Adsorptive removal of dibenzothiophene sulfone from fuel oil using clay material adsorbents

Accepted Manuscript Adsorptive removal of dibenzothiophene sulfone from fuel oil using clay material adsorbents

Angelo Earvin Sy Choi, Susan Roces, Nathaniel Dugos, Aries Arcega, Meng-Wei Wan PII:

S0959-6526(17)31003-X

DOI:

10.1016/j.jclepro.2017.05.072

Reference:

JCLP 9611

To appear in:

Journal of Cleaner Production

Received Date:

28 December 2016

Revised Date:

13 April 2017

Accepted Date:

12 May 2017

Please cite this article as: Angelo Earvin Sy Choi, Susan Roces, Nathaniel Dugos, Aries Arcega, Meng-Wei Wan, Adsorptive removal of dibenzothiophene sulfone from fuel oil using clay material adsorbents, Journal of Cleaner Production (2017), doi: 10.1016/j.jclepro.2017.05.072

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.

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Highlights: 

FTIR, SEM, BET, zeta potential were used for clay adsorbents characterization.



Adsorption capacity followed the order activated clay > bentonite > kaolinite.



Stronger acidic conditions provide higher adsorption capacity.



The Freundlich model aptly describes dibenzothiophene sulfone adsorption.



The adsorption process exhibited a chemical adsorption and an endothermic process.

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Word Count: 6702 Adsorptive removal of dibenzothiophene sulfone from fuel oil using clay material adsorbents Angelo Earvin Sy Choia,b, Susan Rocesa, Nathaniel Dugosa, Aries Arcegac, Meng-Wei Wand,* a Chemical

Engineering Department, De La Salle University, 2401 Taft Ave, Manila, Philippines

0922 b Center

for Clean Technology and Resource Recycling, University of Ulsan, 93 Dehakro, Ulsan,

South Korea 680-749 c

Department of Chemical Engineering, University of the Philippines-Diliman, Quezon City

1101, Philippines d Department

of Environment Engineering and Science, Chia Nan University of Pharmacy and

Science, Tainan, Taiwan 71710

*Corresponding author: Tel: +886-6-266-0615.

Fax: +886-6-366-2668.

E-mail: [email protected]

ABSTRACT Dibenzothiophene sulfone (DBTO) adsorption utilizing clay material adsorbents such as activated clay, bentonite and kaolinite were investigated in this study. The properties of each adsorbent were characterized using Fourier transform infrared spectroscopy, scanning electron microscope, Brunauer, Emmett and Teller surface area analyzer and zeta potential. The effects of pH (1.0 to 5.0), contact time (5 min to 48 hr), temperature (298 to 328 K) and initial

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concentration (10 to 1000 mg/L) were examined in a batch adsorption process to determine the suitability of clay material adsorbents in DBTO removal. Kinetic models of pseudo-first order, pseudo-second order and intraparticle diffusion were used to assess the experimental data. Results showed high correlation to the pseudo-second order kinetic model (R2>0.99) that implies chemisorption as the rate-limiting step. Isotherm models of Langmuir, Freundlich, Temkin and Dubnin-Radushkevich were used to evaluate the equilibrium experimental data. DBTO adsorption showed a good fit towards the Freundlich isotherm (R2>0.99) which indicates a heterogeneous adsorption onto the adsorbent. Thermodynamic studies indicated that DBTO adsorption onto clay material adsorbents was endothermic. Utilizing the adsorbent of activated clay was spontaneous while kaolinite was non-spontaneous at 298 to 328 K. Bentonite was found to be only non-spontaneous at 298K. Activated clay displayed a good potential in adsorbing sulfones to achieve low sulfur fuel oil in an oxidative desulfurization process.

Keywords: Activated clay; Batch adsorption; Bentonite; Dibenzothiophene sulfone; Kaolinite

1. Introduction About 82% of the energy sources worldwide are derived from fossil fuel and half of this comes from petroleum (Al-abduly and Sharma, 2014). The maximum sulfur concentration set by the European Union (EU) for fuel oil is 10-ppm (EUR-Lex, 2007). United States Environmental Protection Agency (USEPA) has set sulfur standards of 30-ppm and 15-ppm for gasoline and diesel oil, respectively (EPA, 2012a, 2012b). Stringent environmental regulations are implemented in recent years to avoid the adverse effects associated to organic sulfur compounds (OSCs). OSCs in fuel oils are converted to sulfur oxides (SOX) and sulfate particulate matter

