Umair Bin Nisar , Wajeeh ur Rehman , Saher Saleem , Kashif Taufail , Faizan ur Rehman , Muhammad Farooq , Siddique Akhtar Ehsan
{"title":"利用熵加权质量指数、统计方法和电阻率层析成像法评估巴基斯坦北部莫蒂村的水质","authors":"Umair Bin Nisar , Wajeeh ur Rehman , Saher Saleem , Kashif Taufail , Faizan ur Rehman , Muhammad Farooq , Siddique Akhtar Ehsan","doi":"10.1016/j.jconhyd.2024.104368","DOIUrl":null,"url":null,"abstract":"<div><p>In this study, twenty-two water samples were collected from boreholes (BH), and streams to evaluate drinking water quality, its distribution, identification of contamination sources and apportionment for Moti village, northern Pakistan. An atomic absorption spectrophotometer (AAS) is utilized to determine the level of heavy metals in water such as arsenic (As), zinc (Zn), lead (Pb), copper (Cu), cadmium (Cd), manganese (Mn), and ferrous (Fe). Groundwater chemistry and its quantitative driving factors were further explored using multivariate statistical methods, Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) models. Finally, a total of eight electrical resistivity tomographs (ERTs) were acquired across i) the highly contaminated streams; ii) the villages far away from contaminated streams; and iii) across the freshwater stream. In the Moti village, the mean levels (mg/l) of heavy metals in water samples were 7.2465 (As), 0.4971 (Zn), 0.5056 (Pb), 0.0422 (Cu), 0.0279 (Cd), 0.1579 (Mn), and 0.9253 (Fe) that exceeded the permissible limit for drinking water (such as 0.010 for As and Pb, 3.0 for Zn, 0.003 for Cd and 0.3 for Fe) established by the World Health Organization (<span>WHO, 2008</span>). The average entropy weighted water quality index (EWQI) of 200, heavy metal pollution index (HPI) of 175, heavy metal evaluation index (HEI) of 1.6 values reveal inferior water quality in the study area. Human health risk assessment, consisting of hazard quotient (HQ) and hazard index (HI), exceeded the risk threshold (>1),indicating prevention of groundwater usage. Results obtained from the PCA and PMF models indicated anthropogenic sources (i.e. industrial and solid waste) responsible for the high concentration of heavy metals in the surface and groundwater. The ERTs imaged the subsurface down to about 40 m depths and show the least resistivity values (<11 Ωm) for subsurface layers that are highly contaminated. However, the ERTs revealed relatively high resistivity values for subsurface layers containing fresh or less contaminated water. Filtering and continuous monitoring of the quality of drinking water in the village are highly recommended.</p></div>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessment of water quality using entropy-weighted quality index, statistical methods and electrical resistivity tomography, Moti village, northern Pakistan\",\"authors\":\"Umair Bin Nisar , Wajeeh ur Rehman , Saher Saleem , Kashif Taufail , Faizan ur Rehman , Muhammad Farooq , Siddique Akhtar Ehsan\",\"doi\":\"10.1016/j.jconhyd.2024.104368\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this study, twenty-two water samples were collected from boreholes (BH), and streams to evaluate drinking water quality, its distribution, identification of contamination sources and apportionment for Moti village, northern Pakistan. An atomic absorption spectrophotometer (AAS) is utilized to determine the level of heavy metals in water such as arsenic (As), zinc (Zn), lead (Pb), copper (Cu), cadmium (Cd), manganese (Mn), and ferrous (Fe). Groundwater chemistry and its quantitative driving factors were further explored using multivariate statistical methods, Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) models. Finally, a total of eight electrical resistivity tomographs (ERTs) were acquired across i) the highly contaminated streams; ii) the villages far away from contaminated streams; and iii) across the freshwater stream. In the Moti village, the mean levels (mg/l) of heavy metals in water samples were 7.2465 (As), 0.4971 (Zn), 0.5056 (Pb), 0.0422 (Cu), 0.0279 (Cd), 0.1579 (Mn), and 0.9253 (Fe) that exceeded the permissible limit for drinking water (such as 0.010 for As and Pb, 3.0 for Zn, 0.003 for Cd and 0.3 for Fe) established by the World Health Organization (<span>WHO, 2008</span>). The average entropy weighted water quality index (EWQI) of 200, heavy metal pollution index (HPI) of 175, heavy metal evaluation index (HEI) of 1.6 values reveal inferior water quality in the study area. Human health risk assessment, consisting of hazard quotient (HQ) and hazard index (HI), exceeded the risk threshold (>1),indicating prevention of groundwater usage. Results obtained from the PCA and PMF models indicated anthropogenic sources (i.e. industrial and solid waste) responsible for the high concentration of heavy metals in the surface and groundwater. The ERTs imaged the subsurface down to about 40 m depths and show the least resistivity values (<11 Ωm) for subsurface layers that are highly contaminated. However, the ERTs revealed relatively high resistivity values for subsurface layers containing fresh or less contaminated water. Filtering and continuous monitoring of the quality of drinking water in the village are highly recommended.</p></div>\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S016977222400072X\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S016977222400072X","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Assessment of water quality using entropy-weighted quality index, statistical methods and electrical resistivity tomography, Moti village, northern Pakistan
In this study, twenty-two water samples were collected from boreholes (BH), and streams to evaluate drinking water quality, its distribution, identification of contamination sources and apportionment for Moti village, northern Pakistan. An atomic absorption spectrophotometer (AAS) is utilized to determine the level of heavy metals in water such as arsenic (As), zinc (Zn), lead (Pb), copper (Cu), cadmium (Cd), manganese (Mn), and ferrous (Fe). Groundwater chemistry and its quantitative driving factors were further explored using multivariate statistical methods, Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) models. Finally, a total of eight electrical resistivity tomographs (ERTs) were acquired across i) the highly contaminated streams; ii) the villages far away from contaminated streams; and iii) across the freshwater stream. In the Moti village, the mean levels (mg/l) of heavy metals in water samples were 7.2465 (As), 0.4971 (Zn), 0.5056 (Pb), 0.0422 (Cu), 0.0279 (Cd), 0.1579 (Mn), and 0.9253 (Fe) that exceeded the permissible limit for drinking water (such as 0.010 for As and Pb, 3.0 for Zn, 0.003 for Cd and 0.3 for Fe) established by the World Health Organization (WHO, 2008). The average entropy weighted water quality index (EWQI) of 200, heavy metal pollution index (HPI) of 175, heavy metal evaluation index (HEI) of 1.6 values reveal inferior water quality in the study area. Human health risk assessment, consisting of hazard quotient (HQ) and hazard index (HI), exceeded the risk threshold (>1),indicating prevention of groundwater usage. Results obtained from the PCA and PMF models indicated anthropogenic sources (i.e. industrial and solid waste) responsible for the high concentration of heavy metals in the surface and groundwater. The ERTs imaged the subsurface down to about 40 m depths and show the least resistivity values (<11 Ωm) for subsurface layers that are highly contaminated. However, the ERTs revealed relatively high resistivity values for subsurface layers containing fresh or less contaminated water. Filtering and continuous monitoring of the quality of drinking water in the village are highly recommended.