DOI : 10.17577/IJERTV3IS111231
- Open Access
- Total Downloads : 1010
- Authors : Gandhi Nenavath, Sirisha D, Hasheena M, Smita Asthana
- Paper ID : IJERTV3IS111231
- Volume & Issue : Volume 03, Issue 11 (November 2014)
- Published (First Online): 26-11-2014
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License:
This work is licensed under a Creative Commons Attribution 4.0 International License
Eco-Friendly Method for Synthesis of Copper Nanoparticles and Application for Removal of Aqueous Sulphur Dioxide (SO2) and Nitrogen Dioxide (NO2)
-
Sirisha1 N. Gandhi1, M. Hasheena1 and Smita Asthana2
-
Center for Environment and Climate Change,
Jawaharlal Nehru Institute of Advanced Studies (JNIAS) Hyderabad, Telangana.
-
Department of Chemistry, St.Anns College for Women, Mehdipatnam, Hyderabad.
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Abstract:- Sulphur dioxide (SO2) gas is a colour less with a pungent smell and is efficiently adsorbed in upper respiratory tract. Lacrimation, rhinorrhoea, cough, bronchial secretion and bronchonstriation occur at high concentrations of SO2. High concentrations of sulfur dioxide can produce acute injury in the form of foliar necrosis, even after relatively short duration exposure. Sulfur dioxide tends to have more toxic effects when acidic pollutants, liquid or solid aerosols, and particulates are also present.Nitrogen dioxide is an irritating gas with an acrid, pungent odour. In the presence of sunlight, nitrogen dioxide can lead to the formation of ozone, nitric acid and nitrate-containing respirable particles. Anthropogenic emissions of nitrogen dioxide are mainly due to combustion processes, including vehicle exhaust, coal, oil, and natural gas, with some emissions occurring as a result of use in industrial processes. Both SO2 and NO2 have major contribution towards Global warming and hence they are known as major green house gases. The present study deals with the adsorption studies that have been carried out by traditional batch processes. The experiments were conducted with respect to contact time, with respect to different dosages of Copper nanoparticles and Copper immobilized beads, with respect to different concentrations of aqueous solutions of SO2 and NO2. It was found that by using Copper nanoparticles adsorbent, percentage removal of SO2 was 90% and in case of NO2 it was 85%.
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INTRODUCTION
As a necessary component of biological systems, sulfur is ubiquitous in the biosphere. As a result, sulfur often occurs in relatively high concentrations in fossil fuels, with coal and crude oil deposits commonly containing 12% sulfur by weight [1-4]. The widespread combustion of fossil fuels has, therefore, greatly increased sulfur dioxide emissions into the atmosphere, with the anthropogenic component now substantially greater than natural emissions on a global basis. Anthropogenic emissions have resulted in increased sulfur dioxide and atmospheric sulfate loadings in many areas. Early attention to these emissions has focused on their impacts on ecosystems and human health, which occur on both a local level and on regional scales [5- 8]. Sulphur dioxide can be detrimental to ecosystems, harming aquatic animals and plants, and can be damaging to a wide range of terrestrial plant life. In addition, aerosols particles have adverse effects on human health, especially in the form of respiratory ailments. However, that any
lower threshold and the attribution by species for these effects is still uncertain. These impacts have prompted regulations in the most affluent countries to limit emissions of sulfur dioxide. In addition to the aforementioned effects, sulfur dioxide forms sulfate aerosols that are thought to have a significant effect on global and regional climate. Sulfate aerosols reflect sunlight into space and also act as cloud condensation nuclei, which tend to make clouds more reflective and change their lifetimes [9-13]. The radiative forcing change wrought by sulfate aerosols may be second only to that caused by carbon dioxide, albeit in the opposite direction. The radiative effects of aerosols are, however, still very uncertain. Modeling aerosols is significantly more difficult than modeling greenhouse gases such as carbon dioxide [14-17] .
On the other hand the evidence on NO2 and health comes from different sources of information, including observational epidemiology, controlled human exposures to pollutants and animal toxicology. The observational data are derived from studies outdoors where NO2 is one component of the complex mixture of different pollutants found in ambient air and from studies of NO2 exposure indoors where its sources include unvented combustion appliances. Interpretation of evidence on NO2 exposures outdoors is complicated by the fact that in most urban locations, the nitrogen oxides that yield NO2 are emitted primarily by motor vehicles, making it a strong indicator of vehicle emissions (including other unmeasured pollutants emitted by these sources). NO2 (and other nitrogen oxides) is also a precursor for a number of harmful secondary air pollutants, including nitric acid, the nitrate part of secondary inorganic aerosols and photo oxidants (including ozone). The situation is also complicated by the fact that photochemical reactions take some time (depending on the composition of the atmosphere and meteorological parameters) and air can travel some distance before secondary pollutants are generated [18-21]. Health risks from nitrogen oxides may potentially result from NO2 itself or its reaction products including O3 and secondary particles. Epidemiological studies of NO2 exposures from outdoor air are limited in being able to separate these effects. Additionally, NO2 concentrations closely follow vehicle emissions in many situations so that NO2 levels are
generally a reasonable marker of exposure to traffic related emissions [22-23].
