Water pollution is one of the most important issues of the 21 st century. It takes place when the pollutants are being entered into a water reservoir without any treatment. Heavy metals are one of the major harmful pollutants that exist in the water; therefore, it is necessary to remove these toxic metals to keep our environment safe. Biosorption is an ecofriendly and economical technique for the elimination of these toxic metals from polluted water. In this research work roots, stems, and leaves of Momordica charantia (Bitter gourd) were used as biosorbent for the elimination of Pb (II) ions from aqueous solution. Many different parameters such as metal ion solution pH, biomass dosage, initial metal ions concentration and contact time were optimized in the batch experiments. The calculated results revealed that biosorption of Pb (II) was maximum at solution pH 5, biosorbent dosage of 0.1 g and 100 ppm of initial metal ions concentration within 240 minutes of contact time. M. charantia ’s leaves showed the highest level of lead biosorption capacity (47.62%), followed by stems (42.36%) and roots (38.47%). The Freundlich isotherm and pseudo-second order kinetics model fitted well for the analytical data. The results indicated that Momordica charantia is an effective biosorbent for Pb (II) ions elimination from wastewater.
Polluted water is a notable challenge for all the countries of the world. Due to the quick non-sustainable industrial, urban development, farming and other framework system, water contamination is rapidly increasing and consequently causing harmful diseases and restricting freshwater accessibility all over the world ( Vishwanath et al., 2017 ). Globally, approximately 2.5 billion are living without the proper sanitation facilities ( UNICEF, 2008 ). Mainly, water pollutants produced by anthropogenic activities are heavy metals, microorganisms, pathogens, nutrients, inorganic compounds, organic material, pesticides, and oxygen consuming compounds ( Akpor & Muchie, 2011 ).
Heavy metals (HM) are amongst the most poisonous pollutants on the earth ( Ashraf et al., 2011 ). They cannot be degraded or destroyed. Though heavy metals are naturally present as a trace constituent of the marine environment, due to industrial sewerage, agriculture wastes, geological and mining projects, their levels have been increased ( Sprocati et al., 2006 ). Heavy metals are fatal due to their bioaccumulation in the living organisms. Bioaccumulation refers to the accumulation of any foreign chemical in a living organism (fish for example) over the period of time, compared to the concentration of that chemical in the surroundings ( Abbas et al., 2014 ). If toxic metals accumulated in biological organism, then it will enter in the food chain. Some of these pollutants sometimes find their way into the human system through the food chain. The fish is the most likely organism to bio-accumulate by heavy metals because they are at the start of food chain and can become the vector for humans ( Bawuro et al., 2018 ).
Lead is among the most toxic heavy metals present in the water. It is occurred naturally and generally present in very small amounts in our earth’s deposit. It is present in almost every part of the earth, the soil, the atmosphere, and the water. There are several lead products used in our homes and surroundings including ceramics, pipes and plumbing materials, batteries, gasoline, toys, paints, folk medicines, and cosmetics ( Chaney & Mielke, 1986 ). Though lead has some beneficial uses, it can be very toxic and dangerous for our environment, leading to lead toxicity to humans, animals, and plants. There are some natural sources of lead exposure, but major sources of lead come from anthropogenic activities ( Gurugubelli et al., 2013 ).
There are various techniques that have been established and used for the elimination of heavy metals in the past decades, such as chemical precipitation, ion exchange, ion flotation, membrane filtration or electrodialysis. But there are some disadvantages of conventional techniques being utilized for the removal of heavy metals, such as greater costs, lower efficiency, and unwanted residue generation ( Beni & Esmaeili, 2020 ). Hence, there is a need for bioremediation which has greater removal efficiency and relatively inexpensive. This led to the discovering of new techniques for the removal of heavy metals from polluted water and pay focuses on biosorptive removal process.
Biosorption can remove heavy metals even at very low concentration by using different types of dead biological mass. These biomasses have special abilities to attach heavy metals ( Ahluwalia & Goyal, 2007 ). Generally, the cell wall composition of several plants, algae, fungi, and bacteria, has the characteristics to perform this phenomenon ( Volesky, 1990 ). Primarily, the cell wall is mostly composed of polysaccharides, proteins, and lipids, which have different functional groups on it, such as hydroxyl, carboxyl, amino, ester, and carbonyl group. These functional groups are of great importance in combining metal ions present in the solution ( Talaro & Talaro, 2002 ).
