Biosorption of heavy metals by utilising onion and

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Biosorption of heavy metals by utilising onion and garlic wastes Article in International Journal of Environment and Pollution · January 2012 DOI: 10.1504/IJEP.2012.050898

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Int. J. Environment and Pollution, Vol. 49, Nos. 3/4, 2012

Biosorption of heavy metals by utilising onion and garlic wastes Rahul Negi, Gouri Satpathy, Yogesh K. Tyagi and Rajinder K. Gupta* University School of Biotechnology, GGS Indraprastha University, Dwarka Sector-16, Delhi-110078, India E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] *Corresponding author Abstract: Onion (Allium cepa L.) and garlic (Allium sativum L.) wastes from market and food canning processes were used for adsorption of Pb2+, Sn2+, Fe2+, Hg2+, As3+ and Cd2+ from multi-component systems at different adsorbent/metal ion ratios. The influence of pH, contact time, temperature and the concentration of adsorbent and adsorbate were studied to optimise the conditions to be utilised on a commercial scale for the decontamination of effluents in a batch adsorption technique. The study was carried out at 50°C and efficiencies were found to be pH dependent. The equilibrium time was 30 minutes and kinetic parameters were calculated using a second order model. The maximum q value was 10.47 ± 0.52 mg g–1 obtained for Pb2+ at an adsorbent loading weight of 0.5 g/100 ml mixed ion solution. Desorption indicates maximum 71% recovery of metal ions, making the remediation process cost effective and reusable. The biomasses were used for removal of heavy metals from both synthetic and industrial effluents and the technique appears industrially applicable and viable. Keywords: heavy metal biosorption; onion wastes; OW; garlic wastes; GW; wastewater. Reference to this paper should be made as follows: Negi, R., Satpathy, G., Tyagi, Y.K. and Gupta, R.K. (2012) ‘Biosorption of heavy metals by utilising onion and garlic wastes’, Int. J. Environment and Pollution, Vol. 49, Nos. 3/4, pp.179–196. Biographical notes: Rahul Negi received his BTech in Biotechnology from University School of Biotechnology, GGS Indraprastha University, Kashmere Gate, Delhi-110043, India. His area of research is biotechnology and waste management. Gouri Satpathy is currently a PhD in Chemistry in the University School of Basic and Applied Sciences, GGS Indraprastha University, Kashmere Gate, Delhi-110043, India. His area of research is food and analytical chemistry and nutraceuticals. Yogesh K. Tyagi is an Assistant Professor in University School of Basic and Applied Sciences, GGS Indraprastha University, Kashmere Gate, Delhi-110043, India. His area of research is biochemistry. Copyright © 2012 Inderscience Enterprises Ltd.

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R. Negi et al. Rajinder K. Gupta is the Dean of University School of Biotechnology, GGS Indraprastha University, Kashmere Gate, Delhi-110043, India. He holds a PhD in Organic Chemistry from India and PhD in Microbiology/Biotechnology from USA. His area of research is biotechnology, food biotechnology and waste management.

