Adsorption Kinetics and Modelling of Copper (II) Ion Sorption Using Mercaptoacetic Acid Modifed Cassava Waste

ISSN: 1573-4377

ADSORPTION KINETICS AND MODELING OF CU(II) ION

SORPTION FROM AQUEOUS SOLUTION BY MERCAPTOACETIC ACID MODIFIED CASSAVA (MANIHOT SCULENTA CRANZ)

WASTES

A.A. Augustine*, B.D. Orike and A.D Edidiong Department of Pure and Industrial Chemistry, University of Port Harcourt, P. M. B. 5323, Choba Port Harcourt, Nigeria. ABSTRACT The rate of removal of Cu(II) ions from aqueous solution by mercaptoacetic acid modified cassava wastes (0.5MCF and 1.0MCF) was studied in batch conditions. The rate of sorption of copper was rapid initially within 5-15 minutes and reached a maximum in 30 minutes. Kinetic modeling analysis of the Elovich, pseudo-first order, pseudo-second order, intraparticle diffusion, mass transfer and intraparticle diffusivity equations using the linear coefficient of determination r2 values showed that the pseudo-second order equation was the most appropriate model for the description of Cu(II) transport. Thus the sorption of Cu(II) ion can be said to follow a pseudo-second order model, with chemical sorption as its rate limiting step. The initial adsorption rate values were: 2.94 x 10-1 and 2.60 x 10-1 mg.g-1.min-1 for 0.5MCF and 1.0MCF adsorbents respectively. KEYWORDS: Copper, kinetic modeling, sorption, cassava waste, mercaptoacetic acid. INTRODUCTION The increased level of environmental contamination as a consequence of industrial development is posing a very serious problem to the global environment. Industrial process for extracting metals or, more generally, all processes involving metals in their productive cycle generate significant heavy metal cations [1]. Mine drainage, metal industries, refining, electroplating, dye and leather industries, domestic effluents, land fill leachate, and agricultural run off all generate wastewater that contain heavy metal ions [2] The presence of these heavy metals in the environment has led to a number of environmental problems. Since most of these heavy metal are non-degradable into nontoxic end products,

Augustine et al. EJEAFChe, 6 (4), 2007. [2221-2234]

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their concentrations in effluents must therefore be reduced to acceptable levels before discharging them into the environment. Otherwise these metal ions could pose threats to public health and or affect the aesthetic quality of potable water. According to World Health Organisation (WHO), the metals of most immediate concern are chromium, copper, zinc, iron, cadmium and lead [3]. Since copper is a widely used material, there are many actual or potential sources of copper pollution. Copper is used in Jewelry, paints, pharmaceutical products, wood preservatives, pigments, metal works, petroleum refinery, motor vehicle and aircraft plating and finishing. Also copper may be found as a contaminant in food, especially shellfish, liver, mushroom, nuts and chocolate. In addition, any processing method or container using copper material may contaminate the product, such as food, water or drink [4]. Copper is essential to human life and is required for various biological processes, but like all heavy metals, is potentially toxic as well [5]. In order to solve the problems of heavy metal pollution in the ecosystem, it is important to bring pragmatic solutions to the issue. There are several methods for treatment of metal contaminated effluents such as precipitation, ion exchange, membrane processes and adsorption. Since the selection of wastewater treatment methods is based on the concentration of waste and the cost of treatment, adsorption is often the method of choice for removal of heavy metals from wastewater [6]. Furthermore, to enhance the cost effectiveness of the adsorption process for heavy metal treatment, various agricultural by-products have been developed as low-cost sorbents. These include: groundnut husk [7], shea butter seed husk [8], wild cocoyam [9], palm kernel fibre [10] and fluted pumpkin [II] In this study, an agricultural by-product, cassava waste in its chemically modified form which is obtained from the processing of cassava tuber (Manihot sculenta cranz) a staple food in Nigeria will be used to remove Cu(II) ions from aqueous solution. Interest in this work will be on the kinetics of Cu(II) ion removal. This is because sorption kinetics is an important parameter in wastewater treatment. Since sorption kinetics can be used to predict the rate of pollutant removal from aqueous solutions in the design of appropriate sorption treatment plants [12]. The different kinetic models that will be used to analyse the kinetic data for Cu(II) ion sorption are, pseudo-first order [13], the pseudo-second order [14], Elovich [15-16], mass transfer [17], intra-particle diffusion [18-19] and intra-particle diffusivity [20]. MATERIALS AND METHODS Adsorbent Cassava fibre waste obtained from the processing of cassava into the staple food “garri” was obtained from a cassava processing mill in a village near Port Harcourt, Rivers State, Nigeria. The cassava fibre waste was airdried and ground using a wiley mill grinder. The powdered cassava fibre was washed with deionized water and wet sieved through a set of sieves (106 and 105µm) and airdried.