In this study the biosorption of lead ions was compared by using leaves (LMC), stems (SMC) and roots (RMC) of Momordica charantia, known as balsam pear or karela, is a tropical vegetable, a common food in Asian cuisine and is often used in ancient medicine as a medicine for diabetes. In Ayurveda, bitter gourd is used as a tonic, stomachic, stimulant, emetic, taming agent, cathartic, and substitute. Bitter gourd has long been used in various primitive Asian systems of medicine. Like most bitter plants, bitter gourd improves digestion ( Munichandran et al., 2016 ). To investigate the biosorption of lead ions, different experiments were carried out using bitter melon leaves, stems, and roots powder as a biosorbent. The optimization of the biosorbents was carried out using FTIR. The effects of different process parameters such as pH, biomass dose, contact time and initial metal concentration on the removal of lead ions from aqueous solution were observed and optimized.
Bitter Gourd (Momordica charantia) utilized in this research was collected from its native habitats located in Narowal District, Pakistan
fine powder samples were separately sealed in the plastic bags which were used in the adsorption experiments.
1) Lead Nitrate (Pb(NO3)2)
2) Hydrochloric Acid (HCl)
3) Sodium Hydroxide (NaOH)
4) Distilled Water (DW)
5) Lead Reference Solution for AAS
Lead Nitrate (molecular formula = Pb(NO3)2; molecular weight = 331.2 g/mol) was obtained from Sigma-Aldrich Chemicals. Stock solution of 1000 ppm of Pb (II) ions was prepared by dissolving 1.598 g of the Pb(NO3)2 in 1 L of distilled deionized water. Experimental solutions of Pb (II) were prepared by using dilution formula (C1V1 = C2V2) from the stock solution. All the other reagents used in this research were of analytical grade.
Batch kinetic adsorption experiments were conducted to find and compare the biosorption capacity of RMC, SMC and LMC from synthetic aqueous solution of Pb (II) ions. The effect of experimental parameters such as metal ion solution pH (3, 4, 5, 6, 7 and 8), biosorbent dosage (0.1, 0.2, 0.3, 0.4 and 0.5 g), initial metal ion concentration (25, 50, 100, 200 and 400 ppm) and contact time (15, 30, 60, 120, 240, 480 and 1440 minutes) were investigated for the sorption of Pb (II) ions onto the LMC, SMC and RMC biomass. All the experiments were performed in 250 mL Erlenmeyer flasks having 100 mL of diluted aqueous solution of Pb (II) ions, covered with aluminum foil, and placed on the orbital shaker at the continuous speed of 120 rpm. After 24 Hours, the flasks were removed from the orbital shaker and filtered the experimental solution with the help of Whatman filter paper. The filtrates were analyzed in the AAS instrument to find the remaining quantity of Pb (II) ions present in the solution and residues were stored in Eppendorf tube for FTIR analysis.
After 24 hours biosorption, the concentration of the metal ions was estimated through an atomic absorption spectrophotometer. The results of lead ions adsorbed by roots, stems and leaves were quantified by using metal uptake formula:
q e = ( C i − C e ) × ( V / 1000 ) m [
where,
qe represents the amount of metal uptake (mg/l).
Ci represents the initial lead ion concentration (mg/l).
Ce represents the final lead ion concentration (mg/l).
V represents the volume of solution (dm3).
m represents the mass of adsorbent (g).
Percentage removal of Pb (II) ions was calculated with the help of general formula:
% R = C i − C e C i × 100 [
where,
% R is the percentage of metal ion adsorbed from initial concentration.
Ci is the initial concentration of lead (mg/l) at the start of biosorption.
Ce is the final concentration of the lead (mg/l) after the biosorption experiment.
In this research, the powder of leaves (LMC), stems (SMC) and roots (RMC) of Momordica charantia (Bitter gourd) was used for the adsorption of Pb (II) ions. The following parameters effects on the biosorption of Pb (II) ions were studied.