1

Introduction

The contamination of water by toxic heavy metals (Pb2+, Sn2+, Fe2+, Hg2+, As3+ and Cd2+) is one of the most serious environmental problems caused by the rapid development of many industries such as mining, photography, fertiliser, surface fishing, energy and fuel producing, pesticide, iron and steel, leather and aerospace and atomic energy installations (McLaughlin et al., 1996; Schalcsha and Ahumada, 1998; Grousset et al., 1999; Faisal and Hasnain, 2004). The wastes containing metals are directly or indirectly discharged into the environment, causing serious environmental pollution and even threatening human life (Berman, 1980; Yong et al., 1998). Conventional methods for heavy metal removal from aqueous solution and soil include chemical precipitation, electrolytic recovery, ion exchange/chelation, solvent extraction/liquid membrane separation and size exclusion processes (Esalah et al., 2000; Canet et al., 2002; Weirich et al., 2002; Shi et al., 2009; Li et al., 2009; Shao et al., 2010). But these methods are often cost prohibitive having inadequate efficiencies at low metal concentrations (Hammaini et al., 2003). Moreover, the resulting sludge has to be concentrated and its disposal or recovery of metals from the sludge represents an enormous problem (Cheng and Shang, 1994). The conventional technologies for effluent treatment are not economically feasible for small-scale industries that are prevalent in developing economies. Therefore, new technologies are required to reduce heavy metal concentrations to environmentally acceptable levels at affordable costs. Hence, biosorption with low-cost materials (industrial, agricultural or urban residues) has emerged as a promising technology for recovering heavy metals from contaminated industrial effluents (Sud et al., 2008). Biosorption is not based on only one mechanism. It consists of several ones that differ quantitatively and qualitatively according to the type of biomass, its origin and its processing. Metal sequestration may involve complex mechanisms, mainly ion exchange, chelation, adsorption by physical forces and ion entrapment in inter and intra fibrilar capillaries and spaces of the structural polysaccharide cell wall network. Both living and dead biomasses (an inactive biomass) as well as cellular products such as polysaccharides can be used for metal removal. Various metal-binding mechanisms have been postulated to be active in biosorption (Gang and Weixing, 1998) by action of metallic ions towards the functional groups present in natural proteins, lipids and carbohydrates positioned on cell walls. Biomaterials previously investigated include use of fungal biomass (Guibal et al., 1992; Mathialagan and Viraraghavan, 2009), bacteria (Deleo and Ehrlich, 1994; Katircioglu et al., 2008; Rani et al., 2009), plants (Wankasi et al., 2006) and agricultural by-products (Horsfall and Abia, 2003; Pandey et al., 2007; Dang et al., 2009; Farooq et al., 2010).

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Studies using biosorbents reveal that both living and dead microbial cells uptake metal ions, hence offering a potentially inexpensive alternative to conventional adsorbents. However, living cells often die due to the toxic effects of the heavy metals. In addition, living cells often require the addition of nutrients and hence increase the biochemical oxygen demand (BOD) and chemical oxygen demand (COD) in the effluent. Therefore the use of dead cells or non-living biomaterials as metal sequestering agents is fast gaining ground since toxic ions do not affect them (Folisio et al., 2008; Grimm et al., 2008). Most of these agricultural by-products are widely available and are of little or no economic value, and some of them in fact present a disposal problem. Moreover, dead cells are cheaper, effective in reducing heavy metals to very low levels and require less care and maintenance. Furthermore, the dead biomass could be easily regenerated and reused (Wankasi et al., 2005; Horsfall et al., 2006). This study may generate useful information for the utilisation of native agricultural wastes (by-products) for the removal of heavy metals from wastewater. The inedible and waste parts of onion and garlic, as agricultural by-products from market and food canning industries could be used as heavy metal adsorbents. In this study, the capabilities of the above biomass for adsorption of heavy metal ions were tested at several experimental conditions. The effects of pH, metal concentration, adsorbent dose, time and temperature on the rate of removal of heavy metals were investigated. The equilibrium data is described by Langmuir adsorption isotherm. The effect of anions on biosorption was studied in industrial effluent with multi-component system. The aim of this work was to check and compare the performance of biosorbents by various cheap and ubiquitous agricultural by-products in multi component systems of the above metal ions mixture.

2

Materials and methods

2.1 Biomass preparation The inedible and waste parts of onion and garlic were obtained from the Agricultural Produce Marketing Committee and food processing industries, Delhi, India in bulk and were ground separately using a food processor (Remi), dried in an oven (Shivaki) at 50°C for 24 h and then screened through a 200 μ mesh sieve. This was done to remove any large particles and to obtain adsorbents with a known particle size range.

2.2 Fourier transform infrared spectroscopy analysis The infrared spectrum of onion and garlic wastes was performed using FTIR-8021PC (Shimadzu), with working range 400–4,500/cm; the samples were introduced as KBr pellet.