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Dissolutions All reagents used for sorption studies were of analytical reagent grade. 1000mg/L of Copper(II) ion stock solution [CuS04.5H20] (BDH) was prepared by diluting a known mass in doubly distilled-deionized water in a 1000cm3 volumetric flask and made up to mark. From the stock solution 30mgL-1 working solutions of Cu(II) ions were prepared by serial dilution. Adsorbent Activation and Chemical Modification The sieved cassava fibre waste was soaked in excess 0.3M trioxonitrate (v) acid (HNO3) solution for 24 hours. It was later filtered airdried and sieved through the mesh sieves. The powdered cassava fibre waste was then divided into two portions (1 and 2) each weighing 20g. The first portion “1” was soaked in excess 0.5M mercaptoacetic acid solution, while portion “2” was also soaked in excess solution of 1.0M mercaptoacetic acid according to the procedure described in [13]. The two mixtures were later filtered after 24 hours, air dried and labeled as 0.5MCF and 1.0MCF for the 0.5M and 1.0M mercaptoacetic acid modified cassava fibre waste respectively. Experimental Procedure Kinetic sorption studies were carried out using 100ml of Cu(II) ion solutions of initial concentration 30mg/dm3. The metal ion solutions were measured into different labeled conical flasks containing 1.0g of each adsorbent (0.5MCF and 1.0MCF). The different flasks were corked and uniformly agitated in a EFL-MK3 shaker at a speed of 25 rpm at a temperature of 280C and pH of 5.0 for 5 minutes. The experimental set up was thereafter repeated for various other time intervals of 10, 15, 20, 25 and 30 minutes. Also kinetic infinity sorption (α) was also carried out for 24 hours. At the end of each contact time, the content of each flask was filtered using a whatman No. 41 filter paper. The concentration of (Cu(II) ion in each filtrate was determined using a Buck scientific flame atomic absorption spectrophotometer (FAAS) model 200A. Data analysis The metal sorption capacity (qt) of the mercaptoacetic modified cassava fibre wastes was calculated from the relationship [22] in eqn (1):

!

qt =ci " ct( )Ms (1)

Also, the percentage of Cu(II) ions removed (%RE) from the aqueous solution by each of the two adsorbents (0.5MCF and 1.0MCF) was calculated using eqn (2):

!

%RE =ci" c

t( )ci

#100

(2)

Whereas the fraction of Cu(II) ions removed by the two adsorbents was determined from the relationship [23].


2224

!

YT

=ci" c

t( )ci" c

e( ) (3)

where qt is the metal sorption capacity of the adsorbent (mg/g), Ci is the initial metal ion concentration (mg/L), Ct is the metal ion concentration in solution at time t (mg/L), Yt is the fraction of the metal adsorbed at time t, Ms is the weight of the adsorbent (g), V is the volume of the metal ion solution used for sorption (dm3) and Ce is the concentration of metal ion, when sorption is completed, ie infinity sorption [ C∞ = Ce]

Kinetic Modeling The study of sorption kinetics describes the adsorbate uptake rate and evidently this rate controls the residence time of adsorbate at the solid liquid interface [3]).

The kinetics of Cu(II) ion sorption on the two mercaptoacetic acid modified cassava adsorbents was analysed using different kinetic models, these include: the pseudo-first order [13], pseudo-second order [14], Elovich [15-16], mass transfer [17], intraparticle diffusion [18-19], and intraparticle diffusivity [20].

