Copper hydrophytoremediation by wetland macrophytes in semi-hydroponic and hydroponic mesocosms

Construction of a novel flavonol fluorescent probe for copper (II) ion detection and its application in actual samples

Copper is an essential trace element in the human body, and its level is directly related to many diseases. While the source of copper in human body is mainly intake from food, then the detection of copper ions (Cu2+) in food becomes crucial. Here, we synthesized a novel probe (E)-3-hydroxy-2-styryl-4H-benzo[h]chromen-4-one (NSHF) and explored the binding ability of NSHF for Cu2+ using nuclear magnetic resonance hydrogen spectroscopy (1H NMR), high-resolution mass spectrometry (HRMS), Job's plot method and density functional theory (DFT). NSHF shows the advantages of fast response time, good selectivity and high sensitivity for Cu2+. The fluorescence intensity ratio (F/F0) of NSHF shows a good linear relationship with the concentration of Cu2+ and the detection limit is 0.061 μM. NSHF was successfully applied to the detection of Cu2+ in real samples. In addition, a simple and convenient Cu2+ detection platform was constructed by combining NSHF with a smartphone and a UV lamp, which can realize the rapid detection of Cu2+. This work provides an effective tool for the real-time detection of Cu2+.

Phytobial remediation advances and application of omics and artificial intelligence: a review

Industrialization and urbanization increased the use of chemicals in agriculture, vehicular emissions, etc., and spoiled all environmental sectors. It causes various problems among living beings at multiple levels and concentrations. Phytoremediation and microbial association are emerging as a potential method for removing heavy metals and other contaminants from soil. The treatment uses plant physiology and metabolism to remove or clean up various soil contaminants efficiently. In recent years, omics and artificial intelligence have been seen as powerful techniques for phytobial remediation. Recently, AI and modeling are used to analyze large data generated by omics technologies. Machine learning algorithms can be used to develop predictive models that can help guide the selection of the most appropriate plant and plant growth-promoting rhizobacteria combination that is most effective at remediation. In this review, emphasis is given to the phytoremediation techniques being explored worldwide in soil contamination.

Phytoremediation of contaminated sediment combined with biochar: Feasibility, challenges and perspectives

The accumulation of contaminants in sediments is accelerated by human activities and poses a major threat to ecosystems and human health. In recent years, various remediation techniques have been developed for contaminated sediments. In this review, a bibliometric analysis of papers on sediment remediation indexed in the WOS database between 2009 and 2023 was conducted using VOSviewer. We describe the development of biochar and plants for sediment contaminant removal. However, the single processes of biochar remediation and phytoremediation can be impeded by (i) low efficiency, (ii) poor tolerance of plants towards pollutants, (iii) difficulty in biochar to degrade pollutants, and (iv) biochar aging causing secondary pollution. Fortunately, combination remediation, realized through the combination of biochar and plants, can overcome the shortcomings of their individual applications. Therefore, we suggest that the remediation of contaminants in sediments can be accomplished by combining biochar with macrophytes and considering multiple limiting factors. Here, we explore the challenges that co-remediation with biochar and macrophytes will face in achieving efficient and sustainable sediment remediation, including complex sediment environments, interaction mechanisms of biochar-macrophyte-microorganisms, emerging pollutants, and integrated life cycle assessments, which can provide references for combined biochar and plant remediation of sediments in the future.