2.3 Analysis of the thermally desorbed volatile compounds using GC/MS with thermal desorption system The thermally desorbed volatile compounds were analysed for the identification of sulphide compounds in onion and garlic wastes on a gas chromatograph 6890 and mass

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spectrometer 5975B (Agilent) in trace ion detection mode. The samples are introduced by thermal desorption system (marker) in direct sampling mode by programming as pre-sampling conditions: purge time up to 1 min, temperature of flow path 120°C, carrier gas: helium, purge gas: nitrogen. Sampling conditions: 100 mg of sample weighed into empty glass tube, number of sampling cycle: 1, pressurisation time: 1 min, flush: 1 min, sampling up to: 3 min, equilibration: 3 min. Post sampling conditions: line purge: 1 min. Adsorption and desorption were done using Tenax TA sorbent trap, at minimum temperature –10°C and maximum heating temperature 300°C respectively. Trap was desorbed up to: 3 min in split mode. The chromatography separation was done with the fused silica 30 m capillary column with 0.25 mm internal diameter and 0.25 μm film thickness (HP-5ms). The oven was programmed from 60°C (0 min) at 3°C /min to 240°C (6 min) at 5°C /min to 280°C (15 min). The mass selective detector (MSD) was used in EI mode with scan range (m/z 30–550), transfer line temperature 300°C, ion source 230°C, quadruple temperature 150°C and solvent delay 3.0 min. The obtained total ion chromatograms were searched against NIST’05 library (NIST, 2005).

2.4 Biosorption experiments using synthetic wastewater All the chemical reagents used in these studies were of analytical grade. The stock solutions of all the metals (1,000 mg/l) were procured from Sigma Aldrich. The stock solutions were diluted with deionised water, to obtain the required concentration used for adsorption experiments. In order to adjust the environmental parameters, sodium hydroxide was used to control the ionic strength and nitric acid was used for keeping proton balance. All the experiments were carried out on a shaker (Kuhner) set at 180 rpm and maintained at the value required in flasks (250 ml) covered with aluminium foil. In all sets of experiments (except for the adsorbent effect experiments), fixed amounts of adsorbents were thoroughly mixed with the metal ion solution (100 ml) having the desired initial concentration. After shaking the flasks for desired time, the reaction mixtures were filtered through Whatman filter paper # 42 and the concentration of metal ion in the filtrate was measured. All experiments were carried out in triplicates. Two different controls were also performed. The control without adsorbent determined if the walls of the flask adsorbed metal ions. The control without metal ions (distilled water was used instead of metal solution) was to estimate any leaching from adsorbents during the study period. Chemical composition and metal ion concentrations were measured by Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) Perkin Elmer Optima 2100DV.

2.5 Biosorption experiments using industrial effluent/waste water The industrial effluent (Table 1) was taken from Asea Brown Boveri Ltd, Faridabad, Delhi and the desired amount of stock standard metal solutions were mixed to obtain 50 mg/l of the six metal ions used for adsorption experiment to verify the effect of anions on biosorption.

Biosorption of heavy metals by utilising onion and garlic wastes Table 1

183

Physico-chemical data of industrial effluent

Parameters pH COD (mg/l) BOD (mg/l) Oil and grease (mg/l) TSS (mg/l) Conductivity (μScm–3) Nitrate (mg/l) Phosphate (mg/l) Chloride (mg/l) Sodium (mg/l) Potassium (mg/l) Calcium (mg/l) Magnesium (mg/l) Iron (mg/l) Manganese (mg/l) Chromium (mg/l) Cobalt (mg/l) Cadmium (mg/l) Nickel (mg/l) Lead (mg/l) Zinc (mg/l) Arsenic (mg/l) Mercury (mg/l) Tin (mg/l)

Results ± SD 6.99 ± 0.5 330 ± 5.4 132 ± 2.3 0.67 ± 0.16 108 ± 12.4 1723 ± 10 43.2 ± 1.2 2.98 ± 0.11 104.3 ± 1.10 87.6 ± 0.002 7.02 ± 0.001 43.2 ± 0.003 0.46 ± 0.001 0.75 ± 0.002 0.04 ± 0.001 1.30 ± 0.002 0.21 ± 0.001 0.001 ± 0.0003 0.040 ± 0.001 0.040 ± 0.002 0.029 ± 0.001 0.001 ± 0.0003 Not detected 0.070 ± 0.001

Note: Results are averages of triplicate determinations ± standard deviation.

