Integrated approach of heavy metal pollution indices and complexity quantification using chemometric models in the Sirsa Basin, Nalagarh valley, Himachal Pradesh, India

Herojeet, Rajkumar; Rishi, Madhuri S.; Kishore, Naval

doi:10.1007/s11631-015-0075-1

Cited by 103 publications

(35 citation statements)

References 44 publications

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“…The HPI is also a risk assessment method that considers the composite effects of individual heavy metal on the overall water quality and suitability for drinking. Many researchers (Horton 1965;Brown et al 1970;Edet and Offiong 2002;Odukoya and Abimbola 2010;Herojeet et al 2015;Wagh et al 2018;Egbueri 2018Egbueri , 2020a have successfully employed HPI extensively in determining the overall quality of water based on heavy metal concentrations. The NIS (2007) drinking water quality standards were used for the…”

Section: Heavy Metal Pollution Index (Hpi)mentioning

confidence: 99%

Chemometric analysis for pollution source identification and human health risk assessment of water resources in Ojoto Province, southeast Nigeria

Egbueri

Mgbenu

2020

Appl Water Sci

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This paper quantified the level of heavy metals contamination, identified possible sources of pollution, and assessed the human health risks associated with drinking water resources in Ojoto Province, Nigeria. The study's gross findings revealed that the suitability of some water sources for consumption purposes in this province is questionable. Based on water quality index, 57.14% of the total samples are within acceptable limits, while 42.86% are unsuitable for drinking. It was observed that the northwestern and southern parts of the study area have more of deteriorated water quality. The health hazard index revealed that 25% of the samples predispose their consumers (both adult and children populations) to high chronic health risks. Moreover, heavy metal pollution index, contamination index, and probability of cancer risk (CR) revealed that about 25% of the total samples were unsuitable and off the CR standard acceptable range of ≤ 1 × 10 −6-1 × 10 −4. Correlation and component factor analyses linked the origin of major ions to geogenic processes and that of the heavy metals to both natural and anthropogenic processes. Cluster analysis divided the samples into two equal classes (50% each): poor and excellent quality waters. This study indicated that Pb is the priority pollutant impacting the water quality. The various assessments revealed that waters from hand-dug wells and deeper boreholes are the least contaminated and hence best suited for drinking than waters from springs, streams, and shallow wells.

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Section: Heavy Metal Pollution Index (Hpi)mentioning

confidence: 99%

Chemometric analysis for pollution source identification and human health risk assessment of water resources in Ojoto Province, southeast Nigeria

Egbueri

Mgbenu

2020

Appl Water Sci

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“…The quality of a river at any point reflects major influences, including the lithology of the basin, atmospheric inputs, climatic conditions and anthropogenic inputs (Bricker and Jones 1995;Reza and Singh 2010;Herojeet et al 2015b;Jung et al 2016). On the other hand, rivers play a major role in assimilation or transporting multitude of pollutants present in municipal and industrial wastewater and runoff from agricultural land (Qadir et al 2008;Wang et al 2013;Malik and Hashmi 2017).…”

Section: Introductionmentioning

confidence: 99%

Quality characterization and pollution source identification of surface water using multivariate statistical techniques, Nalagarh Valley, Himachal Pradesh, India

Herojeet¹,

Rishi

Lata

et al. 2017

Appl Water Sci

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Sirsa River flows through the central part of the Nalagarh valley, belongs to the rapid industrial belt of Baddi, Barotiwala and Nalagarh (BBN). The appraisal of surface water quality to ascertain its utility in such ecologically sensitive areas is need of the hour. The present study envisages the application of multivariate analysis, water utility class and conventional graphical representation to reveal the hidden factor responsible for deterioration of water quality and determine the hydrochemical facies and its evolution processes of water types in Nalagarh valley, India. The quality assessment is made by estimating pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness, major ions (Na ? and K ? ions for pre monsoon and EC during pre and post monsoon at few sites and approx 40% samples of BOD and TC for both seasons exceeds the permissible limits indicate organic contamination from human activities. Water quality classification for designated use indicates that maximum surface water samples are not suitable for drinking water source without conventional treatment. The result of piper trillinear and Chadha's diagram classified majority of surface water samples for both seasons fall in the fields of Ca 2? -Mg 2? -HCO 3 -water type indicating temporary hardness. PCA and CA reveal that the surface water chemistry is influenced by natural factors such as weathering of minerals, ion exchange processes and anthropogenic factors. Thus, the present paper illustrates the importance of multivariate techniques for reliable quality characterization of surface water quality to develop effective pollution reduction strategies and maintain a fine balance between the industrialization and ecological integrity.,

