Innovative Approaches and Evolving Strategies in Heavy Metal Bioremediation: Current Limitations and Future Opportunities
Abstract
:1. Introduction
Research Publications on Heavy Metals
2. Heavy Metals Occurrence and Toxicity in the Environment
3. Biological Remediation Techniques Overview
3.1. Bioremediation
3.2. Phytoremediation
4. Novel Approaches and Emerging Strategies
4.1. Genetic Engineering in Bioremediation
4.2. Nano-Assisted Bioremediation: Synergistic Approaches for Environmental Restoration
5. Complexities and Constraints in Bioremediation: Addressing Key Scientific and Practical Challenges
5.1. From Lab Controlled Experiments to Biosphere: Scaling up Bioremediation for Environmental Restoration to Real-World Implementation
- Initial investment and operational costs—Bioremediation involves lower setup and operational costs, especially for in situ applications (e.g., natural attenuation and bioaugmentation). It utilizes natural or engineered biological systems, reducing the dependency on expensive chemicals and high-energy processes. Depending on the type of bioremediation, costs may vary. For example, phytoremediation, although slower, may require up to 50% less cost compared with conventional treatments, while bioaugmentation requires more investments in process control, strain maintenance, and monitoring [210,211]. Physicochemical methods require high initial costs for equipment, chemicals, and infrastructure, as well as ongoing operational costs due to energy-intensive processes (e.g., electrochemical treatment or advanced oxidation). These methods generate secondary waste, requiring additional treatment and disposal procedures, thus increasing costs [212].
- Long-term sustainability and maintenance costs—Bioremediation tends to be more durable, with minimal long-term maintenance, but some methods such as phytoremediation require months to years to reach the desired level of removal, which can lead to increased monitoring costs. Physico-chemical methods provide rapid removal of heavy metals, but often require repeated applications for sustained results. These methods can degrade the structure of the ecosystem, requiring additional remediation costs [213].
- Cost of waste management—Bioremediation generates less hazardous waste compared to conventional methods, and in some cases the by-products obtained (e.g., biomass or biochar) can be reused for economic value (e.g., fertilizers and biofuels). Physico-chemical methods produce large volumes of toxic sludge or secondary pollutants, which require significant costs for handling, transportation, and disposal [214].
- Cost-effectiveness on a large scale—Bioremediation has the potential to be more economically feasible for large-scale contamination scenarios in integrated practices, both for long-term treatments as well as environmental restoration. Physico-chemical methods, although suitable for highly contaminated sites where rapid treatment is needed, require high costs that make them disadvantageous for long-term remediation [215].
5.2. Management of Bioremediation Waste
5.3. Public Perception and Acceptance from Scientific Innovation to Societal Expectations—Challenges and Pathways Forward
5.4. Future Trends in Bioremediation
- Genetically modified microorganisms (GEMs)—Through advances in biology and genetic engineering, microorganisms with greatly improved metal uptake, resistance, and degradation capabilities have been developed. Novel technologies such as CRISPR and gene editing offer the possibility of optimizing microbial metabolism to create highly specific and efficient mechanisms for bioremediation.
- Nanotechnology—The integration of nanomaterials, such as bio-nanocomposites and biogenic nanoparticles that can stabilize and immobilize metals, is another approach to stimulate microbial activity and control the bioavailability and mobility of metals for efficient remediation;
- Microbial consortia with complementary metabolic pathways can contribute to improved sequestration and degradation of heavy metals;
- Enhancing phytoremediation and rhizoremediation by using genetically modified plants and exploiting plant-microbe interactions represents a sustainable solution, especially for large-scale and in situ applications;
- Electro-bioremediation via integrating electrochemical systems with microbial cells is another approach to improve metal recovery while generating bioenergy, thus leading to a more cost-effective and sustainable remediation process;
- AI (Artificial Intelligence) and Big Data in bioremediation enable AI-based modeling and machine learning to optimize selection programs for microbial strains or plants, predict remediation efficiency, and design large-scale bioremediation strategies with high accuracy and optimized conditions.
