{"title":"尼日利亚卡诺市乌迪尔市亚尔达拉地下水污染现状及污染源识别","authors":"C. C. Onoyima, Nichodemus Emeka Onoyima","doi":"10.21303/2504-5695.2023.003034","DOIUrl":null,"url":null,"abstract":"The recent increase in population growth and industrialization has resulted in higher pollution loads in the environment including the groundwater, which is a vital freshwater resource. Water Quality Index (WQI) was used to assess the water quality of the study area, while multivariate statistical techniques, including Principal Component Analysis (PCA) and Cluster Analysis (CA), were used to identify possible sources of the pollutants. The results of the descriptive statistics show that pH, Chloride, Alkalinity, Nitrate, and Cu are within the WHO standard for drinking water in all the water samples, while Cl-, Cd, Cr, and Pb exceeded the allowable standard in 20 %, 30 %, 10 %, and 40 % respectively of the water samples. CA group sample locations into three distinct clusters: C1 (A, B, E, G, F, and H), C2 (C, J, and I), and C3 (D). C1 has the highest anthropogenic influence followed by C2, while C3 has the least. WQI shows that C1 is in the extremely poor class (WQI>100), C2 is in the poor class (51<WQI<75), and C3 is in the good class (26<WQI<50). The PCA yielded 3 components which explained 72.98 % of the total variance in the data set. The first Component accounts for 38.85 %. Component 2 accounts for 19.76 % of the total variance while Component 3 accounts for 14.37 % of the total variance. The groundwater of the area is mainly impacted by anthropogenic factors such as agricultural activities, domestic waste, and vehicular/traffic input","PeriodicalId":11962,"journal":{"name":"EUREKA: Life Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pollution status and pollution source identification in the groundwater of Yar-Dalla in Wudil, Kano, Nigeria\",\"authors\":\"C. C. Onoyima, Nichodemus Emeka Onoyima\",\"doi\":\"10.21303/2504-5695.2023.003034\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recent increase in population growth and industrialization has resulted in higher pollution loads in the environment including the groundwater, which is a vital freshwater resource. Water Quality Index (WQI) was used to assess the water quality of the study area, while multivariate statistical techniques, including Principal Component Analysis (PCA) and Cluster Analysis (CA), were used to identify possible sources of the pollutants. The results of the descriptive statistics show that pH, Chloride, Alkalinity, Nitrate, and Cu are within the WHO standard for drinking water in all the water samples, while Cl-, Cd, Cr, and Pb exceeded the allowable standard in 20 %, 30 %, 10 %, and 40 % respectively of the water samples. CA group sample locations into three distinct clusters: C1 (A, B, E, G, F, and H), C2 (C, J, and I), and C3 (D). C1 has the highest anthropogenic influence followed by C2, while C3 has the least. WQI shows that C1 is in the extremely poor class (WQI>100), C2 is in the poor class (51<WQI<75), and C3 is in the good class (26<WQI<50). The PCA yielded 3 components which explained 72.98 % of the total variance in the data set. The first Component accounts for 38.85 %. Component 2 accounts for 19.76 % of the total variance while Component 3 accounts for 14.37 % of the total variance. The groundwater of the area is mainly impacted by anthropogenic factors such as agricultural activities, domestic waste, and vehicular/traffic input\",\"PeriodicalId\":11962,\"journal\":{\"name\":\"EUREKA: Life Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EUREKA: Life Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21303/2504-5695.2023.003034\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EUREKA: Life Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21303/2504-5695.2023.003034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pollution status and pollution source identification in the groundwater of Yar-Dalla in Wudil, Kano, Nigeria
The recent increase in population growth and industrialization has resulted in higher pollution loads in the environment including the groundwater, which is a vital freshwater resource. Water Quality Index (WQI) was used to assess the water quality of the study area, while multivariate statistical techniques, including Principal Component Analysis (PCA) and Cluster Analysis (CA), were used to identify possible sources of the pollutants. The results of the descriptive statistics show that pH, Chloride, Alkalinity, Nitrate, and Cu are within the WHO standard for drinking water in all the water samples, while Cl-, Cd, Cr, and Pb exceeded the allowable standard in 20 %, 30 %, 10 %, and 40 % respectively of the water samples. CA group sample locations into three distinct clusters: C1 (A, B, E, G, F, and H), C2 (C, J, and I), and C3 (D). C1 has the highest anthropogenic influence followed by C2, while C3 has the least. WQI shows that C1 is in the extremely poor class (WQI>100), C2 is in the poor class (51
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