The Pseudo-First Order Equation The pseudo-first order equation [13], is generally expressed as:

!

dqt

dt= k

1qe " qt( ) (4)

Where qe and qt are the sorption capacities at equilibrium and at time t, respectively (mgg-1) and K1 is the rate constant of pseudo-first order sorption (Lmin-1). After integration and applying boundary conditions t = 0 to t = t and qt = 0 to qt = qt, the integrated form of equation (4) becomes:

!

log(qe " qt ) = logqe " k1t (5)

When the values of log (qe – qt) were linearly correlated with t, the plot of log (qe - qt) versus t will give a linear relationship from which k1 and qe can be determined from the slope and intercept of the graph respectively. The Pseudo- Second Order Equation The pseudo-second order chemisorption kinetic equation [14] is expressed as eqn 6:

!

dqt

dt= k

2qe " qt( )

2 (6)


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Where qe and qt are the sorption capacity at equilibrium and at time t, (mgg-1) respectively and K2 is the rate constant of the pseudo-second order sorption (g.mg-1. min-1). For the boundary conditions t = 0 to t = t and qt = 0 to qt = qt, the integrated form of eqn (6) becomes:

!

1

qe " qt=1

qe+ k

2t (7)

Which is the integrated rate law for a pseudo-second order reaction. Eqn (7) can be rearranged to obtained:

!

qt =1

1

k2qe2

+t

qe

(8)

Which has a linear form:

!

1

qt=

1

k2qe2

+t

qe (9)

Where h (mg.g-1. min-1) can be regarded as the initial sorption rate as qt/t→0 hence

h= K2qe2 (10)

Furthermore eqn(9) can be written as:

!

t

qt=1

h+t

qe (11)

If the pseudo-second order kinetics is applicable to the experimental data, the plot of t/qt versus t of eqn (II) should give a linear relationship from which qe, k and h can be determined from the slope and intercept of the plot respectively. The Elovich Kinetic Equation The Elovich equation [15-16] is generally expressed as:

!

dqt

dt="e#$qt (12)

Where qt is the sorption capacity at time t (mgg-1), α is the initial adsorption rate (mg.g-1. min-1) and, β is the desorption constant (mg.g-1.min-1) during any one experiment. To simplify the Elovich equation [15] assumed α β t > > 1 and by applying boundary conditions qt = 0 at t = 0 and qt = qt and t = t, [16] eqn (14) becomes:


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!

1

qt=ln("#)

#+ln t

#q (13)

Thus, if a plot of qt versus ln t is linearly correlated, the constants α and β can be computed from the slope and intercept of the graph. Mass Transfer Equation The mass transfer equation [17] is generally expressed as:

!

co" c

t= De

Kot (14)

Where Co is the initial metal ion concentration (mg.dm-3), Ct is the metal ion concentration at time t, t is the shaking time (mins), D is a fitting parameter, Ko is the adsorption constant which is related to the mass transfer adsorption coefficient, Ko = KM, where M is the mass of the adsorbent (g). A linearised form of eqn (14) is:

!

ln(co" c

t) = lnD+ K

ot (15)

If the sorption of Cu(II) ions on the two adsorbent is depicted by the mass transfer model, then a plot of ln (Co – Ct) versus time should give a linear relationship from where the constants lnD and Ko can be determined from the slope and intercept of the plot respectively.

The Intraparticle Diffusision Model The intra-article diffusion [18-19] model is expressed as eqn: 16:

!

R = Kidta (16)

Where R is the percent Cu(II) ions adsorbed, t is the contact time, a is the adsorption mechanism, kid is the intra-particle diffusion rate constant (min-1). Kid may be taken as a rate factor that is percent Cu2+ adsorbed per unit time [22]

A linear form of eqn 16 is:

!

logR = logKid

+ alog t (17) The plot of log R versus log t (eqn 17) should give a linear relationship from where the constants “a” and “Kid” can be determined from the slope and intercept of the plot, respectively.


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The Intra-particle Diffusivity Equation The intra-particle diffusivity equation [20] for the description of sorption kinetics is

!

qt = Xi + K1t (18)

Where: K1 is the initial rate of sorption controlled by intra-particle diffusivity (mg.g-1. min-

1). Xi depicts the boundary layer thickness. If the sorption of Cu(II) ions follows the intra-particle diffusivity equation, then a plot of qt versus T1/2 should give a linear relationship from where K1 and Xi can be determined from the intercept and slope of the plot respectively.

