Environmental Science and Pollution Research

https://doi.org/10.1007/s11356-019-04850-7

RESEARCH ARTICLE

Engineered biochar composites with zeolite, silica,

and nano-zerovalent iron for the efficient scavenging
of chlortetracycline from aqueous solutions
Munir Ahmad 1 & Adel R. A. Usman 1,2 & Muhammad Imran Rafique 1 & Mohammad I. Al-Wabel 1

Received: 23 December 2018 / Accepted: 12 March 2019

# Springer-Verlag GmbH Germany, part of Springer Nature 2019

Abstract
Date palm waste–derived biochar (DBC) was produced through pyrolysis (600 °C) and modified with zeolite (Z-DBC), silica (S-
DBC), or nano-zerovalent iron (nZVI-DBC) to design efficient sorbents. The pristine and engineered biochars were characterized
by SEM, XRD, BET, TGA, CHNS-O, and FTIR to investigate the surface, structural, and mineralogical composition. The nZVI-
DBC exhibited lowest pH (6.15) and highest surface area (220.92 m2 g−1), carbon (80.55%), nitrogen (3.78%), and hydrogen
(11.09%) contents compared with other biochars. Isotherm sorption data for chlortetracycline (CTC) removal from aqueous
solutions was described well by Langmuir and Redlich–Peterson isotherms showing the highest fitness (R2 values in the range of
0.88–0.98 and 0.88–0.99, respectively). Langmuir predicted maximum CTC adsorption capacity was in order of nZVI-DBC
(89.05 mg g−1) > S-DBC (45.57 mg g−1) > Z-DBC (30.42 mg g−1) > DBC (28.19 mg g−1). Kinetics adsorption data was best
described by power function model (R2 = 0.93–0.99), followed by interaparticle diffusion (R2 = 0.85–0.96) model. The nZVI-
DBC performed outclass by removing 98% of CTC, followed by S-DBC (68%), Z-DBC (35%), and DBC (36%).
Chemisorption, H-bonding, and interaparticle diffusion were the operating mechanisms for CTC adsorption onto DBC, S-
DBC, and Z-DBC, while π-π electron donor–accepter interactions and redox reactions augmented these mechanisms for highest
CTC adsorption onto nZVI-DBC. Therefore, nZVI-DBC may serve as an efficient green technology for the removal of CTC
from aqueous solutions and to reduce surface date palm waste pollution.

Highlights
• Magnetic and organo-mineral biochar composites were engineered and
characterized.
• nZVI-DBC has shown highest surface area and lowest pH among all
biochar composites.
• nZVI-DBC exhibited three times more chlortetracycline removal than
pristine biochar.
• Chemisorption, physisorption, and diffusion were sorption controlling
mechanisms.
• π-π interactions and redox reactions augmented chlortetracycline sorp-
tion in nZVI-DBC.
Responsible editor: Tito Roberto Cadaval Jr
Electronic supplementary material The online version of this article
(https://doi.org/10.1007/s11356-019-04850-7) contains supplementary
material, which is available to authorized users.

* Mohammad I. Al-Wabel 2
Department of Soils and Water, Faculty of Agriculture, Assiut
malwabel@ksu.edu.sa University, Asyut 71526, Egypt

1
Soil Sciences Department, College of Food & Agricultural Sciences,
King Saud University, P.O. Box 2460, Riyadh 11451, Kingdom of
Saudi Arabia
 Environ Sci Pollut Res

Keywords Antibiotics . Chemisorption . Redox reactions . Removal mechanism . Surface pollution

Introduction processes, adsorption is the most accepted and widely used

technique as it is inexpensive, practically easy to perform,
Antibiotics are among the most common pharmaceutical and contains lower risk of toxicity (Hao et al. 2012; Zhou
products that have been used widely from the last seven et al. 2012; Ahmaruzzaman 2008). However, the selection
decades for both human and animals to control and pre- of appropriate adsorbent is of critical importance as the
vent infectious diseases. Over 250 antibiotic types have efficiency of adsorbents depends on the type of adsorbent,
been reported currently in use as human and veterinary type of adsorbate, and composition of waste medium.
medicines around the globe with an annual consumption Therefore, it is the dire need of time to develop new low-
of 63,151 ton (Ashfaq et al. 2015; Kümmerer and cost, eco-friendly, and efficient sorbents for the removal of
Henninger 2003). Due to extensive usage, antibiotics and CTC from water media.
their metabolites have been detected in various environ- Biochar has recently been introduced as adsorbent for the
mental matrices such as hospital wastewater (Ashfaq et al. removal of toxic metal ions and organic contaminants from
2015), municipal wastewater (Lindberg et al. 2010), sur- wastewater (Ahmad et al. 2018a). Biochar is a carbon-rich
face water (Makowska et al. 2016), and even in drinking solid material produced from organic wastes through pyroly-
water (Simazaki et al. 2015), because a substantial amount sis in controlled environment under limited oxygen supply
of antibiotics (~ 70%) is not metabolized nor absorbed in (Aly 2017). Adsorption by using biochar is considered to be
the body of the target organism and thus excreted into the an innovative and promising practice as compared with other
environment resulting in soil and water contamination conventional techniques. The presence of functional groups
(Kummerer 2009). The antibiotic contamination is respon- on biochar surface, high surface area, microporous structure,
sible for various disorders in human beings such as diverse surface sites, and net negative charge makes biochar
allergic/anaphylactic reactions, liver injury, delayed blood an efficient adsorbent for a range of organic and inorganic
coagulation, and discoloration of teeth especially in chil- pollutants (Uchimiya et al. 2012; Reddy and Lee 2014).
dren of less than 7 years old (Singh et al. 2014). However, due to heterogeneity in structure and properties,
Among the most commonly used veterinary antibiotics, biochar does not perform consistently. Yao et al. (2013) re-
chlortetracycline (CTC) is a broad spectrum antibiotic ported that unmodified biochar due to its low adsorption ca-
which is used for the treatment of bacterial infection and pacity and low anti-interference ability does not perform up to
as food supplement for livestock and poultry (Bao et al. the mark. On the other hand, due to both positively and neg-
2009). It belongs to the family tetracycline which is com- atively charged surfaces (based on pyrolysis temperature),
monly used for animal production. Widespread use of CTC majority of the biochar possess low adsorption capability for
has resulted in elevated levels of its residues in soil and some anionic pollutants. To conquer the abovementioned con-
underground waters as > 75% of CTC remains unabsorbed straints, researchers are trying to modify the biochar through
and excretes out with animal manure (Montforts 1999). mechanical, chemical, and physical means to improve its ef-
Applying this manure to soil as fertilizer and/or dumping ficiency for enhanced organic and inorganic pollutants’
this in the soil are deteriorating the ecosystem. removal.
Accumulation of CTC residues in soil and water is posing Modifications of biochar may alter its surface functional
adverse ecological threats, and their concentration in plant groups, surface area, surface charges, and ash contents, subse-
and crop tissues is being increased with increased manure quently altering the biochar efficiency for the removal and fix-
application (Kumar et al. 2005). Therefore, CTC residues ation of toxic metal ions and several organic compounds. It has
are recognized as potential organic pollutants and their been reported that the adsorption of organic pollutant such as
occurrence have been reported worldwide which needs im- CTC can be increased by engineering a biochar with more
m e d i at e a t t en t i o n ( D a ug h t o n a n d Te r n e s 1 9 99 ) . oxygen-containing functional groups (Liu et al. 2011).
Consequently, researchers are in surge of low cost and Henceforth, modification of biochar may potentially improve
practically feasible processes to limit antibiotics’ release its surface properties (hydrophobicity/hydrophilicity, surface
into soil and water, as well as to remove the prevailing charge, surface area, and pore volume) resulting in higher ad-
antibiotics from the wastewater. Different processes have sorption of organic pollutants. Various foreign agents such as
been employed to remove various antibiotics from waste- silica, zeolite, and nano-metal oxides have been used for biochar
water including biological treatments, membrane separa- modifications (Dong et al. 2017; Ahmad et al. 2017; Ahmad
tion, activated carbon, adsorption, advanced oxidation pro- et al. 2018a). Zeolite, due to its strong electric field, larger sur-
cess (AOP), and chemical treatments. Among these face area, great ion-exchange capacity, and microstructure, is a
Environ Sci Pollut Res