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Elements | Water | Soil/Sludge Applied to Soil | ||
---|---|---|---|---|
WHO Limits (mg/L) | US-EPA Limits (mg/L) | WHO Limits (mg/kg d.w) | US-EPA Limits (mg/kg d.w) | |
Arsenic (As) | 0.01 | 0.01 | 20 | 0.39 |
Cadmium (Cd) | 0.003 | 0.005 | 3 | 1.4 |
Total Chromium (Cr) | 0.05 | 0.1 | 100 | 100 |
Cobalt (Co) | 0.005 | - | 50 | 7.5 |
Lead (Pb) | 0.01 | 0.015 | 50 | 400 |
Inorganic Mercury (Hg) | 0.006 | 0.002 | 0.004 | 0.2 |
Nickel (Ni) | 0.07 | 0.1 | 100 | 75 |
Remediation Methods | Technologies | Environment | Advantages | Limitations | Ref. |
---|---|---|---|---|---|
Physical |
| Aquatic |
|
| [64] |
| Terrestrial |
|
| [65] | |
Chemical |
| Aquatic |
|
| [66] |
| Terrestrial |
|
| [67] | |
Biological | Phytoremediation
| Aquatic |
|
| [68] |
Bioremediation:
| Terrestrial |
|
| [69] |
Microbial Strains | Heavy Metals | Removal Efficiency (%) | Initial Concentration (mg/L) | Experiment Duration | Treated Media | Reference |
---|---|---|---|---|---|---|
Bacteria | ||||||
Alteromonas macleodii | Pb Ni Cd | 73.8 54 53 | 200 | 10 h | Synthetic broth | [86] |
Cloacibacterium normanense | Ni | 85 | 48 | 2.5 h | Municipal wastewater | [87] |
Ochrobactrum intermedium | Pb Ni | 85.34 74.87 | 100 | 3 days | Aqueous solution | [88] |
Ochrobactrum ciceri | Pb Ni | 71.20 88.48 | 100 | 3 days | Aqueous solution | [88] |
Cutibacterium sp. | Pb | 35.19 | 170 | 7 days | Aqueous solution | [89] |
Lactobacillus plantarum | Cd Pb Ni Cr | 100 100 100 100 | - | 1 h | Battery-manufacturing effluent | [90] |
Bacillus megaterium | Pb Ni Cd | 10.54 73.02 24.68 | 3200 3200 3200 | 4 days | Aqueous solution | [91] |
Rhizopus stolonifera | Pb Ni Cd | 23.79 58.89 17.06 | 3200 3200 800 | 4 days | Aqueous solution | [91] |
Cupriavidus necator | Pb Cr | 63.56 81.32 | 0.247 1.82 | 5 days | Soil | [92] |
Pseudomonas putida | Pb Cr | 83.81 80.77 | 0.247 1.82 | 5 days | Soil | [92] |
Fungi | ||||||
Aspergillus niger | Cr Co As Pb Cd | 100 71.4 69 59 57 | 50 100 1 100 5 | 7 days | Wastewater | [93] |
Aspergillus fumigatus | Pb Cr Ni | 99 75 100 | 30 | 3 days | Aqueous solution | [94] |
Beauveria bassiana | Cd Cr Ni | 63.4 61.13 75 | 30 | 5 days | Aqueous solution | [95] |
Trichoderma harzianum | Cd Pb Ni | 98.63 84.50 69.07 | 2.19 2.69 - | 28 days | Wastewater | [96] |
Saccharomyces cerevisiae | Cd | 69.56 | 500 500 | 5 days | Contaminated soil | [97] |
Bacillus subtilis | Cd | 75.76 | 500 50 | 5 days | Contaminated soil | [97] |
Candida lipolytica | Pb | 30 | 1000 | 120 days | Synthetic wastewater | [98] |
Rhodotorula mucilaginosa | Pb | 25.2 40.6 32.6 25.24 | 500 1000 2000 2500 | 3 days | Aqueous solution | [99] |
Consortia of microorganisms | ||||||
Aspergillus fumigatus and Aspergillus terreus | Cd Cr Pb | 93.28 89.41 97.13 | - | 6 days | Tannery effluent | [100] |
Perenniporia subtephropora, Daldinia starbaeckii, Phanerochaete concrescens, Cerrena aurantiopora, Fusarium equiseti, Polyporales sp., Aspergillus niger, Aspergillus fumigatus, Trametes versicolor | As Cr | 62 42 | - | 100 days | Soil | [101] |
Paecilomyces lilacinus, Antrodia serialis, Penicillium cataractum | As Cr | 48 36 | - | 100 days | Soil | [101] |
Sphingomonas paucimobilis, Rhizobium radiobacter, Bacillus subtilis, Bacillus pumilus | Pb Cd Cr | 98.08 95.43 97.12 | 0.314 0.285 0.174 | 4 days | Industrial wastewater | [102] |