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upon combustion which is detrimental to both the environment and human health. The presence of SOX contributes to the formation of condensation nuclei and is a key precursor to acid rain (Sharma et al., 2011). Sulfate particulate matter contributes to risks of air pollution that causes respiratory problems and ischemic heart disease (Hampel et al., 2015; Srivastava, 2012). OSCs in fuels can also poison the catalyst in engines; corrode parts for internal combustion and lower combustion efficiency (Jiang et al., 2016). The current conventional method for the removal of OSCs in fuel oil is hydrodesulfurization (HDS). HDS requires high temperature (573-723 K), high hydrogen pressure (3.0-5.0 MPa) and expensive catalysts (CoMo/Al2O3 or NiMo/Al2O3) to achieve low sulfur concentrations in fuel oil (Srivastava, 2012). This hydrotreatment process used at a large-scale translates to high operating cost in the refining process (Chen et al., 2010). The carbon to sulfur bond is destroyed utilizing hydrogen with a catalyst in HDS to form hydrogen sulfide and a sulfur free hydrocarbon (Song and Ma, 2004). However, HDS is not effective towards heterocyclic sulfur compounds present in fuel oil such as alkylated dibenzothiophene (DBT) (Srivastava, 2012). A prehydrotreated petroleum-based fuel typically contains 1000 ppm sulfur content and 85 % of the overall sulfur are thiophenic sulfur compounds (Trakarnpruk and Rujiraworawut, 2009). Recent studies combines the selective oxidation and extraction processes at low operating condition to achieve low sulfur fuel oil which is known as oxidative desulfurization (ODS) (Chen et al., 2010; Etemadi and Yen, 2007a; Lu et al., 2014). This process is often coupled with an ultrasound probe in various oxidation systems of peracetic acid (Bolla et al., 2012; Mello et al., 2009), phosphotungstic acid/H2O2 (Chen et al., 2012, 2010; Mei et al., 2003; Wan et al., 2012), ferrate (Choi et al., 2016c, 2014) and Fenton’s reagent (Dai et al., 2008) to accelerate the oxidation of sulfur compounds. Furthermore, the ODS process has also been utilized with a high

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shear mixer at oxidations systems of H2O2 (Fox et al., 2015), ferrate (Choi et al., 2016a), polyoxometalate/H2O2 (Choi et al., 2016b) and phosphotungstic acid/H2O2 (Lu et al., 2014) to enhance its oxidation efficiency. The ODS process can selectively oxidize OSCs including heterocyclic sulfur compounds to its sulfone forms such as DBT to dibenzothiophene sulfone (DBTO). This is due to the electrophilic addition of oxygen towards sulfur without breaking the C-C bonds (Song and Ma, 2003). Oxidized sulfur compounds have a higher polarity as compared to the hydrocarbons present in fuel oils which can be easily removed through either liquid-liquid extraction or solid adsorption (Liu et al., 2008; Mello et al., 2009). The method of liquid-liquid extraction separates compounds based on the relative solubility of two immiscible liquids. This can separate highly polar sulfones from the nonpolar constituents present in oxidized fuel oil using a polar solvent such as acetonitrile (Chen et al., 2010). Several disadvantages associated in the utilization of acetonitrile includes its explosiveness, nonreusability and toxicity which are a serious drawback in solvent extraction (Chen et al., 2010). An alternative method in removing sulfones is through solid adsorption which does not require the use of additional chemicals (Etemadi and Yen, 2007b). Solid adsorption is favored over solvent extraction due to having a higher removal rate and lesser environmental hazards (Chen et al., 2010; Etemadi and Yen, 2007a; Lu et al., 2014). The study of Chen et al. (2010) showed higher sulfone removal efficiency using the method of adsorption than extraction by a difference of 37.9% and 40.7% for diesel oil and pyrolysis oil, respectively. Lu et al. (2014) reported complete sulfone removal in diesel oil through an adsorption process but retained 216-ppm in a liquid-liquid extraction process from an initial sulfur concentration of 1430-ppm. According to Etemadi and Yen (2007a), the adsorbent utilized in solid adsorption is thirty-three times less consumed in terms of material usage than that of the solvent used in liquid-liquid extraction of

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sulfones. Previous studies have utilized various adsorbents such as alumina (Etemadi and Yen, 2007a, 2007c; Lu et al., 2013), modified chitosan (Lu et al., 2015, 2013), granular activated carbon (Lu et al., 2013) and modified activated carbon (Lu et al., 2013) for sulfone adsorption. However, the use of these adsorbents is quite expensive and modification of adsorbents incurs additional costs and complicated preparation procedures. Clay material adsorbents are made of hydrous aluminosilicates sheets and have relatively large specific surface areas (Futalan et al., 2011a, 2011c). This type of adsorbents are low-cost, abundant, and chemically and mechanically stable (Futalan et al., 2011a, 2011c). Clay material adsorbents are often used to aid the removal of heavy metals such as arsenic (Arida et al., 2016), chromium (El-korashy et al., 2016), copper (Chen et al., 2015; Futalan et al., 2011b, 2011c), indium (Calagui et al., 2014), lead (El-korashy et al., 2016; Futalan et al., 2011b), manganese (El-korashy et al., 2016) and nickel (Futalan et al., 2011a, 2011b). However, there are no reports currently available in literature on the specific mechanism and utilization of different clay material adsorbents to remove sulfones such as DBTO. In this study, DBTO removal in a model fuel oil using clay material adsorbents were investigated. The commercially available clay material adsorbents such as activated clay, bentonite and kaolinite were examined through a batch adsorption method. The effect of pH, temperature and initial concentration were studied to evaluate its adsorption capacities at different parametric conditions. A comparative assessment of the physical properties, adsorption kinetics, adsorption isotherms and thermodynamic parameters were examined to evaluate the specific DBTO adsorption mechanisms onto clay material adsorbents. 2. Experimental 2.1.

