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Table 1
Adsorption studies investigate using different parameters.
Parameter Values Investigated
Agitation time, t, min 1, 3, 5, 10, 15, 20, 25, 30, 40, 50, 60, 90, 120,
150 and 180
Bio sorbent size, dp, µm 50µm
adsorbent dosage, w, g/L 5, 10, 15, 20, 25, 30, 40, 50 and 60
Initial Lead concentration, C0,
ppm
20, 40, 60, 80 and 100
pH of aqueous solution 2, 3, 4, 5, 6, 7, 8 and 9
Temperature, K 283, 293, 303, 313 and 323
Table 2
Freundlich and Langmiur at 26 °C.
S.No. Log Ce Log qe Ce Ce/qe
1 0.7262 0.1666 5.324 3.6276
2 1.0579 0.4559 11.428 3.9997
3 1.4567 0.7107 28.626 5.5720
4 1.6832 0.8560 48.216 6.7172
5 1.8464 0.9532 70.212 7.8197
Table 3
Levels of different process variables in coded and un-coded form for%
biosorption of lead using Parthenium stem Powder.
Variable Name Ranges and levels
-1 0 +1
X1 pH of aqueous solution 4 5 6
X2 Initial concentration, C0, mg/L 15 20 25
X3 Bio sorbent dosage. W, g/L 20 30 40
trial effluents. Lead poisoning may result in Plumbosis, learning diffi-
culties that reduce intelligence (IQ), attention deficit disorder, behav-
ioural problems, nervous system damage, speech, and language impair-
ment, reduced muscle growth, decreased bone growth, and kidney
damage. The World Health Organization (WHO) has recommended that
1.5 mg/l of Pb (II) be the upper permissible level for drinking water
(CONRAD and HANSEN, January 2007; GUPTA et al., 1998; GUPTA
and ALI, March 2004; KAPOOR et al., 1999; KRATOCHVIL and
VOLESKY, July 1998). As a result, prior to being supplied to homes,
drinkable water must undergo some sort of treatment. Lead removal
from industrial effluent may be accomplished using a number of tech-
niques. These include electrochemical precipitation (QAISER et al.,
2009), solvent extraction (SAEED et al., 2005), membrane separation
(An Overview of Adsorption, 2017), evaporation (Abollino et al.,
2003), and foam separation (Abou-El-Sherbini and Hassanien, 2010).
They also include reduction followed by chemical precipitation
(NADEEM et al., 2006), ion exchange (OZER, March 2007), reduction
(QAISER et al., 2007), and electrochemical precipitation (QAISER et al.,
2009). The typical chromium removal methods previously mentioned
are either expensive or inefficient at low concentrations (Afkhami et al.,
2008). In recent years, the utilisation of easily accessible biomass that
can remove heavy metals has become the focus of biosorption research
(Ageena, 2010). In this procedure, biological components are used to
create complexes with metal ions utilising their ligands or functional
groups. It is possible to achieve drinking water quality using this tech-
nique as a low-cost method of industrial wastewater purification. Nu-
merous studies have been conducted on bio-adsorbent substances that
are effective in removing heavy metals from aqueous fluids (Ahn et al.,
2009; Al-Degs et al., 2006; Amuda et al., 2007; Aydın et al., 2008;
Baccar et al., 2009). The binding of metals by biomass is known as
biosorption, and these substances are referred to as biosorbents. The re-
sponse surface methodology (RSM) is a combination of statistical and
mathematical approaches for examining the impact of several indepen-
dent factors on the response (Barakat, 2011; Bhattacharyya and Gupta,
2006; Bosco et al., 2005; Caliskan et al., 2011). RSM has a crucial role
to play in the planning and development of processes as well as the en-
hancement of current designs. The experimental technique that under-
lies this methodology, which illustrates the total impacts of the parame-
ters on the process and includes interacting effects amongst the vari-
ables, makes it more practical than the methodologies previously stated
(Chen et al., 2015; Chen et al., 2003; Christidis et al., 1997; Chunfeng et
al., 2009; Chutia et al., 2009). RSM has recently been used to optimise
and assess the interacting impacts of separate components in a variety
of chemical and biological processes. Pinus sylvestris removal of nickel
(Ni (II)) was optimised using response surface approach (Debnath and
Ghosh, 2009). The ideal pH, biomass content, and initial Ni ion concen-
tration were discovered to be 6.17, 18.8 g/l, and 11.18 mg/l, respec-
tively (Demiral and Güngör, 2016). Recently, the increasing number of
emerging contaminants of high concern resulting from industrial and
human-made activities present problems to the environment (Bilal et
al., 2019; Rasheed et al., 2019; Bilal et al., 2018). Several treatment
methods have been proposed for the removal of dyes from contami-
nated waters which include photodecomposition, electrolysis, adsorp-
tion, oxidation, biodegradation and coagulation- –flocculation (Ahmadi
et al., 2019). The effectiveness of Ni ion elimination under these cir-
cumstances was 99.91%. Using biomass from A. niger, researchers have
examined the effects of starting lead concentration, pH, and biomass
concentration on lead biosorption (Demirbas et al., 2009). RSM under
DESIGN EXPERT software was used to identify the ideal conditions for
the removal of Pb (II). The primary goal of this research was to deter-
mine the Parthenium stem powder's biosorption properties for the elim-
ination of lead ions in an aqueous solution. Parthenium stem powder
was used in the experiment as an efficient and affordable material to re-
move lead from an aqueous solution (Fu and Wang, 2011; Guo et al.,
2008; Gupta et al., 2011; Hua et al., 2012).
2. Materials and methods
2.1. Chemicals
All of the chemicals, reagents, such as Lead Nitrate Pb (NO3)2 and
nitric acid (HNO3), and solvents utilised in this work were analytical
reagent quality and were acquired from Merck (Germany) or Sigma-
Aldrich (Germany). Stock solutions were prepared by successively di-
luting standard solutions with double-distilled water.
2.2. Preparation of stock solution
In order to prepare 1000 mL of a 1000 ppm lead stock solution,
1598 mg of lead nitrate Pb(NO3)2 will indeed be dissolved in 1000 mL
of distilled water in a 1000 mL beaker. It will be necessary to dissolve
1598 mg of lead nitrate Pb(NO3)2 in 1000 mL of distilled water in a
1000 mL beaker in order to make 1000 mL of a 1000 ppm lead stock so-
lution. After that, the stock solution was diluted to produce a series of
Pb (II) test solutions with concentrations ranging from 20 to 100 mg/L.
The initial pH was established using a pH metre and 0.1 N HNO3.
