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.

Pollution indices and correlation of heavy metals contamination in the groundwater around brick kilns in Jammu and Kashmir, India.

The present investigation focuses on assessing the water quality of groundwater surrounding brick kilns in the Jammu district of Jammu and Kashmir (J&K). At 43 different brick kiln sites in both north and south regions of Jammu, concentrations of heavy metals were measured using established techniques. The elements zinc, copper, iron, lead, cadmium, nickel, and manganese were analyzed utilizing an Atomic Absorption Spectrophotometer (AAS). The pollution load index value was consistently below unity across all sites, suggesting an absence of pollution and making the water suitable for consumption. The average concentrations, listed in ascending order, were found to be 0.38 mg/L for copper, 0.31 mg/L for zinc, 0.01 mg/L for iron, and 0.09 mg/L for manganese. Notably, concentrations of lead, cadmium, and nickel were found below the detectable levels. Evaluation of contamination factors revealed the sequence Cu > Fe > Zn > Mn, while the geo accumulation index followed the sequence Cu > Fe > Mn > Zn. Comparison of these findings with the established standards of World Health Organization and Bureau of Indian Standards indicated that the recorded ranges were within permissible limits. The study's outcomes suggest that heavy metal emissions from brick kilns may not significantly impact the quality of groundwater. Elevated copper levels found near brick kilns were likely to result from plumbing materials in the study area. Iron and manganese in groundwater seems to have geo-genic origin and not emission-related. This research represents a foundational step in examining groundwater contamination by heavy metals specifically in the neighborhood of brick kilns in Jammu district. It contributes to the establishment of a comprehensive database and serves as a reference point for future studies. Additionally, the study recommends regular monitoring of groundwater to ensure the maintenance of drinking water quality.