Materials

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Chemicals used were analytical grade without further purification. Dibenzothiophene sulfone (C12H8O2S, 98% purity) was acquired from E.Comis Technology Co., Ltd. (Taiwan). Hydrochloric acid (HCl, 37% fuming), potassium bromide (KBr) and toluene (C7H8, 0.99 mass fractions) were purchased from Merck Chemical Company (USA). Sodium hydroxide (NaOH, 98% purity) was obtained from Shimakyu’s Pure Chemicals (Osaka, Japan). Activated clay was supplied by Xinxin Chemical Co., Ltd. (Tainan, Taiwan). Bentonite and kaolinite were procured from Sigma-Aldrich (USA). 2.2.

Instrumental analysis

The infrared spectra of the different clay material adsorbents before and after adsorption were analyzed utilizing a Fourier transform infrared spectrophotometer (FTIR, JASCO FT/IR 410). The FTIR was operated at frequencies ranging from 400 to 4000 cm-1. Samples were homogenized in KBr (1:20) using a mortar and pestle then pressed to pelletized discs. The morphology of various clay material adsorbents was determined before and after adsorption using a scanning electron microscope (SEM, Hitachi S-3000N). The SEM was operated at an accelerating voltage of 20 kV under vacuum utilizing a tungsten filament. A sputter coater was used to coat the samples with a thin layer of gold. The average pore size and surface area of the clay material adsorbents were measured by a surface area analysis that utilizes the Brunauer, Emmett, and Teller (BET) multipoint technique using the adsorption-desorption isotherm of N2 at 77 K. The zeta potential measurements of the clay material adsorbents were carried out using a zeta potential analyzer (ZetaPlus Analyzer, Brookhaven Instrument). The pH of the adsorbent suspension samples was adjusted using HCl or NaOH from pH 1 to 5. The solution was mixed at 298 K.

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The amount of sulfone compound present in the sample was quantified using an Agilent 7890A gas chromatograph (GC, California, USA) equipped with fused-silica capillary column HP-5 ms having 0.25 mm film thickness (J & W Scientific, USA) and an Agilent 355 sulfur chemiluminescence detector (SCD). The initial GC oven temperature was set to 150 ºC for 1 min, heated at a rate of 20 ºC/min to 220 ºC, and retained for 1 min. 2.3.

Adjustment of pH

A 500 mg/L DBTO concentration was prepared by dissolving DBTO in toluene. The DBTO solution with varying pH of 1.0 to 5.0 from an unadjusted pH of 6.0 at 298 K was investigated under batch adsorption study. Clay material adsorbents of 1.0 g were respectively mixed with 10 mL of DBTO solution. These were agitated at 120 rpm utilizing a BT-350 reciprocal shaker bath (Yihder Technology Co., Ltd.) for 48 h. The remaining DBTO concentration was quantified using the gas chromatograph with sulfur chemiluminescence detector (GC-SCD). All values presented are the mean of the three replicates. The experimental data gathered for the adsorption of DBTO onto clay material adsorbents at varying pH were measured through the adsorption capacity using Eq. (1):

qe 

Co  Ce V m

(1)

where Co and Ce are the initial and equilibrium concentration (mg/L) of DBTO present in toluene solution, respectively, m is the mass of clay material adsorbent (g) and V is the volume of DBTO solution (L). 2.4.

Adsorption kinetic studies

Kinetic studies were carried out by mixing 1.0 g of the respective clay material adsorbents with 10 mL DBTO solution (500 mg/L) under agitation speed of 120 rpm at 298 to 328 K. Samples

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were taken at pre-determined time intervals from 5 min to 48 h. All values presented are the mean of the three replicates. Three kinetic model equations such as pseudo-first order, pseudo-second order and intraparticle diffusion were used to determine the adsorption mechanism and kinetic rate constant. The pseudo-first order equation has a linearized form given in Eq. (2) (Hameed et al., 2008):

ln q e  qt   ln q e  k1t

(2)

where qe and qt are the adsorption capacities (mg/g) at equilibrium and at a given time, respectively, k1 and t are the pseudo-first order rate constant (min-1) and reaction time (min), respectively. The pseudo-first order equation of Lagergren was the earliest adsorption rate model that describes a reversible equilibrium on the adsorbent and adsorbate (Vijaya et al., 2008). This kinetic model has an assumption that the rate of occupation of adsorption sites is proportional to the number of unoccupied sites (Chou et al., 2012). The linear form of the pseudo-second order rate equation is expressed by Eq. (3) (Calagui et al., 2014):

t 1 t   2 qt k 2 q e q e

(3)

where k2 (g/mg-min) is the pseudo-second order adsorption rate constant. The intraparticle diffusion equation describes the rate-limiting step of the transport of the solute from the bulk of solution to the adsorbent pores is through an intraparticle process (Bulut and Tez, 2007). This model is expressed in Eq. (4): qt  k i t 0.5  C i