2.6 Desorption studies A known amount of biomass was taken into a 250 ml flask. Batch kinetic studies were first conducted using fresh biomass to determine the time needed for the metal ions binding process to reach the equilibrium state. After the biosorption tests, the filtered biomass was left in 100 ml of 2% HNO3 for one hour at 30°C in a flask. The biomass was separated from the solution by filtration and washed with deionised water until the pH of the filtrate reached 7. Then the recovered biomass was dried in an electric oven at 50°C and the capacity for biosorption of metals was determined. The biosorption-desorption cycle of metal ions-biomass recovery was repeated two times in order to determine the biosorption capacity of recovered biomasses. The filtrate was also analysed for the estimation of the metal recovery.

2.7 Data evaluation The adsorbed phase concentration was calculated using the following equation (Nassar, 1997):

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R. Negi et al. Qe = V ( Ci − C f

)

W

(1)

where Qe denotes the equilibrium concentration of metal in the adsorbate phase, Ci and Cf are the initial and final metal ions concentration in the liquid phase; V is the volume of the solution in litre and W is the weight of adsorbate in gram.

3

Results and discussion

3.1 Chemical characterisation The chemical composition of onion and garlic wastes, suggests that they could have some potential as a biosorbent. The onion wastes (OW) contain 108 ± 1.6 mg/kg Ca, 1.0 ± 0.6 mg/kg Mg, 18 ± 2.7 mg/kg Na and 955 ± 5.3 mg/kg K ions and garlic wastes (GW) contain 945 ± 4.8 mg/kg Ca, 116 ± 2.8 mg/kg Mg, 87 ± 2.8 mg/kg Na, 1,362 ± 6.7 mg/kg K ions. These are present in the above biomass as components of complex organic compounds and thus exchange with heavy metal cations during sorption process (Kratochvil et al., 1998). The presence of carbohydrates and inulin (non-digestible oligosaccharides) in onion and garlic (Van et al., 1995), also theoretically make them good biosorbents (Coudray et al., 2005). The surface FTIR-characterisation indicate the presence of predominant peaks at 3,400.3 cm–1 and 3,377.13 cm–1 (–OH groups), 2,927.7 cm–1 and 2,891.1 cm–1 (C-H groups), 1,622.0 cm–1 and 1,643.2 cm–1 (C = O, C = N), 1,417.6 cm–1 and 1,454.0 cm–1 (–CH3, –CH2–), 1,338.5 cm–1 and 1,263.1 cm–1 (C-O-C, C-F), 1,031.8 cm–1 and 1,026.1 cm–1 (C-O), 927.7 cm–1 and 929.6 cm–1 (cyclic compound), 817.8 cm–1 and 813.8 cm–1 (C = C) and the bands in the range from 599.7 cm–1 to 414.7 cm1 indicate the presence of metal halogen bonds. Those prove the capability of binding to the metal cations (Volesky, 2003). The gas chromatographic analysis of the thermally desorbed volatiles from onion and garlic wastes revealed the principal sulphides present as being: diallyl sulphide, diallyl disulphide, diallyl trisulphide, methyl diallyl disulphide, methyl allyl sulphide, which have the capability to work as ligands in metal complexation (Marcano et al., 2006; Sadik, 2008).

3.2 Factors affecting biosorption The major factors affecting the biosorption processes are: 1

pH

2

temperature

3

contact time

4

biomass concentration in solution

5

initial metal ion concentration.