1) Effect of metal ion solution pH
2) Effect of biosorbent dose
3) Effect of initial metal ions concentration
4) Effect of contact time
The effects of all these parameters on biosorption of Pb (II) ions are described below:
The effect of the pH on the biosorption capacity of Pb (II) ions on the biosorbent, as shown in
| pH | Ci (mg/L) | Ce (mg/L) | Ci − Ce | qe (mg/g) | % Removal | |
|---|---|---|---|---|---|---|
| LMC | 3 | 100 | 90.39 | 9.61 | 9.61 | 9.61 |
| 4 | 100 | 85.45 | 14.55 | 14.55 | 14.55 | |
| 5 | 100 | 52.76 | 47.24 | 47.24 | 47.24 | |
| 6 | 100 | 75.39 | 24.61 | 24.61 | 24.61 | |
| 7 | 100 | 84.85 | 15.15 | 15.15 | 15.15 | |
| 8 | 100 | 91.45 | 8.55 | 8.55 | 8.55 | |
| SMC | 3 | 100 | 87.15 | 12.85 | 12.85 | 12.85 |
| 4 | 100 | 76.56 | 23.44 | 23.44 | 23.44 | |
| 5 | 100 | 57.64 | 42.36 | 42.36 | 42.36 | |
| 6 | 100 | 72.42 | 27.58 | 27.58 | 27.58 | |
| 7 | 100 | 82.44 | 17.56 | 17.56 | 17.56 | |
| 8 | 100 | 90.04 | 9.96 | 9.96 | 9.96 | |
| RMC | 3 | 100 | 90.02 | 9.98 | 9.98 | 9.98 |
| 4 | 100 | 82.49 | 17.51 | 17.51 | 17.51 | |
| 5 | 100 | 61.53 | 38.47 | 38.47 | 38.47 | |
| 6 | 100 | 79.76 | 20.24 | 20.24 | 20.24 | |
| 7 | 100 | 84.8 | 15.20 | 15.20 | 15.20 | |
| 8 | 100 | 91.21 | 8.79 | 8.79 | 8.79 |
Similar trend has been reported for the Pb (II) ions elimination by utilizing Mangifera indica biomass ( Nadeem et al., 2016 ).
At lower pH, the active sites of biomass are most probably to be protonated which resulted into poor metal uptake ( Nadeem et al., 2016 ). At pH 5 for bitter gourd (LMC, SMC and RMC) biomass maximum biosorption occurred. The decreased in biosorption on more than the optimum pH 5.0 was based upon
unavailability of surface for adsorption and metal hydroxide and other ligand complexes formation remarkably lessen the quantity of metal ions adsorbed at high pH ( Vijayaraghavan & Yun, 2008 ).
In comparison among LMC, SMC and RMC, LMC (47.24%) showed the greatest percentage removal of Pb (II) ions followed by SMC (42.36%) and then RMC (38.47%) as shown in the
The metal uptake decreased with the increase of biomass dose from 0.1 to 0.5 g, as shown in
| Biomass Dose (g) | Ci (mg/L) | Ce (mg/L) | Ci – Ce | qe (mg/g) | % Removal | |
|---|---|---|---|---|---|---|
| LMC | 0.1 | 100 | 53.55 | 46.45 | 46.45 | 46.45 |
| 0.2 | 100 | 61.3 | 38.7 | 19.35 | 38.70 | |
| 0.3 | 100 | 68.06 | 31.94 | 10.64 | 31.94 | |
| 0.4 | 100 | 72.44 | 27.56 | 6.89 | 27.56 | |
| 0.5 | 100 | 81.79 | 18.21 | 3.64 | 18.21 | |
| SMC | 0.1 | 100 | 58.36 | 41.64 | 41.64 | 41.64 |
| 0.2 | 100 | 65.74 | 34.26 | 17.13 | 34.26 | |
| 0.3 | 100 | 67.3 | 32.7 | 10.90 | 32.70 | |
| 0.4 | 100 | 71.33 | 28.67 | 7.16 | 28.67 | |
| 0.5 | 100 | 80.76 | 19.24 | 3.84 | 19.24 | |
| RMC | 0.1 | 100 | 62.33 | 37.67 | 37.67 | 37.67 |
| 0.2 | 100 | 74.51 | 25.49 | 12.74 | 25.49 | |
| 0.3 | 100 | 76.58 | 23.42 | 7.80 | 23.42 | |
| 0.4 | 100 | 82.38 | 17.62 | 4.40 | 17.62 | |
| 0.5 | 100 | 85.72 | 14.28 | 2.85 | 14.28 |
increasing the biomass dose and minimum removal observed at 0.5 g; 18.21% for LMC, 19.24% for SMC and 14.28% for RMC was recorded. Similar trends of continuous decrease in the adsorption capacity (qe) and percentage removal have been demonstrated and discussed in many researched works ( Ali et al., 2018 ; Manzoor et al., 2019 ; Padmavathy et al., 2016 ).