wonderful clay mineral and is being widely used to remove remove moisture. The weight of the produced biochar was
pollutants from contaminated soil (Bilgic 2005; Gurses et al. recorded and yield was calculated using Eq. 1.
2006). Likewise, nano-sized silica possesses higher specific sur-
face area and hydrothermal stability. Therefore, combination of
weight of biomass−weight of biochar
biochar with zeolite and/or silica minerals may improve physi- Yield ð%Þ ¼  100 ð1Þ
weight of biomass
ochemical properties of biochar and enhance its potential for
fixation of organic and inorganic toxins in soil and water The produced biochar was washed thrice with deionized
(Wang et al. 2016). Similarly, nano-zerovalent iron (nZVI) due water, grinded, stored in airtight containers, and labeled as
to its nanoscale particle size, large surface area, and reductive DBC.
nature has been used to remediate a range of environmental
contaminants in soil and water (Chatterjee et al. 2010; Meng
et al. 2006; Zhao et al. 2008; Xu et al. 2010). However, the Engineered nano-zerovalent ion–composited biochar
applicability of nZVI is cumbersome due to its oxidative nature synthesis
and aggregation potential (Phenrat et al. 2006; Devi and Saroha
2014). Thus, if composited with biochar, nZVI may get stabi- Date palm waste–derived biochar (DBC) was composited with
lized, consequently resulting in lower agglomeration and more nano-zerovalent iron (nZVI) by following the procedure report-
feasible applicability. Therefore, modification of biochar with ed by Ahmad et al. (2018a). Briefly, 100 mL of 1 M
nZVI, silica, and/or zeolite may alter the functional groups on FeSO 4 .7H 2 O solution was prepared in 4:1 (v/v ration)
the surface of biochar resulting in enhanced H-bonding, cova- ethanol:deionized water solution and poured in a three-neck
lent binding, and π-π electron donor–acceptor interactions sub- flask. 5.6 g of DBC was added into the flask and pH was
sequently resulting in higher adsorption (Mohan et al. 2014; adjusted at 5 using 5 N H2SO4. The suspension was stirred
Wang et al. 2017). However, up to the best of our knowledge, vigorously for 2 h initially and then purged with N2 for 1 h
the efficiency of the engineered biochar composites with nZVI, during stirring. One hundred milliliters of 2 M NaBH4 solution
silica, or zeolite for CTC adsorption has not been reported yet. was added drop-wise into the flask under continues stirring and
Therefore, we proposed that modification of biochar using N2 supply. The immediate reaction took place evolving the H2,
nZVI, silica, or zeolite minerals could produce efficient and black nano-zerovalent iron (Fe0) particles started to accu-
engineered biochars with improved adsorption characteristics. mulate on DBC matrix. After completion of the reaction, 1.12 g
Thus, engineered biochars with nano-zerovalent iron, silica, chitosan in 2% CH3COOH solution was added. The suspen-
and zeolite were produced and characterized in this study. sion was stirred for another 30 min, and 100 mL of 1.2% NaOH
Furthermore, the efficiency of the engineered and pristine bio- solution was poured under gentle stirring. The N2 supply was
chars for the removal of CTC from aqueous solutions was in- stopped; flask was air-tightened and kept overnight. The next
vestigated, and the operating adsorption mechanisms were in- day, the solid precipitates were separated, washed several times
vestigated by employing various isotherms and kinetics models. with ethanol to remove surplus sulfate and iron, dried in
oxygen-free environment, and labeled as nZVI-DBC.

Engineered mineral-composited biochars synthesis

Materials and methods
The DBC mineral composites were engineered according to
Biochar production the procedure adopted by Ahmad et al. (2017). The DBM was
treated with silica and zeolite minerals prior to pyrolysis. The
Date palm tree waste was collected and washed with de- silica was washed with 10% HCl, 30% H2O2 solutions, and
ionized water to remove dust and other impurities. After air deionized water to remove organic matter, carbonates, and
drying, the leaflets were separated from the stem, cut into other impurities, and dried in an oven. Zeolite (clinoptilolite
small pieces, grinded with a mechanical grinder, and 25523: purchased from San Bernardino Co. PO Box. 591
passed through a 0.6-mm screen. This biomass was further Clarkson, NY) was grinded and passed through a 0.6-mm
milled in a ball mill (Fritsch Pulverisette 7, Germany) at sieve. The prepared silica and zeolite minerals were milled
800 rpm for 20 min. A weighed amount of the ball-milled in a ball mill at 800 rpm for 20 min. Four grams of milled
date palm biomass (DBM) was placed in a crucible, loose- silica (S) or zeolite (Z) was added into 1 L deionized water and
ly covered, and pyrolyzed (5 °C per min) at 600 °C for 3 h sonicated (Sonics Vibra-Cell VCX-500 Ultrasonic Processor)
in a tube furnace (Carbolite, type 3216, UK) in oxygen- for 30 min at 35 amp. The suspension was placed on a stirrer;
limited environment. After pyrolysis, the crucible was 20 g of DBM was added and stirred for 3 h. The silica- or
placed in a desiccator for half an hour for cooling and to zeolite-impregnated biomass was separated from the
 Environ Sci Pollut Res

suspension and dried in an oven at 80 °C. After drying, Equilibrium adsorption experiments
weighed amount of solid material was placed in a crucible,
loosely covered, and pyrolyzed (5 °C per min) in a tube fur- Date palm–derived biochar and its composites were tested
nace at 600 °C for 3 h in oxygen-limited environment. After for their efficiency to remove chlortetracycline (CTC) from
the material cooled down, it was weighed to calculate yield the aqueous solution by isotherm sorption batch-type ex-
according to Eq. 1 (after correction of silica and zeolite periments. A stock solution containing 500 mg CTC L−1
weights), washed thrice with deionized water, and dried in was prepared in methanol, which was further diluted in
an oven. Silica- and zeolite-composited biochars were labeled deionized water (18.2 MΩ cm −1 resistivity; Milli-Q,
as S-DBC and Z-DBC, respectively. Germany) to prepare working solutions of 0, 5, 10, 20,
50, and 100 mg CTC L−1. The pH of the working solution
was adjusted at 5 using HCl and NaOH. Twenty-five mil-
Characterization of engineered biochars liliters of each working solution was added into polypro-
pylene conical tubes, and the produced materials were
The proximate analyses such as moisture, volatile matter, suspended separately in tubes at the rate of 1 g L−1. After
and ash contents in the biochars were determined by the shaking at 150 rpm for 24 h at room temperature (23 ±
standard methods provided by ASTM D1762-84 (ASTM 2 °C), the solutions were filtered by 0.45 μm syringe fil-
1989), whereas the resident matter (fixed carbon) was cal- ters. Three replications of each biochar including a blank
culated using the difference method. The pH of the bio- were performed. The equilibrium concentration of CTC in
chars was determined in 1:10 (w/v ratio) of material to the solution was analyzed by high-performance liquid
deionized water suspension. Cation exchange capacity chromatography (HPLC; Prominence-i, LC-2030C,
(CEC) was measured using the method described by Shimadzu, Japan), equipped with an auto-sampler (high-
Richard (1954). The pH at point of zero charge (pHPZC) speed drive LC-2030), a PDA detector, a pump (low-pres-
was estimated by using 0.01 M NaCl in an initial pH range sure gradient solvent delivery LC-2030), and a degasser
of 2–12 (Usman et al. 2015). unit. The equipment was also equipped with a reversed-
The scanning electron microscope (SEM; EFI S50 Inspect, phase Raptor C18 column (100 mm × 21 mm, 2.7 μm par-
Netherlands) was used to observe the structural changes and ticle size, Restek Corporation, USA). The mobile phase A
surface morphology of the biochars. Briefly, a few particles of consisted of ultrapure water and formic acid solution
the material were scattered on the aluminum stubs coated with (99.9:0.1 v/v ratio), while the mobile phase B consisted
adhesive carbon tape (12 mm; PELCO, UK) and coated with of HPLC grade acetonitrile and formic acid (99.9:0.1 v/v
nano-gold particles for 60 s via 108 Auto/SE Sputter Coater ratio). The gradient flow consisted of 70% of mobile phase
(Ted Pella Inc., USA). Images of the material were taken with A and 30% of mobile phase B. The CTC was detected at
different magnifications at 30 kV voltage under high vacuum. 254 nm wavelength with a flow rate of 0.15 mL min−1 and
The thermogravimetric analyzer (TGA-DTG-60H, Shimadzu, a total injection volume of 10 μL. The calibration curve of
Japan) was used to analyze the thermal stability of the bio- CTC concentration versus absorbance was developed by
chars in a temperature range of 0–1100 °C. The Fourier trans- using analytical grade CTC standards between the ranges
form infrared spectroscopy (FTIR; Bruker Alpha-Eco ATR- of 0 and 20 mg L−1. The R2 obtained from the calibration
FTIR, Bruker Optics Inc.) was used to observe the composi- curves was > 0.98. For quality assurance, CTC standards
tion of structural and functional groups in the biochars. X-ray were fed as unknown samples and observed that the recov-
diffractometer (MAXima_X XRD-7000, Shimadzu, Japan) ery was 94.87–103.25%.
was used to analyze the mineralogical phases of the produced The amount of CTC sorbed onto the material was calculat-
biochars. The Brunauer–Emmett–Teller (BET; TriStar II ed using Eq. 3 (Ok et al. 2007).
3020, Micromeritics, USA) method was used to analyze the
surface area, total pore volume, and pore diameter. The

