

Acknowledgements

PT

The authors want to thank the department of Civil and Environmental Engineering at

AC

assistantship.

CE

Michigan Technological University, USA for financial support as graduate teaching

20

ACCEPTED MANUSCRIPT References: [1] K. Kümmerer, Pharmaceuticals in the environment: sources, fate, effects and risks, Springer Science & Business Media, 2008. [2] R.P. Schwarzenbach, B.I. Escher, K. Fenner, T.B. Hofstetter, C.A. Johnson, U. Von

IP

T

Gunten, B. Wehrli, The challenge of micropollutants in aquatic systems, Science, 313 (2006) 1072-1077.

CR

[3] V. Matamoros, J. García, J.M. Bayona, Organic micropollutant removal in a full-scale

US

surface flow constructed wetland fed with secondary effluent, Water research, 42 (2008) 653-660.

AN

[4] L. Hernández-Leal, H. Temmink, G. Zeeman, C. Buisman, Removal of

M

micropollutants from aerobically treated grey water via ozone and activated carbon, Water Research, 45 (2011) 2887-2896.

ED

[5] M. Baghdadi, E. Ghaffari, B. Aminzadeh, Removal of carbamazepine from municipal

PT

wastewater effluent using optimally synthesized magnetic activated carbon: Adsorption and sedimentation kinetic studies, Journal of Environmental Chemical Engineering, 4

CE

(2016) 3309-3321.

AC

[6] M. Guillemot, J. Mijoin, S. Mignard, P. Magnoux, Adsorption of Tetrachloroethylene on Cationic X and Y Zeolites:  Influence of Cation Nature and of Water Vapor, Industrial & Engineering Chemistry Research, 46 (2007) 4614-4620. [7] Z.M. Nagy, M. Molnar, I. Fekete-Kertesz, I. Molnar-Perl, E. Fenyvesi, K. Gruiz, Removal of emerging micropollutants from water using cyclodextrin, The Science of the total environment, 485-486 (2014) 711-719.

21

ACCEPTED MANUSCRIPT [8] P.A. Quinlivan, L. Li, D.R. Knappe, Effects of activated carbon characteristics on the simultaneous adsorption of aqueous organic micropollutants and natural organic matter, Water research, 39 (2005) 1663-1673. [9] M.T. Amin, A.A. Alazba, U. Manzoor, A Review of Removal of Pollutants from

T

Water/Wastewater Using Different Types of Nanomaterials, Advances in Materials

IP

Science and Engineering, 2014 (2014) 24.

CR

[10] J.J. Pignatello, E. Oliveros, A. MacKay, Advanced oxidation processes for organic contaminant destruction based on the Fenton reaction and related chemistry, Critical

US

reviews in environmental science and technology, 36 (2006) 1-84.

AN

[11] S. Skandari, A. Torabian, G. Nabi Bidhendi, M. Baghdadi, B. Aminzadeh, Preparation of engineered carbon nanotube materials and its application in water

M

treatment for removal of hydrophobic natural organic matter (NOM), Desalination and

ED

Water Treatment, 57 (2016) 24855-24866.

[12] D. Hermosilla, N. Merayo, A. Gasco, A. Blanco, The application of advanced

PT

oxidation technologies to the treatment of effluents from the pulp and paper industry: a

CE

review, Environmental science and pollution research international, 22 (2015) 168-191. [13] I. Oller, S. Malato, J.A. Sánchez-Pérez, Combination of Advanced Oxidation

AC

Processes and biological treatments for wastewater decontamination—A review, Science of The Total Environment, 409 (2011) 4141-4166. [14] B.A. E. Aghdam, M. Baghdadi, M.A. Fard, Removal of BTEX from aqueous solutions by paper mill sludge-based activated carbon, Journal of Advances in Chemistry, 11 (2015) 3416-3432.

22

ACCEPTED MANUSCRIPT [15] L. Ai, H. Huang, Z. Chen, X. Wei, J. Jiang, Activated carbon/CoFe 2 O 4 composites: facile synthesis, magnetic performance and their potential application for the removal of malachite green from water, Chemical Engineering Journal, 156 (2010) 243-249.