3.2.1 Effect of pH The effect of pH on adsorption of Pb2+, Sn2+, Fe2+, Hg2+, As3+ and Cd2+ was investigated at pH range 2–7. The efficiency of metal ion removal by the adsorbent is affected by the

Biosorption of heavy metals by utilising onion and garlic wastes

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initial pH of the reaction mixture (Horsfall and Spiff, 2004). The uptake of metal ions is pH dependent, where optimum metal removal occurred at pH 5 for all the above metal ions. The dependence of percent metal removal is similar to the heavy metal ion sorption on agricultural waste sorbents (Rodda et al., 1993). The results show that the equilibrium capacity of metal removal by onion and garlic wastes increased significantly as the pH of the solution increased from 2–5 (Figure 1). If the initial pH is too high, metal ions precipitate out and this defeats the purpose of employing the sorption process. The sorption process is kinetically faster than precipitation (Appel and Lena, 2002). The adsorptive capacities of metal ions increased rapidly as the pH value increased. Furthermore, at pH 6 the adsorptive capacities of cationic ions decreased because of chemical precipitation. Sorption studies were futile above pH 7, due to the formation of insoluble products in investigated solution. Figure 1

Effect of pH in percent removal of metal ions 120

% Removal

100 80 60 40 20 0 2

4

5

6

7

pH As(OW)

As(GW)

Cd(OW)

Cd(GW)

Fe(OW)

Fe(GW)

Pb(OW)

Pb(GW)

Sn(OW)

Sn(GW)

Hg(OW)

Hg(GW)

A decrease in pH was observed at the end of experiments. This was due to the release of proton as result of ion exchange between metal ions and H+ ions. It is due to the mixed effect of ion exchange and surface complexation on the surface of biomasses and the decrease in adsorption at pH greater than 7 is due to the formation of hydroxide. Maximum metal ions removal was achieved at pH 5 and the results suggest that the above biomasses can be used as a potential decontaminant for the removal of above six metal ions from aqueous solution.

3.2.2 Effect of temperature The effect of temperature on the adsorptive capacity of various metals is illustrated at range of 30–60°C (Figure 2). It is clear that the uptake of metal ions increased with an increase in temperature up to 50°C, indicating better adsorption at higher temperatures, which is typical for the biosorption of most metal ions from their solution (McKay et al., 1999). This may be due to the acceleration of adsorption steps or the creation of anionic sites on the adsorbent surface (Nassar and Magdy, 1999). The temperature higher than this may have caused a change in the texture of the biomass, thus reducing its sorption

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capacity. The adsorption of metal ions may involve chemical bond formation and ion exchange since the temperature is the main parameter affecting the above two processes. Figure 2

Effect of temperature on biosorption capacity of metal ions

120

% %Removal Removal

100 80 60 40 20 0 30

40

Tem p(0C)

50

60

As(O)

As(G)

Cd(O)

Sn(G)

Fe(O)

Pb(G)

Sn(O)"

Cd(G)

Hg(O)

Hg(G)

Fe(G)

Pb(O)

3.2.3 Effect of contact time Rapid adsorption was seen in the first 30 minutes, following which the rate of percentage removal of metals remained near constant. Adsorption rate of metals increased with subsequent increase in contact time between the metal solution and the biomass, but the rise in rate of metal removal was negligible beyond the first 30 minutes (Figure 3). Therefore, 30 minutes was found to be the optimum time period for attainment of equilibrium. Equilibrium time for metal ions biosorption 120 100 80 % Removal

Figure 3

60 40 20 0 0

As(O) Pb(O)

50 As(G) Pb(G)

100

150

Tim e(m in)

Cd(O) Sn(O)

Cd(G) Sn(G)

200 Fe(O) Hg(O)

Fe(G) Hg(G)

