Research Updates on Heavy Metal Phytoremediation: Enhancements, Efficient Post-harvesting Strategies and Economic Opportunities

Investigation of the incidence of heavy metals contamination in commonly used fertilizers applied to vegetables, fish ponds, and human health risk assessments

Overuse of fertilizers on agricultural lands and fish ponds may result in serious pollution problems, such as heavy metals that can enter the food chain and pose serious health problems. Due to this, the present study investigates the incidence of heavy metals in commonly used fertilizers and its association with heavy metals in vegetables, soil, fish species, and pond water. Samples were collected from different sites (fields and ponds) in district Kohat, where the application of fertilizers was common and control groups (no fertilizers used). Heavy metal analysis was carried out through a spectrophotometer. Results showed higher Cd and Cr concentrations in triple superphosphate (TSP), Cu and Pb in nitrogen, phosphorus, and potassium (NPK), while lower concentrations were found in gypsum. In vegetables (onion, tomato, brinjal, and potato) and associated soil, most of the heavy metals concentrations were significantly higher (P < 0.05) in fertilizer-applied sites than in the control. Also, the Cd concentration in potatoes and Pb level in all vegetables obtained from sites were greater than the WHO/FAO standard limit. In the case of fish species (Hypophthalmichthys molitrix and Cyprinus carpio) muscles and their habitat (water), all the understudy heavy metals were notably higher (P < 0.05) in fertilizer-applied sites (ponds) than the control group. Collectively, in all vegetables and muscles of fish species, the bioaccumulation factor was higher in sites compared to the control. The estimated daily intake (EDI) and target hazard quotient (THQ) values were also higher in fertilizer-applied sites (fields and ponds) than control. The health index (HI) value was > 1 in vegetables (onion, tomato, and potato) and fish muscles collected from different sites compared to the control. Thus, there is the possibility of severe health risks. The use of fertilizers must be carefully monitored in order to ensure that humans and animals are safe from exposure to heavy metals.

Role of plant growth-promoting rhizobacteria in boosting the phytoremediation of stressed soils: Opportunities, challenges, and prospects

Soil is considered as a vital natural resource equivalent to air and water which supports growth of the plants and provides habitats to microorganisms. Changes in soil properties, productivity, and, inevitably contamination/stress are the result of urbanisation, industrialization, and long-term use of synthetic fertiliser. Therefore, in the recent scenario, reclamation of contaminated/stressed soils has become a potential challenge. Several customized, such as, physical, chemical, and biological technologies have been deployed so far to restore contaminated land. Among them, microbial-assisted phytoremediation is considered as an economical and greener approach. In recent decades, soil microbes have successfully been used to improve plants' ability to tolerate biotic and abiotic stress and strengthen their phytoremediation capacity. Therefore, in this context, the current review work critically explored the microbial assisted phytoremediation mechanisms to restore different types of stressed soil. The role of plant growth-promoting rhizobacteria (PGPR) and their potential mechanisms that foster plants' growth and also enhance phytoremediation capacity are focussed. Finally, this review has emphasized on the application of advanced tools and techniques to effectively characterize potent soil microbial communities and their significance in boosting the phytoremediation process of stressed soils along with prospects for future research.

Influences of Biochar on Bioremediation/Phytoremediation Potential of Metal-Contaminated Soils

A number of anthropogenic and weathering activities accumulate heavy metals in soils, causing adverse effects on soil characteristics, microbial activity (diversity), agricultural practices, and underground aquifers. Controlling soil heavy metal pollution is difficult due to its persistence in soils, resulting in the deposition and transmission into the food web via agricultural food products, ultimately affecting human health. This review critically explores the potential for remediation of metal-contaminated soils using a biochar-based responsible approach. Plant-based biochar is an auspicious bio-based residue substance that can be used for metal-polluted soil remediation and soil improvement as a sustainable approach. Plants with rapid growth and increased biomass can meet the requirements for phytoremediation in large quantities. Recent research indicates significant progress in understanding the mechanisms of metal accumulation and contaminant movement in plants used for phytoremediation of metal-contaminated soil. Excessive contamination reduces plant biomass and growth, which has substantial hyperaccumulating possibilities and is detrimental to the phytoremediation process. Biochar derived from various plant sources can promote the growth and phytoremediation competence of native or wild plants grown in metal-polluted soil. Carbon-enriched biochar encourages native microbial growth by neutralizing pH and providing nutritional support. Thus, this review critically discusses the influence of plant and agricultural waste-based biochar on plant phytoremediation potential in metal-contaminated soils.

Phytoremediation of heavy metals and total petroleum hydrocarbon and nutrients enhancement of Typha latifolia in petroleum secondary effluent for biomass growth

Phytoremediation is an innovative tool which can be used for the treatment of industrial and agricultural wastewater. Typha latifolia (T. latifolia) is an aquatic plant used for phytoremediation of heavy metals (HMs) like cadmium (Cd), cobalt (Co), manganese (Mn), and TPH (total petroleum hydrocarbon) for the treatment of petroleum secondary effluent (PSE). During this experiment, the growth of T. latifolia in biomass, nutrient concentrations, and heavy metals were studied. The results indicated that T. latifolia was more tolerant to Cd, Co, and Mn due to its transfer index (TI) which was found to be greater than 2.9. The enrichment coefficients of the metals, Cd and Co present in the root were found to be higher than 3.31 to 2.56 and 5.35 to 3.55, respectively unlike the stem of T. latifolia. But, the enrichment coefficient of Mn was found to be 1.98 which was expected to be 3.51 at 75%. Similarly, the enrichment coefficients of all the metals, except for Co, in roots of T. latifolia were higher than 5.36. (TI) for Co (2.95) and Mn (2.55) which is better as compared to the enrichment coefficients of Cd (2.35) and TPH (3.45) in PSE. Thus, there is a possibility that PSE could be a source of important nutrients.

Modeling and optimizing the removal of cadmium by Sinapis alba L. from contaminated soil via Response Surface Methodology and Artificial Neural Networks during assisted phytoremediation with sewage sludge

The study was aimed to model and optimize the removal of cadmium from contaminated post-industrial soil via Sinapis alba L. by comparing two modeling approaches: Response Surface Methodology (RSM) and Artificial Neural Networks (ANN). The experimental design was done using the Box-Behnken Design method. In the RSM model, the quadratic model was shown to predict the closest results in comparison to our experimental data. For ANN approach, a two-layer Feed-Forward Back-Propagation Neural Network model was designed. The results showed that sewage sludge supplementation increased the efficiency of the Sinapis alba plant in removing Cd from the soil. After 28 days of exposure, the removal rate varied from 10.96% without any supplementation to 65.9% after supplementation with the highest possible (law allowed) dose of sewage sludge. The comparison proved that the prediction capability of the ANN model was much higher than that of the RSM model (adjusted R-square: 0.98, standard error of the Cd prediction removal: 0.85 ± 0.02). Thus, the ANN model could be used for the prediction of heavy metal removal during assisted phytoremediation with sewage sludge. Moreover, such approach could also be used to determinate the dose of sewage sludge that will ensure highest process efficiency.