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Sulfate (SO42-) is an essential anion in drinking water and a vital macronutrient for plant growth. However, elevated sulfate levels can impact ecosystem or human health and could be an important indicator of acid rock drainage or pollution. Therefore, monitoring SO42- sources and transport is important for water quality assessments. This study focused on exploring the sources and transformations of SO42- as well as estimating the proportional contribution of the potential SO42- pollutant sources to groundwater and surface water in a tropical river basin, the Densu River Basin. The study used major ions combined with stable sulfur and oxygen isotope compositions and a Bayesian isotope mixing model, MixSIAR. The major ion characteristics indicate that SO42- concentrations remain stable throughout the rainy and dry seasons but originate from diverse sources. The multi-isotope model (δ34SSO4, δ18OSO4) identified four potential SO42- sources: detergent, precipitation, sewage, and sulfate fertilizer. However, the δ34SSO4 and δ18OSO4 values of the fertilizer source signatures overlapped with those of precipitation and sewage. Nevertheless, the contributions from each source were disentangled using the MixSIAR model, which revealed sewage as the most dominant SO42- pollutant in the Densu Basin, accounting for ~47 % of sulfate in groundwater and ~ 56 % of sulfate in surface water. Sulfate fertilizer (~33 %) was the second most important source after sewage for groundwater, while detergent (~23 %) was the second most important source for surface water. The redox processes of bacterial sulfate reduction and sulfide oxidation were determined to have a minimal impact on the sulfur isotope fractionation within the basin. This study highlights the benefits of combining major ions, sulfur isotopes and the MixSIAR model for identifying sources of sulfate. This approach accounts for uncertainties in source contributions which allows for more robust and reliable apportionment of sulfate sources. The study emphasizes the need for effective waste management and pollution control measures to protect water quality and provides vital guidelines on how to partition sulfate sources on a large catchment scale and evidence for making pollution management decisions on water resources.

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Fertilizers increase agricultural productivity and farmers' income. However, intensive agriculture frequently overuses fertilizers, which in turn can contaminate surface and groundwater. In this study, hydrochemical and multi-isotope (δ15NNO3, δ18ONO3 and δ18OH2O) data have been combined to identify nitrate pollution sources in Ghana's Densu River Basin, trace the Nitrogen (N) biogeochemical processes in the basin and apportion the contribution of each pollution source. Surface water NO3- ranged from 0.3 to 10.6 mg/L (as N), while groundwater NO3- ranged from 0.9 to 34 mg/L. Hierarchical cluster analysis classified the water samples into three spatial categories: upstream, midstream, and downstream, reflecting river and land use patterns. The multi-isotope model considered five primary NO3- sources: atmospheric deposition, manure/sewage, NH4+ in fertilizers, other NO3- based fertilizers and soil N. Nitrification was identified as the major biogeochemical process upstream, whereas mixing of sources and denitrification dominate the midstream to downstream sections of the basin. Nitrate source apportioning using a MixSIAR model reveal that N fertilizers (40 %) and soil N (34 %) contribute the most to nitrate pollution upstream of the river. From the midstream to downstream sections, manure/sewage (43 %) become the dominant nitrate source, reflecting the transition from agriculture to peri-urban and urban land use. This study has shown that soil erosion and runoff contribute to nitrate pollution in the Densu River, at levels comparable to N fertilizers, and groundwater across the basin is impacted mainly by manure/sewage. The multi-isotope analyses allowed the partitioning of N sources in other ways not possible using only classical hydrochemical methods.

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Soil serves as a vast matrix for heavy metal accumulation and subsequent redistribution to critical aspects of the environment such as groundwater. Soil pollution study is essential for sustainable human health and ecosystem protection. This study provides vital insight into the fate, accumulation, interactions, and health risk posed by heavy metals in soil and groundwater by employing geochemical accumulation index (Igeo), risk assessment models and multivariate data analysis techniques such as principal component analysis (PCA), preference ranking organisation method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive aid (GAIA). The median Igeo estimates show moderate to strong Pb accumulation levels whilst all the other metals indicate uncontaminated to moderate levels. The PCA output point to anthropogenic origin of Pb and Cd in the Tano Basin and surrounding communities. PROMETHEE-GAIA results indicate that Pb, Cd, Zn and Fe accumulated in the soil matrix may potentially leach into the groundwater resources. The carcinogenic lifetime risks posed by Pb, Cd, and Ni metals to adults are within the tolerable acceptable risk and thus do not present an immediate danger in the study area. Due to the significant toxicity, bioaccumulation and biomagnification properties of Pb and Cd in the environment, areas associated with significant anthropogenic activities require regular monitoring and evaluation in order to ensure that these metals are consistently below the regulatory limits. This study has further elucidated the subject of heavy metal pollution and is therefore expected to enhance sustainable protection of the environment and human health.

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