RESULT AND DISCUSSION Effect of Contact Time Kinetics of metal ion sorption governs the rate, which determines the residence time and it is one of the important characteristics defining the efficiency of an adsorbent [25]. The rate at which sorption takes place is of most importance, especially when designing batch sorption systems. Consequently it is important to establish the time dependency of such systems for various pollutant removal processes [26]. Therefore, the required contact time for sorption to be completed is important to give insight into a sorption process. This also provides information on the minimum time required for considerable adsorption to take place and the possible diffusion control mechanism between the metal ion as it moves from the bulk solution towards the adsorbent surface. The kinetic behaviour of Cu(II) ion sorption onto the two mercaptoacetic acid modified cassava waste was examined using agitation times of 5 – 30 minutes. The removal efficiency of the two adsorbents (0.5MCF and 1.0MCF) for Cu(II) ion is illustrated in Figure 1, while the variation of sorption capacity (qt) of Cu2+ with contact time for the adsorbents is shown in Figure 2. It can be seen from the figures that the removal efficiencies of the adsorbents for Cu(II) ion after 25 minutes were 20.33% and 21.00% for 0.5MCF and 1.0MCF adsorbents respectively. Thus, the rate of Cu2+ removal was quite rapid initially, but it gradually becomes slower with passage of time reaching a maximum in 30 minutes. The initial faster rate may be due to the availability of the uncovered surface area of the adsorbent initially, since adsorption kinetics depends on the surface area of the adsorbent [27]. In addition, the variation in the amount of Cu(II) ion removed by the two adsorbents could be related to the nature and concentration of the surface groups (active sites) responsible for interaction with the copper ions.


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Fig. 1: Percentage removal of Cu2+

with time for different adsorbents

15

16

17

18

19

20

21

22

23

24

25

0 5 10 15 20 25 30 35

Time(mins)

%R

em

ov

al

O.5MCF 1.0MCF

Fig.2: Cu2+ Sorption capacity(qt) variation w ith contact time for

adsorbents

0.40

0.45

0.50

0.55

0.60

0.65

0.70

0 5 10 15 20 25 30 35

Time(mins)

So

rpti

on

c

ap

ac

ity

(mg

/g)

0.5MCF 1.0MCF

The cassava waste adsorbent contains abundant cellulosic units including a matrix of: OH-, COO-, CN- and NH2 functional groups that take part in metal ion binding [28]. Also, during chemical modification process the thiol (SH) was incorporated onto the cassava waste using mercaptoacetic acid, thereby increasing the concentration of surface active sites on the adsorbent matrix.

Fig.3: Time -dependence of the fraction of adsorption of Cu2+ for various

adsorbents

0.4

0.45

0.5

0.55

0.6

0.65

0.7

2 2.5 3 3.5 4 4.5 5 5.5 6

T1/2.min1/2

Yt

0.5MCF 1.0MCF

Figure 3 depicts the time-dependence of the fraction of adsorption of Cu(II) ions on the two adsorbents. It can been seen from the figure that as T1/2 increases, the rate fraction of adsorption (Yt) also increases. This indicates that with passage of time, a higher fraction of the Cu(II) ions migrates from the bulk solution through the adsorbent boundary layer onto the active sites of the adsorbent and is adsorbed. This enhanced sorption of the metal ion with increase in agitation time may be due to the decrease in boundary layer resistance to mass transfer in the bulk solution and an increase in kinetic energy of the hydrated metal ion [29].


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Kinetic Modeling of Cu2+ Sorption Many attempts have been made to formulate a general expression describing the kinetics of sorption on solid surfaces for liquid-solid phase sorption on solid systems. This has led to the existence of a series of kinetic equations that are used to model metal ion transport onto adsorbent surfaces Modeling of kinetic data is fundamental for the industrial application of sorption since it gives information for comparison among different biomaterials under different operational conditions for designing and optimizing operational conditions for pollutant removal from wastewater systems. [30]. In order to investigate the mechanism of sorption of copper by the modified cassava wastes and the potential rate-controlling steps, such as mass transport and chemical reactions, kinetic models were used to model the transport of copper. The different kinetic models used were, pseudo-first order, pseudo second order, Elovich, intra-particle diffusion, mass transfer, and intra-particle diffusivity.

