Pollution status and pollution source identification in the groundwater of Yar-Dalla in Wudil, Kano, Nigeria

EUREKA: Life Sciences Pub Date : 2023-07-28 DOI:10.21303/2504-5695.2023.003034

C. C. Onoyima, Nichodemus Emeka Onoyima

{"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}

引用次数: 0

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

查看原文本刊更多论文

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

最近人口增长和工业化的增加导致环境污染负荷增加，包括地下水，这是一种重要的淡水资源。采用水质指数(WQI)对研究区水质进行评价，采用主成分分析(PCA)和聚类分析(CA)等多元统计技术对可能的污染源进行识别。描述性统计结果表明，所有水样的pH、氯化物、碱度、硝酸盐和Cu均在WHO饮用水标准范围内，而Cl-、Cd、Cr和Pb分别有20%、30%、10%和40%的水样超过允许标准。CA将样本位置分为三个不同的集群:C1 (A、B、E、G、F和H)、C2 (C、J和I)和C3 (D)。C1的人为影响最大，其次是C2，而C3的人为影响最小。WQI显示C1为极差级(WQI>100)， C2为差级(51

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