The multifaceted impacts of sulfur dioxide and nitrogen dioxide emissions motivates a close examination of possible future paths for regional and global sulfur dioxide and nitrogen dioxide emissions, which is the goal of the present paper.
-
MATERIALS AND METHODS
-
Selection of adsorbent
There are many commercially available materials for controlling SO2 and NO2, but an attempt was made to find effecient and that which is effect even when used at minute concentrations. Copper Nanoparticles were screened by adding 0.04gm of Copper nanoparticle to 100ml of aqueous solution of SO2 and NO2.
-
Preparation of Copper Nanoparticle:
Source of Copper
Chemicals used in the present study all are including Copper Sulphate (CuSO4. 5H2O) are analytical grade and used as it is. There is no further purification procedures are followed.
Preparation of Seed Extract:
The Sesamum indicum seeds were purchased from local super market of Hyderabad city. 5 gm of Sesamumindicum seeds were weighed and grounded into powder using motar and pestle. Powder was soaked into 100 ml of distilled water and allowed it for continuous stirring with help of magnetic stirrer for 8 hours. After completion of stirring the solution was filtered by using whatmann No. 41 paper twice. The solution was kept in refrigerator for further use. Preparation of Copper Nanoparticles:
Many techniques, including chemical and physical means, have been used to prepare metal nanoparticles, such as chemical reduction using a reducing agent, electrochemical reduction, photo chemical reduction and heat evaporation method. Not only physicists and chemists, but also the biologists are highly interested in synthesizing nanoparticles of different shapes and sized by employing bio-based synthesis of nanometals using plant extracts. In the present study to the 25 ml seed extract 100 ml of 0.01 M CuSO4 solution was added and kept it in microwave oven at 180 watts for 10 minutes. Formations of copper nanoparticles were checked by using UV-vis spectrophotometer (Lambda Scientific Spectrophotometer) at regular intevals [24]. This naturally occurring nanoparticle is generated by the erosion and chemical degradation of plants.
Characterization of CuNp:
The characterization technique involves UV-vis absorption spectra (Figure-1), by color change (Figure-2),
-
Preparation of Standard Samples:
A 100 ppm stock solution of nitrite was prepared by dissolving 177 mg of Analytical grade sodium nitrite in 1000 ml standard flask and made up to the mark with double distilled water [25-27]. From the stock solution of Nitrite the working standards were prepared by taking appropriate quantities to get the desire concentration of
NO2. The 0.1575 gm of sodium sulphite is dissolved in 1000 ml of distilled water to get 100 ppm SO2 solution. The working standards are treated with copper nanoparticles and checked for percentage removal by using Uv-Vis Spectrophotometer. Batch Adsorption Studies were carried out for the removal of SO2 and NO2. The percentage removal of NO2 is calculated by using the following formula [28-30].
-
Experimental Procedure:
In the present study an attempt has been made to prepare and use of green synthesized copper nanoparticles in air pollution controlling technologies. Batch adsorption experiments were adopted for the removal studies. The NO2 analysis was carried by NEDA method and SO2 by west gaeke method [31-34]. The experiments are conducted with respect to contact time, effect of NO2 and SO2 concentrations and copper nanoparticles dosage.
Effects of Copper nanoparticle with respect to Contact them for SO2 and NO2
The initial (before adsorption) and the final (after adsorption) concentration is determined at regular intervals of 5, 10, 15, 20, 30, 40, 50, 60, 70 and 80 minutes. The results are given in Table and Fig.
Effect of initial aqueous SO2 Concentration for SO2 and NO2
Different concentrations of aqueous solution of SO2 are mixed with a fixed amount of adsorbent. The experiments are carried out with contact time that is fixed depending upon contact time experiments. The results are given in Table and Fig.
Effect of Copper nanoparticle Dosages for SO2 and NO2 Definite concentrations of aqueous solution of SO2 are mixed with different amount of adsorbent dosages i.e. 0.01gms, 0.03gms, 0.04gms and 0.06gms respectively. The experiments are carried out with the contact time of one hr. is maintained.