The remarkable decrease in biosorption capacity is due to the present of concentration gradient among the biosorbent and the metal, which means with the increase in biomass quantity brings a decrease in the quantity of metal ion sorbed onto per unit weight of the biosorbent. At lower biosorbent concentration, the number of active sites is greater, with the further increase in biosorbent quantity, the biomass particles aggregated, as a result biosorption efficiency and Pb (II) uptake decreased ( Ali et al., 2018 ).
The overall comparison of result showed in
The percentage biosorption of Pb (II) ions increased from 9.75 mg/g to 101.92 mg/g, 9.43 mg/g to 93.52 mg/g and 9.43 mg/g to 93.52 mg/g and 8.23 mg/g to 88.56 mg/g onto LMC, SMC and RMC biomass samples respectively, as shown in
| Metal Ion Conc. (ppm) | Ci (mg/L) | Ce (mg/L) | Ci – Ce | qe (mg/g) | % Removal | |
|---|---|---|---|---|---|---|
| LMC | 25 | 25 | 15.25 | 9.75 | 9.75 | 39.00 |
| 50 | 50 | 28.55 | 21.45 | 21.45 | 42.90 | |
| 100 | 100 | 52.38 | 47.62 | 47.62 | 47.62 | |
| 200 | 200 | 121.69 | 78.31 | 78.31 | 39.15 | |
| 400 | 400 | 298.08 | 101.92 | 101.92 | 25.48 | |
| SMC | 25 | 25 | 15.57 | 9.43 | 9.43 | 37.72 |
| 50 | 50 | 30.55 | 19.45 | 19.45 | 38.90 | |
| 100 | 100 | 58.44 | 41.56 | 41.56 | 41.56 | |
| 200 | 200 | 126.35 | 73.65 | 73.65 | 36.82 | |
| 400 | 400 | 306.48 | 93.52 | 93.52 | 23.38 | |
| RMC | 25 | 25 | 16.77 | 8.23 | 8.23 | 32.92 |
| 50 | 50 | 32.78 | 17.22 | 17.22 | 34.44 | |
| 100 | 100 | 63.15 | 36.85 | 36.85 | 36.85 | |
| 200 | 200 | 137.15 | 62.85 | 62.85 | 31.42 | |
| 400 | 400 | 311.44 | 88.56 | 88.56 | 22.14 |
and after that decreased with the further increased in the initial metal ion concentration. But adsorption capacity of RMC has been increased continuously on increasing the initial lead ions concentration as seen in
biomass ( Akram et al., 2019 ).
At 25 ppm solution there was abundant availability of active site on the material which was enough to sorbed the Pb (II) ions but as the initial concentration gradually increased the availability of active sites decreased and as a result the percentage removal decreased. The decreased in percentage removal at higher concentration is because of saturation of specific sites and area for binding, which cause lowering in the possible connection of Pb (II) ions with the present active sites of biosorbents, resulting in the decrease of removal percentage of Pb (II) ions at higher metal ion concentration.
Comparatively LMC (47.62%) has the greatest percentage removal for Pb (II) ions than SMC (41.56%) and RMC (36.85%) at 100ppm of initial lead ions concentration, as shown in
LMC, SMC and RMC sorption of Pb (II) ions was fast in the beginning, almost 30.28%, 28.44%, and 23.85% of metal removal takes place in first 15 minutes, respectively. The biosorption increased as the contact time increased and the maximum adsorption observed at 240 minutes 47.45%, 42.05% and 37.92% for LMC, SMC and RMC, respectively, as shown in Figures 17-19. Result indicates that the biosorption of Pb (II) ions were fast during the first 15 minutes, after that biosorption rate increased slowly and after 240 minutes of contact time no further considerable change in biosorption was observed, as shown in
Lead binding onto the biomass was rapid in the beginning. During the biosorption, the concentration of lead ions rapidly decreased. After sometimes the biosorption equilibrium is obtained; the Pb (II) ions concentration remained
same after 240 minutes remains almost constant after approximately 240 minutes. Although the biosorption process continues, the adsorbent reached the saturation stage and after that the adsorbed metal ions started desorbing into the solution. At equilibrium, there will be no significant change in the metal ions
biosorption, i.e., the adsorption rate becomes equal to the desorption rate and no net adsorption takes place. At first there are great number of active sites present on the biosorbent at which the adsorption takes place and with the passage of time it will become difficult for the ions to adsorb on the biosorbent as the forces present between the ions and adsorbent phase which have already adsorb the metal ions ( Bishnoi et al., 2007 ).
