| Literature DB >> 35425067 |
Jonas Bayuo1,2, Mwemezi Rwiza1, Kelvin Mtei1.
Abstract
The disadvantages of conventional methods in water and wastewater management including the demand for high energy consumption, the creation of secondary toxic sludge, and operation cost are much too high for developing countries. However, adsorption using low-cost biosorbents is the most efficient non-conventional technique for heavy metals removal. The high adsorption capacities, cost-effectiveness, and the abundance of agricultural waste materials in nature are the important parameters that explain why these biosorbents are economical for heavy metals removal. The present investigation sought to review the biosorption of lead [Pb(ii)] onto low-cost biosorbents to understand their adsorption mechanism. The review shows that biosorption using low-cost biosorbents is eco-friendly, cost-effective, and is a simple technique for water and wastewater treatment containing lead(ii) ions. The batch biosorption tests carried out in most studies show that Pb(ii) biosorption by the low-cost biosorbents is dependent on biosorption variables such as pH of the aqueous solution, contact time, biosorbent dose, Pb(ii) initial concentration, and temperature. Furthermore, batch equilibrium data have been explored in many studies by evaluating the kinetics, isothermal and thermodynamic variables. Most of the studies on the adsorptive removal of Pb(ii) were found to follow the pseudo-second kinetic and Langmuir isotherm models with the thermodynamics variables suggesting the feasibility and spontaneous nature of Pb(ii) sequestration. However, gaps exist to increase biosorption ability, economic feasibility, optimization of the biosorption system, and desorption and regeneration of the used agricultural biosorbents. This journal is © The Royal Society of Chemistry.Entities:
Year: 2022 PMID: 35425067 PMCID: PMC9003363 DOI: 10.1039/d2ra00796g
Source DB: PubMed Journal: RSC Adv ISSN: 2046-2069 Impact factor: 3.361
Fig. 1Various sources of Pb(ii) pollution in the environment (this figure has been adapted from Mohd et al.[7] with permission from Springer, copyright 2021).
Fig. 2Toxic effects of Pb(ii) on plants, animals, and humans (this figure has been adapted from Abidli et al.[8] with permission from Elsevier, copyright 2021).
Fig. 3Schematic illustration of the pathway of heavy metals and metalloids pollutants in the ecosystem (this figure has been adapted from Abidli et al.[8] with permission from Elsevier, copyright 2021).
Fig. 4Sources of heavy metals and their impact on living organisms.
Fig. 5The effects of heavy metals on human health (this figure has been adapted from Mohd et al.[7] with permission from Springer, copyright 2021).
Fig. 6Illustration of human organs affected due to heavy metals toxicity (this figure has been reproduced from Perumal et al.[40] with permission from MDPI, copyright 2021).
Maximum allowable limits (MAL) and health implications of heavy metals
| Heavy metal | MAL for effluent discharge from industries (mg L−1) | MAL for drinking water (mg L−1) | Health implication | |||
|---|---|---|---|---|---|---|
| WHO | ||||||
| Inland surface water bodies | Marine coastal regions | WHO | European Union standard | USEPA | ||
| Arsenic | — | 0.2 | 0.01 | 0.01 | 0.01 | Cancerous and gastrointestinal disorder |
| Cadmium | 0.1 | 2.0 | 0.003 | 0.005 | 0.005 | Causes cancer, dyspnoea, and lung fibrosis |
| Copper | 0.05–1.5 | 3.0 | 2.0 | 0.2 | 1.3 | Causes stomach pain, irritation of the eyes, nasal cavity, mouth, and headache |
| Chromium | — | 2.0 | 0.05 | 0.05 | 0.1 | Causes tumor in lungs and cancer |
| Iron | 0.1–1.0 | 3.0 | 0.2 | 0.2 | 0.3 | Causes hypertension, contraction of the blood vessel and pulse rate |
| Lead | 0.1 | 2.0 | 0.01 | 0.01 | 0.15 | Causes anemia, joint and muscle ache, elevated blood pressure, kidney inflammation, and carcinogen |
| Manganese | 0.05–0.5 | 2.0 | 0.5 | 0.05 | 0.05 | Fatigue, blindness, and sexual impotence |
| Mercury | — | 0.01 | 0.001 | 0.001 | 0.02 | Diarrhea, headache, abdominal effects, loss of appetite, and paralysis |
| Nickel | — | 5.0 | 0.02 | 0.02 | 0.1 | Cancer of the lung and acute bronchitis |
| Zinc | 5.0–15.0 | 15.0 | 3.0 | — | 5.0 | Causes discomfort and metal fume fever |
Fig. 7Application of low-cost activated carbons derived from agricultural wastes for environmental remediation (this figure has been adapted from Heidarinejad et al.[85] with permission from Springer, copyright 2020).
