Multivariate statistical analysis of heavy metal concentration in soils of Yelagiri Hills, Tamilnadu, India – Spectroscopical approach

Chandrasekaran, A.; Ravisankar, R.; Harikrishnan, N.; Satapathy, K. K.; Prasad, M. V. R.; Kanagasabapathy, K.

doi:10.1016/j.saa.2014.08.093

Cited by 189 publications

(89 citation statements)

References 27 publications

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“…assess the level of metal pollution in the sediments, based on the toxicity of heavy metals and the response of the environment (Chandrasekaran et al, 2015). The equation used was:…”

Section: Potential Ecological Risk Indexmentioning

confidence: 99%

“…where E i is the coefficient of the potential ecological hazard of each heavy metal; T i is the toxicity coefficient of each heavy metal (Chandrasekaran et al, 2015) (Table SM-3). The classification of sediments according to the values of f i (Chandrasekaran et al, 2015), PLI (Priju and Narayana, 2006), E i (Jiao et al, 2015), and RI (Song et al, 2015) appears in Table SM-4.…”

Section: Potential Ecological Risk Indexmentioning

confidence: 99%

“…The classification of sediments according to the values of f i (Chandrasekaran et al, 2015), PLI (Priju and Narayana, 2006), E i (Jiao et al, 2015), and RI (Song et al, 2015) appears in Table SM-4.…”

Section: Potential Ecological Risk Indexmentioning

confidence: 99%

“…The inhibition caused for each sample on growth and (Hakanson, 1980). For PLI: blue = no pollution; red = pollution (Chandrasekaran et al, 2015). For Ei and RI: blue = no pollution; green = moderate pollution; yellow= strong pollution; orange = very strong pollution; red = extremely strong pollution (Jiao et al, 2015).…”

Section: Multivariate Analysis 331 Correlation Between Chemical Anmentioning

confidence: 99%

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Pollution by metals and toxicity assessment using Caenorhabditis elegans in sediments from the Magdalena River, Colombia

Benítez

Flegal

Odigie

et al. 2016

Environmental Pollution

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a b s t r a c tThe Magdalena River is the most important river in Colombia, supplying over 70% of the population of fish and drinking water, and it also is the main river transportation way of the country. It receives effluents from multiple sources along its course such as contaminant agricultural and industrial discharges. To evaluate the toxicity profile of Magdalena River sediments through endpoints such as survival, locomotion, and growth, wild type strains of Caenorhabditis elegans were exposed to aqueous extracts of the sediments. To identify changes in gene expression, GFP transgenic strains were used as reporter genes. Physiological and biochemical data were correlated with metal concentration in the sediments, identifying patterns of toxicity along the course of the river. Levels of some metals such as Cd, Cu, and Ni were above TEC and PEC limits. Effects in survival, growth, and locomotion were observed in most of the samples, and changes in gene expression were evident in the genes mtl-2, sod-4, and gst-1 using fluorescence expression. Cadmium and lead were the metals which were primarily associated with sediment toxicity, and the sampling sites with the highest increased expression of stress response genes were Barrancabermeja and Girardot. However, the diverse nature of toxic profiles observed in C. elegans in the study area showed the pervasiveness of different types of discharges throughout the river system.

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“…assess the level of metal pollution in the sediments, based on the toxicity of heavy metals and the response of the environment (Chandrasekaran et al, 2015). The equation used was:…”

Section: Potential Ecological Risk Indexmentioning

confidence: 99%

Section: Potential Ecological Risk Indexmentioning

confidence: 99%

Section: Potential Ecological Risk Indexmentioning

confidence: 99%

Section: Multivariate Analysis 331 Correlation Between Chemical Anmentioning

confidence: 99%

See 2 more Smart Citations

Pollution by metals and toxicity assessment using Caenorhabditis elegans in sediments from the Magdalena River, Colombia

Benítez

Flegal

Odigie

et al. 2016

Environmental Pollution

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“…Total annual effective dose resulting from activity concentration of 226 Ra, 232 Th, and 40 K ranged from 0.39 to 2.9 (average 1.7) mSv y -1 , which is lower than the total average worldwide exposure to natural radiation sources of 2.4 mSv y -1 and higher than the part due to inhalation which is 1.26 mSv y -1 [6]. suggesting that their content in coal are mostly influenced and controlled by similar origin of sources [27,28].…”

Section: Assessment Of Radiological Hazardsmentioning

confidence: 99%

Lifetime Cancer Risk of Gamma Radioactivity Results from Smoking

Shousha

Ahmad

2016

Cancers Review

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Soil quality indices for metal(loid) contamination: An enzymatic perspective

et al. 2020

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Soil degradation by metal and metalloid (metal[loid]) contamination represents a widespread environmental threat. Most studies investigating soil metal(loid) contamination have disregarded the soil quality concept. Enzyme activities (EAs) are good soil quality indicators due to their direct connection to functions related to C, N, P, and S cycles and their sensitivity to metal(loid) contamination. This review (a) provides an overview of the development of soil quality indices (SQIs) based on EAs in metal(loid) contaminated soils, and (b) evaluates the effects of individual metal(loid)s and their combinations on the activities of the most common enzymes involved in the C, N, P, and S cycles. Four intracellular mechanisms dominate the inhibition of EAs by metal(loid)s: (a) transcription inhibition, (b) protein denaturation, (c) cell division inhibition, (d) cell membrane disruption. These mechanisms can also be further exacerbated in soil by nonspecific exoenzyme inhibition. The main EAs used as indicators for metal(loid) contaminated soils are dehydrogenase (DHA), arylsulfatase (ARY), urease (UA), acid phosphatase (Pacid), alkaline phosphatase (Palk), and catalase (CAT). These enzymes are sensitive to metal(loid) contamination, with DHA and ARY being the most sensitive indicators (62 and 56% inhibition, respectively, when averaged over all metal[loid] contamination levels). Other enzymes are inhibited by 32% (UA), 23% (Palk), 18% (Pacid), and 18% (CAT). We suggest principles for the development of SQIs considering biotic soil functions via the use of EAs. This review is the first presenting SQIs based on EAs for metal(loid) contaminated soils, and represents the first quantitative analysis of metal(loid) effects on EAs.

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Multivariate statistical analysis of heavy metal concentration in soils of Yelagiri Hills, Tamilnadu, India – Spectroscopical approach

Cited by 189 publications

References 27 publications

Pollution by metals and toxicity assessment using Caenorhabditis elegans in sediments from the Magdalena River, Colombia

Pollution by metals and toxicity assessment using Caenorhabditis elegans in sediments from the Magdalena River, Colombia

Lifetime Cancer Risk of Gamma Radioactivity Results from Smoking

Soil quality indices for metal(loid) contamination: An enzymatic perspective

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