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3.2.4 Biomass concentration in solution The amount of biomass employed was found to influence the efficiency of the adsorption process. This parameter was optimised in conjunction with the other optimised parameters (50 ppm metal at pH 5) by shaking different weights of biomass (0.25 to 2 g). Increasing the doses further did not affect the percentage removal. The percentage of metal removal did not increase in a sequential manner due to metal ion concentration shortage in solution at high dose rates (Figure 4). The mechanism of metal removal by the biomass is complex. It may involve metal interactions or coordination to functional groups present in natural proteins, lipids and carbohydrates positioned in cell wall (Kumar, 2006). Figure 4

Effect of adsorbent dose on removal of metal ions

120 100

% Removal

80 60 40 20 0 0.25

0.5of adsorbent(gm ) 1 Quantity

2

As(OW)

As(GW)

Cd(OW)

Cd(GW)

Pb(OW)

Pb(GW)

Sn(OW)

Sn(GW)

Fe(OW)

Fe(GW)

Hg(OW)

Hg(GW)

3.2.5 Initial concentration of metal ions The effect of metal ions’ concentration was studied by batch adsorption experiments carried out using the concentration range of 10–50 mg/l. The results obtained were analysed using Langmuir isotherms [Figures 5(a) and 5(b)]. The adsorption capacity increased with an increasing the initial ion concentration. This is in agreements with the results obtained by the other investigators (Dimitrova and Mehandgiev, 1998). Since the adsorption isotherms are important to describe how adsorbents will interact with adsorbate and so are critical for design purposes, therefore the correlation of equilibrium data using an equation is essential for practical adsorption operations (Hashem et al., 2007). Langmuir equation: q = qmax bCeq 1 + bCeq

(2)

where q is milligrams of metal accumulated per gram of the biosorbent material; Ceq is the metal residual concentration in solution; qmax is the maximum specific corresponding to the site saturation and b is the ratio of adsorption and desorption rates. The isotherm constants and their correlation coefficients (r2), the qmax are listed in Table 2.

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Figure 5

The Langmuir adsorption isotherms of metal ions by (a) onion waste and by (b) garlic waste

60 50

Ce/Qe

40 30 20 10 0 0

10

20 Ce As(OW) Hg(OW) Linear (Fe(OW))

Cd(OW) Sn(OW) Linear (Hg(OW))

30

40

50

Fe(OW) Linear (Cd(OW)) Linear (Sn(OW))

60

pb(OW) Linear (As(OW)) Linear (pb(OW))

(a) 60 50

Ce/Qe

40 30 20 10 0 0

10

20

Cd(GW) Sn(GW) Linear (Hg(GW))

Ce

30

As(GW) Hg(GW) Linear (pb(GW))

40

50

Fe(GW) Linear (Cd(GW)) Linear (Sn(GW))

60

pb(GW) Linear (As(GW)) Linear (Fe(GW))

(b) Table 2 Metal

Langmuir adsorption parameter of onion and garlic wastes Qmax (mg/g)

Langmuir constant (b)

Correlation coefficient ( r2)

OW

GW

OW

GW

OW

GW

As

2.56

2.304

1.26

1.75

0.9021

0.941

Fe

8.012

8.459

2.415

1.786

0.950

0.909

Pb

9.957

10.496

6.615

5.249

0.954

0.951

Sn

7.812

7.132

2.943

2.73

0.961

0.964

Cd

1.36

1.47

1.04

1.02

0.882

0.989

Hg

4.95

5.12

1.655

1.255

0.943

0.907

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189

According to the extended Langmuir model for the multi-element systems studied, the maximum sorption uptake of the onion and garlic wastes remained practically constant for each metal ion for both biomasses, which is an indication that the active sites of the biomass are constant and independent of the metal solution used. The values of b are indicative of the affinity of the sorbent by the sorbate, and therefore high values of b are associated with a high metal adsorbed/metal desorbed ratio (Veglio et al., 1997; Lau et al., 1999). The b is higher for lead than for the other metals (Table 2). Therefore, lead has a higher affinity for the sites of the adsorbent material in the multi-component adsorption systems studied. Furthermore, the affinity of onion and garlic wastes by metals followed the order: Pb2+ > Sn2+ > Fe2+ > Hg2+ > As3+ > Cd2+. These results support the hypothesis drawn by other authors, that the preference of a biosorbents for metals is related to the physicochemical parameters of the metal (Sag et al., 2001). Table 3 shows some properties of the six metal ions used in this study. Table 3

