article · Environmental Geochemistry and Health
Groundwater contamination by fluoride and nitrate was investigated across two agricultural regions in Ghana's Birimian province. Analysis of water samples revealed predominantly alkaline conditions, with fluoride levels reaching up to 1.5 milligrams per litre and nitrate concentrations surpassing 500 milligrams per litre in certain locations. While standard pollution indices classified between roughly 82 and 94 percent of water samples as safe for human consumption, health risk assessments identified potential hazards ranging from low to very high. Nitrate presented a sixfold higher oral exposure threat than fluoride. Spatial mapping, correlation analysis, and artificial neural network modelling demonstrated that fluoride concentrations stem primarily from natural geological formations in central and southern zones. Conversely, elevated nitrate levels in northern areas were strongly linked to agricultural inputs, showing the influence of human activities on regional groundwater quality.
Contaminated groundwater poses serious risks to rural populations relying on untreated drinking sources. Identifying whether toxic contaminants like nitrate and fluoride originate from agricultural fertilisers or natural rock minerals enables regional authorities to pinpoint specific pollution hotspots. This knowledge helps direct targeted water purification efforts and farming interventions to protect public health and support safe rural water supplies.
The combined mapping, index calculation, and artificial neural network modelling framework could be adapted by environmental monitoring agencies, municipal water authorities, and water remediation firms to guide regional water management. Because the work remains an observational field study paired with predictive models, practical deployment would require developing the modelling approach into validated decision-support software or tailored monitoring toolkits for field operators.
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Increasing global reports of fluoride (F−) and nitrate (NO3−) contamination in groundwater highlight the urgency of identifying pollution hotspots to safeguard public health. This study investigates groundwater quality in two agricultural regions of Ghana’s Birimian province, filling a vital research gap. This study utilized a diverse set of tools, including physicochemical analyses, violin plot visualizations, the Pollution Index of Groundwater (PIG), the Water Pollution Index (WPI), health risk assessments, Pearson’s correlation analysis, and artificial neural network modeling. These approaches evaluated the key factors affecting groundwater quality, identified contamination sources and hotspots, and assessed associated human health risks. Results revealed predominantly alkaline groundwater (pH 7–9), with F− ranging from 0.0 to 1.5 mg/L and NO3− exceeding 500 mg/L in some areas. The PIG and WPI rated 81.94–94.44% of samples suitable for consumption, with mean scores of 0.54 and 0.51, respectively, highlighting NO3−, pH, and K+ as primary quality influencers. Violin plots showed multimodal distributions in TDS, NO3−, Ca2+, and Mg2+, suggesting complex hydrogeochemical dynamics. Health risk assessments indicated oral exposure risks ranging from low to very high, with NO3− posing a sixfold greater threat than F−. Spatial analysis tied F− contamination in central and southern areas to geological formations, while higher NO3− in the northern part aligned with agricultural activities. Correlation analysis and neural network modeling confirmed the geogenic origin of F− whereas the mixed sources of NO3− strongly tied to anthropogenic inputs. These insights urge targeted remediation and offer a scalable framework for global groundwater challenges.
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DOI: 10.1007/s10653-025-02453-5
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