T

[16] A. Jafari Kang, M. Baghdadi, A. Pardakhti, Removal of cadmium and lead from

IP

aqueous solutions by magnetic acid-treated activated carbon nanocomposite,

CR

Desalination and Water Treatment, 57 (2016) 18782-18798.

[17] G. Gao, Q. Zhang, Z. Hao, C.D. Vecitis, Carbon nanotube membrane stack for sequential

regenerative

electro-Fenton,

US

flow-through

science

&

AN

technology, 49 (2015) 2375-2383.

Environmental

[18] A.R. Khataee, M. Zarei, A.R. Khataee, Electrochemical Treatment of Dye Solution

M

by Oxalate Catalyzed Photoelectro‐Fenton Process Using a Carbon Nanotube‐PTFE

ED

Cathode: Optimization by Central Composite Design, CLEAN–Soil, Air, Water, 39 (2011) 482-490.

PT

[19] H. Gao, S. Zhao, X. Cheng, X. Wang, L. Zheng, Removal of anionic azo dyes from

CE

aqueous solution using magnetic polymer multi-wall carbon nanotube nanocomposite as adsorbent, Chemical Engineering Journal, 223 (2013) 84-90.

AC

[20] M. Alizadeh Fard, A. Vosoogh, B. Barkdoll, B. Aminzadeh, Using polymer coated nanoparticles for adsorption of micropollutants from water, Colloids and Surfaces A: Physicochemical and Engineering Aspects, 531 (2017) 189-197. [21] R.A. Bini, R.F.C. Marques, F.J. Santos, J.A. Chaker, M. Jafelicci Jr, Synthesis and functionalization

of

magnetite

nanoparticles

with

different

amino-functional

alkoxysilanes, Journal of Magnetism and Magnetic Materials, 324 (2012) 534-539.

23

ACCEPTED MANUSCRIPT [22] S.K. Ghadiri, S. Nasseri, R. Nabizadeh, M. Khoobi, S. Nazmara, A.H. Mahvi, Adsorption of nitrate onto anionic bio-graphene nanosheet from aqueous solutions: Isotherm and kinetic study, Journal of Molecular Liquids, 242 (2017) 1111-1117. [23] Y.-L. Zhang, J. Zhang, C.-M. Dai, X.-F. Zhou, S.-G. Liu, Sorption of carbamazepine

T

from water by magnetic molecularly imprinted polymers based on chitosan-Fe 3 O 4,

IP

Carbohydrate polymers, 97 (2013) 809-816.

CR

[24] P.S. Bäuerlein, T.L. ter Laak, R.C.H.M. Hofman-Caris, P. de Voogt, S.T.J. Droge, Removal of charged micropollutants from water by ion-exchange polymers – Effects of

US

competing electrolytes, Water Research, 46 (2012) 5009-5018.

AN

[25] A. Dada, A. Olalekan, A. Olatunya, O. Dada, Langmuir, Freundlich, Temkin and Dubinin–Radushkevich isotherms studies of equilibrium sorption of Zn2+ unto

M

phosphoric acid modified rice husk, IOSR Journal of Applied Chemistry, 3 (2012) 38-45.

ED

[26] S.-C. Tsai, K.-W. Juang, Comparison of linear and nonlinear forms of isotherm models for strontium sorption on a sodium bentonite, Journal of Radioanalytical and

PT

Nuclear Chemistry, 243 (2000) 741-746.

CE

[27] S. Ghadiri, R. Nabizadeh, A. Mahvi, S. Nasseri, A. Mesdaghinia, S. Talebi, Potential of granulated modified nanozeolites Y for MTBE removal from aqueous

AC

solutions: Kinetic and isotherm studies, Polish Journal of Chemical Technology, 14 (2012) 1-8.

[28] K.Y. Foo, B.H. Hameed, Insights into the modeling of adsorption isotherm systems, Chemical Engineering Journal, 156 (2010) 2-10.