Preparation of Copper Immobilized beads
Copper Immobilized beads are prepeared by using Sodim alginate and Calcium chloride. An aqueous solution of sodium alginate was prepared by adding 1gm of sodium alginate to 100 ml of distilled water and 0.1M (1.1gm/100ml) of aqueous calcium chloride was prepared. When the sodium alginate was added drop wise to the calcium chloride solution, spherical, green-colored calcium alginate beads were formed. Both empty beads as well as beads containing Copper nanoparticles were prepared. (amount of CuNp is 5 mg/100ml of sodium alginate).
Effect of Copper Copper Immobilized beads with respect to Contact time for SO2 and NO2
The initial (before adsorption) and the final (after adsorption) concentration is determined at regular intervals of Time i.e. 5, 30, 80, and 120 minutes. The results are given in Table and Fig.
Effect of initial aqueous SO2 Concentration for SO2 and NO2
Different concentrations of aqueous solution of SO2 are mixed with a fixed amount of adsorbent. The experiments
are carried out with contact time that is fixed depending upon contact time experiments. The results are given in Table and Fig.
Effect of Copper Copper Immobilized beads Dosages for SO2 and NO2
Definite concentrations of aqueous solution of SO2 are mixed with different amount of adsorbent dosages i.e. 0.5 gm, 1.0 gm, 1.5 gm and 2.0 gm respectively. The experiments are carried out with the contact time of one hour is maintained.
-
-
RESULTS AND DISCUSSION
-
Effect of Contact time:
1 0 0
% R e m o v a l
8 0
6 0
4 0
2 0
0
0 2 0 4 0 6 0 8 0 1 0 0
C o n t a c t t im e ( in m in )
-
0 p p m
-
0 p p m
-
0 p p m
-
A. UV-visible Analysis of Copper Nanoparticles:
The change of pure copper to copper nanoparticles was determined by measuring the UV-visible spectrum the most
confirmatory device for detection of surface Plasmon
Figure-3: Effect of Contact Time between Copper Nano particle and SO2
1 0 0
resonance property of copper nanoparticles by diluting a small aliquot of the sample in distilled water, the results and adsorption maxima were shown in figure-1 & figure-2.
% R e m o v a l
9 0
8 0
7 0
6 0
5 0
0 5 0 1 0 0 1 5 0
C o n t a c t t im e ( i n m in )
-
0 p p m
-
0 p p m
-
0 p p m
Figure-1: Graphical form of absorbance for synthesis of CuNp by using
Sesamum indicum seeds extract
Figure-2: Change in colour of Sesamum indicum seeds extract during copper nanoparticles synthesis
Figure-4: Effect of Contact Time between Immobilized CuNp beads and SO2
The adsorption of SO2 by Copper nanoparticles at different concentrations increased with increase in contact time. The percentage removal of SO2 is rapid at the beginning and became stable after short interval of time indicating a favourable condition for controlling SO2 by copper Nanoparticles. The optimum contact time for 40 ppm, 50 ppm and 60 ppm are 40 min, 30 min and 15 min, with
85%, 85% and 90% removal respectively. The nanoparticles have a unique property such as high surface area which immediately adsorbs the SO2 molecules which are more even at higher concentration. However, the same experiments were conducted with immobilized copper nanoparticles (Ca- alginate + CuNP), observed a rapid adsorption process and adsorbed with in 10 -15 minutes for all three concentration performed in present study. There was no significant change observed in percentage removal of SO2 (Fig-4). From the results it can be concluded that the percentage removal of SO2 in both conditions are identical, but immobilized copper nanoparticles has taken less contact time for removal of aqueous SO2 compared to copper Nanoparticles. The reason behind this structural variability increases by the process of immobilization, which leads to difference in structure of green synthesized copper nanoparticles [35-36].
9 5
% R e m o v a l
9 0
8 5
8 0
7 5
0 2 0 4 0 6 0
C o n t a c t T im e in m in
3 7 .5 p p m
6 0 p p m
1 5 p p m
1 0 0
% R e m o v a l
8 0
6 0
4 0
2 0
0
0 5 0 1 0 0
-
.5 g m
-
.0 g m
-
.5 g m
-
.0 g m
Figure-5: Effect of Contact Time between Copper Nano particle and NO2.
1 0 0
C o n c e n t r a t io n i n p p m
Figure-8: Effect of Concentration between Immobilized CuNP beads and
-
7 . 5 p p m
6 0 p p m
% R e m o v a l
9 0
1 5 p p m
8 0
7 0
6 0
0 2 0 4 0 6 0 8 0
C o n t a c t T i m e i n m i n
Figure-6: Effect of Contact Time between Immobilized CuNP beads and NO2
The adsorption of NO2 by Copper nanoparticles at different
concentrations increased with increase in contact time. The percentage removal of aqueous NO2 is high at higher concentration and taken less optimum contact time compared to lower concentration in both conditions i.e. CuNp and immobilized CuNp. The results are shown in Fig- 5 & 6, which indicates that immobilized copper
SO2.