(4)

where ki (mg/g-min1.5) is the adsorption rate constant of the intraparticle diffusion model, and Ci (mg/g) is the thickness of the boundary layer.

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2.5.

Adsorption equilibrium studies

DBTO with concentrations of 10 to 1000 mg/L were utilized for equilibrium studies. The experiments were performed using 1.0 g of activated clay, bentonite and kaolinite in an Erlenmeyer flask containing 10 mL of DBTO solution at room temperature, respectively. The solutions with a pH of 1.0 were agitated at 120 rpm using a shaker bath for 48 h. All values presented are the mean of the three replicates. The equilibrium data of DBTO adsorption to each respective clay material adsorbents at constant temperature of 298 K were analyzed using four models that include Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich isotherms. The Langmuir adsorption isotherm model assumes that the maximum adsorption corresponds to a saturated monolayer of solute molecules on the surface of the adsorbent, no transmigration of adsorbed molecules on the surface of the adsorbent, and no lateral interaction between the adsorbed molecules (Chou et al., 2010). This is represented in Eq. (5):

qe 

qmax bCe 1  bCe

(5)

where qe is the adsorption capacity at equilibrium (mg/g), qmax is the maximum adsorption capacity for a monolayer coverage (mg/g), b is the constant related to the free energy of adsorption (mL/mg) and Ce is the equilibrium concentration of DBTO (mg/L). The linearized form of this model is expressed by Eq. (6):

 1 1 1    q e q max  bq max

 1   C e

  

(6)

The Freundlich adsorption isotherm model is applicable for non-ideal adsorption that describes a multilayer adsorption on energetically heterogeneous surface (Kamari and Wan Ngah, 2009).

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The empirical and linearized form of the Freundlich equation are given in Eqs. (7) and (8), respectively: qe  K F Ce1 / n

(7)

log q e  log k F 

1 log C e n

(8)

where kf and n are the relative adsorption capacity (mg/g) and favorability of the adsorption process (1/L), respectively. A value of n < 1 signifies a physical adsorption process while n > 1 represent an adsorption process which is chemical in nature (Chou et al., 2010). The Temkin isotherm model takes into consideration the effects of indirect adsorbate/adsorbate interactions which suggest that the heat of adsorption of all adsorbed molecules in the layer decreases linearly with coverage (Allen et al., 2004). The Temkin isotherm model can be expressed as Eq. (9):

qe   ln Ce

(9)

where β is related to the heat of adsorption (J/mol) and α is the Temkin isotherm binding constant (L/g). The linearized form of Temkin isotherm is given in Eq. (10):

qe   ln    ln Ce (10) The Dubinin–Radushkevich adsorption isotherm equation is used to determine the process of adsorption to be physical or chemical in nature which is represented by the empirical and linearized form in Eqs. (11) and (12) (Futalan et al., 2011b):

qe  X m e  B

2

ln qe  ln X m  B 2

(11) (12)

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where Xm is the theoretical saturation capacity (mg/g), B is the Dubinin–Radushkevich constant (kJ2/mol2) and ε is the Polanyi potential given in Eq. (13):



  RT ln1  

1 Ce

  

(13)

where R is the universal gas constant (8.314 J/mol-K), T is the absolute temperature (K). The B constant is related to the mean free energy of adsorption which is computed through Eq. (14): E

1

(14)

2B

where E is the mean adsorption energy (kJ/mol). The values of E < 40 kJ/mol implies physical adsorption while E > 40 kJ/mol suggests chemical adsorption (Al-Anber, 2011). In the adsorption equilibrium studies, an error function is required to evaluate the fit of the isotherm in the experimental equilibrium data. In this study, the linear correlation coefficients and the error function of the sum of the square of the error (ERRSQ) are utilized. The smallest value of the ERRSQ indicates the best fit data for the model. The ERRSQ is calculated as shown in Eq. (15): ERRSQ   qe ,exp  qe ,theo i N

2

(15)

i 1

where qe,

exp

and qe,

theo

are the experimental and theoretical calculated adsorption capacities,

respectively. 2.6.

