Musaab A.A. Mohammed , Norbert P. Szabó , Elamin D. Suliman , Magboul M.S. Siddig , Mohammed N.M. Hassan , Péter Szűcs
{"title":"苏丹努比亚含水层地下水污染物对人类健康风险的综合评估:结合来源分配和概率分析","authors":"Musaab A.A. Mohammed , Norbert P. Szabó , Elamin D. Suliman , Magboul M.S. Siddig , Mohammed N.M. Hassan , Péter Szűcs","doi":"10.1016/j.envc.2025.101176","DOIUrl":null,"url":null,"abstract":"<div><div>Groundwater contamination is a significant global challenge, particularly in arid and semi-arid regions where groundwater is a primary source for drinking and irrigation. This contamination is closely associated with human health risks, potentially leading to severe diseases and long-term health consequences. In this study, the groundwater quality of the Nubian Aquifer System (NAS) in the Shendi area, Sudan, is assessed to evaluate health risks linked to nitrogen compounds (NO₂, NO₃, NH₃) and fluoride (F). The analysis integrates self-organizing maps (SOM), principal component analysis (PCA), and Monte Carlo-based health risk simulations. SOM analysis revealed distinct clustering patterns in groundwater samples, identifying three major hydrochemical trends. PCA indicated that elevated NO₃ concentrations were localized, primarily associated with agricultural runoff, while NO₂ and NH₃ reflected pollution from both agriculture and wastewater. High fluoride concentrations were linked to geogenic sources, particularly water-rock interactions with fluorine-bearing minerals. The Monte Carlo simulation assessed probabilistic health risks, revealing higher mean hazard quotients (HQs) and hazard index (HI) values for children compared to adults. Children’s mean HI of 1.06 significantly exceeds the safe threshold, indicating potential non-carcinogenic health hazards. Sobol sensitivity analysis identified the most influential parameters in shaping health risks, including average exposure time, body weight, and exposure duration, with strong parameter interactions amplifying these effects. Among contaminants, NO₃ and F contributed the most to cumulative HI values. These findings underscore the urgent need for targeted interventions, such as advanced water treatment, stricter pollution controls, and public health awareness programs to mitigate groundwater contamination and protect vulnerable populations.</div></div>","PeriodicalId":34794,"journal":{"name":"Environmental Challenges","volume":"20 ","pages":"Article 101176"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated assessment of human health risks from groundwater pollutants in Nubian Aquifer, Sudan: Combining source apportionment and probabilistic analysis\",\"authors\":\"Musaab A.A. Mohammed , Norbert P. Szabó , Elamin D. Suliman , Magboul M.S. Siddig , Mohammed N.M. Hassan , Péter Szűcs\",\"doi\":\"10.1016/j.envc.2025.101176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Groundwater contamination is a significant global challenge, particularly in arid and semi-arid regions where groundwater is a primary source for drinking and irrigation. This contamination is closely associated with human health risks, potentially leading to severe diseases and long-term health consequences. In this study, the groundwater quality of the Nubian Aquifer System (NAS) in the Shendi area, Sudan, is assessed to evaluate health risks linked to nitrogen compounds (NO₂, NO₃, NH₃) and fluoride (F). The analysis integrates self-organizing maps (SOM), principal component analysis (PCA), and Monte Carlo-based health risk simulations. SOM analysis revealed distinct clustering patterns in groundwater samples, identifying three major hydrochemical trends. PCA indicated that elevated NO₃ concentrations were localized, primarily associated with agricultural runoff, while NO₂ and NH₃ reflected pollution from both agriculture and wastewater. High fluoride concentrations were linked to geogenic sources, particularly water-rock interactions with fluorine-bearing minerals. The Monte Carlo simulation assessed probabilistic health risks, revealing higher mean hazard quotients (HQs) and hazard index (HI) values for children compared to adults. Children’s mean HI of 1.06 significantly exceeds the safe threshold, indicating potential non-carcinogenic health hazards. Sobol sensitivity analysis identified the most influential parameters in shaping health risks, including average exposure time, body weight, and exposure duration, with strong parameter interactions amplifying these effects. Among contaminants, NO₃ and F contributed the most to cumulative HI values. These findings underscore the urgent need for targeted interventions, such as advanced water treatment, stricter pollution controls, and public health awareness programs to mitigate groundwater contamination and protect vulnerable populations.</div></div>\",\"PeriodicalId\":34794,\"journal\":{\"name\":\"Environmental Challenges\",\"volume\":\"20 \",\"pages\":\"Article 101176\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Challenges\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667010025000952\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Challenges","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667010025000952","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Environmental Science","Score":null,"Total":0}
Integrated assessment of human health risks from groundwater pollutants in Nubian Aquifer, Sudan: Combining source apportionment and probabilistic analysis
Groundwater contamination is a significant global challenge, particularly in arid and semi-arid regions where groundwater is a primary source for drinking and irrigation. This contamination is closely associated with human health risks, potentially leading to severe diseases and long-term health consequences. In this study, the groundwater quality of the Nubian Aquifer System (NAS) in the Shendi area, Sudan, is assessed to evaluate health risks linked to nitrogen compounds (NO₂, NO₃, NH₃) and fluoride (F). The analysis integrates self-organizing maps (SOM), principal component analysis (PCA), and Monte Carlo-based health risk simulations. SOM analysis revealed distinct clustering patterns in groundwater samples, identifying three major hydrochemical trends. PCA indicated that elevated NO₃ concentrations were localized, primarily associated with agricultural runoff, while NO₂ and NH₃ reflected pollution from both agriculture and wastewater. High fluoride concentrations were linked to geogenic sources, particularly water-rock interactions with fluorine-bearing minerals. The Monte Carlo simulation assessed probabilistic health risks, revealing higher mean hazard quotients (HQs) and hazard index (HI) values for children compared to adults. Children’s mean HI of 1.06 significantly exceeds the safe threshold, indicating potential non-carcinogenic health hazards. Sobol sensitivity analysis identified the most influential parameters in shaping health risks, including average exposure time, body weight, and exposure duration, with strong parameter interactions amplifying these effects. Among contaminants, NO₃ and F contributed the most to cumulative HI values. These findings underscore the urgent need for targeted interventions, such as advanced water treatment, stricter pollution controls, and public health awareness programs to mitigate groundwater contamination and protect vulnerable populations.