24

ACCEPTED MANUSCRIPT [29] B.C. McCool, A. Rahardianto, Y. Cohen, Antiscalant removal in accelerated desupersaturation of RO concentrate via chemically-enhanced seeded precipitation (CESP), Water Research, 46 (2012) 4261-4271. [30] D.-P. Li, Y.-R. Zhang, X.-X. Zhao, B.-X. Zhao, Magnetic nanoparticles coated by

T

aminoguanidine for selective adsorption of acid dyes from aqueous solution, Chemical

IP

engineering journal, 232 (2013) 425-433.

CR

[31] K. Ebie, F. Li, Y. Azuma, A. Yuasa, T. Hagishita, Pore distribution effect of activated carbon in adsorbing organic micropollutants from natural water, Water Research, 35

US

(2001) 167-179.

AN

[32] A. Alsbaiee, B.J. Smith, L. Xiao, Y. Ling, D.E. Helbling, W.R. Dichtel, Rapid removal of organic micropollutants from water by a porous β-cyclodextrin polymer, Nature, 529

M

(2016) 190-194.

ED

[33] Y.S. Ho, G. McKay, Pseudo-second order model for sorption processes, Process Biochemistry, 34 (1999) 451-465.

PT

[34] M.A. Fard, B. Aminzadeh, M. Taheri, S. Farhadi, M. Maghsoodi, MBR excess

CE

sludge reduction by combination of electrocoagulation and Fenton oxidation processes, Separation and Purification Technology, 120 (2013) 378-385.

AC

[35] M. Alizadeh Fard, B. Aminzadeh, H. Vahidi, Degradation of petroleum aromatic hydrocarbons using TiO2 nanopowder film, Environmental technology, 34 (2013) 11831190. [36] S.W. Nam, D.J. Choi, S.K. Kim, N. Her, K.D. Zoh, Adsorption characteristics of selected hydrophilic and hydrophobic micropollutants in water using activated carbon, J Hazard Mater, 270 (2014) 144-152.

25

ACCEPTED MANUSCRIPT [37] S. Lee, J.-S. Lee, M.-K. Song, J.-C. Ryu, B. An, C.-G. Lee, C. Park, S.-H. Lee, J.W. Choi, Effective regeneration of an adsorbent for the removal of organic contaminants developed based on UV radiation and toxicity evaluation, Reactive and Functional Polymers, 95 (2015) 62-70.

T

[38] M.A. Filippa, G.M. Melo, E.I. Gasull, Ketoprofen Solubility in Organic Solvents and

IP

Aqueous Co-solvent Systems: Interactions and Thermodynamic Parameters of

CR

Solvation.

[39] M. Alizadeh Fard, A. Torabian, G.R.N. Bidhendi, B. Aminzadeh, Fenton and photo-

US

Fenton oxidation of petroleum aromatic hydrocarbons using nanoscale zero-valent iron,

AN

Journal of Environmental Engineering, 139 (2013) 966-974. [40] J. Anotai, M.-C. Lu, P. Chewpreecha, Kinetics of aniline degradation by Fenton and

AC

CE

PT

ED

M

electro-Fenton processes, Water Research, 40 (2006) 1841-1847.

26

ACCEPTED MANUSCRIPT Figure captions: Fig 1. The XRD pattern of MCN (a) and the FT-IR spectrum for MCN and acid washed CN (b). Fig 2. Effect of contact time on the micropollutants adsorption. Error bars show the

IP

T

minimum and maximum adsorption capacity.

CR

Fig. 3 Conceptual model of adsorption of the micropollutants onto MCN.

US

Fig. 4 Freundlich (a) and Langmuir (b) isotherm plots for the adsorption of Metolachor and Bisphenol-A onto MCN.

AN

Fig 5. Van’t Hoff plot for adsorption of Metolachor and Bisphenol-A onto MCN.

M

Fig 6. Average removal efficiencies of the studied micropollutants onto MCN by multiple

ED

cycles of regeneration. Error bars indicate the minimum and maximum removal

AC

CE

PT

efficiencies.