| Time (minutes) | Ci (mg/L) | Ce (mg/L) | Ci – Ce | qe (mg/g) | % Removal | |
|---|---|---|---|---|---|---|
| LMC | 15 | 100 | 69.72 | 30.28 | 30.28 | 30.28 |
| 30 | 100 | 66.33 | 33.67 | 33.67 | 33.67 | |
| 60 | 100 | 63.58 | 36.42 | 36.42 | 36.42 | |
| 120 | 100 | 59.55 | 40.45 | 40.45 | 40.45 | |
| 240 | 100 | 52.55 | 47.45 | 47.45 | 47.45 | |
| 480 | 100 | 52.4 | 47.60 | 47.60 | 47.60 | |
| 1440 | 100 | 52.15 | 47.85 | 47.85 | 47.85 | |
| SMC | 15 | 100 | 71.56 | 28.44 | 28.44 | 28.44 |
| 30 | 100 | 69.48 | 30.52 | 30.52 | 30.52 | |
| 60 | 100 | 65.88 | 34.12 | 34.12 | 34.12 | |
| 120 | 100 | 61.22 | 38.78 | 38.78 | 38.78 | |
| 240 | 100 | 57.95 | 42.05 | 42.05 | 42.05 | |
| 480 | 100 | 57.35 | 42.65 | 42.65 | 42.65 | |
| 1440 | 100 | 57.13 | 42.87 | 42.87 | 42.87 | |
| RMC | 15 | 100 | 76.15 | 23.85 | 23.85 | 23.85 |
| 30 | 100 | 74.07 | 25.93 | 25.93 | 25.93 | |
| 60 | 100 | 71.24 | 28.76 | 28.76 | 28.76 | |
| 120 | 100 | 66.48 | 33.52 | 33.52 | 33.52 | |
| 240 | 100 | 62.08 | 37.92 | 37.92 | 37.92 | |
| 480 | 100 | 61.93 | 38.07 | 38.07 | 38.07 | |
| 1440 | 100 | 61.25 | 38.75 | 38.75 | 38.75 |
The overall comparative result analysis of LMC, SMC and RMC showed in
The FTIR analysis was performed to find the interactions between the Pb (II) and functional groups present on the biomass. FTIR spectra of before and after biosorption were compared for LMC, SMC and RMC as shown in
the present of –COOH group. The peak at around 1650 - 1640 cm−1 is due to the stretching of C=O ( Guerrero-Coronilla et al., 2014 ). Absorption bands at 1460 - 1420 cm−1 are describing the bending of –OH groups and stretching of C-O groups ( Saygideger et al., 2005 ). The peaks around 1100 - 1080 cm−1 are due to the vibration of C-O-C groups. The peaks near 910 - 890 cm−1 may be inorganic or due to the stretching vibrations of C-C group ( Amar et al., 2020 ). After biosorption the FTIR spectra of LMC, SMC and RMC showed the changes in the major peak and also developed some new peaks as shown in
Biosorption equilibrium is commonly explained by isotherms modeling, which are plotted between equilibrium uptake and sorbate concentration in the solution at specific temperature. There are a number of different adsorption isotherm models reported in the literature. But the Langmuir and the Freundlich isotherm models are mostly used for the adsorption equilibrium explanation ( Sheha & Metwally, 2007 ).
The Langmuir isotherm model helps to explain the adsorption of metal ions on the active sites present on adsorbent under isothermal conditions. It is used to explain the equilibrium association among the adsorbate and adsorbent sites ( Liu, 2006 ). The Langmuir isotherm can be mathematically explained as:
C e q e = 1 q max K L + C e q max [
where,
Ce represents the remaining metal ions concentration at equilibrium.
qe represents the metal ion sorbed (mg/g) at equilibrium.
qmax (mg/g) represents the maximum amount of ions adsorbed.
KL represents the Langmuir adsorption isotherm constant.
The graph was plotted against Ce/qe along with Ce. KL and qmax were calculated by taking values of intercept and slope. Langmuir isotherm model have been shown for LMC, SMC and RMC in Figures 24-26, respectively.
Freundlich adsorption isotherm is an empirical model and yields a linear plot. The adsorbate forms both monomolecular and multimolecular layer on the adsorbent active sites ( Al-Ghouti & Da’ana, 2020 ). The Freundlich isotherm can be expressed in the form of equation as:
q e = K F C e 1 / n [
This equation can be arranged in linear from after taking logarithms as:
log q e = log K F + 1 n log C e [
where, Ce represents the concentration of metal ions at equilibrium (mg/L).
qe represents the adsorbed quantity of Pb (II) at equilibrium.
