Assessment of heavy metal pollution in Nigerian surface freshwaters and sediment: A meta-analysis using ecological and human health risk indices

Human health risk assessment from potentially toxic elements in the soils of Sudan: A meta-analysis

Potentially toxic elements (PTEs) in soils threaten human health through several exposure pathways. However, health risks posed by PTEs in soils in developing countries have not yet been comprehensively investigated. Thus, such countries lack important information that is needed to implement sustainable solutions. In this study, we assessed the human health risks for 10 PTEs, including arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), manganese (Mn), nickel (Ni), lead (Pb), and zinc (Zn), in Sudan focusing on soils affected by anthropogenic activities, such as industrial processes, gold mining, tannery, waste dumping, traffic (affecting roadsides), urban/rural agriculture, river, and coastal sediment land uses (LUs). For this purpose, we did a meta-analysis using 3430 PTE concentrations reported from 981 anthropogenically-affected soils in 76 publications between 1996 and 2024. Ingestion was the most common exposure pathway for both carcinogenic and non-carcinogenic PTEs. Hg and Mn were the main non-carcinogenic PTEs leading to adverse health effects in children in industrially-affected soils and coastal sediments, with average hazard quotient (HQ) and hazard index (HI) values >1. Cr and Ni caused the highest carcinogenic risk to children in all anthropogenically-affected soils as indicated by average incremental lifetime cancer risk values (ILCR >1 × 10-4). Further major cancer risks for children were caused by As in urban agricultural and industrial LUs, Cd in >70 % of all LUs, and Pb at industrial and waste dump sites. Adults were under high cancer risks due to Cd in waste dump (ILCR = 9.09 × 10-4) and Cr and Ni (ILCR >1 × 10-4) in >75 % of all LUs. Cd contributed >50 % and >70 % to ILCR for children and adults along roadsides, respectively. Our findings can guide future research on the links between soil PTEs and human health risks in developing countries. We recommend establishing effective management strategies to reduce risks to human health based on the presence of PTEs in Sudanese soils.

Review of mayflies (Insecta Ephemeroptera) as a bioindicator of heavy metals and microplastics in freshwater

Heavy metal and microplastic pollutions are prevalent in freshwater ecosystems, with many freshwater bodies being contaminated by one or both of these pollutants. Recent studies reported extreme detections of Cd, Pb and Zn, high concentrations of Cr, Pb and Cu and microplastics acting as vectors of pollutants, including heavy metals. Mayflies can serve as bioindicators of heavy metal contamination in freshwater ecosystems because changes in their community structure, physiology, and behaviour can reflect and help predict the concentrations of metals in these environments. This review discusses the ecological alterations induced by tissue metal concentration in mayflies and other macroinvertebrates. As sensitive taxa to heavy metal contamination, mayflies can reflect the impacts of this pollution through their ethology and relationship to the substrate, highlighting issues such as eutrophication, alterations in community structure, inhibitory effects and sediment toxicity. Mayflies are also highly affected by microplastic exposure, which leads to ingestion, bioaccumulation, biomagnification, habitat and community alteration, behavioural changes, physiology alteration and toxicity. Mayflies bioindication metrics for assessing the impact of heavy metals and microplastics include the examination of community alteration, functional feeding behaviour, molecular structure, dietary and toxicity impacts, bioaccumulation and biomagnification and biomarkers. Current challenges for the utilization of mayflies as bioindicators include temporal variations in sensitivity, lack of universally recognised protocols and need for standardised protocols for microplastic analysis. Additionally, the applicability of mayflies as bioindicators may vary across different ecosystems, emphasising the need for selecting suitable indicators that align with the unique characteristics of the ecosystem.

Health risks and pathological effects of heavy metals in Oreochromis mossambicus from Usuma River, Nigeria