27

ACCEPTED MANUSCRIPT Tables: Table 1. Experimental ranges and independent variable values used in CCD design. Unit

Symbol

Coded values of variables -α

-1

0

11

45

55

50

75

90

7

11

13

X1

3

5

7

Contact time

min

X2

5

15

30

X3

10

25

X4

1

CR

US

Mg/L

3

AC

CE

PT

ED

M

AN

MCN dose

IP

-

concentration

28

+α

9

Solution pH

Micropollutant µg/L

1

T

Variable

ACCEPTED MANUSCRIPT Table 2. Experimental and modeled removal efficiencies for Bisphenol-A. Independent Run # variable

X1

X2 X3 X4

24.8

31.9

22

7

45 50 7

95.4

92.3

3

30 15 1

20.1

38.2

23

7

45 50 3

85.1

79.4

3

5

15 50 3

41.6

56.6

24

5

45 50 7

4

5

15 15 3

40.2

33.6

25

7

45 50 7

96.3

92.3

5

9

30 50 7

84.9

85.0

26

7

15 10 3

44.2

35.1

6

7

45 50 7

95.1

92.3

27

7

45 50 7

95.8

92.3

7

11 45 50 7

94.4

99.3

28

7

30 50 7

90.3

81.6

8

9

45 50 7

92.1

95.6

29

45 50 7

96.4

92.3

9

5

30 75 3

94.2

99.1

10

3

45 50 7

93.2

86.7

11

5

30 50 7

90.4

12

3

30 50 11

81.9

13

7

30 10 3

51.2

14

9

5

84.9

15

5

30 25 7

16

11 30 25 11

17

9

18

3

19

7

94.3

IP

US

2

89.3

9

30 50 7

88.1

85.0

31

7

45 50 7

95.9

92.3

78.7

32

7

45 50 7

95.7

92.3

87.8

33

7

45 50 1

49.8

44.2

45.6

34

9

45 50 7

94.8

95.6

97.9

35

7

30 25 7

68.6

60.7

70.8

57.8

36

7

45 10 7

54.2

62.8

91.6

78.2

37

7

45 25 3

76.1

59.1

15 25 3

45.7

44.3

38

3

30 50 3

67.5

65.8

15 50 11

54.9

70.6

39

7

45 50 7

96.0

92.3

3

5

45.2

61.2

40

7

45 50 7

96.1

92.3

20

7

15 50 7

67.2

67.1

41

7

30 50 9

91.2

87.3

21

5

30 10 3

25.9

42.6

42

7

45 50 7

96.2

92.3

50 13

ED

PT

75 11

M

30

CE

11 5

AC

1

T

10 1

CR

X4

Modeled Experimental Removal Removal (%) (%)

AN

X1 X2 X3

Independent Run # variable

Modeled Experimental Removal Removal (%) (%)

X1: Solution pH, X2: Contact time (min), X3: Initial Bisphenol-A concentration (µg/L), X4: MCN dosage (mg/L)

29

ACCEPTED MANUSCRIPT

t-Value

10.04929

0.13726

2.41521

2.11×10-8

0.95891

0.00861

0.00471

4.34×10-12

0.93459

0.00978

0.00191

6.13×10-05

0.28767

0.00765

0.00192

0.04934

0.00157

0.00229

0.00057

0.04475

0.00120

0.00041

0.04

0.04446

0.00101

0.00018

1.71×10-10

-0.00870

0.00021

0.00007

0.02

0.00082

0.00031

0.04

0.00304

0.00102

0.01

30

IP

p-Value

0.02 1.32×10-12

0.00032

1.42×10-09

CR

0.00831

US

CE

PT

ED

0.00891 0.04973

T

Std. error

AC

Intercept

Coeff. estimate

M

Parameter

AN

Table 3. Regression analysis for Bisphenol-A removal.

ACCEPTED MANUSCRIPT Table 4 Adsorption kinetic parameters modeled by pseudo second-order equation for removal of the studied micropollutants by MCN.