The percentage removal of aqueous SO2 is increased with increase in SO2 concentration in both conditions i.e. CuNp and Immobilized CuNp, because the mobility of adsorbate molecules low at higher concentrations and interaction between adsorbate molecules towards adsorbent is high at higer concentration due to less dilution of water molecules (Debye-Hukels theory). From the results (Fig- 7 & 8) it can be concluded that both mobilized and immobilized copper nanoparticles has the capacity to removal aqueous SO2 even at higher concentration. Although the degradation was same for both cases, but with the immobilized copper nanoparticles more dosage is required which was due to reductive surface area for adsorption [38-40].
8 0
nanoparticles has the more adsorption capacity compare to mobilized CuNp with a lesser contact time period. The reason behind this, the immobilized copper nanoparticles may have high catalytic properties and show more capacity of adsorption than uniformly functionalized nanoparticles [37]. From the above experiments it can be report that the both immobilized and non immobilized copper nanoparticles which is prepared by using Sesamumindicum seed extract has the efficiency to remove aqueous SO2 and
% R e m o v a l
6 0
4 0
2 0
0
0 5 0 1 0 0 1 5 0
c o n c e n t r a t io n in p p m
C u N P
Im m o b iliz e d C u N P
SO2 from a liquid media. However, the percentage removal of aqueous NO2 and SO2 are identical (85-90%) when the experiments are perfomed with Copper nanoparticles, where a siginificant change was observed in percentage removal of aqueous SO2 and NO2 when the experiments conducted with respect to immobilized copper nanoparticles. It indicates that the immobilized copper nanoparticles attracts more towards aqueous NO2 compared to SO2.
-
Effect of Initial SO2 and NO2 Concentrations on Adsorption process:
1 0 0
Figure-9: Effect of Intitial NO2 concentration on CuNP and Immobilized CuNP.
NO2 is a reddish brown gas with pungent and irritating odour. It obsorbs light and leads to the yellow haze seen hanging over cities. It is one of the important components of smog. The removal NO2 is increased with increase in NO2 concentration indicates the adsorption rate increase as the NO2 concentration increases. This can be attributed to greater driving force and consequently higher adsorption rate is observed. Polar covalent bonds present in NO2 enhance the adsorption processs by binding towards active sites on copper nanoparticles, where this attraction is low
% R e m o v a l
8 0
6 0
4 0
2 0
0
0 5 0 1 0 0
C o n c e n t r a t io n i n p p m
0 .0 1 g m
0 .0 4 g m
with immobilized copper nanoparticles which results lower percentage removal of NO2. The Copper nanoparticles react with NO2 very fast and sharp compared to SO2, because of the reactivity difference between SO2 and NO2 with Copper nanoparticles. The molecules of NO2 and SO2 are said to be good and strong oxidizing agents but SO2 acts as reducing agent in presence of water due to amphertic nature [40], due to this reason the overall
Figure-7: Effect of Concentration between Copper Nano particle and SO2
percentage removal of NO2 is high compared to SO2.
-
Effect of Adsorbent Dosage:
The percentage removal of NO2 and SO2 increases with increase in the dosage of the nano copper particles and
immobilized copper nanoparticles. The amount of copper nanoparticles required for removal of NO2 and SO2 is veryless compared to the amount of immobilized copper nanoparticles. The percentage removal of SO2 and NO2 in both conditions (CuNp & immobilized CuNp) is low at lower concentration and high at higher concentrations. The reason behind this, the number of gas molecules is low at lower concentration and they are highly mobile due to high dilution factor. Due to this reason interaction between adsorbate and adsorbent is low at lower concentration compared to higher concentration. The removal efficiency of immobilized copper nanoparticles is low for the removal aqueous SO2 and NO2 compared to copper nanoparticles, even though the immobilized copper nanoparticles are more sugestable adsorbent for the removal of aqueous SO2 and NO2 because separation, purification and storage of copper nanoparticles is very expensive. Howevwr, immobilization by using calcium chloride and sodium alginate is a cost effective process. Even though the dosage of the immobilized copper nanoparticles is more which provides meso porous structures with high surface area, which are able to to provide simple accessability and more chances for guest molecules and light to receive by the
active sites. From economic point of view, the usage of copper nanoparticles for the removal SO2 and NO2 is not
-
Kinetic Models:
In order to examine the controlling mechanism of adsorption processes such as mass transfer and chemical reaction, several kinetic models are used to test experimental data. The mechanism of adsorption involves the chemical reaction of functional groups present on the surface of the adsorbent and adsorbate. In present study the experimental data were tested with Pseudo first order, Pseudo Second order, Elovich model and intra particle diffusion models [41].