C o −C e
CHNSO elemental analyzer (series II, PerkinElmer, USA) qe ¼ v ð3Þ
was used to assess the elemental composition. The percent m
carbon (C), nitrogen (N), hydrogen (H), and sulfur (S) content
where Co and Ce are the initial and equilibrium concentra-
was analyzed with the CHNSO analyzer directly, while oxy-
tions of CTC (mg L−1), qe is the amount of CTC sorbed
gen (O) was calculated using Eq. 2 and atomic ratios of O/C
(mg g−1), m is the mass of material (g), and v is the volume
and H/C were calculated.
of solution (L).
O ð%Þ ¼ 100−½C ð%Þ þ H ð%Þ þ N ð%Þ þ S ð%Þ þ ash ð%Þ To investigate the efficiency of the biochars for the adsorp-
tion of CTC, nonlinear forms of the Freundlich, Langmuir,
ð2Þ
Redlich–Peterson, Temkin, and Dubinin–Radushkevich
Environ Sci Pollut Res

equations (Eqs. 4, 5, 6, 7, and 8, respectively) were applied Kinetics adsorption experiments

(Ahmad et al. 2013; Redlich and Peterson 1959).
Kinetics adsorption experiments were conducted to investi-
qe ¼ K F C 1=n
e ð4Þ gate the rate of CTC adsorption onto the produced biochars.
A working solution containing 100 mg CTC L−1 was prepared
qe ¼
QL C e K L
ð5Þ in deionized water using the stock solution (500 mg L−1 in
1 þ K L Ce methanol), and the pH was adjusted at 5. The biochars were
AC e suspended in 25 mL of the working solution in a polypropyl-
qe ¼ ð6Þ ene conical flask at the rate of 1 g L−1, and shaken on a
1 þ BC ge
mechanical shaker at 150 rpm at room temperature (23 ±
2 °C). The mixtures were withdrawn from the shaker after 0,
RT
qe ¼ lnðAC e Þ ð7Þ 60, 120, 180, 360, and 720 min, and the solutions were sepa-
b
rated from the biochars and filtered through 0.45 μm syringe

 2 filters. Three replications of each material and a control (with-
1
qe ¼ qD exp −BD RTln 1 þ ð8Þ out biochars) were also included. The concentration of CTC in
Ce the filtrates was analyzed by HPLC. Amount of CTC sorbed
onto per unit mass of the material was calculated using Eq. 3.
where K F is the Freundlich sorptive affinity parameter The CTC removal percentage was calculated by using Eq. 12.
(L g−1), 1/n is the Freundlich component related to linear-

ity, Q L is the Langmuir maximum adsorption capacity C o −C t
Removal% ¼  100 ð12Þ
(mg g−1), KL is the Langmuir sorption equilibrium constant Co
(L mg−1), A and B are the Redlich–Peterson equation con-
stant (L g−1 and (L mg−1)g, respectively), and g is the ex- To predict the mechanism for CTC adsorption onto the
ponent having the value between 0 and 1. A is the binding DBC and engineered composites (nZVI-DBC, S-DBC, and
constant (L mg−1), b is the heat of adsorption, qD is the Z-DBC), various kinetic models such as first-order, second-
maximum adsorption capacity of the adsorbent (mg g−1), order, pseudo-first-order, pseudo-second-order, Elovich, pow-
and BD is the mean free energy of sorption used to calcu- er function, and intraparticle diffusion (Eqs. 13, 14, 15, 16, 17,
late the bonding energy (E) for the ion-exchange mecha- 18, and 19, respectively) were applied (Ahmad et al. 2018b).
nism according to Eq. 9.
lnqt ¼ lnqo −k 1 t ð13Þ
1
E ¼ pffiffiffiffiffiffiffiffi ð9Þ 1 1
2BD ¼ −k 2 t ð14Þ
qt qo
0
Langmuir separation factor (RL), as given in Eq. 10, was lnðqe −qt Þ ¼ lnqe −k 1 t ð15Þ
used to assess the favorability of CTC adsorption onto the t 1 1
biochars. ¼ 0 2þ t ð16Þ
qt k 2 q e qe
1 1
1 qt ¼ lnðαβÞ þ lnt ð17Þ
RL ¼ ð10Þ β β
1 þ K LCo
lnqt ¼ lnb þ k f ðlnt Þ ð18Þ
The coefficient of determination (R2) was calculated by qt ¼ c þ k id t 0:5
ð19Þ
using Eq. 11 to determine the closeness between the experi-
mental adsorption data and the model predicted data (Ahmad where qt and qo are the amounts of CTC sorbed (mg g−1) at
et al. 2018b). time t and time 0 (min), respectively, t is the time interval, k1
and k2 are the first- and second-order rate constants, respec-
 2 tively, qe is the adsorption capacity at equilibrium (mg g−1), k1′
qem −qec and k2′ are the pseudo-first- and pseudo-second-order rate
R2 ¼  2 ð11Þ constants, respectively, α is the initial adsorption rate
∑ qem −qec þ ðqem −qec Þ2 (mg g−1 min−1), β is the adsorption constant, b is the rate
constant, kf is the rate coefficient value (mg g−1 min−1), kid is
where qec and qem are the calculated and measured amounts of the apparent diffusion rate constant (in [mg g−1]-0.5), and c is
CTC sorbed (mg g−1) onto the biochars at equilibrium. the diffusion constant.
 Environ Sci Pollut Res

The standard error of estimate (SEE) and the coefficient of 4.77% in DBM to 1.58% in DBC due to volatilization and
determination (R2) were calculated by using Eqs. 11 and 20, thermalization, which further reduced to 0.73% and 0.00% in
respectively, to determine the closeness between the experi- S-DBC and Z-DBC, respectively, while increased in nZVI-
mental adsorption data and the model predicted data (Ahmad DBC. The volatiles were reduced from 66.36% in DBM to
et al. 2018b). 10.05% in DBC. The nZVI-DBC composite showed the
highest volatiles among all the composites, i.e., 18.88%, while
SEE ¼ ∑ni¼1 ðqem −qec Þ2 ð20Þ the lowest were exhibited by S-DBC followed by Z-DBC
(7.59% and 10.87%, respectively). The volatiles are generally
where qem and qec are the measured and calculated CTC ad- considered as an indication of biochar stability (Usman et al.
sorption capacities (mg g−1) of the biochars, and n is the num- 2015); therefore, lower volatiles in S-DBC suggested higher
ber of measurements. stability of this composite.
It was interesting to notice that fixed carbon contents in-
creased with pyrolysis from 20.50% in DBM to 50.10% in
Results and discussion DBC, which further increased to 24.91% and 31.22% in Z-
DBC and S-DBC, respectively (excluding the contents of the
Characterization silica and zeolite minerals), while it reduced to 10.64% when
composited with nZVI. The lowest fixed carbon might be due
Proximate, chemical analyses, surface area, and elemental to the presence of graphene and Fe3C contents in nZVI-DBC
composition composite which remained undecomposed and therefore were
confused with the ash contents. The ash contents increased
Proximate composition, elemental composition, chemical with pyrolysis from 8.36% in DBM to 38.27% in DBC, which
analyses, and surface area analyses of the date palm waste– further increased to 60.87%, 60.46%, and 64.22% in nZVI-
derived biochar and its derived composites are presented in DBC, S-DBC, and Z-DBC, respectively (excluding the con-
Table 1. After excluding the contribution of the mineral silica tents of silica and zeolite minerals in S-DBC and Z-DBC
and zeolite, S-DBC and Z-DBC exhibited 37% and 32% more composites, respectively). It has already been established that
yield compared with DBC, suggesting that the mineral com- the ash contents increased with pyrolysis, due to formation
posites of biochar were more resilient to thermal decomposi- and/or condensation of mineral compounds (Ozcimen and
tion. The moisture contents reduced with pyrolysis from Ersoy-Mericboyu 2010; Sun et al. 2014). The pH of the

Table 1 Proximate, chemical, surface area, pore size, and pore volume analyses and elemental composition with their molar ratio results of date palm
tree leaves waste biomass and its derived biochars

Parameters Unit DBM DBC nZVI-DBC S-DBC Z-DBC

Yield % – 31.78 ± 4.78 – 43.54 ± 2.27 41.83 ± 4.27

Moisture % 4.77 ± 0.03 1.58 ± 0.75 3.96 ± 0.08 0.73 ± 0.10 0.00 ± 0.00
Volatiles % 66.36 ± 5.53 10.05 ± 1.49 18.88 ± 1.23 7.590 ± 0.21 10.87 ± 1.28
Fixed carbon % 20.50 ± 5.72 50.10 ± 0.98 10.64 ± 3.51 31.22 ± 0.32 24.91 ± 1.37
Ash % 8.360 ± 0.21 38.27 ± 1.26 60.87 ± 7.31 60.46 ± 0.02 64.22 ± 0.09
pH 1:10 5.95 ± 0.03 10.1 ± 0.02 6.15 ± 0.02 8.85 ± 0.04 9.37 ± 0.01
Cation exchangeable capacity cmol kg−1 66.01 ± 0.00 57.83 ± 13.26 72.55 ± 3.95 41.27 ± 0.84 86.43 ± 0.65
Surface area m2 g−1 0.393 198.36 220.92 124.73 134.77
Pore size nm 28.42 5.614 5.819 6.023 9.843
Total volume in pores cm3 g−1 0.00021 0.1069 0.06082 0.054 0.06075
C % 41.21 75.59 8055 74.64 73.03
H % 7.23 4.89 11.09 1.35 13.36
N % 2.89 0.00 1.38 0.00 0.00
O % 48.67 19.51 4.19 24.01 13.61
S % 0.00 0.00 0.00 0.00 0.00
O/C – 0.89 0.19 0.043 0.24 0.14
H/C – 2.09 0.77 1.64 0.22 2.18