2.3. Preparation of the adsorbent
The stem of the Parthenium plant was gathered from several areas
of Chennai, Tamil Nadu, based on a review of the literature and the
availability of locally produced agrowaste materials. The sample was
adequately cleaned with deionized water after collection to get rid of
surface contaminants like dust. The sorbent was first dried at ambient
temperature in an open container, and then it was completely dried (re-
moving all moisture contents) in an electric oven (Model: LEB-1–20) for
24 h at 105 °C. The dry sorbent was pulverised, and the proper particle
size was separated by sieves before being kept for further analysis. Ma-
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Table 4
Results from BBD for Lead biosorption by Parthenium Stem Powder.
Run No. X1, W X2, Co X3, pH % biosorption of Lead
Experimental Predicted
1 -1.000 -1.000 0.000 80.08 80.0180
2 1.000 -1.000 0.000 81.18 81.1880
3 -1.000 1.000 0.000 78.39 78.4960
4 1.000 1.000 0.000 79.72 79.6660
5 -1.000 0.000 -1.000 76.19 76.2160
6 1.000 0.000 -1.000 77.38 77.3860
7 -1.000 0.000 1.000 76.02 75.9480
8 1.000 0.000 1.000 77.08 77.1180
9 0.000 -1.000 -1.000 80.59 80.6000
10 0.000 1.000 -1.000 79.12 79.0770
11 0.000 -1.000 1.000 80.29 80.3320
12 0.000 1.000 1.000 78.82 78.8100
13 0.000 0.000 0.000 85.44 86.4400
14 0.000 0.000 0.000 85.44 86.4400
15 0.000 0.000 0.000 85.44 86.4400
Table 5
ANOVA of Lead biosorption for entire quadratic model.
Source of variation SS df Mean square (MS) F-value P > F
Model 140.9347 6 23.4891 283.7276 0.00000
Error 0.6623 8 0.08279
Total 141.5970 14
Df- degree of freedom; SS- sum of squares; F- factor F; P- probability.
R2=0.9896; R2 (adj):0.9799.
Table 6
Estimated regression coefficients for the lead biosorption onto Parthenium
stem powder.
Terms Regression
Coeffecient
Standard error of
coeffecient
t-value p-value
Meam/Interc -83.3350 4.836059 -17.2320 0.000000
(1) Dosage, w, g/L(L) 2.6395 0.090417 29.1925 0.000000
Dosage, w, g/L(Q) -0.0430 0.001497 -28.7334 0.000000
(2) Concentration, Co,
mg/L(L)
1.9270 0.240444 8.0143 0.000043
Concentration, Co,
mg/L(Q)
-0.0521 0.005990 -8.6985 0.000024
(3) pH (L) 44.3850 1.500836 29.5735 0.000000
pH (Q) -4.4525 0.149738 -29.7352 0.000000
terial recovered by crushing and grinding is filtered through B.S.S.
meshes. The mean particle sizes were maintained between 50 and
150 µm (Ince, 2014; Ince et al., 2017; Ince and Kaplan Ince, 2017). The
finished product were kept in glass bottles for further use. Morosanu
et.al. was investigated the Biosorption of lead ions from aqueous efflu-
ents by rapeseed biomass (86).
2.4. Adsorption studies
The results of the investigation into the adsorption of metals were
examined using a variety of factors, including temperature, pH of the
aqueous solution, agitation duration, adsorbent dose, and adsorbate
concentration is depicted in table 1. The adsorbate and adsorbent solu-
tion were taken in 250 ml conical flasks and it was shaken mechanically
at 180 rpm speed in a motorised shaker. Mesh paper was used to pour
and separate the adsorbate from the adsorbent. The ultimate residual
metal content was assessed by an atomic absorption spectrophotometer
post adsorption. The following equation was used to calculate the per-
centage of lead removed from an aqueous solution (1). The following
equation was used to determine the metal uptake (qe) at equilibrium
(2).
(1)
(2)
Where qe (mg/g) denotes the quantity of lead adsorbed per unit
weight of the adsorbent, C0 and Ce denote the initial and equilibrium
metal ion concentrations (mg/l), v denotes the volume of the aqueous
solution (ml), and w denotes the weight of the adsorbent (g).
2.4. Experimental plan
Three independent factors, such as pH (X1), Co (X2), and w (X3) are
chosen based on preliminary tests for the analysis of the optimal situa-
tion for the percent removal of Pb (II). Box Behnken design (BBD) under
RSM of STATISTICA 6.0 (Stat-Ease Inc., Tulsa, OK, USA) was used to
analyse the connection between the parameters and response. The BBD
design was used for this investigation because it is effective, adaptable,
and reliable. According to BBD, fifteen tests are carried out. The
amount of Pb (II) elimination was regarded as the experimental design's
response (Y). Samples collected after the intended optimal duration are
subjected to an AAS analysis. The STATISTICA programme (version
6.0), developed by Stat Ease Inc. in the USA, was used to do the regres-
sion analyses, visual analyses, and analyses of variance (ANOVA).
Through the use of Student's t-test and p-values, the statistical signifi-
cance of the coefficient was ascertained. The proportion of variance ob-
tained by the model was explained by the multiple coefficients of deter-
mination, R2.
3. Results and discussion
3.1. Effect of contact time
The results obtained by graphing the% removal of lead against agi-
tation time for various concentrations are illustrated in Fig. 2. Contact
time was changed from 0 to 200 min under neutral circumstances with
a constant amount of sorbent (10 g), initial concentration (20 mg/L),
and shaking speed (150 rpm). The maximum amount of adsorption was
attained at intervals of 50 min, and additional extensions of time did
not result in any appreciable increases (Jamil et al., 2010). The initial
absorption of metal ions was higher and there were more empty spaces
on the surface of the sorbent, so there was a constant rise in adsorption
capacity by extending the time frame from 0 to 50 min. However, be-
cause empty spaces have already been filled and equilibrium has been
reached, a further increase could not enough alter the adsorption of
metals.
3.2. Effect of aqueous lead solution pH
The initial pH of the adsorption system is crucial because it impacts
the surface morphology of the sorbent and the binding properties of sor-
bate. The chosen pH range was 2–10, and the starting sorbate concen-
tration was 20 mg/L with 10 g of sorbent. The outcome shown in Fig. 3
demonstrates that the adsorption capability is fairly poor in acidic envi-
ronments. A pH value of 5 is used to estimate the extreme% elimination
of lead for different initial concentrations. The quantity of sorbate that
is adsorbed onto the surface of the sorbent increases when the pH is
raised. Metals must compete with H+ ions for adsorption on sorbent
surfaces at low pH values because H+ ions are overexpressed at those
pH levels. However, when the pH level is elevated, it results in a large
increase in adsorption because of the attraction created between posi-
tively charged metal ions and negatively charged sorbent surfaces by -
OH groups. Therefore, it was determined that the ideal pH range for
lead is between 4 and 6, where it exhibits the optimal adsorption behav-
iour. The amount of heavy metal adsorption increases with more con-
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Table 7
Comparison between optimum values from BBD and experimentation.