Physico-chemical properties of the metals tested

Metal Atomic weight Charge Oxidation states Electronic configuration Ionic radius Electronegativity Atomic weight

Pb

Hg

Sn

207.2

200.59

118.71

2

2

2

+2, +4

+1, +2

+2, +4

[Xe] 4f14 5d10 6s2 6p2

[Xe] 4f14 5d10 6s2

[Kr] 4d10 5s2 5p2

1.19 Å

1.02 Å

1.12 Å

2.33

2.00

1.96

Cd

As

Fe

112.41

74.92

55.845

Charge

2

3

2

Oxidation states

+2

+3, +5

+2, +3

[Kr] 5s2 4d10

[Ar] 4s2 3d10 4p3

[Ar] 3d6 4s2

0.95 Å

0.58 Å

0.61 Å

1.69

2.18

1.83

Electronic configuration Ionic radius Electronegativity

The diffusion of metals with higher atomic weight can generate higher momentum energy. This fact may facilitate the biosorption of the metal by increasing the probability of an effective collision between the metal and the solid surface. For this reason metals with higher atomic weights have more affinity for the biosorbents (Sag et al., 2001). Another factor to consider is the ionic radius. It has been reported that, in the ion-exchange process, larger multivalent ions are more effectively removed than smaller ones (Chong and Volesky, 1996; Prasad and Saxima, 2004). On the other hand, lead has unpaired electrons and could be attracted by a magnetic field probably originating in the biosorbents. Nevertheless, cadmium is very stable (absence of unpaid electron) and could be repelled by a magnetic field. Moreover, there are two possible oxidation states (+2, +4) associated with Pb2+ and only one for Cd2+. The higher the electro-negativity of the atom, the more easily the ion is sorbed by the biosorbents (Chong and Volesky, 1996). The final behaviour will be a combination of all the above factors (Pérez et al., 2008).

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3.2.6 Biosorption kinetics Kinetics and equilibrium are the two major parameters for evaluating adsorption dynamics. The effect of contact time on metal ions removal was investigated for an initial concentration of 50 mg/L at pH 5. It was observed that the percentage removal of metal ions initially increased with contact time and the equilibrium was attained within 30 minutes (Figure 4). dqt / dt = K ( qe − qt ) Figure 6

2

(3)

Kinetics of metal ions adsorption onto the (a) onion waste and the (b) garlic waste 180 160 140 120

t/qt

100 80 60 40 20 0 0

50

100

150

200

t (tim e) Linear (Cd(ow )) Linear (Pb(ow ))

Linear (As(ow )) Linear (Hg(ow ))

Linear (Fe(ow )) Linear (Sn(gw ))

(a) 160 140 120 t/qt

100 80 60 40 20 0 0

50

t (tim e)

100

150

Linear (Cd(gw ))

Linear (As(gw ))

Linear (Hg(gw ))

Linear (Sn(gw ))

Linear (Pb(gw ))

Linear (Fe(gw ))

(b) Note: Lines represent modelled results using the pseudo-second order equation.