Triclosan

5.6

0.06

0.993

Bisphenol-A

6.9

0.08

0.995

Tonalide

6.4

0.07

0.994

Metolachlor

5.3

0.06

0.994

Ketoprofen

6.5

0.08

0.993

Estriol

5.2

0.06

0.992

IP

(µg/mg. min)

CR

(µg/mg)

AN

US

k

T

R2

qe

AC

CE

PT

ED

M

Compound

31

ACCEPTED MANUSCRIPT Table 5 Langmuir and Freundlich constants for the adsorption of studied micropollutants on MCN. Freundlich parameters

Langmuir parameters

Micropollutant K

qm

2

1/n

1/n

R2

R

IP

0.925

0.70

0.864

0.66

0.856

19.68

0.62

0.866

26.67

0.69

0.875

18.24

0.65

0.881

0.62

0.925

20.53

Bisphenol-A

0.48

0.7

0.864

28.55

Tonalide

0.61

0.66

0.856

27.32

Triclosan

0.71

0.62

0.866

Ketoprofen

0.5

0.69

0.875

Estriol

0.67

0.65

0.881

AC

CE

PT

ED

M

AN

CR

0.66

US

0.62

Metolachlor

32

T

(µg/mg)

ACCEPTED MANUSCRIPT

Micropollutant

T (oC)

qm (µg/mg)

R2

Metolachor

25

20.53

0.985

35

31.31

0.982

45

35.27

T

Table 6 Langmuir fitting parameters for MCN at different temperatures.

25

28.55

35

37.72

45

42.34

25

27.32

35

IP CR

0.975

19.68

0.991

25.65

0.986

30.32

0.976

26.67

0.981

35

34.72

0.969

45

39.27

0.988

25

18.24

0.991

35

23.50

0.981

45

28.39

0.978

M ED

PT

45

CE

25

AC

0.992

40.24

35

Estriol

0.989

0.966

25

Ketoprofen

0.971

36.78

45 Triclosan

0.982

US

Tonalide

AN

Bisphenol-A

0.979

33

ACCEPTED MANUSCRIPT Table 7 Thermodynamic parameters for the adsorption of the studied micropollutants onto MCN. ΔGo (kJ/mol) ΔSo (J/mol K)

298 K

308 K

318 K

Metolachor

78.66

20.42

-1.10

-1.72

-2.81

Bisphenol-A

142.91

40.89

-2.36

-3.40

-4.79

Tonalide

151.48

42.37

-2.31

-3.82

-5.63

Triclosan

67.62

19.28

-1.42

-2.20

-2.44

Ketoprofen

135.62

36.71

-2.21

-3.32

-4.62

Estriol

71.09

20.33

-0.96

-1.71

-2.46

AC

CE

PT

ED

M

AN

US

CR

IP

T

Micropollutant ΔHo (kJ/mol)

34

ACCEPTED MANUSCRIPT Table 8 the effect of dissolved organic matter on adsorption removal of the tested micropollutants at 20 and 90 minutes of contact time. Contact time of 20 minutes

Contact time of 90 minutes

with ultrapure water

water

SRFA

SRFA

T

water

Metolachlor

65

18

89

38

Bisphenol-A

82

23

99

Tonalide

76

20

97

47

Triclosan

70

15

90

32

Ketoprofen

75

19

98

36

Estriol

64

12

87

30

AC

CE

PT

ED

M

AN

US

CR

ultrapure water

IP

Micropollutant % removal from % removal from % removal from % removal from

35

42

with

ACCEPTED MANUSCRIPT Supplementary materials: Using recyclable magnetic carbon nanotube to remove micropollutants from aqueous solutions

IP

T

Mohammad Alizadeh Fard* and Brian Barkdoll

CR

Department of Civil and Environmental Engineering, Michigan Technological University,

AN

US

1400 Townsend Dr., Houghton, MI 49931, USA

*Corresponding author. Tel.: +1 906 231 3654, fax: +1 906 487 2943.