Pseudo first order equation:
A simple kinetic analysis of adsorption is the pseudo-first- order equation in the form [42-44].
dqt/dt = k1 (qe- qt)
Where k1 is the rate constant of pseudo-first-order adsorption and qe denotes the amount of adsorption at equilibrium. After definite integration by applying the initial conditions qt = 0 at t = 0 and qt = qt at t = t, the linear equation is as follows
log (qe- qt) = log qe k1 t
2.303
C u N p
2 . 0
suitable. Due to high recovery cost and toxicity of nanoparticles, the immobilized nanoparticles are preferred (easy recovery) for removal.
1 0 0
1 . 5
l o g ( q e – q t )
1 . 0
-
-
0 p p m
-
0 p p m
-
0 p p m
1 0 p p m
8 0 2 0 p p m
% R e m o v a l
4 0 p p m
6 0 6 0 p p m
8 0 p p m
4 0 1 0 0 p p m
2 0
0 . 5
0 . 0
0 1 0 2 0 3 0 4 0
C o n t a c t T im e in m in
0
0 . 0 0 0 . 0 2 0 . 0 4 0 . 0 6
a m o u n t o f a d s o r b e n t i n g m
Figure-10: Effect of Dosage between Copper Nano particles and SO2
Figure-13: Pseudo Forst Order Kinetic Model for removal of SO2 with CuNp
1 0 0
% R e m o v a l
8 0
6 0
4 0
2 0
-
0 p p m
-
0 p p m
4 0 p p m
6 0 p p m
8 0 p p m
1 0 0 p p m
1 .5
1 .0
im m o b iliz e d C u N p
-
0 p p m
-
0 p p m
-
0 p p m
0
0 . 0 0 . 5 1 . 0 1 . 5 2 . 0
a m o u n t o f a d s o r b e n t i n g m
Figure-11: Effect of Dosage between Immobilized CuNP beads and SO2
1 0 0
3 7 . 5 p p m o f N P
1 5 p p m o f N P
0 .5
l o g ( q e – q t )
0 .0
– 0 .5
5 1 0 1 5
C o n ta c t T im e in m in
% R e m o v a l
9 0
3 7 .5 p p m o f IB
1 5 p p m o f IB
8 0
7 0
6 0
0 . 0 0 0 . 0 5 0 . 1 0 0 . 1 5
a m o u n t o f a d s o r b e n t i n g m
Figure-12: Effect of Dosage between CopperNano particles and Immobilized CuNP beads NO2. (NP= Nanoparticle, IB= immobilized nanoparticles)
Figure-14: Pseudo First Order Kinetic model for SO2 removal with immobilized CuNp
The plots of log (qe- qt) versus t at different time intervals are represented in figure-13 for both SO2 and NO2. The results are shown in figure-13 -16 for both CuNp and Immobilized CuNp. The graphs indicating that adsorption process is not validity of Lagergren rate equation of first order kinetics for the removal of aqueous SO2 with immobilized CuNp (IB-CuNp) as adsorbent compare to CuNp. Where the kinetic data for removal of SO2 by CuNp
is shown higher correlation coefficient values. It indicates that removal of SO2 by CuNp as adsorbent follows Pseudo
C u N p
First orer Kinetic model. The adsorption rate value k1 is calculated from the slope and shown in table-1.
C u N p
1 .0
0 .8
t / q t
0 .6
-
0 p p m
-
0 p p m
-
0 p p m
1 .0
l o g ( q e – q t )
0 .5
0 .0
3 8 p p m
6 0 p p m
1 5 p p m
0 .4
0 .2
0 .0
0 1 0 2 0 3 0 4 0
C o n ta c t T im e in m in
-0 .5
5 1 0 1 5 2 0
C o n ta c t T im e in m in
Figure-17: Pseudo Second Order Kinetic Model for removal of SO2 with CuNp
im m o b iliz e d C u N p
-1 .0
Figure-15: Pseudo First Order Kinetic model for removal of NO2 with CuNp.