KF represents Freundlich constant.
1/n is Freundlich exponent.
A graph of logCe has plotted against log qe. The value of 1/n is equivalent to the slope and KF was calculated from the value of intercept. The graphs of Freundlich adsorption isotherm model is shown in Figures 27-29 for LMC, SMC and RMC, respectively.
Langmuir and Freundlich isotherms parameters were calculated with the help of their respective graphs and data is shown in
| Biosorbent | Langmuir Isotherm Parameters | Experimental q value (mg/g) | Freundich Isotherm Parameter | ||||
|---|---|---|---|---|---|---|---|
| Xm (qmax) mg/g | KL mg/g | R2 | KF (mg/g) | 1/n | R2 | ||
| LMC | 177.31 | 0.0051 | 0.8482 | 47.62 | 1.4903 | 0.7888 | 0.9212 |
| SMC | 165.29 | 0.0047 | 0.8856 | 42.36 | 1.3116 | 0.7895 | 0.9433 |
| RMC | 178.90 | 0.0034 | 0.8808 | 38.47 | 0.9622 | 0.8229 | 0.9617 |
Freundlich isotherm model demonstrated the biosorption well instead of Langmuir isotherm model. Similar investigation had been investigated in the biosorption of Pb (II) ions by Moringa oleifera seed powder biomass ( Kowanga et al., 2016 ).
Kinetic models have been used to recognize the rate of chemical reactions. It is used to describe the speed of a reaction under different experimental conditions. Kinetics of biosorption was observed by different mathematical models. In this research work pseudo-first order and pseudo-second order kinetic model has been used.
Mathematical expression of pseudo-first order kinetic model is showed in the Equation (3):
log ( q e − q t ) = log q e − k 1 t 2.303 [
where,
qe represent the equilibrium concentration of metal ions (mg/g).
qt represents the adsorbed concentration of metal ions at time interval t.
k1 known as the rate constant for pseudo-first order kinetic model.
In order to find the value of k1, a graph is plotted against log(qe – qt) and time. The graphical representation of pseudo-first order reaction models are shown in Figures 30-32 for LMC, SMC and RMC, respectively.
Mathematical derivation of pseudo-second order kinetic model is explained as:
t q t = 1 k 2 q e 2 + 1 q e t [
where,
qe represent the adsorption at equilibrium stage (mg/g).
qt represents the biosorption at time interval t.
k2 is the rate constant for pseudo-second order kinetic model.
For pseudo-second order reaction a graph is plotted between t/q and t. The graphical representation of pseudo-second order reaction models are shown in Figures 33-35 for LMC, SMC and RMC, respectively.
The comparison between the pseudo-first and the pseudo-second order kinetic model is shown in
| Biosorbent | Pseudo-first Order Kinetic Model | Pseudo-second Order Kinetic Model | ||||
|---|---|---|---|---|---|---|
| qe mg/g | k1 | R2 | qe mg/g | k2 | R2 | |
| LMC | 16.98 | 0.0048 | 0.8318 | 48.56 | 0.0016 | 0.9998 |
| SMC | 13.63 | 0.0043 | 0.8483 | 43.23 | 0.0047 | 0.9999 |
| RMC | 13.31 | 0.0055 | 0.8339 | 39.17 | 0.0017 | 0.9999 |
The comparative result showed that LMC (47.62) has the highest biosorption potential for the elimination of Pb (II) ions followed by SMC (42.36) and finally by the RMC (38.47). Freundlich isotherm model suited better than Langmuir isotherm model with the R2 calculated as 0.9212, 0.9433 and 0.9617, for LMC, SMC and RMC, respectively. Kinetic studies showed the pseudo-second-order model was best fitted in defining the kinetics of the biosorption of lead ions onto the bitter gourd biomass with the R2 value of 0.9998, 0.9999 and 0.9999, for LMC, SMC and RMC, respectively. Results indicated that adsorption capacity gradually decreased with the increase of adsorbent dose and gradually increased with the increase in initial Pb (II) ions concentration. The results reported during this research work showed that the bitter gourd could be utilized as a good biosorbent for the biosorption of Pb (II) ions from polluted water.
The authors declare no conflicts of interest regarding the publication of this paper.
Khan, B., & Khan, A. J. (2023). Biosorptive Removal of Lead Ions from Aqeuous Stream by Using Leaves, Stems and Roots of Momordica charantia Biomass. Journal of Geoscience and Environment Protection, 11, 28-57. https://doi.org/10.4236/gep.2023.1112003