Variable BBD Experimental
Biosorbent dosage, w, g/L 30.67403 30.00000
Initial Lead concentration, mg/L 18.49328 20.00000
pH of aqueous solution 4.98428 5.00000
% Biosorption 85.57892 85.440
tact. The breakeven point of lead removed in the current experiment is
72.74% at pH=5. Adsorption capability decreases as pH is raised more
as a result of the development of metal hydrides.
3.3. Initial lead concentration on percentage removal of lead metal
Another crucial factor that influences the adsorption phenomena is
the sorbate's initial concentration. To achieve this, the initial concentra-
tion of lead was changed between 20 and 160 mg/L while all other vari-
ables remained constant. The results of the initial lead concentration so-
lution are displayed in Fig. 4 as a percentage of the lead metal being re-
moved. With an increase in C0 from 20 mg/L to 160 mg/L, the percent-
age of lead biosorption is reduced from 73.38 percent (1.4676 mg/g) to
56.1175 percent (8.9788 mg/g). As there were empty spaces on the sur-
face of the sorbent, a lead adsorption on Parthenium stem powder was
first seen to have a quick rise in adsorption capacity. So the adsorption
of sorbate onto accessible sites increased along with the concentration.
These adsorption sites are easily occupied by the adsorbate, and the
concentration in this range is positively influenced by adsorption capac-
ity. The adsorption phenomenon is unaffected by a further rise in con-
centration from 60 to 120 ppm. Once equilibrium is attained, an in-
crease in concentration has no effect on the adsorption phenomenon be-
cause the surface of the adsorbent is saturated with sorbate. This is
brought on by the fact that there are fewer resident sites available when
concentrations of sorbate are quite high.
3.4. Effect of adsorbent dosage
The variations in the concentration of lead in aqueous solution with
adsorbent dosage are exposed in Fig. 5 and stated in Table 4. The ulti-
mate concentration of lead metal at room temperature drops as the
biosorbent dose rises, meaning that more lead metal is being removed
overall. The quantity of active sites accessible for lead biosorption
would grow with an increase in biosorbent dose. Therefore, 30 g/L
doses are used in all additional trials (Kosa et al., 2012).
3.5. Langmuir model
This is employed to determine the adsorption of the applied adsor-
bent. The Freundlich isotherm for the elimination of lead on parthe-
nium is the basis for the Langmuir model, as depicted in Fig. 6.
(3)
Here, qe represents the amount of metal adsorbed in the solid (bio-
mass), Ce represents the amount of metal remaining available in the so-
lution, b represents the ratio of adsorption to desorption rates, and
qmax represents the maximum amount of specific absorption corre-
sponding to site saturation. The Langmuir model equations have two
derivatives, which are (3) & (4).
(4)
(5)
The current data, displayed in Table 4, at 260 °C, demonstrates non-
linearity for the Langmuir isotherm shown in Table 2.
4. Kinetics of adsorption
4.1. Pseudo–second order kinetic model
Kinetic studies offer knowledge on the optimal conditions, the sorp-
tion mechanism, and potential rate-controlling steps in the batch ad-
sorption process. The following formula was used to determine the
quantity of lead adsorbed during different periods of time.
(6)
Where Qt stands for the quantity of lead adsorbed at any given time
t, and q0 and qe stand for the initial and equilibrium concentrations, re-
spectively. The quantity of sorbent in grammes is given by Wasorbent,
while the volume of lead solution collected is denoted by V(L). It is pos-
sible to experimentally ascertain the values of qt, q0, qe, Wsorbent, and
V. This led to the interpretation of the t/qt value for second-order kinet-
ics.
According to the pseudo-second-order adsorption kinetic model,
(7)
Where k2 is the rate constant of pseudo-second-order adsorption
(mg g - 1min-1) eqn (6) can be rearranged to obtain a more useful form
as
(8)
The linear form is
(9)
Fig. 1. Preparation of parthenium stem adsorbent.
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Fig. 2. Variation of final lead concentration with agitation time.
Fig. 3. Effect of pH on the percentage removal of lead on Parthenium stem powder.
where k2 is determined from a plot of t/qt vs. t. Fig. 7 depicts the
second order kinetics for the adsorption of lead by parthenium stem
powder. Since R2 is proximity to 1, the model can accurately predict
the removal of lead by Parthenium stem powder (Nadeem et al., 2006;
Nano and Strathmann, 2006; O'Connell et al., 2008; Orhan and
Kocaoba, 2007).
4.2. Thermodynamics of biosorption
Biosorption is temperature dependant which is associated with
three thermodynamic parameters namely change in enthalpy of
biosorption (∆H), change in entropy of biosorption (∆S), and change in
Gibbs free energy (∆G). Due to its relevance in real-world situations,
enthalpy is the most often utilised thermodynamic function. The ad-
sorption experiment was conducted under various temperature ranges
for thermodynamic investigations, and measured parameters included
enthalpy (H), entropy (S), and Gibbs free energy (G).
For this purpose,
(10)
(11)
(12)
have been used. Kc, the equilibrium constant, and R, the natural gas
constant, are calculated as
(13)
where qe is the metal concentration adsorbed in the solid (biomass),
and Ce is the residual metal concentration in the solution under equilib-
rium conditions, that can be calculated experimentally.
The Vant Hoff's equation states that
(14)
(15)
Where, the biosorption affinity is denoted by (qe/Ce).
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Fig. 4. Effect of initial concentration of lead on percentage Removal of lead metal.
Fig. 5. Effect of Dosage on the final concentration of lead by Parthenium stem powder.
The biosorption behaviour is investigated by experiments with tem-
perature ranges between 283 and 323 K. Fig. 8 depicts the charts
demonstrating the influence of temperature on lead biosorption for var-
ious initial metal concentrations (Rao et al., 2007).
The exothermic/endothermic and physical/chemical natures of
sorption will be indicated by a negative value for ∆H. It can be easily re-
versed by supplying the heat equal to the calculated ∆H (Pan et al.,
2010).