Adsorption thermodynamic studies

Thermodynamic studies were conducted using 500 mg/L DBTO solution as the initial concentration, pH 1.0, and agitated for 48 h at a speed of 120 rpm. Thermal effects for DBTO

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adsorption onto clay materials adsorbents were studied under three temperatures settings at 298 K, 313 K and 328 K. The nature of adsorption can be understood through the determination of thermodynamic parameters of Gibbs free energy (ΔG) (kJ/mol), enthalpy (ΔH) (kJ/mol) and entropy (ΔS) (kJ/mol-K) at various temperatures. The equilibrium constant Kc (mg-L/g-mol) is indicated in Eq. (16):

Kc 

C ads Ce

(16)

where Cads is the amount of DBTO adsorbed by the clay material adsorbent at equilibrium (mg/L) and Ce is the amount of DBTO remaining in the solution at equilibrium (mg/L). The van’t Hoff equation is used to evaluate the thermodynamic parameters (Calagui et al., 2014; Futalan et al., 2011b). This is utilized to determine the spontaneity of the adsorption process as shown in Eq. (17):

G   RT ln K c

(17)

The relationship of ΔG, ΔS and ΔH is expressed in Eq. (18): ln K c 

S H  R RT

(18)

3. Results and discussion 3.1.

FTIR analysis

FTIR spectra of clay material adsorbents before and after DBTO adsorption are shown in Fig. 1. The –OH stretching in the hydroxyl groups and –C–H stretching in the alkane functional group vibrations corresponds to the bands between 3433 to 3628 cm-1 and 2863 to 2953 cm-1, respectively (de Luna et al., 2013; Xiao et al., 2012). The peaks at 1734 cm-1 is attributed to – C=O stretching in the carboxyl group (Deng et al., 2009). The peak at 1638 to 1643 cm-1

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indicates –N-H bending in the amide group while the bands at 1511 to 1524 cm-1 refers to –N–O asymmetric stretching. The peaks at 1103 to 1280 cm-1 and 1027 to 1049 cm-1 corresponds to – C–N stretching and –C–O stretching, respectively. The –O–H bending and –R–NH2 stretching vibrations is attributed to the peaks from 919 to 923 cm-1 and from 788 to 797 cm-1, respectively. The peaks between 695 to 714 cm-1 indicates –C–Cl stretching while bands at 525 to 617 cm-1 refers to –C–Br stretching. The functional groups involved in DBTO adsorption using the clay material adsorbents can be observed by the change in IR peaks after adsorption. For activated clay, the peak at 3433 cm-1 notably shifted to a lower wavelength of 3430 cm-1. This implies that the hydroxyl (–OH) groups were involved in DBTO adsorption. The occurrence of –N–H stretching is the functional group responsible for DBTO adsorption utilizing bentonite due to a noticeable shift of peak from 1643 cm-1 to a lower wavelength of 1639 cm-1. Meanwhile, the peak at 1638 cm-1 markedly shifted to a higher wavelength of 1646 cm-1, which indicates that the –N–H groups in kaolinite were involved in DBTO adsorption. 3.2.

Surface morphology

The SEM micrographs of activated clay, bentonite and kaolinite before and after DBTO adsorption at a magnification of five-hundred times are shown in Fig. 2. The surface morphology of the clay material adsorbents displayed open pores and cavities on its surface before DBTO adsorption. The pores, cavities and surfaces of each adsorbent were filed up after the DBTO adsorption causing a smoother surface due to the occurrence of DBTO onto the clay material adsorbents. 3.3.

Surface area analysis

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The physical characteristics of activated clay, bentonite and kaolinite are listed in Table 1. According to the International Union of Pure and Applied Chemistry, the total porosity is divided into three categories based on the pore diameter (d) (Futalan et al., 2011a). The categories include micropores (d < 2 nm), mesopores (2 < d < 50 nm) and macropores (d > 50 nm). Result shows that activated clay and kaolinite are mesoporous while bentonite is macroporous prior to DBTO adsorption. The physical properties such as surface area, total pore volume and micropore area values for each clay material adsorbent are arranged in the sequence of activated clay > bentonite > kaolinite. All of the physical properties for each clay material adsorbent were decreased after adsorption due to the DBTO molecules blocking the pores and covering the surface of the adsorbent. This supports the adhesion of DBTO adsorbates onto the surface of each adsorbent. 3.4.