AC

CE

PT

ED

M

Email address: [email protected] (M. Alizadeh Fard)

36

ACCEPTED MANUSCRIPT Table S1 Molecular description of the micropollutants. Compound

Metolachlor

Bisphenol-A

Tonalide

Triclosan

Ketoprofen

Estriol

Chemical formula

C15H22ClNO2

C15H16O2

C18H26O

C12H7Cl3O2

C16H14O3

C18H24O3

228.29

258.4

289.53

254.28

288.39

51

119

Molecular

mass

T

283.8 (g/mol) 530

192

1.8

10

Log Kow

3.13

2.2-3.4

5.9–6.3

4.76

2.99

2.55

Log Koc

1.34-3.36

2.06-3.59

3.80–4.80

3.38-4.20

2.12

3.08

Pka

-

9.6

-

7.9

4.4

10.5

AC

CE

PT

ED

M

AN

US

CR

IP

Solubility (mg/L)

37

ACCEPTED MANUSCRIPT

Run #

Experimental Modeled Removal (%) Removal (%)

1

17.5

25.6

22

90.5

87.7

2

16.4

28.3

23

80.2

74.8

3

37.5

50.1

24

89.4

84.7

4

35.3

30.4

25

91.4

87.7

5

84.9

85.0

26

39.3

30.5

6

89.6

91.4

27

90.9

87.7

7

85.4

91.3

28

85.4

77.0

8

82.1

85.2

29

91.5

9

86.2

89.3

30

83.2

10

86.2

86.8

31

91

87.7

11

84.2

79.7

32

90.8

87.7

12

82.9

85.4

33

44.9

39.6

13

49.1

42.4

34

89.9

91.0

14

84.9

92.1

35

63.7

56.1

15

66.2

55.8

36

49.3

58.2

16

88.6

74.3

37

71.2

54.5

17

41.2

40.3

38

62.6

61.2

18

44.9

57.1

39

91.1

87.7

19

40.2

52.3

40

91.2

87.7

20

60.1

65.3

41

86.3

82.7

21

22.4

39.5

42

91.3

87.7

AC

CE

38

IP

CR

US

AN

M

ED

Experimental Modeled

T

Run # Removal (%) Removal (%)

PT

Table S2 Experimental and modeled removal efficiencies for Metolachlor.

87.7 80.4

ACCEPTED MANUSCRIPT Table S3 Experimental and modeled removal efficiencies for Tonalide.

Run #

Experimental Modeled Removal (%) Removal (%)

1

24.4

31.2

22

94.2

90.8

2

19.7

37.5

23

83.9

77.9

3

41.2

55.9

24

93.1

87.8

4

39.8

32.9

25

95.1

90.8

5

84.5

84.3

26

43

33.6

6

94.7

91.6

27

94.6

90.8

7

94

98.6

28

89.1

80.1

8

91.7

94.9

29

95.2

9

93.8

98.4

30

86.9

10

92.8

86

31

94.7

90.8

11

90

78

32

94.5

90.8

12

81.5

87.1

33

48.6

42.7

13

50.8

44.9

34

93.6

94.1

14

84.5

97.2

35

67.4

59.2

15

70.4

57.1

36

53

61.3

16

91.2

77.5

37

74.9

57.6

17

45.3

43.6

38

66.3

64.3

18

54.5

69.9

39

94.8

90.8

19

44.8

60.5

40

94.9

90.8

20

66.8

66.4

41

90

85.8

21

25.5

41.9

42

95

90.8

AC

CE

PT

39

IP

CR

US

AN

M

ED

Experimental Modeled

T

Run # Removal (%) Removal (%)

90.8 83.5

ACCEPTED MANUSCRIPT

Run #

Experimental Modeled Removal (%) Removal (%)