0 . 4
0 . 3
-
0 p p m
-
0 p p m
-
0 p p m
-
1 .0
l o g ( q e – q t )
0 .5
Im m o b ilz e d C u N p
3 8 p p m
6 0 p p m
1 5 p p m
0 . 2
t / q t
0 . 1
0 . 0
0 5 1 0 1 5 2 0
C o n t a c t T im e in m in
Figure-18: Pseudo second Order kinetic model for SO2 removal with immobilized CuNp
0 .0
– 0 .5
1 0 2 0 3 0 4 0 5 0
C o n ta c t T im e in m in
1 . 5
t / q t
1 . 0
C u N p
3 8 p p m
6 0 p p m
1 5 p p m
Figure-16: Pseudo First Order Kinetic model for removal of NO2 with immobilized CuNp
The removal of aqueous NO2 by CuNp and immobilized CuNp is perfectly fited into both Pseudo first order kinetic and Pseudo Second order kinetic models but the correlation coefficient values of pseudo second order kinetic model, slightly more compare to pseudo first order kinetic model
0 . 5
0 . 0
0 5 1 0 1 5 2 0
C o n t a c t T im e in m in
in both cases (CuNp & IB-CuNp). The statistical data concluding that removal of NO2 follows Pseudo second order kinetic model. The adsorption rate value k1 is calculated from the slope and shown in table-2.
Figure-19: Pseudo Second Order Kinetic Model for removal of NO2 with CuNp
I m m o b i l z e d C u N p
1 . 5
Pseudo Second order equation:
Pseudo-second order model is derived on the basis of adsorption capacity of the solid phase, expressed as:
t/qt = 1 + t/qe k2qe2
Where k2 is the rate constant of pseudo second order
1 . 0
t / q t
0 . 5
0 . 0
3 8 p p m
6 0 p p m
1 5 p p m
adsorption (g/mg min) and qe capacity (mg/gm) [45].
is the equilibrium adsorption
0 1 0 2 0 3 0 4 0 5 0
C o n t a c t T im e in m in
Figure-20: Pseudo Second Order Kinetic model for NO2 removal with immobilized CuNp
The plots of t/qt versus t at different time intervals are represented in figure- 17 -20. From the figure-18-20, it was observed that the relationship is linear and R2 values are very high compared to pseudo first order kinetics. The graph indicating that adsorption process is following
pseudo second order kinetics for the removal of SO2 and NO2 using both CuNp and IB-CuNp, except the removal
C u N p
process of SO2 by CuNp. The correlation coefficient values of pseuo seconder oreder kinetic model is lesser than pseudo first order in this condition. The adsorption rate value K2 is calculated from the slope and shown in table 1 & 2. The CuNp follows pseudo first order kinetic model with SO2 as adsorbate, where as both pseudo first and second order kinetic models were fited with NO2 as adsorbate indicating that the difference in reactivity due to the nature of adsorate molecules present in liquid medium. Elovich Model:
6 0
q t
4 0
2 0
0
0 1 2 3 4 5
l n ( t )
3 8 p p m
6 0 p p m
1 5 p p m
Adsorption data can also be analyzed using the Elovich equation at the following linear form
dqt/dt = exp (- qt)
Where, is the initial adsorption rate (mg·g-1·min-1) and
-1
Figure-23: Elovich Model for removal of NO2 with CuNp
i m m o b i l iz e d C u N p
6 0
is the desorption constant (g·mg
) during any one
-
-
8 p p m
experiment. If the adsorption of aqueous solutions of SO2
6 0 p p m
and NO2
by CuNp and immobilized CuNp, fits to the
-
0 1 5 p p m
Elovich model, a plot of qt versus ln (t) should give a linear relationship with a slope of (1/) and an intercept of 1/ ln (). The results for Elovich model represented in figure- 21-24 for both SO2 and NO2 removal process with both adsorbents.
q t
2 0
0
0 1 2 3 4 5
l n ( t )
C u N p
Figure-24: Elovich Model for removal of NO2 with immobilized CuNp
8 0
6 0
q t
4 0
2 0
0
0 1 2 3 4 5
l n ( t )
-
0 p p m
-
0 p p m
-
0 p p m
Intraparticle diffusion Model:
Theoretical treatments of intraparticle diffusion yield rather complex mathematical relationships which differ in form of functions of the geometry of the sorbent particle. A functional relationship common to most treatments of intra particle diffusion is that uptake varies almost proportionately with the half power of time rather than time
t. Assuming that the rate is controlled by pore and intra particle diffusion, the amount adsorbed (qt) is proportional
Figure-21: Elovich Model for removal of SO2 with CuNp
i m m o b i l iz e d C u N p
8 0
-
0 p p m
-
0 p p m
6 0
-
0 p p m
-
-
q t
4 0
to the t1/2, as shown below qt = kidt1/2 + I
Where qt is the amount of adsorbed (mg/g) at time t (min), and I is the intercept (mg/g). kid and I values are obtained from the slopes and intercept of the linear plot.