200

Biosorption of heavy metals by utilising onion and garlic wastes

191

This equation was integrated and arranged to get the following equation. t / qt = 1/ kqe2 + 1/ qe (t )

(4)

where k is the sorption coefficient, qe is the equilibrium capacity and qt is the sorption capacity at any time ‘t’. Time, t was plotted against t / qt and straight lines having correlation coefficient of 0.99 were fitted in the data for all metals. The sorption coefficient k and equilibrium capacity qe were calculated from the slope and intercept of lines [Figures 6(a) and 6(b)] and are shown in Table 4. Table 4 Metal

Metal ions sorption data derived from pseudo second order kinetics model Qe (mg/g) OW

GW

K (g mg–1 min–1) OW

GW

Correlation coefficient ( r2) OW

GW

As

1.58

1.93

0.3840

0.3924

0.999

0.9991

Fe

7.96

8.01

0.2337

0.1887

0.9998

0.9997

Pb

9.64

9.83

0.0751

0.0703

0.9994

0.9996

Sn

9.45

9.46

0.0986

0.1025

0.9997

0.998

Cd

1.19

1.27

0.4752

0.4956

0.998

0.9992

Hg

4.92

5.01

0.2024

0.1243

0.9996

0.999

The values obtained for equilibrium capacity for both metals were very close to those obtained experimentally after 30 min of sorption. It confirmed that 30 minutes was sufficient for sorption to attain equilibrium and sorption followed pseudo second order kinetics.

4

Effect of anions on metal biosorption

The studies conducted using synthetic metal ion solution (multi-element standard) revealed the practicability of the leached biomass as a potential sorbent for removal of metal ions from industrial effluents. The metal ions and the range of concentrations chosen were representative of typical industrial waste and effluents. In a set of experiments with the above biomasses, it was demonstrated that 50 mg l–1 of metal ions present in the industrial waste could be removed up to 53 % at pH 6.99. The removal of toxic metal at pH 5 increased the percentage removal of metal ions up to 76 % as shown in Figure 7.

5

Desorption

The recovery of metal ions (as a percentage of adsorbed metal ion concentration) with 100 ml of 2% HNO3 was observed in the order: Fe (71.0%) > Sn (66.2%) > Pb (59.6%) > Cd (59.2%) > As (57.6%) > Hg (57.2%). The recovered biomass exhibited good biosorption capacity (Figure 8). It demonstrates the potential of recycling the metals as well as reuse of the biomass. Once the metals are recovered, the biomass material, which is biodegradable, will cause no environmental damage and may be utilised as natural soil conditioners or fertiliser. Hence, the above biomasses could be used for cleansing the

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environment and industrial waste eluent from trace metals. So recycling of sorbent can be done to make the remediation process cost effective. Figure 7

Effect of anions in industrial effluent (with and without adjusted pH) on percent removal of metal ions (see online version for colours) pH(6.99)(OW)

80

pH(5.0)(OW)

Metal adsorption (%)

70

pH(6.99)(GW)

60

pH(5.0)(GW)

50 40 30 20 10 0 Fe

Figure 8

Pb

Sn

Hg

Cd

As

Ratio of biosorption capacity for fresh (onion and garlic wastes) and desorbed biomasses 12

Qe(mg/g)

10 8 6 4 2 0 As

Fe

Pb

Sn

Cd

Hg

Nam e of Cations Qe(mg/g)OW Qe(mg/g)OW(recoverd after desorption) Qe(mg/g)GW Qe(mg/g)GW(recovered after desorption)

6

Conclusions

This preliminary study concerning the adsorption capacities of onion and garlic wastes indicates great potential for the reduction of metal ions in wastewater. The biosorption process followed Langmuir model for all metals, which indicates that ion exchange took place on the surface of adsorbent. The adsorption mechanism of metal ions on the above biomass involves either cation exchange or complexation between the metal cation and

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the hydroxide ion present in the solution or coordination to functional group positioned in the biomass cell walls. The maximum sequestrations of metal ions were found to be at pH 5 and at temperature of 50°C in 30 min with dry biomass 0.5 g/100 ml metal solutions. Desorption with 2% nitric acid produces a maximum of 71% recovery of metal ions with possibility of biomass reuse to make the remediation process cost effective. This may also provide an affordable, environmental friendly and low maintenance technology for small and medium scale industries in developing countries.

Acknowledgements We are grateful to State Grading Laboratory, Directorate of Agricultural Marketing, Delhi, India for all their support.

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