Bio-Based Nanomaterials for Groundwater Arsenic Remediation: Mechanisms, Challenges, and Future Perspectives
Abstract
:1. Introduction
1.1. Sources and Environmental Presence
1.2. Role of Bio-Based Nanomaterials in Groundwater Arsenic Remediation
2. Mechanisms of Arsenic Remediation
2.1. Adsorption
2.2. Filtration/Membrane Technology
2.3. Photocatalysis
2.4. Redox Reactions
2.5. Complexation
2.6. Ion Exchange
2.7. Coagulation–Flocculation
3. Challenges of and Advances in Arsenic Remediation
3.1. Challenges of Arsenic Remediation
3.1.1. Stability and Selectivity
3.1.2. Affordable Scalability
3.1.3. Ability to Regenerate and Recycle
3.2. Recent Advances in Arsenic Remediation
3.2.1. Bio- Nano- Materials Design
3.2.2. Surface Modifications
3.2.3. Hybrid Systems
4. Future Perspectives and Research Directions
4.1. Integration of Bio-Based Nanomaterials with Smart Sensing Technologies
4.2. Development of Sustainable Arsenic-Contaminated Water-Treatment Frameworks
4.3. Smart Design and Life-Cycle Integration for Bio-Based Arsenic Adsorbents
4.4. Green Synthesis and Life-Cycle Assessment (LCA)
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Category | Effect | Reference |
---|---|---|
Human Health | Skin lesions, cancers (skin, lung, bladder), cardiovascular disease | [9] |
Neurological effects and cognitive impairment in children | [10] | |
Diabetes, hypertension, and metabolic disorders | [11] | |
Adverse birth outcomes due to prenatal arsenic exposure | [12] | |
Environment | Disruption of microbial communities in arsenic-contaminated sites | [13] |
Decreased aquatic biodiversity | [14] | |
Sediment arsenic accumulation and benthic toxicity | [15] | |
Agriculture | Phytotoxic effects: reduced plant growth and yield loss | [16] |
Arsenic accumulation in rice and vegetables | [17] | |
Microbial community and enzyme activity decline in agricultural soil | [18] | |
Socio-economic | Health care costs and productivity loss in arsenic-affected regions | [19] |
Loss of income and agricultural productivity | [20] | |
Mental health challenges among chronically exposed populations | [21] |
Category | Source | Arsenic (kt/a) |
---|---|---|
Natural | Windblown dusts | 2.6 |
Sea salt spray | 1.7 | |
Volcanoes | 3.8 | |
Forest fires | 0.19 | |
Anthropogenic | Fossil-fuel combustion | 0.81 |
Non-ferrous metal production | 3.46 | |
Iron and steel production | 0.35 | |
Cement production | 0.27 | |
Waste disposal | 0.12 | |
Biogenic | Continental particulates | 0.26 |
Continental volatiles | 1.3 | |
Marine | 2.3 |
Bio-Based Nanomaterial | Derived Sources | Possible Nanostructure/Form | As Species Targeted | Remediation Mechanism(s) | Reference |
---|---|---|---|---|---|
Chitosan | Shrimp shells, fungi | Nanoparticles, beads, films | As (V), As (III) | Adsorption, coagulation/flocculation ion exchange | [30,31,32] |
Cellulose | Plant biomass | Aerogels, membranes | As (V) | Adsorption | [33,34] |
Modified Biochar | Rice husk, sawdust | Porous nanosheets, powder | As (III), As (V) | Adsorption, redox reaction | [35,36,37,38,39] |
Algae-Based | Green/brown algae | Hydrogel, nanopowder | As (III), As (V) | Complexation, ion exchange | [40,41,42] |
Lignin-Based | Forestry/agricultural waste | Nanoparticles | As (III), As (V) | Adsorption, complexation, ion exchange | [43,44] |