Fig.4: Pseudo-first order kinetics of Cu2+

on different adsorbents

-0.50

-0.45

-0.40

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0 5 10 15 20 25 30 35

Time(mins)

log

(qe

-qt)

0.5MCF 1.0MCF

Fig.5:Pseudo-second order kinetics of Cu

2+ on different adsorbents

0

10

20

30

40

50

0 5 10 15 20 25 30 35

Time(mins)

t/q

t

0.5MCF 1.0MCF

The pseudo-first order plot of Cu2+ on the cassava waste adsorbents is illustrated in Figure 4. From the plot the pseudo-first order rate constant, K1 and the sorption capacity, qe were computed from the slope and intercept of the plot and presented in Table 1. It can be seen that the values of the pseudo-first order rate constant increased with chemical modification. While the sorption capacity, qe values decreased with chemical modification. Figure 5 depicts the plot of t/qt versus contact time for the pseudo-second order equation for sorption of Cu(II) ions. From the plot the values of the pseudo-second rate constant K2, the initial adsorption rate h and the sorption capacity qe computed from the slope and intercept are presented in Table 2. It can be seen that the values of K2 and h decreased with chemical modification, while the sorption capacity qe, increased with chemical modification.


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Table 1: Kinetic constants for pseudo-first order Equation. Adsorbent k1 (L.min-1) qe (mg.g-1) 0.5MCF 1.15 X 10-2 1.973

1.0MCF 1.17 X 10-2 1.676

Table 2: Kinetic parameters for pseudo-second order Equation. Adsorbent qe (mg.g-1) k2 (g.mg-1

. min-1) h (mg.g-1. min-1) 0.5MCF 0.669 6.56 X 10-1 2.94 X 10-1

1.0MCF 0.703 5.25 X 10-1 2.60 X 10-1

Table 3: Kinetic constants for Elovich Equation Adsorbent α (mg.g-1. min-1) β (mg.g-1.min-1) 0.5MCF 6.48 X 10-2 15.822

1.0MCF 7.40 X 10-2 13.900

The Elovich equation plot for Cu(II) ion sorption is shown in Figure 6. Table 3 shows the constants of the Elovich equation α the initial adsorption rate and β the desorption capacity that were obtained from the slope and intercept of the Elovich plot. It can be seen that the initial adsorption rate increased with chemical modification. While the desorption constant decreased with chemical modification. Since adsorption and desorption are interrelated in surface transport, it can be said that there exist an inverse relationship between α and β as presented in Table 3.

Fig.6: Elovich sorption model for Cu2+

on different adsorbents

0.50

0.52

0.54

0.56

0.58

0.60

0.62

0.64

0.66

0.68

2.00 2.20 2.40 2.60 2.80 3.00 3.20 3.40 3.60

ln time

qt(m

g/g

)

0.5MCF 1.0MCF

Fig. 7:Intraparticle Diffusion kinetics for Cu2+ sorption onto different

adsorbents

1.2

1.22

1.24

1.26

1.28

1.3

1.32

1.34

1.36

0.6 0.8 1 1.2 1.4 1.6

Log T

Lo

g R

0.5MCF 1.0MCF

Figure 7 shows the plot of Log R (percent removal) versus Log T for the description of the intra-particle diffusion kinetics of Cu(II) removal. The computed values of the constants, the intra-particle diffusion constant (Kid) and the adsorption mechanism (a) are presented in Table 4. The values show that both constants increased with chemical modification. The mass transfer plot of ln (Co-Ct) versus time is seen in Figure 8. The fitting parameter (ln D) that is a measure of the apparent distribution ratio, the adsorption constant Ko and the mass


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transfer adsorption coefficient Km values were computed from the slope and intercept and are presented in Table 5. From the table it can be seen that the values of lnD, Ko and Km increased with chemical modification. The increase in the value of lnD, which is a measure of the apparent distribution ratio of the Cu(II) ion between the bulk solution and the adsorbent surface portrays that as chemical modification of the adsorbent increases a higher concentration of the Cu(II) ions are transported from the bulk solution onto the active sites of the adsorbent particles. Table 4: Kinetic parameters for Intra-particle Diffusion Equation Adsorbent Kid (min-1) A 0.5MCF 14.01 1.09 X 10-1

1.0MCF 14.41 1.10 X 10-1

Table 5: Kinetic constants for mass transfer Equation Adsorption lnD Ko (min-1) km (g.L-1.min-1) 0.5MCF 1.604 7.0 X 10-3 3.50 X 10-3

