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首页> 外文期刊>Water Quality, Exposure and Health >Water Quality Assessment of Some Freshwater Bodies Supporting Vegetation in and Around Chandigarh (India), Using Multivariate Statistical Methods
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Water Quality Assessment of Some Freshwater Bodies Supporting Vegetation in and Around Chandigarh (India), Using Multivariate Statistical Methods

机译:应用多元统计方法评估印度昌迪加尔及其周边地区一些支持植被的淡水水体的水质

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An increasing trend in water pollution of freshwater bodies through anthropogenic means is evident, and its impact is turning freshwater unsuitable for human consumption. In addition to physicochemical nature of such water, presence of the type of vegetation has been significant in labeling such bodies for different levels of pollution. Physicochemical parameters include important criteria like temperature, free carbon dioxide (CO_2), turbidity, total alkalinity, electrical conductivity, nitrate etc., which provide an idea for the portability of water for irrigation and drinking purposes. In this investigation, eight water bodies (76°46'45.96'' E, 30°44'01.19'' N) have been studied and categorized into different water quality indices as per permissible limits of WHO, ICMR, and ISI standards. The values of water quality index (WQI) at water bodies (ponds) S_1-S_8 were 46.12, 56.90, 79.96, 103.31, 120.39, 14.53, 29.47, and 30.58 respectively, which clearly indicated anthropogenic activities to different levels. The water bodies S_1-S_5 could be categorized as "D-E", and water at S_6-S_8 as "A-B" as per Central Pollution Control Board (CPCB) guidelines. Principal component analysis (PCA) has been applied to classify the water bodies into four different categories which produced the same results as WQI. Agglomerative cluster analysis (CA) was performed for delineating and grouping the similar pollution causing areas. The parameters like free CO_2, turbidity, total alkalinity, electrical conductivity and TDS were higher in Eichhornia crassipes infested water bodies than the one supporting growth of a stonewort (Chara corallina). Management strategies to save water from deterioration should be focused accordingly, keeping in view this information gathered.
机译:通过人为手段造成的淡水水体污染的增加趋势显而易见,其影响正在使淡水不适合人类消费。除了此类水的物理化学性质外,在标记此类物体的不同污染水平方面,植被类型的存在也很重要。理化参数包括重要标准,例如温度,游离二氧化碳(CO_2),浊度,总碱度,电导率,硝酸盐等,这为灌溉和饮用水的便携性提供了一个思路。在这项调查中,根据WHO,ICMR和ISI标准的允许限值,对八个水体(东经76°46'45.96'',北纬30°44'01.19'')进行了分类,并将其分为不同的水质指标。水体(池)S_1-S_8的水质指数(WQI)分别为46.12、56.90、79.96、103.31、120.39、14.53、29.47和30.58,清楚地表明了不同水平的人为活动。根据中央污染控制委员会(CPCB)的准则,水体S_1-S_5可以分类为“ D-E”,而水位S_6-S_8可以分类为“ A-B”。应用主成分分析(PCA)将水体分为四个不同类别,它们产生的结果与WQI相同。进行了聚类分析(CA),以划定和分组相似的污染源区域。凤眼莲感染的水体中的游离CO_2,浊度,总碱度,电导率和TDS等参数均高于石supporting(Chara Corallina)的生长。应相应地着眼于节约用水以防止水质恶化的管理策略,同时要注意收集到的信息。

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