DBM, date palm waste biomass; DBC, date palm waste–derived biochar; nZVI-DBC, date palm waste–derived biochar composite with nano-zerovalent
iron; S-DBC, date palm waste–derived biochar composite with silica; Z-DBC, date palm waste–derived biochar composite with zeolite
Environ Sci Pollut Res

DBM (5.95) increased almost twofold in DBC (10.10), while and aromaticity of the biochar-based composites have been
3 and 4 unite in S-DBC and Z-DBC, respectively, with pyrol- presented with van Krevelen diagram (Fig. S1 in the
ysis due to lower acid functional groups and condensation of Supplementary Material), indicating that the biochar-based
basic functional groups (Ahmad et al. 2018c). However, the materials possessed lower O/C ratios suggesting higher stabil-
pH of the composites was lower than that of the DBC. The ity than the DBM.
lowest pH of nZVI-DBC (6.15) could be due to several wash-
ings which were performed during its synthesis, which might
have washed out all the soluble basic cations (Ahmad et al. Ultimate analyses
2017). The CEC of the DBM reduced from 66.01 cmol kg−1 to
57.83 and 41.27 cmol kg−1 in DBC and S-DBC, respectively. The surface morphology as indicated by the SEM images
This reduction in CEC might be due to loss of surface func- (Fig. 1a–e) represented the formation of channelized surface
tional groups and increased carbon aromaticity during pyrol- of the biochar composites as a result of pyrolysis. The rod-like
ysis (Joseph et al. 2010). The highest CEC was noticed in Z- structures on nZVI-DBC represented the presence of Fe0 par-
DBC (86.43 cmol kg−1), followed by nZVI-BC ticles onto biochar matrix, while the presence of silica and
(72.55 cmol kg−1) composites, which might be due to the zeolite mineral particles was also observed on the surface of
presence of zeolite and nanoscale iron particles in the matrix, S-DBC and Z-DBC, respectively. The variation in the miner-
respectively (Ahmad et al. 2017) alogical phases of the biochars was investigated with XRD
Surface area, pore size, and pore volume analyses results of (Fig. 2a, b). A sharp peak in DBM at 2θ = 21.48 was desig-
the biochars have also been shown in Table 1. The nZVI-DBC nated as mellite (Al2[C6(COO)6].16H2O), which reduced to
showed the highest BET surface area (220.92 m2 g−1) among its minimum in all the composited biochars. Likewise, the
all the biochars, followed by DBC (198.36 m2 g−1), while S- peaks ascribed as calcite (CaCO3) and sylvite (KCl) in DBM
DBC and Z-DBC exhibited lowest surface area (124.73 and were also reduced after pyrolysis. The peaks at 2θ = 44 and 63
134.77 m2 g−1, respectively) compared with DBC alone. The in nZVI-DBC confirmed the presence of Fe0 particles (Ahmad
highest surface area of nZVI-DBC was due to the presence of et al. 2018a). A small peak of graphene was also detected at
Fe0 particles in the biochar matrix, while the lower surface 2θ = 18.5 in nZVI-DBC. The peaks at 2θ = 9.82, 11.14, 19.06,
area of S-DBC and Z-DBC was due to the blockage of pores and 22.29 were designated as clinoptilolite (zeolite) in Z-
in the biochar matrix with silica and zeolite particles (Ahmad DBC. The peaks at 2θ = 20.88 and 26.68 were designated as
et al. 2017, 2018a). Pore size reduced from 28.420 nm in SiO2, while a peak at 2θ = 50.18 was designated as feldspar in
DBM to ~ 5–10 nm in biochars due to condensation of aro- S-DBC. The FTIR spectra of the synthesized composites are
matic structure and loss of volatiles. The total volume in pores presented in Fig. 2c. A broad band in DBM at 3300 cm−1 was
was lower in the composite biochars (0.06082, 0.0500, and ascribed as O–H stretches of H-bonding of the water mole-
0.06075 cm3 g−1 in nZVI-DBC, S-DBC, and Z-DBC, respec- cules, which vanished with pyrolysis. Likewise, two bands
tively) compared with the biochar (0.10690 cm3 g−1). The around 2900 cm−1 in DBM were designated as O–H and ali-
reduction in the pore volume in the composite biochars could phatic C–H stretches, which were lost during pyrolysis. A
be due to the blockage of mesopores with Fe0, silica, and band at 1089 cm−1 in all the biochars (except nZVI-DBC)
zeolite particles (Rawal et al. 2016). The elemental composi- was due to C–O–C stretches (polysaccharide cellulose). The
tion of the biochars showed that the carbon (C) contents in- bands around 3300 and 1625 cm−1 in nZVI-DBC were due to
creased with the pyrolysis from 41.21% in DBM to 75.59% in N–H stretches (due to the presence of chitosan). The presence
DBC due to carbonization. It was interesting to observe that of Fe0 nanoparticles in nZVI-DBC was confirmed with a
the C contents in S-DBC and Z-DBC remained comparable sharp band at 3426 cm−1 due to the presence of stretching
(74.64% and 73.03%, respectively) to that in DBC, while vibration of –OH, suggesting the formation of ferric
increased slightly in nZVI-DBC (80.55%). The contents of oxyhydroxide (FeOOH) layer on Fe0 nanoparticles (Singh
H reduced with pyrolysis in DBC and S-DBC, while increased et al. 2011). A band at 777 cm−1 in S-DBC was ascribed
in Z-DBC and nZVI-DBC, which could be due to the bonding as Si–O. A band representing clinoptilolite (Na, K, Ca)2–
of H with minerals. Likewise, the N and O contents reduced 3Al3(Al,Si)2Si13O36.12H2O due to TO4 (tetrahedral) of Al–
with thermalization of the DBM, which could be due to loss of Si was overlapped at 1089 cm−1 in Z-DBC. Thermal de-
the functional groups as a result of dehydration and depoly- gradability of the biochars as assessed through TGA ther-
merization (Al-Wabel et al. 2013). The O/C molar ratios indi- mograms is presented in Fig. S2. Weight loss around
cated that all biochar-based materials possess the lower values 200 °C was due to the loss of non-structural free water,
compared with DBM, suggesting a decrease in hydrophobic- while from 300 to 400 °C was due to the decomposition
ity and surface polarity with pyrolysis. The lowest H/C molar of cellulosic and hemicellulosic compounds (Yang et al.
was exhibited by S-DBC, suggesting the higher aromatic na- 2007). The complete weight loss due to the degradation
ture of the composite (Usman et al. 2015). The surface polarity of lignin occurred around 650–800 °C for nZVI-DBC, S-
 Environ Sci Pollut Res

Fig. 1 Scanning electron microscope (SEM) images of a date palm CTC (chlortetracycline) adsorption, g date palm waste–derived biochar
waste–derived biomass (DBM), b date palm waste–derived biochar composite with nano-zerovalent iron (nZVI-DBC) after CTC adsorption,
(DBC), c date palm waste–derived biochar composite with nano- h date palm waste–derived biochar composite with silica (S-DBC) after
zerovalent iron (nZVI-DBC), d date palm waste–derived biochar com- CTC adsorption, and i date palm waste–derived biochar composite with
posite with silica (S-DBC), e date palm waste–derived biochar composite zeolite (Z-DBC) after CTC adsorption
with zeolite (Z-DBC), f date palm waste–derived biochar (DBC) after

DBC, and Z-DBC, while at 900 and 1010 °C for DBM and the isotherms that the CTC adsorption increased with increase
DBC, respectively (Hernandez-Mena et al. 2014). in initial solution concentration until equilibrium (Ahmad
et al. 2018a, b). The nZVI-DBC exhibited H-type (high-
Equilibrium CTC adsorption affinity) isotherm suggesting a strong adsorbent-adsorbate in-
teractions, while the other sorbents demonstrated L-type iso-
The efficacy of the engineered and pristine biochars for CTC therm suggesting less availability of the active sites (Ahmad
adsorption was evaluated in equilibrium batch adsorption ex- et al. 2018b). Overall, the five isotherms presented a similar
periments. The nonlinear forms of Langmuir, Freundlich, trend for CTC adsorption following the order of nZVI-DBC >
Temkin, Dubinin–Radushkevich, and Redlich–Peterson iso- S-DBC > Z-DBC > DBC. The isotherm parameters obtained
therms were employed to evade the errors, and the resultant from nonlinear regressions are provided in Table 2. All the
adsorption isotherms are presented in Fig. 3. It is obvious in all employed models exhibited good fitness with R2 > 0.78;
Environ Sci Pollut Res