The ∆H is related to ∆G and ∆S as
(10)
Biosorption is not feasible when ∆S is less than 1, but it is possible
when ∆S > 1. The possibility of sorption is indicated by a ∆G value < 1
(Pan et al., 2009). A process is said to be extremely reversible if the
value of ∆S is smaller than zero. If ∆S is greater than or equal to zero, it
implies that the process is reversible. The spontaneity of biosorption is
shown by the negative value for ∆G. While the positive result suggests
that sorption is not spontaneous (Phuengprasop et al., 2011; Peng et al.,
2004; Pyrzyńska and Bystrzejewski, 2010; Qi and Aldrich, 2008). Addi-
tionally, equilibrium constants that changed with temperature were
used to estimate thermodynamic constants. The process was described
as being spontaneous by the negative value of ∆G°. The endothermic
character and irreversibility of biosorption were both demonstrated by
the positive values of ∆H and ∆S (Qu et al., 2013).
4.3. Optimization using Box-Behnken design
Various pH levels, ranging from 4 to 6, were used for the trials. Dif-
ferent bio sorbent dosages of 20–40 g/L and various lead concentra-
tions of 15–25 mg/L are connected to and altered simultaneously to
cover the combination of parameters in BBD. The values and ranges of
the independent factors that were chosen are listed in Table 3. The opti-
mization of the parameters is done using Table-4 (Rožić et al., 2000).
The regression equation for the optimization is as follows: percent
biosorption of lead (Y) is a function of pH (X1), initial lead concentra-
tion Co (X2), and biosorbent dose (X3). The following equation for lead
biosorption has been generated by multiple regression analysis of ex-
perimental data (Sarkar et al., 2011):
(16)
Table 5 provides the aforementioned regression model result for
Eqn. (9) in the form of an analysis of variance (ANOVA). The com-
parison between the% biosorption attained through trials and that
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Fig. 6. Freundlich isotherm for the removal of lead on Parthenium stem powder at 26 °C.
Fig. 7. Second order kinetics adsorption of lead by Parthenium stem powder.
anticipated may be seen by looking at the optimal set of conditions
for highest percentage biosorption of lead, which is pH = 4.98428,
biosorption dose (w) = 30.67403 g/L, and initial lead concentration
of Co=18.49328 mg/L determined at this optimum condition. The
experimental results and the projected results are quite consistent
(Sharma et al., 2009; Singh et al., 2010; Srivastava and Majumder,
2008; Şahin and Saka, 2013). The variability of the model in the ob-
served response values is measured by the correlation coefficient (R2)
(Turan and Ozgonenel, 2013). Stronger and better at predicting the
outcome is the R2 value up to 1. In the current investigation, the re-
gression coefficient's value (R2 = 0.9998) shows that the model does
not adequately explain 0.0002 percentage of the overall changes
(Unuabonah et al., 2008). The statistical significance of the ratio of
the mean square due to regression and the mean square owing to
residual error may be tested using the ANOVA Table 5. It is clear
from that table that the F-statistics value for the entire model is
higher (Verma et al., 2008). This significant result suggests that the
model equation can properly describe the percent elimination. P val-
ues below 0.05 typically suggest statistical insignificance for the
model at the 95 percent level of confidence. Table 5 displays the
model's predicted percentage of biosorption. Table 6 shows that all of
the squared terms and linear terms for all of the variables are signifi-
cant (P < 0.05). Previous researches the natural low-methoxyl pectin
extracted from sunflower heads with oxalic acid were investigated
based on the Box–Behnken design statistical modelling (91) insignifi-
cant (P ≥ 0.05)
The model is reduced to the following form by excluding undistin-
guished terms in eq. (9)
(17)
4.4. Interaction effects of biosorption variables
The percentage of lead biosorption using Parthenium Stem powder
for various combinations of dependant variables are displayed in a
three-dimensional image of response surface contour plots [Fig. 9(a) to
(c)] (Vieira et al., 2010). Each plot is defined as a function of two vari-
ables at a time, with the other variables being fixed at zero. The percent
of biosorption is at low and high levels of the variables, as shown by re-
sponse surface contour plots. The figures make the importance of each
variable's function in the percent biosorption of lead quite evident. The
optimal set of circumstances for maximal lead biosorption are (Witek-
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Fig. 8. Vant Hoff's plot for biosorption.
Fig. 9. Response surface plots for the effect of (a) initial solution pH and biomass dosage (g/l) on the lead removal (%). l (b) initial lead ion concentration (mg/l)
and biomass dosage (g/l); (c) initial solution pH and initial lead ion concentration (mg/l).
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Krowiak et al., 2011; Wu et al., 2011; Yang et al., 2007; Yuvaraja et al.,
2014; Zhao et al., 2011):
Table 7 compares the experimentally determined optimal values to
those that BBD anticipated. The experimental results and those from the
BBD are very similar.
5. Conclusions
The Parthenium stem powder can remove lead from aqueous solu-
tion, up to 72.74% for 20 mg/l at pH=5 and 26 °C. It has been observed
that the optimum circumstances for Parthenium stem powder are a pH
of 5, an equilibrium duration of 50 min, and a dose of 1.5 g/100 ml. An
increase in the dose of the adsorbent results in a greater proportion of
lead being removed from the aqueous solution. Although activated car-
bon has a prominent role in the treatment of wastewater, its usage is oc-
casionally constrained due to its expensive price. In order to substitute
the overpriced activated carbon, a variety of low-cost bio-adsorbents,
including Parthenium stem powder, were studied. According to ther-
modynamic statistics, the proportion of biosorption rises with a modest
rise in temperature. Additionally, the analysis shows that biosorption as
ΔH is endothermic, which is advantageous. The process is irreversible
as ΔS is positive and suggests that randomness at the solid/solution in-
terface increases with biosorption of lead (II) onto Parthenium steam
powder. The spontaneity of the biosorption as ΔG is negative. However,
it is crucial to dispose of the used adsorbents in a manner that is
favourable to the environment. This research opens up a new avenue
for the disposal and regeneration of the adsorbent. (Eqn (1)-8, 10–17,
Fig 1).
Uncited references
(Kabbashi et al., 2009; Karami, 2013; Khan et al., 2008; Khraisheh
et al., 2004; Kurniawan et al., 2006; Li et al., 2015; Manju et al., 2002;
Marques et al., 2000; Monser and Adhoum, 2002; IrinaMorosanu and
CarmenPduraru, 25 October 2017; Peng et al., 2020).
Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influ-
ence the work reported in this paper.
Acknowledgements
This work was funded by the Researchers Supporting Project Num-
ber (RSP-2021/261) King Saud University, Riyadh, Saudi Arabia.