Plant Species | Heavy Metals | Removal Efficiency (%) | Initial Concentration (mg/L) | Experiment Duration | Treated Media | Reference |
---|---|---|---|---|---|---|
Sorghum bicolor | Ni | 97.28 | 25 | 20 min | Aqueous solution | [128] |
Cr | 99.8 | 5 | 30 min | |||
Helianthus annuus | Pb | 70.88 | 10 | 4 weeks | Contaminated soil | [129] |
Hydrangea paniculata | Pb | 50.65 | 10 | 4 weeks | Contaminated soil | [129] |
Echinochloa pyramidalis | Cd Ni Pb | 37.99 22.25 88.74 | 5 | 6 weeks | Soil contaminated with wastewater | [130] |
Ludwigia stolonifera | Cd Ni Pb | 48.04 32.3 84.29 | 5 | 6 weeks | Soil contaminated with wastewater | [130] |
Tagetes patula | Cd Cr Pb | 31.61 47.56 94.99 | 0.715 0.513 1.098 | 8 weeks | Contaminated river water | [131] |
Portulaca grandiflora | Cd Cr Pb | 55.94 18.52 92.81 | 0.715 0.513 1.098 | 8 weeks | Contaminated river water | [131] |
Bassica scoparia | Cd Cr Pb | 100 26.12 93.72 | 0.715 0.513 1.098 | 8 weeks | Contaminated river water | [131] |
Ricinus communis | Cr Cd Ni Pb | 34.48 99.89 48.27 53.43 | 0.002 0.019 0.014 0.018 | Not specified | Distillery sludge | [132] |
Eichhornia crassipes | Cr | 99.98 | 10.4749 | 3 h | Tannery effluent | [133] |
Lemmna minor | Cd Cr Ni Pb | 44.93 32.26 74.48 79.1 | 0.0227 0.5252 0.1117 0.2526 | 5 weeks | Industrial wastewater from tannery and battery industries | [134] |
Phragmites australis | Cd Cr Ni Pb | 43.3 51.2 55.8 45.7 | 0.079 0.142 0.088 0.060 | 2 weeks | Urban sewage mixed with industrial effluent | [135] |
Typha latifolia | Cd Cr Ni Pb | 39.7 45.6 51.1 40 | 0.079 0.142 0.088 0.060 | 2 weeks | Urban sewage mixed with industrial effluent | [135] |
Consortia of plants | ||||||
Phragmites australis and Typha latifolia | Cd Cr Ni Pb | 60 68.1 73.8 61 | 0.079 0.142 0.088 0.060 | 2 weeks | Urban sewage mixed with industrial effluent | [135] |
Echinochloa pyramidalis and Ludwigia stolonifera | Cd Ni Pb | 61.52 27.8 93.22 | 5 | 6 weeks | Soil contaminated with wastewater | [130] |
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Firincă, C.; Zamfir, L.-G.; Constantin, M.; Răut, I.; Jecu, M.-L.; Doni, M.; Gurban, A.-M.; Șesan, T.E. Innovative Approaches and Evolving Strategies in Heavy Metal Bioremediation: Current Limitations and Future Opportunities. J. Xenobiot. 2025, 15, 63. https://doi.org/10.3390/jox15030063
Firincă C, Zamfir L-G, Constantin M, Răut I, Jecu M-L, Doni M, Gurban A-M, Șesan TE. Innovative Approaches and Evolving Strategies in Heavy Metal Bioremediation: Current Limitations and Future Opportunities. Journal of Xenobiotics. 2025; 15(3):63. https://doi.org/10.3390/jox15030063
Chicago/Turabian StyleFirincă, Cristina, Lucian-Gabriel Zamfir, Mariana Constantin, Iuliana Răut, Maria-Luiza Jecu, Mihaela Doni, Ana-Maria Gurban, and Tatiana Eugenia Șesan. 2025. "Innovative Approaches and Evolving Strategies in Heavy Metal Bioremediation: Current Limitations and Future Opportunities" Journal of Xenobiotics 15, no. 3: 63. https://doi.org/10.3390/jox15030063
APA StyleFirincă, C., Zamfir, L.-G., Constantin, M., Răut, I., Jecu, M.-L., Doni, M., Gurban, A.-M., & Șesan, T. E. (2025). Innovative Approaches and Evolving Strategies in Heavy Metal Bioremediation: Current Limitations and Future Opportunities. Journal of Xenobiotics, 15(3), 63. https://doi.org/10.3390/jox15030063