Biogenic nZVI | Green tea, eucalyptus | Zero-valent iron nanoparticles | As (V) | Reduction, adsorption | [45,46,47,48] |
Nano-silica | Algae, agricultural residue | Nanoparticles | As (V) | Adsorption | [50,51,52] |
Bio-Based Adsorbent | Adsorbate | Optimum pH | Kinetic Constants k1: Pseudo 1st Order (/min); k2: Pseudo 2nd Order (g/mg·min); kp: Intra-Particle Diffusion (mg/g·(min)1/2); β: Desorption Constant (g/mg) (Elovich Model); qe: Equilibrium Adsorption Capacity (mg/g) | Surface Area (m2/g) | Maximum Adsorption Capacity (Qm) (mg/g) | Reference |
---|---|---|---|---|---|---|
TiO2-loaded biochar | As (III) | – | k1 = 0.0020 k2 = 0.0284 kp = 1.6106 β = 0.516 (For initial concentration 80 mg/L) | 128.22 | 58.456 | [65] |
Chitosan–magnetic graphene oxide nanocomposite | As (III) | 7.3 | k1 = 0.0767 k2 = 0.0317 kp = 0.5755 | 152.38 | 45 | [66] |
Chitosan–Fe-crosslinked complex | As (III) | 9.0 | k1 = 0.0024 (qe = 2.51) k2 = 0.0042 (qe = 1.69) kp = 42.05 | – | 13.4 | [67] |
Chitosan-coated bentonite | As (V) | – | k1 = 0.0117 (qe = 0.002201) k2 = 4.502 (qe = 0.00834) kp = 1.519 × 109 | – | – | [68] |
Control chitosan biosorbent beads (CCBB) and Magnetic chitosan biosorbent beads (MCBB) | As (III), As (V) | 6.7 | For CCBB, k1 = 0.000667, k2 = 0.27 [As (III)] k1 = 0.000975, k2 = 0.17 [As (V)] For MCBB, k1 = 0.00078, k2 = 0.40 [As (III)] k1 = 0.00076, k2 = 0.32 [As (V)] | 38.27 (CCBB) 52.48 (MCBB) | For CCBB 18.87 As (III) 26.13 As (V) For MCBB 73.69 As (III) 79.49 As (V) | [69] |
Chitosan quinoxaline Schiff base (CsQ) and cross-linked chitosan quinoxaline Schiff base (CsQG) | As (V) | 7 (CsQ) 6 (CsQG) | For CsQ, k1 = 0.0027, K2 = 00.064 For CsQG, k1 = 0.0196, K2 = 0.0195 | – | 8.811 (CsQ) 31.95 (CsQG) | [70] |
Aluminum-modified food-waste biochar | As (III) | – | k1 = 0.00496 (qe = 19.5) k2 = 0.000317 (qe = 20.5) | – | 52.2 | [71] |
Zero-valent iron/biochar composite | As (III), As (V) | – | – | – | 129.24 As (III) 127.15 As (V) | [72] |
Membrane Type | Pore Size | As Species | Initial As Concentration | pH Range | Removal Efficiency (%) | Reference |
---|---|---|---|---|---|---|
Microfiltration (MF) | 0.1–10 μm | As (III) | 20–50 mg/L | 7.6–7.9 | 96% | [79,80] |
Ultrafiltration (UF) | 2–100 nm | As (V) | 100 ng/L | 8 | >99% | [75,84,86] |
Nanofiltration (NF) | 1–10 nm | As (V) | 0–200 μg/L | 6.75 | >99% | [80,81] |
Reverse Osmosis (RO) | 0.1–1 nm | As (III), As (V) | 10–1000 μg/L | 5.5–8.5 | >99% | [75,87] |
Method | Mechanism | Nanomaterials Used | Mode of Action | Advantages | Disadvantages | Reference |
---|---|---|---|---|---|---|
Adsorption | Binding of arsenic ions to adsorbent surfaces | Chitosan-coated NPs, MnFe2O4-biochar, iron oxide nanoneedles | Physical/chemical binding, surface complexation, electrostatic interactions | -Cost-effective and simple -High efficiency with materials like chitosan and biochar -Easy regeneration | -Limited selectivity in the presence of competing ions -Potential fouling after multiple uses | [58,59,60] |
Filtration/Membranes | Physical separation and selective transport using nanoporous structures | Nanofiltration membranes, bio-nanocomposites, TiO2-coated, iron oxide nanofiber filters | Physical blocking, size exclusion coupled with adsorption | -High selectivity -Can achieve >99% arsenic removal -Good for continuous-flow systems | -Expensive fabrication and operation -Membrane fouling -Not always feasible for rural areas | [73,76,77] |