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“…Sediments are essential components of lakes, providing food for benthic organisms and accumulating multiple pollutants such as pesticides; additionally, sediments are the most important reservoirs of metals in aquatic systems [1,10,14]. Over the past three decades, metals in water and sediments of freshwater ecosystems have been the focus of interest of several researchers [15][16][17]. Therefore, the development of evaluation methods to monitor metal pollution is essential.…”

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confidence: 99%

Distribution Coefficient and Metal Pollution Index in Water and Sediments: Proposal of a New Index for Ecological Risk Assessment of Metals

Sedeño‐Díaz

López‐López

Mendoza-Martínez

et al. 2019

Water

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The Lake of Texcoco is a closed basin with soils that confer salinity, conductivity, and alkalinity to it. It has undergone a reduction in size, incorporation of wastewater, and short-term desiccation, and includes temporary wetlands interconnected during the rainy season, some of which receive treated wastewater. Sediments contain metals, thus affecting water quality. Five artificial lakes were studied, and 12 metals (As, Ba, Cd, Cu, Cr, Fe, Mg, Mn, Hg, Ni, Pb, and Zn) were monitored bimonthly in water and sediments from June 2015 to March 2018. The Metal Pollution Index (MPI) and the Distribution Coefficient (Kd) were computed. Fe and Cd were the most and least stable metals in sediments, respectively (mean Log(Kd) = 4.24 and 2.079). Based on Log(K d ), metals were ranked as Fe > Mn > Zn > Cu > Mg > Cr > Ni > Ba > Pb > Hg > As > Cd. Log(K d ) values < 3 and > 5 indicate that metals occur mainly in water and sediments, respectively. The Mean Distribution Coefficient Log(K d MPI ) is a novel index proposed to assess ecological risk from metals in a water body. This index allows determining the phase (liquid or solid) where metals predominate, negatively affecting either free-swimming or benthic organisms. Log(K d MPI ) values indicated that metals occur primarily in the liquid phase in all lakes studied.Water 2020, 12, 29 2 of 20 of metals derived from anthropogenic sources such as urban, agricultural, and industrial areas are discharged into aquatic environments [5], then transported through the water column and accumulated in sediments, thus posing an ecological risk to benthic organisms, fish, and other aquatic organisms, and ultimately affecting humans [8,12].Lakes are among the most vulnerable and fragile aquatic ecosystems, because they function as sinks for a wide range of dissolved and particulate substances [13]. Sediments are essential components of lakes, providing food for benthic organisms and accumulating multiple pollutants such as pesticides; additionally, sediments are the most important reservoirs of metals in aquatic systems [1,10,14]. Over the past three decades, metals in water and sediments of freshwater ecosystems have been the focus of interest of several researchers [15][16][17]. Therefore, the development of evaluation methods to monitor metal pollution is essential.

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Integrated approach of heavy metal pollution indices and complexity quantification using chemometric models in the Sirsa Basin, Nalagarh valley, Himachal Pradesh, India

Cited by 103 publications

References 44 publications

Chemometric analysis for pollution source identification and human health risk assessment of water resources in Ojoto Province, southeast Nigeria

Chemometric analysis for pollution source identification and human health risk assessment of water resources in Ojoto Province, southeast Nigeria

Quality characterization and pollution source identification of surface water using multivariate statistical techniques, Nalagarh Valley, Himachal Pradesh, India

Distribution Coefficient and Metal Pollution Index in Water and Sediments: Proposal of a New Index for Ecological Risk Assessment of Metals

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