References
An overview of adsorption technique for heavy metal removal from water/wastewater: a
critical review year 2017, Volume 3, Issue 2, 10–19, 28.12.2017 Muharrem INCE
Olcay KAPLAİNCE https://doi.org/10.29132/ijpas.358199.
Abollino, O., Aceto, M., Malandrino, M., Sarzanini, C., Mentasti, E., 2003. Adsorption of
heavy metals on Na-montmorillonite. effect of pH and organic substances. Water Res.
37, 1619–1627. https://doi.org/10.1016/S0043-1354(02)00524-9.
Abou-El-Sherbini, K.S., Hassanien, M.M., 2010. Study of organically-modified
montmorillonite clay for the removal of copper(II). J. Hazard. Mater. 184 (1–3),
654–661. https://doi.org/10.1016/j.jhazmat.2010.08.088.
Afkhami, A., Madrakian, T., Amini, A., Karimi, Z., 2008. Effect of the impregnation of
carbon cloth with ethlyenediaminetetraacetic acid on its adsorption capacity for the
adsorption of several metal ions. J. Hazard. Mater. 150, 408–412. https://doi.org/
10.1016/j.jhazmat.2007.04.123.
Ageena, N.A., 2010. The use of local sawdust as an adsorbent for the removal of copper
Ion from wastewater using fixed bed adsorption. Eng. Technol. J. 28 (2), 224–235.
https://etj.uotechnology.edu.iq/article_26933.html.
Ahmadi, S., Igwegbe, C.A., Rahdar, S., 2019. The application of thermally activated
persulfate for degradation of acid blue 92 in aqueous solution. Int. J. Ind. Chem.
Biotechnol.
Ahn, C.K., Park, D., Woo, S.H., Park, J.M., 2009. Removal of cationic heavy metal from
aqueous solution by activated carbon impregnated with anionic surfactants. J.
Hazard. Mater. 164, 1130–1136. https://doi.org/10.1016/j.jhazmat.2008.09.036.
Al-Degs, Y.S., El-Barghouthi, M.I., Issa, A.A., Khraisheh, M.A., Walker, G.M., 2006.
Sorption of Zn(II), Pb(II), and Co(II) using natural sorbents: equilibrium and kinetic
studies. Water Res. 40, 2645–2658. https://doi.org/10.1016/j.watres.2006.05.018.
AMARASINGHE, B.M.W.P.K., WILLIAMS, R.A., January 2007. Tea waste as a low cost
adsorbent for the removal of Cu and Pb from wastewater. Chem. Eng. Journal 132
(1–3), 299–309. https://doi.org/10.1016/J.CEJ.2007.01.016.
Amuda, O.S., Giwa, A.A., Bello, I.A., 2007. Removal of heavy metal from industrial
wastewater using modified activated coconut shell carbon. Biochem. Eng. J. 36,
174–181. https://doi.org/10.1016/j.bej.2007.02.013.
Aydın, H., Bulut, Y., Yerlikaya, Ç., 2008. Removal of copper (II) from aqueous solution by
adsorption onto low-cost adsorbents. J. Environ. Manag. 87, 37–45. https://doi.org/
10.1016/j.jenvman.2007.01.005.
BABARINDE, N.A.A., BABALOLA, J.O., SANNI, R.A., September 2006. Biosorption of lead
ions from aqueous solution by maize leaf. Int. J. Phys. Sci. 1 (1), 23–26.
Baccar, R., Bouzid, J., Feki, M., Montiel, A., 2009. Preparation of activated carbon from
Tunisian olive-waste cakes and its application for adsorption of heavy metal ions. J.
Hazard. Mater. 162, 1522–1529. https://doi.org/10.1016/j.jhazmat.2008.06.041.
Barakat, M.A., 2011. New trends in removing heavy metals from industrial wastewater.
Arabian J. Chem. 4, 361–377. https://doi.org/10.1016/j.arabjc.2010.07.019.
BEKTAS, Nihal, AGIM, Burcu Akman, KARA, Serdar, August 2004. Kinetic and
equilibrium studies in removing lead ions from aqueous solution by natural sepiolite.
J. Hazard. Mater. 112 (1–2), 115–122.
Bhattacharyya, K.G., Gupta, S.S., 2006. Kaolinite, montmorillonite, and their modified
derivatives as adsorbents for removal of Cu(II) from aqueous solution. Sep. Purif.
Technol. 50 (3), 388–397. https://doi.org/10.1016/j.seppur.2005.12.014.
Bilal, M., Rasheed, T., Iqbal, H.M.N., Yan, Y., 2018. Peroxidases-assisted removal of
environmentally-related hazardous pollutants with reference to the reaction
mechanisms of industrial dyes. Sci. Total Environ. 644, 1–13.
Bilal, M., Rasheed, T., Nabeel, F., Iqbal, H.M.N., Zhao, Y., 2019. Hazardous contaminants
in the environment and their laccase-assisted degradation-a review. J. Environ.
Manag. 234, 253–264.
Bosco, S.M.D., Jimenez, R.S., Carvalho, W.A., 2005. Removal of toxic metals from
wastewater by Brazilian natural scolecite. J. Colloid Interface Sci. 281, 424–431.
https://doi.org/10.1016/j.jcis.2004.08.060.
Caliskan, N., Kul, A.R., Alkan, S., Sogut, E.G., Alacabey, I., 2011. Adsorption of zinc(II) on
diatomite and manganese-oxide-modified diatomite: a kinetic and equilibrium study.
J. Hazard. Mater. 193, 27–36. https://doi.org/10.1016/j.jhazmat.2011.06.058.
CHEN, J.Paul, WANG, Lin, ZOU, Shuai-Wen, July 2007. Determination of lead biosorption
properties by experimental and modeling simulation study. Chem. Eng. J. 131 (1–3),
209–215. https://doi.org/10.1016/j.cej.2006.11.012.
Chen, L., Zhaoa, X., Pan, B., Zhang, W., Hua, M., Lv, L., Zhang, W., 2015. Preferable
removal of phosphate from water using hydrous zirconium oxide-based
nanocomposite of high stability. J. Hazard. Mater. 284, 35–42. https://doi.org/
10.1016/j.jhazmat.2014.10.048.
Chen, W.J., Hsiao, L.C., Chen, K.K.Y., 2003. Metal desorption from copper(II)/nickel(II)-
spiked kaolin as a soil component using plant-derived saponin biosurfactant. Process
Biochem. 43 (5), 488–498. https://doi.org/10.1016/j.procbio.2007.11.017.
Christidis, G.E., Scott, P.W., Dunham, A.C., 1997. Acid activation and bleaching capacity
of bentonites from the islands of Milos and Chios, Aegean, Greece. Appl. Clay Sci. 12,
329–347. https://doi.org/10.1016/S0169-1317(97)00017-3.