Effect of pH

Fig. 3a to c shows the determination of the point of zero net charge (pznc) in clay material adsorbents through the zeta potential at different pH (1.0 to 5.0). The pznc is where the total concentration of surface anionic sites is equal to the total concentration of surface cationic sites. Results indicate that the pHpznc are at 4.7, 3.3 and 4.2 for activated clay, bentonite and kaolinite, respectively. The surface charge of clay material adsorbents is positive at pH < pHpznc. This promotes an electrostatic attraction in anions which is favorable for anion contaminants such as oxidized sulfur compounds. Therefore, the pH of the solution is an important control parameter in the adsorption

process. The influence of pH on DBTO adsorption onto activated clay, bentonite and kaolinite at room temperature is shown in Fig. 3d. At pH 1.0, the adsorption capacities were 3.20 mg/g, 1.94 mg/g and 1.43 mg/g for activated clay, bentonite and kaolinite, respectively. The adsorption capacities at pH 5.0 became 1.88 mg/g, 0.73 mg/g and 0.58 mg/g for activated clay, bentonite and kaolinite,

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respectively. The increase in pH decreases the adsorption capacity due to the increasing tendency of electrostatic repulsion in anions as supported by the pznc of each clay material adsorbents. A lower pH promotes positively charged sites on the surface of the adsorbent due to the presence of hydronium (H+) ions at acidic concentrations which attracts negatively charged DBTO (Ahmad et al., 2005). Thus, DBTO adsorption is favorable with an optimum pH at 1.0. 3.5.

Kinetic studies

The kinetic analysis in the adsorption process is needed to determine the rate of adsorption of DBTO onto clay material adsorbents which is essential to process design. This would also aid in examining the adsorption mechanism which appropriately determines the rate-limiting step using the results in the experimental data shown in Fig. 4. Table 2 shows the summary of the corresponding adsorption parameters and coefficient of determination (R2) of the pseudo-first order, pseudo-second order and intraparticle diffusion kinetic model equations. Results indicate that DBTO adsorption onto clay material adsorbents were favorable at higher temperatures. This is due to the enlargement of pores in the adsorbent that promotes the collision between the DBTO and clay material adsorbents over all the surface and its pores which in turn increase mass transfer at higher temperature settings (Chen et al., 2016). The adsorption capacity for each adsorbent followed a trend of activated clay > bentonite > kaolinite as shown by the experimental qe. Low R2 values were observed in the pseudo-first order (R2<0.88) and intraparticle diffusion (R2<0.80) equations, and the experimental and theoretical qe were substantially different which implies that neither of the models can appropriately described the rate-limiting step of the adsorption process. It is evident that the pseudo-second order kinetic model best describes the adsorption kinetics due to having the highest coefficient of determination (R2 > 0.99) and similar experimental and theoretical qe

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values. This indicates that chemisorption is the rate determining step of the adsorption of DBTO using activated clay, bentonite and kaolinite from 298 to 328 K. This implies that the formation of covalent bonds enabled exchange or sharing of electrons between the adsorbate and the binding sites of the adsorbents (de Luna et al., 2013; Futalan et al., 2011b; Taffarel and Rubio, 2010). Furthermore, the pseudo-second order rate constant (k2) determines how fast DBTO adsorption onto the surface of the clay material adsorbents. It is observed that the activated clay has the highest kinetic constant (k2 = 0.0111 g/mg-min) at room temperature. In a large-scale basis of the adsorption process, a room temperature (298 K) setting is highly favorable due to being less energy intensive which incurs less cost in comparison to higher temperature settings. 3.6.

Equilibrium studies

The isotherm models under the adsorption process are used to describe the relationship between adsorbate and adsorbent when adsorption reaches equilibrium at different initial concentrations as shown in Fig. 5. The equilibrium models provide insights on the adsorption mechanism, surface properties and adsorbent affinity through the equation parameters and its underlying thermodynamic assumptions. The adsorption parameters and R2 of Langmuir, Freundlich, Temkin and Dubinin–Radushkevich isotherms are summarized in Table 3a. Based on the R2 values, the DBTO adsorption onto clay material adsorbents did not fit well with Temkin (R2<0.82) and Dubinin–Radushkevich (R2<0.63) models. It is apparent that the Freundlich isotherm best describes the adsorption process due to having the highest R2 value (R2>0.99). This implies the occurrence of a heterogeneous adsorption. The clay material adsorbents showed values of n > 1 which supports the findings in the kinetic study that followed a pseudo-second order adsorption rate. This reiterates the occurrence of chemical adsorption. Results indicate that activated clay has the highest kf and

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lowest n values over bentonite and kaolinite. This means that having the lowest n value makes the adsorbate have the highest affinity towards the functional groups of the adsorbent which results to a high kf value (Futalan et al., 2011b). Based on the error analysis of ERSSQ, the validity of the linearized and non-linearized isotherm model showed that the Freundlich isotherm model has the best fit to describe the DBTO adsorption onto clay material adsorbents due to having the lowest ERSSQ value. 3.7.