Fig. 2 X-ray diffraction patterns (a and b) and Fourier transform infrared zerovalent iron), S-DBC (date palm waste–derived biochar composite
spectroscopy spectra (c) of DBC (date palm waste–derived biochar), with silica), and Z-DBC (date palm waste–derived biochar composite
nZVI-DBC (date palm waste–derived biochar composite with nano- with zeolite) (G: graphene, M: mellite, S: sylvite, C: calcite, H: halite)

however, the Langmuir and Redlich–Peterson isotherms (12.536 J mol−1), followed by S-DBC (6.476 J mol−1), Z-
showed the highest fitness to the adsorption data by generating DBC (4.688 J mol − 1 ), and DBC (3.155 J mol − 1 ).
the highest R2 values in the range of 0.88–0.98 and 0.88–0.99, Furthermore, the Dubinin–Radushkevich-predicted maxi-
respectively, compared with the rest of the isotherms. The mum CTC adsorption capacities (QD) were highest for
Langmuir isotherm–predicted maximum CTC adsorption ca- nZVI-DBC (72.369 mg g − 1 ), followed by S-DBC
pacities (QL) of the engineered biochars were 89.05, 45.57, (40.941 mg g −1 ), Z-DBC (29.430 mg g −1 ), and DBC
30.42, and 28.19 mg g−1 for nZVI-DBC, S-DBC, Z-DBC, and (24.569 mg g−1), while the bonding energies (E) for all the
DBC, respectively, suggesting the nZVI-DBC as the most engineered biochars were less than 8 kJ g−1. Further, the fa-
efficient sorbent for CTC among the tested biochars. The vorability for the adsorption of CTC onto the engineered bio-
Freundlich isotherm–predicted sorptive affinity (KF) followed chars was tested with the help of Freundlich-predicted 1/n
the same order giving the highest value for nZVI-DBC (component related to linearity) and Langmuir-predicted RL
(25.665 L g−1), followed by S-DBC (17.005 L g−1), Z-DBC (separation factor). It has been established that RL = 0 indi-
(12.310 L g−1), and DBC (8.146 L g−1), suggesting the highest cates irreversible, 0 < RL < 1 indicates favorable, RL = 1 indi-
adsorption onto nZVI-DBC due to the greater availability of cates linear, and RL > 1 indicates unfavorable isotherm
adsorption sites. (Mohan et al. 2011). In the current study, the RL values ranged
As the Redlich–Peterson equation integrates the features of from 0.008 to 0.547 suggesting a favorable adsorption of CTC
both Freundlich and Langmuir, it can be employed either for onto the engineered biochars (Fig. S3). It was noticed that any
heterogeneous or homogenous systems (Foo and Hameed increase in initial CTC concentrations has resulted in reduc-
2010). The best fit of the Redlich–Peterson model also sug- tion of RL values. Specifically, the calculated RL values for
gested that multiple mechanisms were involved in the CTC tested initial concentrations were in the range of 0.026–
adsorption onto engineered biochars (Liu et al. 2010). The 0.340, 0.016–0.243, 0.008–0.141, and 0.058–0.547 for
Redlich–Peterson-predicted g values were in the range of nZVI-DBC, S-DBC, Z-DBC, and DBC, respectively. It is
0.533–0.992, suggesting that the imitation for Langmuir iso- clear from the presented results that RL values for all the bio-
therm was more than Freundlich. The nZVI-DBC showed the chars were less than unity, suggesting a favorable adsorption
lowest value of g, suggesting higher CTC adsorption, which is process. Likewise, 1/n ranged between 0.249 and 0.484 for all
also in agreement with Langmuir and Freundlich isotherms. the biochars, suggesting that the sorptive affinity was favor-
The higher heat of adsorption (b) as predicted by Temkin able for the adsorption of CTC onto all the tested biochars due
isotherm was seen in the case of nZVI-DBC to the strong bonding of CTC and sorbents (Ahmad et al.
 Environ Sci Pollut Res

Fig. 3 CTC (chlortetracycline) adsorption isotherms fittings on a palm waste–derived biochar composite with nano-zerovalent iron (nZVI-
Langmuir, b Freundlich, c Redlich–Peterson, d Temkin, and e Dubinin– DBC), date palm waste–derived biochar composite with silica (S-DBC),
Radushkevich models by date palm waste–derived biochar (DBC), date and date palm waste–derived biochar composite with zeolite (Z-DBC)
Environ Sci Pollut Res

Table 2 Nonlinear parameters of

Langmuir, Freundlich, and Isotherms Parameters nZVI- S-DBC Z-DBC DBC
Redlich–Peterson isotherms indi- DBC
cating CTC (chlortetracycline)
adsorption onto date palm waste– Langmuir QL (mg g−1) 89.05 45.57 30.42 28.19
derived biochar (DBC), date palm KL (L g−1) 0.388 0.624 1.219 0.165
waste–derived biochar composite R2 0.96 0.98 0.96 0.88
with nano-zerovalent iron (nZVI-
DBC), date palm waste–derived Freundlich KF (L g−1) 25.664 17.005 12.310 8.146
biochar composite with silica (S- 1/n 0.484 0.285 0.249 0.287
DBC), and date palm waste– R2 0.98 0.91 0.92 0.90
derived biochar composite with
Redlich–Peterson A (L g−1) 0.304 21.884 40.812 5.514
zeolite (Z-DBC)
B (L mg−1)g 49.820 0.304 1.812 0.255
g 0.533 0.992 0.929 0.913
R2 0.98 0.99 0.96 0.88
Temkin b (J mol−1) 12.536 6.476 4.688 3.155
A (L g−1) 18.174 25.017 18.663 30.403
R2 0.94 0.94 0.94 0.78
Dubinin–Radushkevich QD (mg g−1) 72.369 40.941 29.430 24.569
E (kJ g−1) 0.0019 0.0008 0.0003 0.008
R2 0.90 0.96 0.96 0.80

2018a, b). These results suggested that all the investigated DBC, Z-DBC, and DBC compared with nZVI-DBC.
biochars were suitable for the removal of CTC from aqueous Likewise, SEE was found to be the lowest for power function,
solutions. The nZVI-DBC was found to be the most efficient intraparticle diffusion, Elovich, pseudo-first-order, and
engineered biochar with highest CTC adsorption efficiency. pseudo-second-order models compared with first- and
second-order models. The parameters derived from the kinet-
Kinetics CTC adsorption ics models are presented in Table 4. The nZVI-DBC exhibited
highest rate constant (b = 0.20), followed by Z-DBC (0.11), S-
Kinetics sorption batches were performed at a constant tem- DBC (0.05), and DBC (− 0.19) as predicted by power func-
perature to investigate the rate of CTC adsorption onto the tion. Likewise, the highest diffusion constant (c) was demon-
engineered biochars, and the dynamics of adsorption are pre- strated by nZVI-DBC (8.88), followed by Z-DBC (3.15), S-
sented in Fig. 4. Three adsorption stages, i.e., rapid, relatively DBC (0.10), and DBC (− 1.68). Elovich-predicted rate con-
slow, and equilibrium, are obvious in the dynamics of CTC stant (β) was highest for S-DBC (− 6.51) followed by nZVI-
adsorption. The rapid adsorption stage exhibited the highest DBC (− 5.13). As the rate constants determine the time for a
CTC adsorption during initial 180 min, by removing 90%, reaction completion, therefore, highest rate constants of nZVI-
43%, 30%, and 21% CTC through nZVI-DBC, S-DBC, Z- DBC suggested that it required shorter time to sorb CTC com-
DBC, and DBC, respectively. During the relatively slow stage pared with the other tested biochars. The initial adsorption
(180 to 360 min), nZVI-DBC, S-DBC, Z-DBC, and DBC rates as predicted by pseudo-second-order (h) and Elovich
removed 97%, 63%, 29%, and 28% of CTC, respectively. (α) models have followed the similar trend by generating the
The nZVI-DBC was found to be the most efficient sorbent highest value for nZVI-DBC (5.76 and 11.5 mg g−1 min−1,
removing 98% CTC, followed by S-DBC (68%), Z-DBC respectively), followed by S-DBC (0.44 and
(35%), and DBC (36%) after 360 min (equilibrium stage). 7.80 mg g −1 min −1 , respectively), Z-DBC (0.44 and
The kinetics adsorption data was subjected to kinetics models 3.84 mg g−1 min −1, respectively), and DBC (0.13 and
such as first-order, second-order, pseudo-first-order, pseudo- 2.41 mg g−1 min−1, respectively). The maximum adsorption
second-order, Elovich, power function, and intraparticle dif- capacities (qe) were in the order of nZVI-DBC, S-DBC, Z-
fusion. The estimated error functions of these models DBC, and DBC, which were in correspondence with the
(Table 3) indicated their appropriateness for the adsorption Langmuir and Freundlich isotherms.
of CTC onto the tested biochars (except first- and second- The rate coefficient (kf) values as estimated from power
order). Based on the R2 values, power function, intraparticle function model were highest for nZVI-DBC
diffusion, and Elovich were the most appropriate, while first- (0.70 mg g−1 min−1), followed by S-DBC
and second-order were inappropriate models for CTC adsorp- (0.63 mg g−1 min−1), Z-DBC (0.52 mg g−1 min−1), and DBC
tion onto the tested biochars. However, pseudo-first-order and (0.51 mg g−1 min−1), suggesting increase in CTC adsorption
pseudo-second-order models were more appropriate for S- onto these biochars with time. Similar to other parameters, the
 Environ Sci Pollut Res