Chunfeng, W., Jiansheng, L., Xia, S., Lianjun, W., Xiuyun, S., 2009. Evaluation of zeolites
synthesized from fly ash as potential adsorbents for wastewater containing heavy
metals. J. Environ. Sci. 21, 127–136. https://doi.org/10.1016/S1001-0742(09)
60022-X.
Chutia, P., Kato, S., Kojima, T., Satokawa, S., 2009. Adsorption of As(V) on surfactant-
modified natural zeolites. J. Hazard. Mater. 162, 204–211. https://doi.org/10.1016/
j.jhazmat.2008.05.024.
CONRAD, Kathrine, HANSEN, Hans Christian Bruun, January 2007. Sorption of zinc and
lead on coir. Bioresour. Technol. 98 (1), 89–97. https://doi.org/10.1016/
j.biortech.2005.11.018.
Debnath, S., Ghosh, U.C., 2009. Nanostructured hydrous titanium(IV) oxide: synthesis,
characterization and Ni(II) adsorption behavior. Chem. Eng. J. 152, 480–491. https://
doi.org/10.1016/j.cej.2009.05.021.
Demiral, H., Güngör, C., 2016. Adsorption of copper(II) from aqueous solutions on
activated carbon prepared from grape bagasse. J. Clean. Prod. 124, 103–113. https://
doi.org/10.1016/j.jclepro.2016.02.084.
Demirbas, E., Dizge, N., Sulak, M.T., Kobya, M., 2009. Adsorption kinetics and
equilibrium of copper from aqueous solutions using hazelnut shell activated carbon.
Chem. Eng. J. 148, 480–487. https://doi.org/10.1016/j.cej.2008.09.027.
Fu, F.L., Wang, Q., 2011. Removal of heavy metal ions from wastewaters: a review. J.
Environ. Manag. 92, 407–418. https://doi.org/10.1016/j.jenvman.2010.11.011.
Guo, X., Zhang, S., Shan, X.Q., 2008. Adsorption of metal ions on lignin. J. Hazard. Mater.
151, 134–142. https://doi.org/10.1016/j.jhazmat.2007.05.065.
Gupta, V.K., Agarwal, S., Saleh, T.A., 2011. Chromium removal by combining the
magnetic properties of iron oxide with adsorption properties of carbon nanotubes.
Water Res. 45, 2207–2212. https://doi.org/10.1016/j.watres.2011.01.012.
GUPTA, Vinod K., ALI, Imran., March 2004. Removal of lead and chromium from
wastewater using bagasse fly ash-a sugar industry waste. J. Colloid Interface Sci. 271
(2), 321–328. https://doi.org/10.1016/j.jcis.2003.11.007.
9
10. C
O
R
R
E
C
T
E
D
P
R
O
O
F
C. Kavitha et al. South African Journal of Chemical Engineering xxx (xxxx) 1–11
GUPTA, Vinod K.;, MOHAN, Dinesh, SHARMA, Saurabh., 1998. Removal of lead from
waste water using bagasse fly ash-A sugar industry waste material. Sep. Sci. Technol.
33 (9), 1331–1343. https://doi.org/10.1080/01496399808544986.
Hua, M., Zhang, S., Pan, B., Zhang, W., Lv, L., Zhang, Q., 2012. Heavy metal removal from
water/wastewater by nanosized metal oxides: a review. J. Hazard. Mater. 211–212,
317–331. https://doi.org/10.1016/j.jhazmat.2011.10.016.
Ince, M., 2014. Comparision of low-cost and eco-friendly adsorbent for adsorption of Ni
(II). Atomic Spectroscopy 35 (5), 223–233. https://doi.org/10.46770/
AS.2014.05.006.
Ince, M., Ince, O.K., Asam, E., Önal, A., 2017. Using food waste biomass as effective
adsorbents in water and wastewater treatment for Cu(II) removal. Atomic
Spectroscopy 38 (5), 142–148. https://doi.org/10.46770/AS.2017.05.004.
Ince, M., Kaplan Ince, O., 2017. Box–Behnken design approach for optimizing removal of
copper from wastewater using a novel and green adsorbent. Atomic spectroscopy 38
(6), 200–207. https://doi.org/10.46770/AS.2017.06.005.
IrinaMorosanu, CarmenTeodosiu, CarmenPduraru, DumitritaIbanescu, 25 October 2017.
LaviniaTofan, B,6iosorption of lead ions from aqueous effluents by rapeseed biomass.
N. Biotechnol. 39 (Part A), 110–124. . Pages.
Jamil, M., Zia, M.S., Qasim, M., 2010. Contamination of agro-ecosystem and human
health hazards from wastewater used for irrigation. J. Chem. Soc. of Pakistan 32,
370–378.
Kabbashi, N.A., Atieh, M.A., Al-Mamun, A., Mirghami, M.E.S., Alam, M.D.Z., Yahya, N.,
2009. Kinetic adsorption of application of carbon nanotubes for Pb(II) removal from
aqueous solution. J. Environ. Sci. 21, 539–544. https://doi.org/10.1016/S1001-0742
(08)62305-0.
KAPOOR, A., VIRARAGHARAN, T., CULLIMORE, R.D., October 1999. Removal of heavy
metals using the fungus Aspergillus niger. Bioresour. Technol. 70 (1), 95–104.
https://doi.org/10.1016/s0960-8524(98)00192-8.
Karami, H., 2013. Heavy metal removal from water by magnetite nanorods. Chem. Eng. J.
219, 209–216. https://doi.org/10.1016/j.cej.2013.01.022.
Khan, S., Cao, Q., Zheng, Y.M., Huang, Y.Z., Zhu, Y.G., 2008. Health risks of heavy metals
in contaminated soils and food crops irrigated with wastewater in Beijing, China.
Environ. Pollut. 152, 686–692. https://doi.org/10.1016/j.envpol.2007.06.056.
Khraisheh, M.A.M., Al-degs, Y.S., Mcminn, W.A.M., 2004. Remediation of wastewater
containing heavy metals using raw and modified diatomite. Chem. Eng. J. 99,
177–184. https://doi.org/10.1016/j.cej.2003.11.029.
Kosa, S.A., Al-Zhrani, G., Salam, M.A., 2012. Removal of heavy metals from aqueous
solutions by multi-walled carbon nanotubes modified with 8-hydroxyquinoline.
Chem. Eng. J. 181–182, 159–168. https://doi.org/10.1016/j.cej.2011.11.044.