C u N P
2 0
0
0 2 4 6
l n ( t )
8 0
-
0 p p m
-
0 p p m
6 0
-
0 p p m
q t
4 0
Figure-22: Elovich Model for removal of SO2 with immobilized CuNp
It was evident from the figure-21 and 24, the adsorption process fits for Elovich model for the removal of SO2 with CuNp and NO2 with IB-CuNp as adsorbents. A significant change was observed in correlation coefficient values with increase in concentration of adsorbate molecules in both conditions. This result concluding that the elovich model for SO2 (CuNp as adsorbent) and NO2 (IB-CuNp as adsorbent) removal follows Elovich model at lower concentrations. The R2 and ASS (Absolute Sum of Squares) values were given in table- 1 & 2 [46].
2 0
0
0 2 4 6 8 1 0
t1 /2
Figure-25: Intraparticle Diffusion Model for removal of SO2 with CuNp
i m m o b i l iz e d C u N p
8 0
6 0
q t
4 0
2 0
0
0 5 1 0 1 5
t 1 / 2
-
0 p p m
-
0 p p m
-
0 p p m
Where Dp = Pore diffusion coefficient Cp = Initial solution Concentration
Kf = Fluid to particle transfer coefficient Rp = Radius of the particle
p = Density of media VL= volume of the sample
The rate of the pore diffusion coefficient and other functional kinetic parameters calcluted by respective
Figure-26: Intraparticle Diffusion Model for removal of SO2 with
formula is represented in table-3.
immobilized CuNp
Figure-25 and 26 represents the plots of qt versus t
1/2
for
Solid Diffusion Model:
The solid diffusivity Ds is a very complicated parameter to
adsorption of SO2 by CuNp and immobilized CuNp, at various initial `concentrations. From the figures and table- 1 & 2 it can conclude that the adsorption mechanism is not fits to intra particle diffusion model [47].
C u N p
evaluate due to large number of factors that control the solid diffusion rate. Some of these factors are type of adsorbent, its internal structure and particle size, particle loading, the solid-liquidratio in the system and the initial concentration in solution. All these factors and many other
6 0
q t
4 0
2 0
0
0 2 4 6 8 1 0
t 1 / 2
3 8 p p m
6 0 p p m
1 5 p p m
factors interfere with evaluating Ds from the classical diffusivity equation. Therefore starting value of kf and Ds can be input in the model. The corrected values are obtained by super position of experimental and theroritical data such that they yield congruent curve. The linear formula for solid diffusion is as follows
Figure-27: Intraparticle Diffusion Model for removal of NO2 with CuNp
i m m o b i l iz e d C u N p
Combined Diffusion Model:
Adsorbent particles are heterogenous systems formed by the porous solid phase and fluid phase filling the
6 0
q t
4 0
2 0
0
0 2 4 6 8 1 0
t 1 / 2
3 8 p p m
6 0 p p m
1 5 p p m
void fraction of the solid. The internal diffusion can be expressed bye two simultaneous mechanisms of diffusion, including molecular or knudson diffusion and surface diffusion. If one combines and considers this combined parallel resistance within the adsorbent pellet, a material balance for spherical particle results in the following partial differential equations [48].
)
Figure-28: Intraparticle Diffusion Model for removal of NO2 with immobilized CuNp
The adsorptiove removal of aqueous NO2 by CuNp showing high correlation coefficient values at lower concentrations compare to higher concentration. This observation concluding that removal of NO2 by copper nanoparticles follows intraparticle diffusion model at lower concentrations and deviates at higher concentrations.