Fig. 4 CTC (chlortetracycline)

adsorption kinetics onto date
palm waste–derived biochar
(DBC), date palm waste–derived
biochar composite with nano-
zerovalent iron (nZVI-DBC), date
palm waste–derived biochar
composite with silica (S-DBC),
and date palm waste–derived
biochar composite with zeolite
(Z-DBC)

highest apparent diffusion rate constant (kid) was exhibited by modeled data suggested mono-layer coverage of CTC onto
nZVI-DBC (2.83 [mg g−1]−0.5), followed by S-DBC (2.15 homogenous surface of the biochars, while the closeness with
[mg g−1]−0.5), DBC (1.08 [mg g−1]−0.5), and Z-DBC (0.95 Freundlich-modeled data suggested multi-layer CTC adsorp-
[mg g−1]−0.5), suggesting a quick adsorption of CTC onto tion onto the biochars onto heterogeneous surface of the ma-
nZVI-DBC due to interaparticle diffusion process. Hence, terial (Ahmad et al. 2018a, b). Additionally, mono- and multi-
based on adsorption dynamics, power function, interaparticle layer adsorptions were aided by the best fitness of Redlich–
diffusion, and Elovich models best described the adsorption Peterson model, which combines the benefits of both the
kinetics of CTC onto the tested biochars. Moreover, nZVI- Langmuir and Freundlich isotherms. The porous structure of
DBC exhibited the highest rate constants, initial adsorption the biochars further facilitated the physical adsorption of CTC
rates, and apparent diffusion rate constants compared with as indicated by the Dubinin–Radushkevich isotherm.
other tested biochars. However, it was noticed that the bonding energies (E) were
less than 8 kJ g−1 for all the biochars, suggesting that ion-
Mechanism for CTC removal complexation mechanism was not involved in the adsorption
process (Ho et al. 2002). This adsorption process was further
Various kinetics and empirical models were used to under- supported by best fit of Temkin isotherm, which assumes
stand the mechanism of CTC adsorption by using the chemisorption of an adsorbate onto the adsorbent. To further
engineered biochars. The best fitness of the Redlich– investigate the operating adsorption mechanism, adsorption
Peterson model suggested that both the Langmuir and dynamics data was used. The adsorption of CTC was well
Freundlich isotherms were applicable for the CTC adsorption described by power function, Elovich, and interaparticle dif-
data. The closeness of experimental data with Langmuir- fusion models. The best fitness of power function model (R2

Table 3 Standard errors of estimate (SEE) of kinetic models for CTC zerovalent iron (nZVI-DBC), date palm waste–derived biochar compos-
(chlortetracycline) adsorption onto date palm waste–derived biochar ite with silica (S-DBC), and date palm waste–derived biochar composite
(DBC), date palm waste–derived biochar composite with nano- with zeolite (Z-DBC)

Sorbent First-order Second-order Pseudo-first-order Pseudo-second-order Elovich Intraparticle diffusion Power function

R2 SEE R2 SEE R2 SEE R2 SEE R2 SEE R2 SEE R2 SEE

nZVI-DBC 0.34 0.003 0.02 0.485 0.84 4.0 × 10−5 0.33 2.8 × 10−4 0.89 5.8 × 10−3 0.85 1.6 × 10−3 0.96 2.8 × 10−5
S-DBC 0.45 0.004 0.07 0.019 0.82 3.4 × 10−4 0.90 1.6 × 10−4 0.79 1.3 × 10−4 0.94 1.9 × 10−3 0.99 1.9 × 10−7
Z-DBC 0.38 0.011 0.01 0.192 0.79 3.5 × 10−7 0.98 2.7 × 10−5 0.94 3.9 × 10−4 0.90 1.0 × 10−3 0.98 0.652
DBC 0.62 0.028 0.11 0.299 0.95 1.8 × 10−4 0.70 0.010 0.56 4.4 × 10−4 0.96 9.5 × 10−4 0.93 5.0 × 10−5
Environ Sci Pollut Res

Table 4 Standard errors of estimate (SEE) of kinetic models for CTC zerovalent iron (nZVI-DBC), date palm waste–derived biochar compos-
(chlortetracycline) adsorption onto date palm waste–derived biochar ite with silica (S-DBC), and date palm waste–derived biochar composite
(DBC), date palm waste–derived biochar composite with nano- with zeolite (Z-DBC)

Sorbent First-order Second-order Pseudo-first-order Pseudo-second-order Elovich Intraparticle diffusion Power function

k1 k2 k1′ qe k2′ qe h a β kid c kf b

nZVI-DBC 3.6 × 10−3 1.0 × 10−5 − 6.2 × 10−5 3.83 1.0 × 10−5 3282 5.76 11.5 − 5.13 2.83 8.88 0.70 0.20
S-DBC 3.7 × 10−3 2.0 × 10−5 − 6.2 × 10−5 3.77 1.1 × 10−4 62.16 0.44 7.80 − 6.51 2.15 0.10 0.63 0.05
Z-DBC 2.8 × 10−5 1.0 × 10−5 − 4.5 × 10−5 2.65 6.2 × 10−4 26.66 0.44 3.84 − 1.53 0.95 3.15 0.52 0.11
DBC 3.6 × 10–3 −1.2 × 10−4 − 4.7 × 10−3 3.15 9.7 × 10−5 36.02 0.13 2.41 − 3.60 1.08 − 1.68 0.51 − 0.19

ranged between 0.93 and 0.99) suggested a strong relationship multi-layer chemisorption (covalent binding with the surface
between the mass of CTC adsorbed on a unit mass of the functional groups) as the rate-limiting step in CTC adsorption
biochars and time of reaction. The R 2 values for the onto the tested biochars, which corresponded to the results of
interaparticle diffusion model ranged between 0.85 and 0.96, Freundlich and Temkin isotherms. The chemisorption process
indicating the heterogeneous diffusion of CTC particles into was further supported by the fitness of pseudo-second-order
the porous surface of the biochars. Likewise, the best fitness of model to some extent (R2 ranged between 0.33 and 0.98).
Elovich model (R2 ranged between 0.56 and 0.89) suggested Beside heterogeneous diffusion and chemisorption, the CTC

Fig. 5 a XRD (X-ray diffraction) and b FTIR (Fourier transform infrared composite with nano-zerovalent iron (nZVI-DBC), date palm waste–
spectroscopy) spectra after CTC (chlortetracycline) adsorption onto date derived biochar composite with silica (S-DBC), and date palm waste–
palm waste–derived biochar (DBC), date palm waste–derived biochar derived biochar composite with zeolite (Z-DBC)
 Environ Sci Pollut Res

adsorption was also aided by the physical adsorption onto the (having both positive and negative electrical charges on dif-
surfaces as described by pseudo-first-order kinetics model and ferent locations). Therefore, due to the presence of both neg-
Langmuir isotherm. Therefore, it was stated that the CTC ative and positive charges simultaneously on CTC, the solu-
adsorption onto the biochars was being controlled with mul- tion pH range of 2–6 is considered to be optimum for CTC
tiple sorption processes including diffusion into pores, chem- adsorption (Guocheng et al. 2012). The adsorption of CTC
ical reactions with the surface functional groups, and physical onto the biochars was confirmed by analyzing the post-
adsorption on the surfaces of the tested biochars. The highest sorption biochar samples with SEM, XRD, and FTIR. The
adsorption of CTC onto nZVI-DBC followed by S-DBC and SEM images showed whitish compounds on the surface and
Z-DBC could be due to the decline in solution pH towards within the pores, which might be referred to the CTC mole-
acidity (Fig. S4a and b), as the CTC adsorption is highly cules (Fig. 1f–i). Three new peaks in all the biochars detected
influenced by the solution pH and hydrophobicity of the sor- at 2θ = 4.28, 10.09, and 11.86 were ascribed as CTC in XRD
bent (Torres-Pérez et al. 2012). The correlation of solution pH patterns of post-sorption biochar samples (Fig. 5a). Likewise,
with CTC adsorption has presented a significant negative cor- a small band at 1527 cm−1 and a shoulder peak at 1079 cm−1
relation with R2 value of 0.92 (Fig. S4c). Therefore, nZVI- were designated as CTC in FTIR spectra of post-sorption bio-
DBC exhibited the highest CTC adsorption due to lowest chars (Fig. 5b). The variations at 1079 and 1527 suggested
solution pH compared with other biochars. It has been ob- that some chemical interactions have occurred between amide
served that the maximum rise in solution pH for DBC, groups of CTC with C–O–C, Si–O, and N–H groups of bio-
nZVI-DBC, S-DBC, and Z-DBC was 7.44, 5.5, 6.6, and 6.8, chars, respectively (Zhang et al. 2015). Therefore, the CTC
respectively, suggesting that the solution pH remained below adsorption onto DBC, S-DBC, Z-DBC, and nZVI-DBC was
the pH at point of zero charge for all the sorbents (pHPZC for being controlled by multiple mechanisms such as (i) chemical
DBC, nZVI-DBC, S-DBC, and Z-DBC was 8.7, 5.2, 8.1, and adsorption, (ii) physical adsorption (H-bonding), and porous
9.2, respectively) (Fig. S4d). These results suggested that both diffusion.
negative and positive surface charges were prevailing on the It has been reported that the surface polarity of the adsor-
all the adsorbents. As the solution pH was in the range of bent is of critical importance in controlling the adsorption of
3.30–7.44, the protons from phenolic-pentanedione of CTC an organic pollutant via π-π electron donor–accepter interac-
were released, which has transformed CTC into zwitterion tions. Due to the lowest O/C ratio (0.043) of nZVI-DBC