KRATOCHVIL, David, VOLESKY, Bohumil., July 1998. Advances in the biosorption of
heavy metals. Trends Biotechnol. 16 (7), 291–300. https://doi.org/10.1016/S0167-
7799(98)01218-9.
Kurniawan, T.A., Chan, G.Y.S., Lo, W.H., Babel, S., 2006. Physico-chemical treatment
techniques for wastewater laden with heavy metals. Chem. Eng. J. 118, 83–98.
https://doi.org/10.1016/j.cej.2006.01.015.
Li, Q., Yu, J., Zhou, F., Jiang, X., 2015. Synthesis and characterization of dithiocarbamate
carbon nanotubes for the removal of heavy metal ions from aqueous solutions.
Colloids and Surfaces A: Physicochem.Eng. Aspects 482, 306–314. https://doi.org/
10.1016/j.colsurfa.2015.06.034.
Manju, G.N., Krishnan, K.A., Vinod, V.P., Anirudhan, T.S., 2002. An investigation into the
sorption of heavy metals from wastewaters by polyacrylamide-grafted iron(III) oxide.
J. Hazard. Mater. 1, 221–238. https://doi.org/10.1016/s0304-3894(01)00392-2.
Marques, P.A.S.S., Rosa, M.F., Pinheiro, H.M., 2000. pH effects on the removal of Cu2+,
Cd2+ and Pb2+ from aqueous solution by waste brewery waste. Bioprocess Eng. 23,
135–141. https://doi.org/10.1007/PL00009118.
Monser, L., Adhoum, N., 2002. Modified activated carbon for the removal of copper, zinc,
chromium and cyanide from wastewater. Sep. Purif. Technol. 26, 137–146. https://
doi.org/10.1016/S1383-5866(01)00155-1.
Nadeem, M., Mahmood, A., Shahid, S.A., Shah, S.S., Khalid, A.M., McKay, G., 2006.
Sorption of lead from aqueous solution by chemically modified carbon adsorbents. J.
Hazard. Mater. 138, 604–613. https://doi.org/10.1016/j.jhazmat.2006.05.098.
NADEEM, M., MAHMOOD, A., SHAHID, S.A., SHAH, S.S., KHALID, A.M., MCKAY, G.,
December 2006. Sorption of lead from aqueous solution by chemically modified
carbon adsorbents. J. Hazard. Mater. 138 (3), 604–613. https://doi.org/10.1016/
j.jhazmat.2006.05.098.
Nano, G.V., Strathmann, T.J., 2006. Ferrous iron sorption by hydrous metal oxides. J.
Colloid Interface Sci. 297, 443–454. https://doi.org/10.1016/j.jcis.2005.11.030.
O’Connell, D.W., Birkinshaw, C., O’Dwyer, T.F., 2008. Heavy metal adsorbents prepared
from the modification of cellulose: a review. Bioresour. Technol. 99, 6709–6724.
https://doi.org/10.1016/j.biortech.2008.01.036.
Orhan, Y., Kocaoba, S., 2007. Adsorption of toxic metals by natural and modified
clinoptilolite. Ann. Chim. 97 (8), 781–790. https://doi.org/10.1002/
adic.200790061.
OZER, A., March 2007. Removal of Pb(II) ions from aqueous solutions by sulphuric acid-
treated wheat bran. J. Hazard. Mater. 141 (3), 753–761. https://doi.org/10.1016/
j.jhazmat.2006.07.040.
Pan, B., Pan, B., Zhang, W., Lv, L., Zhang, Q., Zheng, S., 2009. Development of polymeric
and polymer-based hybrid adsorbents for pollutants removal from waters. Chem. Eng.
J. 151, 19–29. https://doi.org/10.1016/j.cej.2009.02.036.
Pan, B., Qiu, H., Pan, B., Nie, G., Xiao, L., Lv, L., Zhang, W., Zhang, Q., Zheng, S., 2010.
Highly efficient removal of heavy metals by polymer-supported nanosized hydrated
Fe(III) oxides: behavior and XPS study. Water Res. 44, 815–824. https://doi.org/
10.1016/j.watres.2009.10.027.
Peng, S.H., Wang, W.X., Li, X.D., Yen, Y.F., 2004. Metal partitioning in river sediments
measured by sequential extraction and biomimetic approaches. Chemosphere 57,
839–851. https://doi.org/10.1016/j.chemosphere.2004.07.015.
Peng, X., Yang, G., Shi, Y., et al., 2020. Box–Behnken design based statistical modeling for
the extraction and physicochemical properties of pectin from sunflower heads and the
comparison with commercial low-methoxyl pectin. Sci Rep 10, 3595. https://doi.org/
10.1038/s41598-020-60339-1.
Phuengprasop, T., Sittiwong, J., Unob, F., 2011. Removal of heavy metal ions by iron
oxide coated sewage sludge. J. Hazard. Mater. 186, 502–507. https://doi.org/
10.1016/j.jhazmat.2010.11.065.
Pyrzyńska, K., Bystrzejewski, M., 2010. Comparative study of heavy metal ions sorption
onto activated carbon, carbon nanotubes, and carbon-encapsulated magnetic
nanoparticles. Colloids and Surfaces A: Physicochem. Eng. Aspects 362, 102–109.
https://doi.org/10.1016/j.colsurfa.2010.03.047.
QAISER, Suleman, SALEEMI, Anwar Rasheed, AHMAD, Muhammad Mahmood, July
2007. Heavy metal uptake by agro based waste materials. Electron. J. Biotechnol. 10
(3), 409–416.
QAISER, Suleman, SALEEMI, Anwar Rasheed, UMAR, Muhammad, July 2009.
Biosorption of lead from aqueous solution by Ficus religiosa leaves: batch and column
study. J. Hazard. Mater. 166 (2–3), 998–1005.
Qi, B.C., Aldrich, C., 2008. Biosorption of heavy metals from aqueous solutions with
tobacco dust. Bioresour. Technol. 99, 5595–5601. https://doi.org/10.1016/
j.biortech.2007.10.042.
Qu, X., Alvarez, P.J.J., Li, Q., 2013. Applications of nanotechnology in water and
wastewater treatment. Water Res. 47 (12), 3931–3946. https://doi.org/10.1016/
j.watres.2012.09.058.
Rao, G.P., Lu, C., Su, F., 2007. Sorption of divalent metal ions from aqueous solution by
carbon nanotubes: a review. Sep. Purif. Technol. 58, 224–231. https://doi.org/
10.1016/j.seppur.2006.12.006.
Rasheed, T., Bilal, M., Nabeel, F., Adeel, M., Iqbal, H.M.N., 2019. Environmentally-related
contaminants of high concern: potential sources and analytical modalities for
detection, quantification, and treatment. Environ. Int. 122, 52–66.