Heavy metals environmental pollution has become a global menace requiring constant biomonitoring and concerted efforts towards its reduction. There are reports of heavy metals pollution of Usuma River, Gwagwalada, Federal Capital Territory, Nigeria. However, information on the direct and indirect health impacts of such pollution on inhabiting fish and on their human consumers are non-existent, especially in Oreochromis mossambicus. The analyses of the physicochemical parameters of Usuma River water, fish heavy metals, histopathological changes, and health risks were performed according to standard procedures. The physicochemical characteristics of the Usuma River water were within acceptable ranges. The Pb bioaccumulation at 2.5100 ± 0.42 mg/kg was significantly (p < 0.05) higher than the values recorded for Cd at 0.4267 ± 0.16 mg/kg and zinc at 0.6027 ± 0.02 mg/kg. Nevertheless, Pb and Cd bioaccumulated more than their recommended permissible levels. Human health risks assessment revealed no immediate carcinogenic risk at a target rate of between 1.2690 × 10-5 - 2.3530 × 10-5. The current heavy metals' concentration posed no long-term non-carcinogenic risk at a hazard index of less than one. This is because the target rate figure above 1.0 × 10-3 and the hazard index figure above one signifies great health risks. The recorded gills and hepatic cellular changes did not affect organ functionalities as their obtained degree of tissue change figures were all below 10 based on the protocol. Although there was a positive strong correlation between the water temperature and its biochemical oxygen demand as well as between the water dissolved oxygen content and gill cellular changes, a negative strong correlation existed between the water pH and its electrical conductivity and total dissolved solids. The findings highlighted the progressing volatility of heavy metals pollution dynamics within the study area that could pose great human health risks, if unchecked.

Utilizing machine learning to evaluate heavy metal pollution in the world's largest mangrove forest

The world's largest mangrove forest (Sundarbans) is facing an imminent threat from heavy metal pollution, posing grave ecological and human health risks. Developing an accurate predictive model for heavy metal content in this area has been challenging. In this study, we used machine learning techniques to model sediment pollution by heavy metals in this vital ecosystem. We collected 199 standardized sediment samples to predict the accumulation of eleven heavy metals using ten different machine learning algorithms. Among them, the extremely randomized tree model exhibited the best performance in predicting Fe (0.87), Cr (0.89), Zn (0.85), Ni (0.83), Cu (0.87), Co (0.62), As (0.68), and V (0.90), achieving notable R2 values. On the other hand, the random forest outperformed for predicting Cd (0.72) and Mn (0.91), whereas the decision tree model showed the best performance for Pb (0.73). The feature attribute analysis identified FeV, CrV, CuZn, CoMn, PbCd, and AsCd relationships resembled with correlation coefficients among them. Based on the established models, the prediction of the contamination factor of metals in sediments showed very high Cd contamination (CF ≥ 6). The Moran's I index for Cd, Cr, Pb, and As were 0.71, 0.81, 0.71, and 0.67, respectively, indicating strong positive spatial autocorrelation and suggesting clustering of similar contamination levels. Conclusively, this research provides a comprehensive framework for predicting heavy metal sediment pollution in the Sundarbans, identifying key areas needing urgent conservation. Our findings support the adoption of integrated management strategies and targeted remedial actions to mitigate the harmful effects of heavy metal contamination in this vital ecosystem.

Novel modified semi-carbonized fiber prepared using discarded clothes for derisking Cu(II) and Pb(II) contaminated water

We report a novel modified semi-carbonized fiber (CF) prepared using cotton and acrylic clothes for derisking contaminated water to realize the resource utilization of discarded clothes in wastewater treatment. In this study, amphoteric and auxiliary modifiers were used to modify CFs for preparing amphoteric and amphoteric-auxiliary CFs. The basic physicochemical properties of different modified CFs were determined, and the microscopic morphology of modified CFs was detected. The isothermal adsorption characteristics of Cu(II) and Pb(II) on different modified CFs were investigated by the batch method, and the effect mechanisms of temperature, pH, ionic strength, and material dose were compared. Physicochemical properties and microscopic morphology results proved that amphoteric and auxiliary modifiers were modified on the CF surface and changed the surface properties of CF. The adsorption capacities of Cu(II) and Pb(II) on modified CFs increased with the increase in equilibrium concentration of Cu(II) and Pb(II), and the isotherm was more suitable for Freundlich model fitting than that of the Langmuir model. The maximum adsorption capacities (qm) of Cu(II) and Pb(II) on different modified CFs were 60.72-81.26 mg/g and 102.58-161.72 mg/g, respectively, and presented the trend of amphoteric-auxiliary CFs > amphoteric CFs > CFs. Increasing pH and temperature and decreasing ionic strength and material dose were beneficial to Cu(II) and Pb(II) adsorption. The Cu(II) and Pb(II) adsorption process was a spontaneous, endothermic, and entropy-increasing reaction, and the adsorption rate was controlled by chemisorption. The adsorption amount of amphoteric-auxiliary CFs maintained about 65% of original materials after 3 times of regeneration. Electrostatic attraction, precipitation, complexation, and ion exchange were the main adsorption mechanisms. The cation exchange capacity and total pore volume of modified CFs were key to determining qm of Cu(II) and Pb(II).