Fig. 6 Proposed mechanisms involved in CTC (chlortetracycline) ad- DBC), date palm waste–derived biochar composite with silica (S-
sorption onto date palm waste–derived biochar (DBC), date palm DBC), and date palm waste–derived biochar composite with zeolite (Z-
waste–derived biochar composite with nano-zerovalent iron (nZVI- DBC)
Environ Sci Pollut Res

among all the studied sorbents and lowest pHPZC (5.2), the adsorption data was best described by power function,
chances of CTC adsorption onto nZVI-DBC via π-π electron interaparticle diffusion, pseudo-first-order, and Elovich
donor–accepter interactions enhanced significantly. models. Chemisorption, H-bonding, and porous diffusion
Additionally, the Fe0 particles in the nZVI-DBC acted as re- were the main mechanisms controlling CTC adsorption onto
ducing agent, which might adsorb the CTC molecule via π-π DBC, S-DBC, and Z-DBC. However, the highest CTC re-
electron donor–accepter interactions on one hand, and re- moval by nZVI-DBC was resulted by the augmentation of
duced the CTC molecules on the other hand by removing – chemisorption, H-bonding, and diffusion process with π-π
CH3, –NH2, –OH, and –CHO groups (Chen et al. 2011; electron donor–accepter interactions and redox reactions.
Rajapaksha et al. 2015). The degraded CTC molecules after Therefore, nZVI-DBC can be used as an efficient sorbent for
the loss of functional groups may further adsorb onto the cost-effective and eco-friendly removal of CTC from waste-
nZVI-DBC matrix after reduction, while the Fe0 particles water. Moreover, producing biochar from date palm waste
were converted to Fe 3 + and Fe 2 + after oxidation. through pyrolysis may reduce surface pollution. Hence, date
Additionally, the amino group in CTC may have produced palm–derived biochar composited with nZVI could serve as
Fe–N covalent bonds with Fe3+ and Fe2+ after oxidation of an economic and green technology for the remediation of
Fe0, resulting in higher CTC adsorption in nZVI-DBC com- CTC-contaminated wastewater.
pared with other biochars (Zhang et al. 2015). It has been
reported from the previous researches that the adsorption of Funding information This work was funded by the Dean of Scientific
the organic pollutants onto carbon-based sorbents might be Research at King Saud University through research group no. RG-1439-
controlled by π-π interaction, H-bonding, hydrophobic inter- 043.
action, electrostatic interactions, and pore-filling (Swathi and
Sebastian 2009; Han et al. 2014; Gao et al. 2012). Likewise, Compliance with ethical standards
Jiang et al. (2013) stated that O-containing functional groups
were responsible for higher tetracycline adsorption due to π–π Conflict of interest The authors declare that they have no conflict of
interest.
electron donor–acceptor interactions. The absence of O-
containing functional groups at 3426 and 1650 cm−1 in post-
sorption sorbents confirmed the presence of π–π interactions
between the sorbents and CTC (Fig. 5b). Therefore, it was
concluded that (i) chemisorption, (ii) H-bonding, and (iii) dif- References
fusion into the surface pores could be the operating mecha-
nisms controlling CTC adsorption onto DBC, S-DBC, and Z- Ahmad M, Lee SS, Rajapaksha AU, Vithanage M, Zhang M, Cho JS, Lee
DBC, while (i) chemisorption, (ii) H-bonding, (iii) diffusion SE, Ok YS (2013) Trichloroethylene adsorption by pine needle bio-
chars produced at various pyrolysis temperatures. Bioresour
into the surface pores, (iv) redox reactions, and (v) π-π elec- Technol 143:615–622
tron donor–accepter interactions could be the operating mech- Ahmad M, Ahmad M, Usman AR, Al-Faraj AS, Abduljabbar A, Ok YS,
anisms for CTC adsorption onto nZVI-DBC composites Al-Wabel MI (2017) Date palm waste-derived biochar composites
(Fig. 6). with silica and zeolite: synthesis, characterization and implication
for carbon stability and recalcitrant potential. Environ Geochem
Health 1–18. https://doi.org/10.1007/s10653-017-9947-0
Ahmad M, Ahmad M, Usman AR, Al-Faraj AS, Abduljabbar AS, Al-
Conclusion Wabel MI (2018a) Biochar composites with nano zerovalent iron
and eggshell powder for nitrate removal from aqueous solution with
Date palm waste–derived biochar (DBC) was used to design coexisting chloride ions. Environ Sci Pollut Res 25:25757–25771
Ahmad M, Ahmad M, Usman ARA, Al-Faraj AS, Ok YS, Hussain Q,
various engineered biochars with nZVI, silica, and zeolite
Abduljabbar A, Al-Wabel MI (2018b) An efficient phosphorus
(nZVI-DBC, S-DBC, and Z-DBC, respectively), and tested scavenging from aqueous solution using magnesiothermally modi-
for chlortetracycline (CTC) removal from aqueous solutions. fied bio-calcite. Environ Technol 39:1638–1649
The produced biochars were characterized to investigate Ahmad M, Usman AR, Al-Faraj AS, Ahmad M, Sallam A, Al-Wabel MI
chemical, structural, and surface properties. The nZVI-DBC (2018c) Phosphorus-loaded biochar changes soil heavy metals
availability and uptake potential of maize (Zea mays L.) plants.
exhibited lowest pH (6.15) and highest surface area Chemosphere 194:327–339
(220.92 m2 g−1) compared with other biochars. Isotherm and Ahmaruzzaman M (2008) Adsorption of phenolic compounds on low-
kinetics batch adsorption experiments were conducted to in- cost adsorbents: a review. Adv Colloid Interf Sci 143:48–67
vestigate the efficiency of the produced sorbent materials for Al-Wabel MI, Al-Omran A, El-Naggar AH, Nadeem M, Usman ARA
CTC removal from aqueous solutions. Langmuir-predicted (2013) Pyrolysis temperature induced changes in characteristics and
chemical composition of biochar produced from conocarpus wastes.
maximum CTC adsorption capacity was in the order of Bioresour Technol 131:374–379
nZVI-DBC (89.05 mg g−1) > S-DBC (45.57 mg g−1) > Z- Aly HM (2017) Biochar and its importance in adsorption of antibiotic and
DBC (30.42 mg g−1) > DBC (28.19 mg g −1). Kinetics heavy metals from aqueous solutions. Ecol Quest 24:75–78
 Environ Sci Pollut Res