1.0MCF 1.610 9.1 X 10-3 4.55 X 10-3

The intra-particle diffusivity equation for the description of the sorption of Cu(II) ions from the aqueous solution onto the surface of the cassava waste adsorbents (0.5MCF and 1.0MCF) is shown in Figure 9. From the slope and intercept of the plot, the values of the initial sorption rate K1 and the boundary layer thickness, Xi were computed and presented in Table 6. Examination of Table 6 shows that the values of the initial sorption rate increased with chemical modification, while that of the boundary layer thickness decreased with chemical modification. Thus it can be said that there is a decrease in boundary layer thickness (Xi) between the bulk solution and the adsorbent particle as the initial adsorption rate (K1) of Cu(II) ion increases. Hence there is said to exist an inverse relationship between, the initial sorption rate k1 and the boundary layer thickness, Xi which leads to the observed pattern of Cu(II) ion sorption from the intra-particle diffusivity equation. Table 6: Kinetic parameters for Intra-particle Diffusivity Equation

Adsorbent K1(mg.g-1.min-0.5) X1 0.5MCF 3.62 X 10-2 4.29 X 10-1

1.0MCF 4.15 X 10-2 4.22 X 10-1


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Fig.8: Mass transfer kinetic model for Cu2+ on various adsorbents

1.50

1.55

1.60

1.65

1.70

1.75

1.80

1.85

1.90

1.95

2.00

0 5 10 15 20 25 30 35

Time(mins)

ln(C

o-C

t)

0.5MCF 1.0MCF

Fig. 9:Intra-particle Diffusivity model for Cu2+ sorption on various adsorbents

0.5

0.52

0.54

0.56

0.58

0.6

0.62

0.64

0.66

0.68

2 2.5 3 3.5 4 4.5 5 5.5 6

T1/2.min1/2

qt(m

g/g

)

0.5MCF 1.0MCF

Coefficient of Determination Analysis For an appropriate description of the mechanism of Cu(II) ion sorption, it was necessary that different kinetic models be tested to determine their extent of fitness to the experimental sorption data. The optimization procedure to be able to select the best fit model requires the selection of an error function in order to evaluate the fit of the kinetic models to the experimental sorption data. The choice of error function can affect the parameters derived-error functions based primarily on absolute deviation bias of the fit towards high concentration data and this weighing increases when the square of the deviation is used to penalize extreme errors. The coefficient of determination, r2 was chosen as the error function for the kinetic model analysis. This is because linear regression implicitly minimizes the sum of the squares of the errors to determine the equation parameters [31]. Table 7 presents the values of the linear coefficient of determination (r2) values of the different kinetic models used to evaluate the sorption of Cu(II) onto the two modified cassava waste adsorbents. Examination of Table 7 shows that the pseudo-second order kinetic equation had the highest r2 values. Thus this kinetic model was taken as the best fit equation for the description of the mechanism of sorption of Cu(II) ions. In addition, examination of the sorption capacity values (qe) of the pseudo second order model shows that the values were in the same range as the experimental sorption capacity values. Therefore, the sorption of Cu(II) ions from aqueous solution onto the mercaptocacetic acid modified cassava waste adsorbents was found to follow the pseudo-second order kinetic equation. Similar conclusion was also reported for the sorption of some heavy metal ions onto various adsorbent surfaces [32-35]. Furthermore, the pseudo-second order is based on the assumption that sorption follows a second order mechanism, with chemsorption as the rate limiting step. So the rate of occupation of adsorption sites is proportional to the square of the number of unoccupied sites [4].


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Table 7:Linear coefficient of determination (r2) of kinetic models Kinetic Model Adsorbent

0.5MCF 1.0MCF

Pseudo-first order 0.9804 0.9514

Pseudo-second order 0.9940 0.9896

Elovich 0.8848 0.8370

Intraparticle diffusion 0.9333 0.8087

Mass transfer 0.8867 0.9726

Intraparticle diffusivity 0.9512 0.9152

CONCLUSION It appears that majority of sorption kinetic studies reported in literature often use one or two models to test their data and then conclude on the appropriate model for their work. However, it is the view in this study that metal ion sorption may be described by more than one kinetic model. Thus it is necessary that several kinetic equations be used to model metal ion sorption. A detailed analysis of six kinetic equations were used to investigate the sorption of Cu(II) ions onto the chemically modified cassava wastes. From the kinetic model analysis using coefficient of determination, the pseudo-second order model was the most fitting for the description of Cu(II) ion transport from the bulk solution onto the surface of the chemically modified cassava waste adsorbents. REFERENCES

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Adsorption Kinetics and Modelling of Copper (II) Ion Sorption Using Mercaptoacetic Acid Modifed Cassava Waste