Rožić, M., Cerjan-Stefanović, Š., Kurajica, S., Vančina, V., Hodžić, E., 2000. Ammonical
nitrogen removal from water by treatment with clays and zeolites. Water Res. 34 (14),
3675–3681. https://doi.org/10.1016/S0043-1354(00)00113-5.
SAEED, Asma, IQBAL, Muhammed, AKHTAR, M.Waheed, January 2005. Removal and
recovery of lead(II) from single and multimetal (Cd, Cu, Ni, Zn) solutions by crop
milling waste (black gram husk). J. Hazard. Mater. 117 (1), 65–73.
Şahin, Ö., Saka, C., 2013. Preparation and characterization of activated carbon from acorn
shell by physical activation with H2O-CO2 in two-step pretreatment. Bioresour.
Technol. 136, 163–168. https://doi.org/10.1016/j.biortech.2013.02.074.
Sarkar, S., Chatterjee, P.K., Cumbal, L.H., SenGupta, A.K., 2011. Hybrid ion exchanger
supported nanocomposites: sorption and sensing for environmental applications.
Chem. Eng. J. 166, 923–931. https://doi.org/10.1016/j.cej.2010.11.075.
SENTHILKUMAR, R., VIJAYARAGHAVAN, K., THILAKAVATHI, M., IYER, P.V.R., VELAN,
M., March 2007. Application of seaweeds for the removal of lead from aqueous
solution. Biochem. Eng. J. 33 (3), 211–216. https://doi.org/10.1016/
j.bej.2006.10.020.
Sharma, P., Singh, G., Tomar, R., 2009. Synthesis and characterization of an analogue of
heulandite: sorption applications for thorium(IV), europium(III), samarium(II) and
iron(III) recovery from aqueous waste. J. Colloid Interface Sci. 332, 298–308. https://
doi.org/10.1016/j.jcis.2008.12.074.
Singh, A., Sharma, R.K., Agrawal, M., Marshall, F.M., 2010. Health risk assessment of
heavy metals via dietary intake of foodstuffs from the wastewater irrigated site of a
dry tropical area of India. Food and Chem. Toxicol. 48, 611–619. https://doi.org/
10.1016/j.fct.2009.11.041.
Srivastava, N.K., Majumder, C.B., 2008. Novel biofiltration methods for the treatment of
heavy metals from industrial wastewater. J. Hazard. Mater. 151, 1–8. https://doi.org/
10.1016/j.jhazmat.2007.09.101.
Turan, N.G., Ozgonenel, O., 2013. Study of montmorillonite clay for the removal of
copper (II) by adsorption: full Factorial design approach and cascade forward neural
network. The Sci. World J. 342628. https://doi.org/10.1155/2013/342628. .
IDpages.
Unuabonah, E.I., Adebowale, K.O., Olu-Owolabi, B.I., Yang, L.Z., Kong, L.X., 2008.
Adsorption of Pb(II) and Cd (II) from aqueous solutions onto sodium tetraborate-
modified kaolinite clay: equilibrium and thermodynamic studies. Hydrometallurgy
93, 1–9. https://doi.org/10.1016/j.hydromet.2008.02.009.
Verma, V.K., Tewari, S., Rai, J.P.N., 2008. Ion exchange during heavy metal bio-sorption
from aqueous solution by dried biomass of macrophytes. Bioresour. Technol. 99,
1932–1938. https://doi.org/10.1016/j.biortech.2007.03.042.
Vieira, M.G.A., Neto, A.F.A., Gimenes, M.L., da Silva, M.G.C., 2010. Sorption kinetics and
equilibrium for the removal of nickel ions from aqueous phase on calcined bofe
bentonite clay. J. Hazard. Mater. 177 (1–3), 362–371. https://doi.org/10.1016/
j.jhazmat.2009.12.040.
WANG, Yuen-Hua, LIN, Su-Hsia, JUANG, RueyShin, August 2003. Removal of heavy
metal ions from aqueous solutions using various low-cost adsorbents. J. Hazard.
Mater. 102 (2), 291–302. https://doi.org/10.1016/S0304-3894(03)00218-8.
Witek-Krowiak, A., Szafran, R.G., Modelski, S., 2011. Biosorption of heavy metals from
aqueous solutions onto peanut shell as a low-cost biosorbent. Desalination 265,
126–134. https://doi.org/10.1016/j.desal.2010.07.042.
Wu, P., Zhang, Q., Dai, Y., Zhu, N., Dang, Z., Li, P., Wu, J., Wang, X., 2011. Adsorption of
Cu(II), Cd(II) and Cr(III) ions from aqueous solutions on humic acid modified Ca-
montmorillonite. Geoderma, 164 (3–4), 215–219. https://www.cabdirect.org/
cabdirect/abstract/20113300955.
Yang, L., Wu, S., Chen, J.P., 2007. Modification of activated carbon by polyaniline for
enhanced adsorption of aqueous arsenate. Ind. Eng. Chem. Res. 46, 2133–2140.
https://doi.org/10.1021/ie0611352.
Yuvaraja, G., Krishnaiah, N., Subbaiah, M.V., Krishnaiah, A., 2014. Biosorption of Pb(II)
from aqueous solution by Solanum melongena leaf powder as a low-cost biosorbent
10
11. C
O
R
R
E
C
T
E
D
P
R
O
O
F
C. Kavitha et al. South African Journal of Chemical Engineering xxx (xxxx) 1–11
prepared from agricultural waste. Colloids and Surfaces B: Biointerfaces 114, 75–81.
https://doi.org/10.1016/j.colsurfb.2013.09.039.
ZHANG, Yue, BANKS, Charles., February 2006. A comparison of the properties of
polyurethane immobilised Sphagnum moss, seaweed, sunflower waste and maize for
the biosorption of Cu, Pb, Zn and Ni in continuous flow packed columns. Water Res.
40 (4), 788–798. https://doi.org/10.1016/j.watres.2005.12.011. . vol.
Zhao, G., Wu, X., Tan, X., Wang, X., 2011. Sorption of heavy metal ions from aqueous
solutions: a review. The Open Colloid Sci. J. 4, 19–31. https://doi.org/10.2174/
1876530001104010019.
ZULKALI, M.M.D., AHMAD, A.L., NORULAKMAL, N.H., January 2006. Oryza sativa L.
husk as heavy metal adsorbent: optimization with lead as model solution. Bioresour.
Technol. 97 (1), 21–25. https://doi.org/10.1016/j.biortech.2005.02.007. . vol.
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