American Society for Testing and Materials (ASTM) (1989) Standard Kümmerer K, Henninger A (2003) Promoting resistance by the emission
methods for chemical analysis of wood charcoal, ASTM D1762- of antibiotics from hospitals and households into effluent. Clin
84. Philadelphia, PA, USA Microbiol Infect 9:1203–1214
Ashfaq M, Khan KN, Rasool S, Mustafa G, Saif-Ur-Rehman M, Nazar Lindberg RH, Fick J, Tysklind M (2010) Screening of antimycotics in
MF, Sun Q, Yu CP (2015) Occurrence and ecological risk assess- Swedish sewage treatment plants-waters and sludge. Water Res 44:
ment of fluoroquinolone antibiotics in hospital waste of Lahore, 649–657
Pakistan. Environ Toxicol Pharmacol 42:16–22 Liu QS, Zheng T, Wang P, Jiang JP, Li N (2010) Adsorption isotherm,
Bao Y, Zhou Q, Guan L, Wang Y (2009) Depletion of chlortetracycline kinetic and mechanism studies of some substituted phenols on acti-
during composting of aged and spiked manures. Waste Manag 29: vated carbon fibers. Chem Eng J 157:348–356
1416–1423 Liu WJ, Zeng FX, Jiang H, Zhang XS (2011) Preparation of high adsorp-
Bilgic C (2005) Investigation of the factors affecting organic cation ad- tion capacity bio-chars from waste biomass. Bioresour Technol 102:
sorption on some silicate minerals. J Colloid Interface Sci 281:33– 8247–8252
38 Makowska N, Koczura R, Mokracka J (2016) Class 1 integrase, sulfon-
Chatterjee S, Lim SR, Woo SH (2010) Removal of reactive black 5 by amide and tetracycline resistance genes in wastewater treatment
zero-valent iron modified with various surfactants. Chem Eng J 160: plant and surface water. Chemosphere 144:1665–1673
27–32 Meng Y, Guan B, Wu Z, Wang D (2006) Enhanced degradation of carbon
Chen H, Luo H, Lan Y, Dong T, Hu B, Wang Y (2011) Removal of tetrachloride by surfactant-modified zero-valent iron. J Zhejiang
tetracycline from aqueous solutions using polyvinylpyrrolidone Univ Sci 7:702–707
(PVP-K30) modified nanoscale zero valent iron. J Hazard Mater Mohan D, Rajput S, Singh VK, Steele PH, Pittman CU Jr (2011) Modeling
192:44–53 and evaluation of chromium remediation from water using low cost
Daughton CG, Ternes TA (1999) Pharmaceuticals and personal care bio-char, a green adsorbent. J Hazard Mater 188:319–333
products in the environment agents of subtle change. Environ Mohan D, Sarswat A, Yong SO, Jr CUP (2014) Organic and inorganic
Health Perspect 107:907–938 contaminants removal from water with biochar, a renewable, low
Devi P, Saroha AK (2014) Synthesis of the magnetic biochar composites cost and sustainable adsorbent – a critical review. Bioresour Technol
for use as an adsorbent for the removal of pentachlorophenol from 160:191–202
the effluent. Bioresour Technol 169:525–531 Montforts MH (1999) Environmental risk assessment for veterinary me-
Dong H, Deng J, Xie Y, Zhang C, Jiang Z, Cheng Y, Hou K, Zeng G dicinal products. Part 1: other than GMO-containing and immuno-
(2017) Stabilization of nanoscale zero-valent iron (nZVI) with mod- logical products. RIVM report 601300 001, N120. National Institute
ified biochar for Cr(VI) removal from aqueous solution. J Hazard of Public Health and the Environment, Bithoven
Mater 332:79–86
Ok YS, Yang JE, Zhangm YS, Kim SJ, Chung DY (2007) Heavy metal
Foo KY, Hameed BH (2010) Insights into the modeling of adsorption
adsorption by a formulated zeolite-Portland cement mixture. J
isotherm systems. Chem Eng J 156:2–10
Hazard Mater 147:91–96
Gao Y, Li Y, Zhang L, Huang H, Hu J, Shah SM, Su X (2012) Adsorption
Ozcimen D, Ersoy-Mericboyu A (2010) Characterization of biochar and
and removal of tetracycline antibiotics from aqueous solution by
bio-oil samples obtained from carbonization of various biomass ma-
graphene oxide. J Colloid Interface Sci 15:540–546
terials. Renew Energy 35:1319–1324
Guocheng LÜ, Limei WU, Xiaolong WANG, Libing LIAO, Xiaoyu
Phenrat T, Saleh N, Sirk K, Tilton RD, Lowry GV (2006) Aggregation
WANG (2012) Adsorption of chlortetracycline from water by rec-
and sedimentation of aqueous nanoscale zerovalent iron dispersions.
tories. Chin J Chem Eng 20:1003–1007
Environ Sci Technol 41:284–290
Gurses A, Dogar C, Yalcin M, Acikyildiz M, Bayrak R, Karaca S (2006)
The adsorption kinetics of the cationic dye, methylene blue, onto Rajapaksha AU, Vithanage M, Ahmad M, Seo DC, Cho JS, Lee SE, Lee
clay. J Hazard Mater 131:217–228 SS, Ok YS (2015) Enhanced sulfamethazine removal by steam-
Han L, Sun K, Jin J, Wei X, Xia X, Wu F, Gao B, Xing B (2014) Role of activated invasive plant-derived biochar. J Hazard Mater 290:43–50
structure and microporosity in phenanthrene sorption by natural and Rawal A, Joseph SD, Hook JM, Chia CH, Munroe PR, Donne S, Lin Y,
engineered organic matter. Environ Sci Ttechnol 48:11227–11234 Phelan D, Mitchell DR, Pace B, Horvat J (2016) Mineral–biochar
Hao R, Xiao X, Zuo X, Nan J, Zhang W (2012) Efficient adsorption and composites: molecular structure and porosity. Environ Sci Technol
visible-light + photocatalytic degradation of tetracycline hydrochlo- 50:7706–7714
ride using mesoporous BiOI microspheres. J Hazard Mater 209: Reddy DHK, Lee S-M (2014) Magnetic biochar composite: facile syn-
137–145 thesis, characterization, and application for heavy metal removal.
Hernandez-Mena L, Pecora A, Beraldo A (2014) Slow pyrolysis of bam- Colloids Surf A Physicochem Eng Asp 454:96–103
boo biomass: analysis of biochar properties. Chem Eng Trans 37: Redlich OJDL, Peterson DL (1959) A useful adsorption isotherm. J Phys
115–120 Chem 63:1024–1024
Ho YS, Porter JF, McKay G (2002) Equilibrium isotherm studies for the Richard LA (1954) Diagnoses and improvement of saline and alkali soils.
sorption of divalent metal ions onto peat: copper, nickel and lead Agriculture handbook, vol 60. USDA, USA
single component systems. Water Air Soil Pollut 141:1–33 Simazaki D, Kubota R, Suzuki T, Akiba M, Nishimura T, Kunikane S
Jiang HY, Zhang DD, Xiao SC, Geng CN, Zhang X (2013) Occurrence (2015) Occurrence of selected pharmaceuticals at drinking water
and sources of antibiotics and their metabolites in river water, purification plants in Japan and implications for human health.
WWTPs, and swine wastewater in Jiulongjiang River basin, South Water Res 76:187–200
China. Environ Sci Pollut Res 20:9075–9083 Singh R, Misra V, Singh RP (2011) Synthesis, characterization and role of
Joseph SD, Camps-Arbestain M, Lin Y, Munroe P, Chia CH, Hook J, Van zero-valent iron nanoparticle in removal of hexavalent chromium
Zwieten L, Kimber S, Cowie A, Singh BP, Lehmann J (2010) An from chromium-spiked soil. J Nanopart Res 13:4063–4073
investigation into the reactions of biochar in soil. Soil Res 48:501–515 Singh S, Shukla S, Tandia N, Kumar N, Paliwal R (2014) Antibiotic
Kumar K, Gupta SC, Baidoo KS, Chander Y, Rosen CJ (2005) Antibiotic residues: a global challenge. Pharma Sci Monitor 5
uptake by plants from soil fertilized with animal manure. J Environ Sun Y, Gao B, Yao Y, Fang J, Zhang M, Zhou Y, Chen H, Yang L (2014)
Qual 34:2082–2086 Effects of feedstock type, production method, and pyrolysis temper-
Kummerer K (2009) Antibiotics in the aquatic environment-a review-part ature on biochar and hydrochar properties. Chem Eng J 240:574–
I. Chemosphere 75:417–434 578
Environ Sci Pollut Res

Swathi RS, Sebastian KL (2009) Long range resonance energy transfer Yang H, Yan R, Chen H, Lee DH, Zheng C (2007) Characteristics of
from a dye molecule to graphene has (distance)(-4) dependence. J hemicellulose, cellulose and lignin pyrolysis. Fuel 86:1781–
Chem Phys 130:086101 1788
Torres-Pérez J, Gérente C, Andrès Y (2012) Sustainable activated carbons Yao Y, Gao B, Chen J, Yang L (2013) Engineered biochar reclaiming
from agricultural residues dedicated to antibiotic removal by adsorp- phosphate from aqueous solutions: mechanisms and potential appli-
tion. Chin J Chem Eng 20:524–529 cation as a slow-release fertilizer. Environ Sci Technol 47:8700–
Uchimiya M, Bannon DI, Wartelle LH (2012) Retention of heavy metals 8708
by carboxyl functional groups of biochars in small arms range soil. J Zhang Z, Lan H, Liu H, Qu J (2015) Removal of tetracycline antibiotics
Agric Food Chem 60:1798–1809 from aqueous solution by amino-Fe (III) functionalized SBA15.
Usman AR, Abduljabbar A, Vithanage M, Ok YS, Ahmad M, Ahmad M, Colloids Surf A Physicochem Eng Asp 471:133–138
Elfaki J, Abdulazeem SS, Al-Wabel MI (2015) Biochar production Zhao X, Shi Y, Cai Y, Mou S (2008) Cetyltrimethylammonium
from date palm waste: charring temperature induced changes in bromidecoated magnetic nanoparticles for the preconcentration of
composition and surface chemistry. J Anal Appl Pyrol 115:392–400 phenolic compounds from environmental water samples. Environ
Wang Y, Lu H, Liu Y, Yang S (2016) Removal of phosphate from aque- Sci Technol 42:1201–1206
ous solution b SiO2 –biochar nanocomposites prepared by pyrolysis Zhou Q, Li Z, Shuang C, Li A, Zhang M, Wang M (2012) Efficient
of vermiculite treated algal biomass. RSC Adv 6:83534–83546 removal of tetracycline by reusable magnetic microspheres with a
Wang B, Jiang YS, Li FY, Yang DY (2017) Preparation of biochar by high surface area. Chem Eng J 210:350–356
simultaneous carbonization, magnetization and activation for
norfloxacin removal in water. Bioresour Technol 233:159–165
Publisher’s note Springer Nature remains neutral with regard to juris-
Xu J, Gao N, Tang Y, Deng Y, Sui M (2010) Perchlorate removal using
dictional claims in published maps and institutional affiliations.
granular activated carbon supported iron compounds: synthesis,
characterization and reactivity. J Environ Sci 22:1807–1813