Thermodynamic studies

The slope and intercept of the van’t Hoff linear plot of ln Kc against 1/T can be used to compute the values of ΔH and ΔS. High R2 values (R2>0.99) were observed which indicates that the thermodynamic properties can be appropriately be determined using the van’t Hoff equation. The observed thermodynamics properties using clay material adsorbents in the temperature range of 298 to 328K are given in Table 3b. Negative values of ΔG using activated clay indicate that the adsorption process is feasible and spontaneous at all temperatures, while utilizing kaolinite resulted to positive values of ΔG which implies that DBTO adsorption is non-spontaneous. For bentonite, DBTO adsorption is spontaneous at 313 to 328 K but only non-spontaneous at 298 K. The decreasing values of ΔG with its corresponding increase in temperature indicate that the adsorption is favorable at higher temperature. Lower negative values of ΔG imply higher favorability and spontaneity towards DBTO adsorption. This supports the reason why the adsorption capacity of activated clay is higher than that of bentonite and kaolinite. This is due to having the lowest ΔG values at all temperatures. The positive ΔH values for all clay material adsorbents indicate an endothermic process. Hence, this supports that increasing the temperature results to higher DBTO adsorption capacity. Positive values of ΔS signify an increased in the degrees of freedom of the adsorbed DBTO for activated clay, bentonite and kaolinite.

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3.8.

Adsorption mechanism

DBTO adsorption onto different clay material adsorbents were examined to determine the mechanism of the adsorbent–adsorbate interaction. As compared with DBT, DBTO can be easily adsorbed due to being polar in nature (Lu et al., 2015). The FTIR analysis is utilized to determine the interaction of the adsorbate (DBTO) towards the active functional groups on the surface of the adsorbent (clay material adsorbents) (Monash and Pugazhenthi, 2009). Based on the FTIR results, the hydroxyl and amine were the main functional groups involved in DBTO adsorption onto the clay material adsorbents. The presence of the oxygen atom in DBTO forms a bond with the hydrogen molecules of the hydroxyl and amine groups. Furthermore, the adsorption equilibrium studies illustrated that DBTO followed the Freundlich isotherm model due to having the highest R2 and the lowest ERSSQ. This indicates that DBTO would adsorbed onto different binding sites on clay material adsorbents. This further validates the FTIR results, where the hydroxyl and amine groups were the functional groups in clay material adsorbents that adsorbs DBTO. The adsorption kinetics followed a pseudo-second order model for DBTO adsorption which involves the formation of valency forces through the sharing or exchange of electrons between the sorbate and sorbate (Saǧ and Aktay, 2002). The main mechanism of adsorption suggests the occurrence of chemisorption. This involves the formation of strong chemical bonds between DBTO onto the clay material adsorbents. 3.9.

Comparison of research findings

The clay material adsorbents in this study were compared to the past adsorbents (Chen et al., 2016; Lu et al., 2013) utilized for DBTO adsorption. From Table 4, activated clay has the highest adsorption capacity (3.01 mg/g) among the other clay material adsorbents. Activated clay has a comparable adsorption capacity to granulated activated carbon (3.50 mg/g), while the aluminum

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oxide (4.50 mg/g), chitosan-coated bentonite (4.44 mg/g) and ion impregnated activated carbon (4.90 – 4.94 mg/g) showed superior DBTO adsorption performance. Clay material adsorbents are known to cost cheap and abundant in nature that makes it an attractive adsorbent material in the aspect of oxidative desulfurization. One drawback of the utilization of activated carbon and aluminum oxide adsorbents is its expensive costing. For the chitosan-coated bentonite and ion impregnated activated carbon, the disadvantages include the additional preparative and complicated procedure in its synthesis incurring additional costing. 4. Conclusions Different clay material adsorbents were utilized for DBTO adsorption in this study. The surface area and adsorption capacity are shown highest in activated clay over bentonite and kaolinite. Different kinetic and isotherm models for adsorption were used to evaluate the experimental data. The pseudo-second order adsorption kinetic model best describes the adsorption of DBTO onto clay material adsorbents which indicates chemisorption as its rate determining step. The Freundlich model suitably fit the equilibrium data which describes a heterogeneous and monolayer adsorption. The thermodynamic parameters indicate an endothermic DBTO adsorption onto clay material adsorbents. Utilizing activated clay is spontaneous while kaolinite is non-spontaneous on DBTO adsorption in all temperatures. For bentonite, DBTO adsorption is spontaneous in all temperatures except at 298 K. Among the clay material adsorbents, activated clay showed to be a promising low-cost adsorbent in terms of removing sulfone compounds under the oxidative desulfurization process. ACKNOWLEDGMENTS

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Figure Captions Fig. 1. FT-IR spectra of (a) activated clay, (b) bentonite and (c) kaolinite before and after DBTO adsorption. Fig. 2. SEM micrographs of (a) activated clay, (b) bentonite and (c) kaolinite before adsorption and (d) activated clay, (e) bentonite and (f) kaolinite after adsorption with DBTO solution. Fig. 3. Zeta potential of (a) activated clay, (b) bentonite and (c) kaolinite and (d) its effect on DBTO adsorption at varying pH. Fig. 4. DBTO adsorption using (a) activated clay, (b) bentonite and (c) kaolinite at varying contact time and temperature. Fig. 5. Effect of initial concentration on DBTO adsorption using activated clay, bentonite and kaolinite.