Photocatalysis | Light-driven oxidation combined with adsorption | BiOI, TiO2, biochar-based composites, carbon nanotube hybrids | Oxidation of As (III) to As (V), followed by adsorption | -Uses solar energy -Effective for As (III) to As (V) conversion | -Depends on light source -Some materials have low visible light efficiency | [88,89] |
Redox Reactions | Oxidation-reduction conversion to less toxic and more adsorbable arsenic forms | Biochar@Fe/Cu, MnO2-biochar, redox-active MOFs (e.g., ferrocene-based) | Redox transformation followed by adsorption | -Converts toxic As (III) to less toxic As (V) -Synergistic adsorption–redox activity | -May require specific pH conditions -Material degradation possible over time | [98,99,100] |
Complexation | Formation of stable complexes between functional groups and arsenic ions | Biochar@Fe/Cu, chitosan-stabilized magnetic NPs, MnFe2O4 nanocomposites | Surface complexation via hydroxyl, carboxyl, and amino groups, sometimes aided by photocatalysis | -High binding affinity with functional groups -Can be selective and efficient | -Functional group leaching may reduce long-term efficiency -Surface modification can be costly | [104] |
Ion Exchange | Replacement of arsenic ions (As5+/As3+) with functional groups (e.g., –NH3⁺, –OH) present on the nanomaterial surface | Chitosan nanoparticles, chitin nanofibers | Amino and hydroxyl groups bind arsenic ions through electrostatic attraction and ligand exchange | -Good for low-concentration arsenic -Reversible process -Eco-friendly materials like chitosan | -Limited capacity -Sensitive to competing anions -Regeneration of chemicals may reduce sustainability | [107,108] |
Coagulation–flocculation | Neutralization of surface charges and formation of aggregates that trap arsenic species | Modified chitosan (e.g., with Fe3+, Al3+), chitin-based nanoflocculants | Positively charged biopolymers interact with negatively charged arsenate/arsenite or suspended solids to form flocs | -Fast and scalable -Uses biodegradable coagulants like chitosan -Low-cost option | -Produces sludge -Less effective for dissolved arsenic -Needs post-treatment (filtration/sedimentation) | [109,110,112] |
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Rahman, M.M.; Uddin, M.N.; Parvez, M.M.H.; Mohotadi, M.A.A.; Ferdush, J. Bio-Based Nanomaterials for Groundwater Arsenic Remediation: Mechanisms, Challenges, and Future Perspectives. Nanomaterials 2025, 15, 933. https://doi.org/10.3390/nano15120933
Rahman MM, Uddin MN, Parvez MMH, Mohotadi MAA, Ferdush J. Bio-Based Nanomaterials for Groundwater Arsenic Remediation: Mechanisms, Challenges, and Future Perspectives. Nanomaterials. 2025; 15(12):933. https://doi.org/10.3390/nano15120933
Chicago/Turabian StyleRahman, Md. Mahbubur, Md. Nizam Uddin, Md Mahadi Hassan Parvez, Md. Abdullah Al Mohotadi, and Jannatul Ferdush. 2025. "Bio-Based Nanomaterials for Groundwater Arsenic Remediation: Mechanisms, Challenges, and Future Perspectives" Nanomaterials 15, no. 12: 933. https://doi.org/10.3390/nano15120933
APA StyleRahman, M. M., Uddin, M. N., Parvez, M. M. H., Mohotadi, M. A. A., & Ferdush, J. (2025). Bio-Based Nanomaterials for Groundwater Arsenic Remediation: Mechanisms, Challenges, and Future Perspectives. Nanomaterials, 15(12), 933. https://doi.org/10.3390/nano15120933