Fig. 8Sources of agro-based biosorbents.
Fig. 9Adsorption process to clean up polluted water using low-cost adsorbents.
Agricultural waste bioadsorbents for heavy metal ions sequestration
| S/N | Bioadsorbent | Metal ion | Removal efficiency or | References |
|---|---|---|---|---|
| 1 | Thiolated saw dust | Pb( | 2.87 mg g−1 |
|
| 2 | Groundnut shell | Cr( | 87.6 and 96.61%, respectively |
|
| 3 | Shea fruit biomass | Cd( | 76.86% |
|
| 4 | Coffee waste-derived biochars | Cd( | 11.41 and 1.18 mg g−1, respectively |
|
| 5 | Banana peels | Cu( | 99.79 and 88.94%, respectively |
|
| 6 | Spent tea leaves | As( | 87% |
|
| 7 | Coconut shell char | Ni( | 0.58 mg g−1 |
|
| 8 | Olive stones | Cd( | 77.4, 80.5, and 94.5%, respectively |
|
| 9 | Brewed tea waste | Pb( | 1.197, 1.457, 1.163 and, 2.468 mg g−1, respectively |
|
| 10 | Orange peel | Cd( | 128.23 mg g−1 |
|
| 11 | Jute stick activated carbon | Cd( | 73.53 mg g−1 |
|
| 12 | Oil palm fibers | Pb( | 16.67, 16.59, 16.65 and 16.54 mg g−1, respectively |
|
| 13 | Sunflower waste carbon | Cd( | 99.8% |
|
| 14 | Modified corn stalks biochar | Cr( | 138.89 mg g−1 |
|
| 15 |
| As( | 47.08 mg g−1 |
|
| 16 | Sagwan sawdust | Cr( | 9.62 mg g−1 |
|
| 17 |
| As( | 66.2 and 15.8%, respectively |
|
| 18 | Activated carbon from sugarcane bagasse | Hg( | 61% |
|
| 19 | Succinylated hay | Cd( | 75.19 mg g−1 and 57.77 mg g−1, respectively |
|
| 20 | Carbon derived from corn straw | Cr( | 175.44 mg g−1 |
|
| 21 | Modified chicken feather | 88.9% | 88.9% |
|
| 22 |
| Pb( | 7.17, 7.81, 8.26, and 8.68 mg g−1, respectively |
|
| 23 | Fe-modified rice straw biochars | As( | 69.6% |
|
| 24 | Spent tea leaves | Cr( | 95.42% |
|
| 25 | Bagasse biochar | Pb( | 75.376% |
|
| 26 | Corn and rice husks | Pb( | >90% |
|
| 27 | Rice husk ash | Pb( | 75% |
|
| 28 | Corn silk | Cu( | 15.35 and 13.98 mg g−1, respectively |
|
| 29 | Mung bean husk | As( | 98.75% |
|
| 30 |
| Cd( | 90% |
|
| 31 | Mustard waste biomass | Pb( | 94.56, 96.15 and 76.48%, respectively |
|
| 32 | Banana peel | Cd( | 93.2 and 83.78%, respectively |
|
| 33 | Coco-peat biomass | Pb( | 0.484, 0.151, 0.383 and, 0.181 mmol g−1, respectively |
|
| 34 | Coffee residues | Pb( | 96 and 44%, respectively |
|
Adsorption potential of some agricultural bioadsorbents for Pb(ii) ions removal from aqueous solution
| Adsorbent | Modifying agent | Experimental variable considered | Constants | Suited equilibrium model analysis (EMA) | EMA, | Kinetics model analysis (KMA) | KMA, | Optimum conditions | % Removal or | References |
|---|---|---|---|---|---|---|---|---|---|---|
| Wood biomass | — | Concentration ( | Agitation speed, pH, temperature | Langmuir | 0.986 | Pseudo-second-order | 0.9988 |
| 100% |
|
| Walnut and almond shells | — | Contact time (CT), dosage (D), pH | Agitation speed, concentration, temperature | Langmuir | 0.9952 and 0.9884, respectively | Pseudo-second-order | 0.9902 and 0.9879, respectively | CT = 240 min, | — |
|
| Cotton shells | — | Contact time (CT), concentration ( | pH, temperature | Freundlich | 0.99 | — | — | CT = 90 min, | 90% |
|
| Pomelo leaves | — | Contact time (CT), pH | Temperature, concentration dosage | Sips | 0.9769 | Pseudo-second-order | 0.9982 | CT = 150 min, pH = 4 | 207.2 mg g−1 |
|