Pore Diffusion Model:
In pore diffusion model it is assumed that the adsorbate diffuses into the pores in the fluide phase and it is taken up by adsorption on walls of pores. The molecules cannot diffuse along the walls of the pores in the adsorbed state,that can migrate only by desorbing first. The linear formula for pore diffusion as follows
+
-
-
CONCLUSIONS:
Copper nanoparticles (CuNp) and immobilized copper (IB- CuNp), were successfully employed as adsorbent for removal of SO2 and NO2 from aqueous solutions of SO2 and NO2 respectively. The obtained results indicated a demonstration
S.N
o
Parameter s
Aqueous SO2
concentratio
n
(40 ppm)
Aqueous SO2
concentratio
n (50ppm)
Aqueous SO2
concentratio
n
(60 ppm)
Pseudo first order kinetic model
COPPER NANOPARTICLES
01
R2
0.947
0.759
0.999
ASS
0.048
0.098
0.000
K1
0.118
0.191
0.121
02
IMMOBILIZED COPPER NANOPARTICLES
R2
0.617
0.000
0.863
ASS
0.075
0.000
0.026
K1
0.743
0.752
0.368
Pseudo Second order kinetic model
COPPER NANOPARTICLES
03
R2
0.944
0.318
0.650
ASS
0.009
0.126
0.001
K2
0.021
0.021
0.007
04
IMMOBILIZED COPPER NANOPARTICLES
R2
0.999
0.999
0.995
ASS
0.0008
0.0003
0.0004
K2
0.030
0.022
0.015
Elovich model
COPPER NANOPARTICLES
03
R2
0.901
0.849
0.663
ASS
47.32
57.64
335.6
0.886
1.442
-0.050
0.131
0.152
0.106
IMMOBILIZED COPPER NANOPARTICLES
R2
0.427
0.569
0.721
ASS
2.005
5.970
140.0
4.555
3.986
1.817
3.058
1.328
0.195
Intraparticle diffusion model
COPPER NANOPARTICLES
04
R2
0.775
0.674
0.501
ASS
99.12
87.36
484.7
kid
2.685
1.953
3.206
I
12.95
25.44
30.71
IMMOBILIZED COPPER NANOPARTICLES
R2
0.227
0.329
0.471
ASS
2.704
9.300
265.8
kid
0.1001
0.2400
1.7270
I
31.21
41.08
42.81
S.N
o
Parameter s
Aqueous NO2 concentratio n
(40 ppm)
Aqueous NO2 concentratio n
(50ppm)
Aqueous NO2 concentratio n
(60 ppm)
Pseudo first order kinetic model
COPPER NANOPARTICLES
01
R2
0.999
0.999
0.977
ASS
0.000
0.000
0.000
K1
0.445
0.484
0.534
02
IMMOBILIZED COPPER NANOPARTICLES
R2
0.936
0.906
0.935
ASS
0.052
0.004
0.002
K1
0.385
0.407
0.487
Pseudo Second order kinetic model
COPPER NANOPARTICLES
03
R2
0.999
0.999
0.999
ASS
0.000
0.000
0.000
K2
0.026
0.019
0.077
04
IMMOBILIZED COPPER NANOPARTICLES
R2
0.999
0.999
0.999
ASS
0.005
0.0006
0.0001
K2
0.029
0.018
0.085
Elovich model
COPPER NANOPARTICLES
03
R2
0.459
0.459
0.598
ASS
5.532
1.532
0.125
3.464
4.617
4.148
1.107
2.105
5.555
IMMOBILIZED COPPER NANOPARTICLES
R2
0.958
0.598
0.676
ASS
0.839
5.572
0.061
2.699
3.651
4.260
0.547
0.832
6.756
Intraparticle diffusion model
COPPER NANOPARTICLES
04
R2
0.305
0.305
0.305
ASS
7.88
1.970
0.608
kid
0.323
0.161
0.089
I
31.87
49.93
12.41
IMMOBILIZED COPPER NANOPARTICLES
R2
0.909
0.422
0.520
ASS
2.352
8.010
0.090
kid
0.845
0.421
0.054
I
27.60
49.18
11.03
adsorption activity even nanoparticles were immobilized. The highest efficiency of immobilized nanoparticles is explained on the basis of surface chemistry of the nanoparticles. A detailed kinetic investigative studies have been carried out and indicated the adsorption of NO2 by copper nanoparticles followed both Pseudo first order kinetic model and pseudo second order kinetic model, where adsorption of SO2 by CuNp followed Pseudo second order kinetic model in comparision. Elovich model and intraparticle diffusion models were followed by NO2 at low concentration
and deviation is observed at higher concentrations with immobilized copper nanoparticles as adsorbent. The obtained result concluding that rate dertmining step for removal of aqueous NO2 by immobilized CuNp is through itraparticle diffusion. Kinetic data tends to fit well for pseudo second oreder kinetic model for SO2 removal by immobilized CuNp confirming the chemisorption of SO2. Kinetic data did not fits into Elovich model and Intraparticle diffusion model (IB-CuNp as adsorbent for removal of SO2) indicating that adsorption is controlled by pore surface only. The interesting feature in the immobilization of nanoparticles enables effective removal of toxic gases by adsorption process. This approach should find relevant industrial application in different sectors of industry. This report on adsorbent activity opens up new opportunities for the development of new nano adsorbent systems, despite a number of challenges and difficulties , there is a great potential for application of immobilized nanoparticles.
Parameter
Pore Diffusion (SO2)
Pore Diffusion (NO2)
Solid
Diffusion (NO2)
CuNp
IB-
CuN P
CuNp
IB-
CuN P
Cu Np
IB-
CuN P
Cp
40
ppm
40
ppm
15
ppm
15
ppm
15
pp m
15
ppm
Dp
2.469
X 10-3
m2/se c
7.054
X 10-3
m2/se c
8.426
X 10-3
m2/se c
6.662
X 10-3
m2/se c
Nil
p
0.99823 gm/cm3
-
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