1

16.7

25.1

22

89.6

86.4

2

15.6

27.8

23

79.3

73.5

3

36.7

49.6

24

88.5

83.4

4

34.5

29.9

25

90.5

86.4

5

84.1

84.5

26

38.4

29.2

6

88.8

90.9

27

90

86.4

7

84.6

90.8

28

84.5

75.7

8

81.3

84.7

29

90.6

9

85.4

88.8

30

82.3

10

85.4

86.3

31

90.1

86.4

11

83.4

79.2

32

89.9

86.4

12

82.1

84.9

33

44

38.3

13

48.3

41.9

34

89

89.7

14

84.1

91.6

35

62.8

54.8

15

65.4

55.3

36

48.4

56.9

16

87.8

73.8

37

70.3

53.2

17

40.4

39.8

38

61.7

59.9

18

44.1

56.6

39

90.2

86.4

19

39.4

51.8

40

90.3

86.4

20

59.3

64.8

41

85.4

81.4

21

21.6

39

42

90.4

86.4

AC

CE

40

IP

CR

US

AN

M

ED

Experimental Modeled

T

Run # Removal (%) Removal (%)

PT

Table S4 Experimental and modeled removal efficiencies for Triclosan.

86.4 79.1

ACCEPTED MANUSCRIPT

Run #

Experimental Modeled Removal (%) Removal (%)

1

24.2

31.7

22

94.3

90.6

2

19.5

38.0

23

84

77.7

3

41

56.4

24

93.2

87.6

4

39.6

33.4

25

95.2

90.6

5

84.3

84.8

26

43.1

33.4

6

94.5

92.1

27

94.7

90.6

7

93.8

99.1

28

89.2

79.9

8

91.5

95.4

29

95.3

9

93.6

98.9

30

87

10

92.6

86.5

31

94.8

90.6

11

89.8

78.5

32

94.6

90.6

12

81.3

87.6

33

48.7

42.5

13

50.6

45.4

34

93.7

93.9

14

84.3

97.7

35

67.5

59.0

15

70.2

57.6

36

53.1

61.1

16

91

78.0

37

75

57.4

17

45.1

44.1

38

66.4

64.1

18

54.3

70.4

39

94.9

90.6

19

44.6

61.0

40

95

90.6

20

66.6

66.9

41

90.1

85.6

21

25.3

42.4

42

95.1

90.6

AC

CE

41

IP

CR

US

AN

M

ED

Experimental Modeled

T

Run # Removal (%) Removal (%)

PT

Table S5 Experimental and modeled removal efficiencies for Ketoprofen.

90.6 83.3

AC

CE

PT

ED

M

AN

US

CR

IP

T

ACCEPTED MANUSCRIPT

Fig. S2. Freundlich (a) and Langmuir (b) isotherms for the adsorption of Tonalide and Triclosan onto MCN.

42

AC

CE

PT

ED

M

AN

US

CR

IP

T

ACCEPTED MANUSCRIPT

Fig. S3. Freundlich (a) and Langmuir (b) isotherms for the adsorption of Ketoprofen and Estriol onto MCN.

43

AN

US

CR

IP

T

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

M

Fig. S4 Van’t Hoff plot for adsorption of Tonalide and Triclosan onto MCN.

44

AN

US

CR

IP

T

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

M

Fig. S5 Van’t Hoff plot for adsorption of Ketoprofen and Estriol onto MCN.

45

AC

CE

PT

ED

M

AN

US

CR

IP

T

ACCEPTED MANUSCRIPT

Fig. 1

46

AN

US

CR

IP

T

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

M

Fig. 2

47

AC

CE

PT

ED

M

AN

US

CR

IP

T

ACCEPTED MANUSCRIPT

Fig. 3

48

US

CR

IP

T

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

M

AN

Fig. 4

49

AC

CE

PT

ED

M

AN

US

CR

IP

T

ACCEPTED MANUSCRIPT

Fig. 5

50

AN

US

CR

IP

T

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

M

Fig. 6

51

M

AN

US

CR

IP

T

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

Graphical abstract

52

ACCEPTED MANUSCRIPT Highlights



Magnetic carbon nanotubes (MCN) were synthesized using a new hydrothermal method. MCN adsorbed more than 92% of the studied micropollutants.



Prediction models were developed for the adsorption of the tested adsorbates.



Methanol regeneration experiments ensured recyclability of the adsorbent.

AC

CE

PT

ED

M

AN

US

CR

IP

T



53