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Zeta Potential (mV)

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Figure 4

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Figure 5 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0

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TABLE 1: Surface area and pore characteristics of clay material adsorbents before and after DBTO adsorption. Physical properties BET surface area (m2/g) Langmuir surface area (m2/g) Micropore area (m2/g) Average pore diameter (nm) Total pore volume (cm3/g)

Activated Clay Before After 281.47 218.51 270.09 202.04 20.405 <0.001 16.14 14.97 0.3762 0.3311

Bentonite Before After 23.9 16.729 23.343 13.753 <0.001 <0.001 136.30 49.70 0.1047 0.0872

Kaolinite Before 9.482 7.019 <0.001 46.19 0.0444

After 8.708 7.01 <0.001 43.59 0.0425

TABLE 2: Kinetic parameters for DBTO adsorption using clay material adsorbents. qe, Pseudo first-order model Pseudo-second order model Temperature expt’l. Adsorbent k1 qe, theo k2 qe, theo (K) (mg/g) (min-1) (mg/g) R2 R2 (g/mg-min) (mg/g) Activated 298 3.0724 0.0012 0.7079 0.8456 0.0111 3.0624 0.9995 Clay 313 3.9087 0.0016 1.5550 0.8800 0.0052 3.9306 0.9993 328 4.8288 0.0021 1.2668 0.8269 0.0083 4.8611 0.9999 298 2.3614 -0.0028 1.0910 0.7934 0.0106 2.3696 0.9988 Bentonite 313 2.9293 -0.0016 1.5675 0.8620 0.0039 2.9863 0.9993 328 3.5755 -0.0023 1.4638 0.8680 0.0058 3.6381 0.9995 Kaolinite 298 1.4943 -0.0015 0.8720 0.8692 0.0058 1.5295 0.9987 313 1.8575 -0.0018 0.9367 0.8677 0.0067 1.8972 0.9987 328 2.2667 -0.0016 0.9910 0.8405 0.0072 2.2897 0.9992

Intraparticle diffusion model ki Ci R2 (mg/g-min0.5) (mg/g) 0.0212 2.1317 0.6593 0.0473 1.8869 0.7763 0.0476 2.8970 0.7001 0.0198 1.4919 0.6658 0.0487 0.8634 0.7782 0.0510 1.5017 0.7292 0.0262 0.3608 0.7984 0.0295 0.6123 0.7787 0.0319 0.9122 0.7778

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TABLE 3: (a) Isotherm and (b) thermodynamic parameters for DBTO adsorption using clay material adsorbents. (a) Isotherm model Isotherm parameters Langmuir

Activated Clay LTFM ERSSQ 0.033 0.003 0.051 5.140 0. 9873 31.254 0.295 0.061 0.108 1.541 1.829 0.9901 0.718 0.487 0.205 0.205 0.596 0.596 0.8108 2.222 2.222 1.418 3.381 -6 2.19x10 2.19x10-3 478.15 15.121 0.6278 10.064 0.957

b qmax R2 ERSSQ Freundlich kf n R2 ERSSQ Temkin α β R2 ERSSQ DubininXm Radushkevich B E R2 ERSSQ (b) Thermodynamics Temperature (K) Adsorbent 298 Activated Clay 313 328 298 Bentonite 313 328 298 Kaolinite 313 328

Bentonite LTFM 0.040 0.039 0.9715 16.456 0.044 1.628 0.9903 0.265 0.151 0.430 0.7275 1.783 1.008 2.89x10-6 416.33 0.5869 5.779

ΔG (kJ/mol) -0.572 -3.239 -5.333 0.307 -1.731 -3.885 2.731 2.083 1.356

ERSSQ 0.001 6.352 0.187 0.026 1.402 0.152 0.151 0.430 1.783 2.485 4.32x10-3 10.762 0.948

Kaolinite LTFM 0.025 0.016 0.9673 4.565 0.023 1.669 0.9947 0.015 0.104 0.241 0.7983 0.320 0.575 7.97x10-6 250.55 0.5874 1.317

ERSSQ 0.001 2.503 0.014 0.018 1.557 0.007 0.104 0.241 0.320 1.275 5.56x10-3 9.482 0.201

ΔH (kJ/mol) 46.8248

ΔS (kJ/mol-K) 0.1593

41.9291

0.1396

16.3766

0.0458

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TABLE 4: Comparison of research findings of DBTO adsorption Adsorbents Aluminum oxide Chitosan-coated bentonite Granular activated carbon

qe (mg/g) 4.50 4.44 3.50

Reference (Lu et al., 2013) (Lu et al., 2013) (Chen et al., 2016)

Ion impregnated activated carbon: Cu2+ 4.90 Fe3+ 4.92 2+ Ni 4.94

(Chen et al., 2016) (Chen et al., 2016) (Chen et al., 2016)

Clay material adsorbents: Activated clay 3.07 Bentonite 2.36 Kaolinite 1.49

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