Spatiotemporal variation of the nutrients and heavy metals in mangroves using multivariate statistical analysis, Gulf of Kachchh (India)

2021 ◽  
Vol 195 ◽  
pp. 110803 ◽  
Author(s):  
Parul Maurya ◽  
Rina Kumari
Keyword(s):  
Heavy Metals ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Spatiotemporal Variation ◽  
Multivariate Statistical ◽  
Gulf Of Kachchh

Assessment of Heavy Metals Content in the Proximity of a Contaminated Site From Cluj-Napoca (Romania)

2020 ◽  
Vol 65 (2) ◽  
pp. 17-37
Author(s):  
Georgiana Grosu ◽  
◽  
Carmen Andreea Roba ◽  
Ramona Bălc ◽  
Maria Lucia Bizău-Cârstea ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Sediment Contamination ◽  
Contaminated Site ◽  
Pollution Indices ◽  
Chemical Parameters ◽  
Multivariate Statistical ◽  
Water And Sediment ◽  
Physico Chemical

The present study was conducted in the proximity of a contaminated site from Cluj-Napoca city (Cluj County, Romania), where metal processing activities have been carried out for decades. Metal content and physico-chemical parameters were analyzed in soil, water and sediment samples, while organic matter (OM) and total organic carbon (TOC) was additionally analyzed for the soil samples. The sources of heavy metals were evaluated based on multivariate statistical analysis, while the soil and sediment contamination degree was assessed based on specific pollution indices. The calculated indices indicated a significant pollution with Cd and Pb, which may represent a risk if the area would become a residential area. Keywords: heavy metals, contaminated site, soil pollution indices, multivariate statistical analysis, Cluj-Napoca

Risk estimation and multivariate statistical analysis of the heavy metal content of drinking water samples

2018 ◽  
Vol 34 (10) ◽  
pp. 714-725
Author(s):  
Rajan Jakhu ◽  
Rohit Mehra
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Drinking Water ◽  
Statistical Analysis ◽  
Water Samples ◽  
Multivariate Statistical Analysis ◽  
Inductively Coupled Plasma ◽  
Principal Component ◽  
Multivariate Statistical ◽  
Drinking Water Samples

Drinking water samples of Jaipur and Ajmer districts of Rajasthan, India, were collected and analyzed for the measurement of concentration of heavy metals. The purpose of this study was to determine the sources of the heavy metals in the drinking water. Inductively coupled plasma mass spectrometry was used for the determination of the heavy metal concentrations, and for the statistical analysis of the data, principal component analysis and cluster analysis were performed. It was observed from the results that with respect to WHO guidelines, the water samples of some locations exceeded the contamination levels for lead (Pb), selenium (Se), and mercury (Hg), and with reference to the EPA guidelines, the samples were determined unsuitable for drinking because of high concentrations of Pb and Hg. Using multivariate statistical analysis, we determined that copper, manganese, arsenic, Se, and Hg were of anthropogenic origin, while Pb, copper, and cadmium were of geogenic origin. The present study reports the dominance of the anthropogenic contributions over geogenics in the studied area. The sources of the anthropogenic contaminants need to be investigated in a future study.

Multivariate statistical analysis of heavy metals in street dust of Baoji, NW China

2010 ◽  
Vol 173 (1-3) ◽  
pp. 744-749 ◽  
Author(s):  
Xinwei Lu ◽  
Lijun Wang ◽  
Loretta Y. Li ◽  
Kai Lei ◽  
Li Huang ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Street Dust ◽  
Multivariate Statistical ◽  
Nw China
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