Groundwater Quality Assessment, Fluoride Removal, and Health Risk Analysis
This research community focuses on evaluating the safety of drinking water and groundwater supplies, with a specific emphasis on removing fluoride and heavy metals to mitigate associated human health risks.
The work centers on statistical analysis of water quality parameters, including the development of quality indices and the application of multivariate methods to assess contamination levels. A significant portion of the literature addresses the remediation of fluoride through adsorption techniques and the evaluation of heavy metal exposure in surface and groundwater systems. Machine learning models are increasingly applied to predict water quality and assess health risks, while studies frequently examine the interplay between irrigation water use and human health outcomes. The research is heavily grounded in case studies from specific river basins and regions, particularly in India, China, and Nigeria, where groundwater contamination poses a direct threat to local populations.
The community is most prominent in research tracked for Fluorine, accounting for 5.6% of all Fluorine research and comprising 10,640 papers. It also represents a notable share of research on Magnesium (1.0%), Calcium (0.8%), Sodium (0.8%), and Chlorine (0.8%).
The community comprises 22,899 papers, with the highest publication volumes in Water, Environmental Science and Pollution Research, and Environmental Earth Sciences.
Recent work continues to apply machine learning and artificial intelligence for predicting groundwater quality and assessing health risks, alongside new studies on advanced materials for fluoride and phosphate removal from industrial leachates and natural water sources.