| Fish scale and bean husk | — | Contact time (CT), pH, dosage ( | Agitation speed | Temkin and Langmuir, respectively | 0.5178 and 0.8978, respectively | Pseudo-second-order | 1.000 and 0.9999, respectively | CT = 30 min, pH = 7, | 90% |
|
| Coconut waste | HCl | pH, agitation time (AT), concentration ( | Agitation speed dosage, temperature | Langmuir | 0.969 | Pseudo-second-order | 0.999 | pH = 6, | 50.33 mg g−1 |
|
| Winemaking waste | — | Stirring rate (SR), temperature ( | Contact time, temperature | Langmuir | 0.9989 | Pseudo-second-order | 0.9999 | SR = 500–750 rpm, | 58 mg g−1 |
|
| Lobeira fruit | — | pH, dosage ( | Agitation speed, concentration, temperature | Langmuir | 0.9611 | — | — | pH = 2, | 93% |
|
| Eggplant peel | — | Contact time (CT), pH, dosage ( | Agitation speed | Langmuir | 0.9996 | Pseudo-second-order | 0.9998 | CT = 60 min, pH = 4, | 88.33 mg g−1 |
|
| Shrimp shells chitosan | NaOH | Contact time (CT), pH | Temperature, concentration dosage | — | — | — | — | CT = 90 min, pH = 4 | 99.88% |
|
| Sugarcane bagasse | — | Concentration ( | Agitation speed, pH, temperature | Freundlich | 0.999 | — | — |
| 90–98% |
|
| Coffee husk | — | Dosage ( | Agitation speed, pH, temperature | Freundlich | 0.9800 | Pseudo-second-order | 1.000 |
| 98% |
|
| Cucumber peel | — | pH, contact time (CT), and temperature ( | Agitation speed, dosage, concentration | Langmuir | 0.999 | Pseudo-second-order | 1.000 | pH = 5, CT = 60 min, | 90% |
|
| Black walnut husk | — | pH, contact time (CT), concentration ( | Agitation speed | Freundlich | 0.964 | Pseudo-second-order | 0.999 | pH = 4, CT = 60 min, | 96% |
|
| Sugarcane bagasse derived activated carbon | H2SO4 | pH, contact time (CT), concentration ( | Agitation speed, temperature, dosage | Langmuir | 0.9508 | Pseudo-second-order | 0.9942 | pH = 5, CT = 180 min, | 23.4 mg g−1 |
|
|
| — | pH, dosage ( | Agitation speed | Freundlich | 0.9700 | — | — | pH = 3, | >91% |
|
| Pineapple waste | NaOH | pH, contact time (CT), temperature ( | Agitation speed, dosage, concentration | — | — | — | — | pH = 4, CT = 30 min, | >95% |
|
Linearized adsorption kinetics model equations
| Model | Linear form | Plot | References |
|---|---|---|---|
| Pseudo-first-order |
| log( |
|
| Pseudo-second order |
|
|
|
| Elovich |
|
|
|
| Intra-particle diffusion |
|
|
|
Linearized adsorption isotherm model equations
| Isotherm | Linear form | Plot | Significance | References |
|---|---|---|---|---|
| Henry |
|
| For very low concentrations |
|
| Langmuir | (I) |
| For monolayer adsorption on homogeneous surfaces |
|
| (II) |
| |||
| (III) |
| |||
| (IV) |
| |||
| Freundlich |
| log | For dilute solutions, over a small concentration range |
|
| Dubinin–Radushkevich (D–R) | ln qe = ln | ln | Describes adsorption with a Gaussian energy distribution onto a heterogeneous surface |
|
|
| ||||
| Temkin |
|
| Based on the adsorbent–adsorbate interactions |
|
| or | ||||
| Where | ||||
| Harkin–Jura |
|
| For multilayer adsorption on the absorbent surface with heterogeneous pore distribution |
|
| Elovich |
|
| Based on chemical adsorption kinetics of adsorbate unto biomaterials |
|
| Redlich–Peterson (R–P) |
|
| It can be applied either in homogeneous or heterogeneous systems |
|
| Jossens |
|
| For energy dissemination of solute–solid interactions |
|