A modified indexing approach for assessment of heavy metal contamination in Deepor Beel, India. (November 2019)
- Record Type:
- Journal Article
- Title:
- A modified indexing approach for assessment of heavy metal contamination in Deepor Beel, India. (November 2019)
- Main Title:
- A modified indexing approach for assessment of heavy metal contamination in Deepor Beel, India
- Authors:
- Dash, Siddhant
Borah, Smitom Swapna
Kalamdhad, Ajay - Abstract:
- Graphical abstract: Highlights: Water quality samples from Deepor Beel were analysed for 7 different heavy metals: Cu, Mg, Mn, Fe, Cr, Cd and Pb. Spatial and temporal plots indicated heavy metal contamination of Deepor Beel. Heavy metal index (HMI) was developed using principal components from principal component analysis. Proposed HMI was compared with the existing heavy metal pollution indices. HMI proved to be a more effective tool as compared to the existing HPI model. Abstract: In the present study, spatial and temporal variability of the heavy metals were investigated for Deepor Beel, India and a modified indexing approach for heavy metal contamination was proposed based on the statistical analyses of the monitored values. Water samples from 23 monitoring stations were collected for a period of one year and subjected to analysis for 7 different heavy metals (Mg, Cr, Cd, Fe, Mn, Cu, and Pb). The observed water quality dataset was first subjected to hierarchical clustering (HCA), which categorized the 23 monitoring locations into 3 statistically independent clusters based on the site similarities i.e. Low pollution (LP), High pollution (HP) and Moderate pollution (MP) respectively. Principal component analysis (PCA) technique was then applied to the three independent clusters to obtain principal components (PCs). These PCs were employed for calculating the weights of each component, from which the proposed heavy metal index (HMI) was estimated. The overall HMI value forGraphical abstract: Highlights: Water quality samples from Deepor Beel were analysed for 7 different heavy metals: Cu, Mg, Mn, Fe, Cr, Cd and Pb. Spatial and temporal plots indicated heavy metal contamination of Deepor Beel. Heavy metal index (HMI) was developed using principal components from principal component analysis. Proposed HMI was compared with the existing heavy metal pollution indices. HMI proved to be a more effective tool as compared to the existing HPI model. Abstract: In the present study, spatial and temporal variability of the heavy metals were investigated for Deepor Beel, India and a modified indexing approach for heavy metal contamination was proposed based on the statistical analyses of the monitored values. Water samples from 23 monitoring stations were collected for a period of one year and subjected to analysis for 7 different heavy metals (Mg, Cr, Cd, Fe, Mn, Cu, and Pb). The observed water quality dataset was first subjected to hierarchical clustering (HCA), which categorized the 23 monitoring locations into 3 statistically independent clusters based on the site similarities i.e. Low pollution (LP), High pollution (HP) and Moderate pollution (MP) respectively. Principal component analysis (PCA) technique was then applied to the three independent clusters to obtain principal components (PCs). These PCs were employed for calculating the weights of each component, from which the proposed heavy metal index (HMI) was estimated. The overall HMI value for Deepor Beel was found to be 123.52, which classified the water in Deepor Beel as "Poor". Leaching from the contaminated landfill in the proximity to the wetland was found to be a primary source of contamination with respect to heavy metals. The efficacy of HMI was verified by comparing it with the existing heavy metal pollution index (HPI), contamination index (CI) and heavy metal evaluation index (HEI). Results of this study indicate HMI to be a more effective and reliable tool for water quality assessment with respect to heavy metal contamination. … (more)
- Is Part Of:
- Ecological indicators. Volume 106(2019)
- Journal:
- Ecological indicators
- Issue:
- Volume 106(2019)
- Issue Display:
- Volume 106, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 106
- Issue:
- 2019
- Issue Sort Value:
- 2019-0106-2019-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-11
- Subjects:
- Water quality -- Heavy metals -- Statistical tools -- HPI -- HMI -- CI
Environmental monitoring -- Periodicals
Environmental management -- Periodicals
Environmental impact analysis -- Periodicals
Environmental risk assessment -- Periodicals
Sustainable development -- Periodicals
333.71405 - Journal URLs:
- http://www.sciencedirect.com/science/journal/1470160X/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ecolind.2019.105444 ↗
- Languages:
- English
- ISSNs:
- 1470-160X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3648.877200
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14801.xml