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.

scholarly journals Ultra-portable, smartphone-based spectrometer for heavy metal concentration measurement in drinking water samples

2021 ◽  
Vol 11 (11) ◽  
Author(s):  
Satyam Srivastava ◽  
Vinay Sharma
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Drinking Water ◽  
Data Collection ◽  
Metal Concentration ◽  
Water Samples ◽  
Heavy Metal Concentration ◽  
Concentration Measurement ◽  
Visible Radiation ◽  
Drinking Water Samples

AbstractHeavy metals are very toxic and hazardous for human health. Onsite screening of heavy metal contaminated samples along with location-based automation data collection is a tedious job. Traditionally high-end equipment’s such as gas chromatography mass spectrometer (GC–MS) and atomic absorption spectrometers have been used to measure the concentration of different heavy metals in water samples but most of them are costly, bulky, and time consuming, and requires expert human intervention. This manuscript reports an ultra-portable, rapid, cost-effective, and easy-to-use solution for onsite heavy metal concentration measurement in drinking water samples. Presented solution combines off-the-shelf available chemical kits for heavy metal detection and developed spectrometer-based readout for concentration prediction, quality judgment, and automatic data collection. Two chemical kits for copper and iron detection have been imported form Merck and have been used for overall training and testing. The developed spectrometer has capability to work with smartphone-based android app and also can work in standalone mode. The developed spectrometer uses white light-emitting diode as a source and commercially imported spectral sensor (AS7262) for visible radiation reception. A low-power sub-GHZ-based wireless embedded platform has been developed and interfaced with source and detector. A power management module also has been designed to monitor the battery status and also to generate low battery indication. Overall modules has been packaged in custom designed enclosure to avoid external light interference. The developed system has been trained using standard buffer samples with known heavy metal concentrations and further tested for water samples collected from institute colony and nearby villages. The obtained results have been validated with commercially imported system from HANNA instruments, and it has been observed that developed system has shown excellent accuracy to predict heavy metal concentration (tested for Fe and Cu) in water samples.

scholarly journals Application of Multivariate Statistical Analysis to Identify Water Sources in A Coastal Gold Mine, Shandong, China

2019 ◽  
Vol 11 (12) ◽  
pp. 3345 ◽  
Author(s):  
Guowei Liu ◽  
Fengshan Ma ◽  
Gang Liu ◽  
Haijun Zhao ◽  
Jie Guo ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Statistical Analysis ◽  
Water Samples ◽  
Multivariate Statistical Analysis ◽  
Water Inrush ◽  
Principal Component ◽  
Component Analysis ◽  
Gold Mine ◽  
Mining Operations ◽  
Multivariate Statistical

Submarine mine water inrush has become a problem that must be urgently solved in coastal gold mining operations in Shandong, China. Research on water in subway systems introduced classifications for the types of mine groundwater and then established the functions used to identify each type of water sample. We analyzed 31 water samples from −375 m underground using multivariate statistical analysis methods. Cluster analysis combined with principle component analysis and factor analysis divided water samples into two types, with one type being near the F3 fault. Principal component analysis identified four principle components accounting for 91.79% of the total variation. These four principle components represented almost all the information about the water samples, which were then used as clustering variables. A Bayes model created by discriminant analysis demonstrated that water samples could also be divided into two types, which was consistent with the cluster analysis result. The type of water samples could be determined by placing Na+ and CHO3− concentrations of water samples into Bayes functions. The results demonstrated that F3, which is a regional fault and runs across the whole Xishan gold mine, may be the potential channel for water inrush, providing valuable information for predicting the possibility of water inrush and thus reducing the costs of the mining operation.

Heavy Metal Pollution of Soil around the Gangue Hill: A Case Study from Zhuxiangzhuang Coal Mine, Northern Anhui Province, China

2011 ◽  
Vol 356-360 ◽  
pp. 114-118
Author(s):  
Xiang Hong Liu ◽  
Lin Hua Sun ◽  
Song Chen
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Statistical Analysis ◽  
Coal Mine ◽  
Multivariate Statistical Analysis ◽  
Anhui Province ◽  
Multivariate Statistical ◽  
And Cluster Analysis ◽  
Cu And Zn

Heavy metal concentrations of soils around two gangue hills from Zhuxiangzhuang coal mine, northern Anhui province, China had been determined by using X-Ray Fluorescence, and the calculation of enrich factor and index of geo-accumulation, as well as multivariate statistical analysis (including principle component analysis and cluster analysis) had been brought out to light: V, Cr, Fe, Cu and Zn of soils are unpolluted when normalize to soil environmental background value of China. However, when normalized to their minimum concentrations, Zn is light pollution. Two sources of heavy metals have been identified by using multivariate statistical analysis, including lithogenic (V and Fe) and anthropogenic (Cr, Cu and Zn). The soils from the area between two gauge hills have the highest degrees of heavy metals pollution relative to other areas, implying that the method in the Zhuxianzhuang coal mine is useful for environmental protection.

scholarly journals Evaluation of the Radiological and Chemical Risk for Public Health from Flour Sample Investigation

2021 ◽  
Vol 11 (8) ◽  
pp. 3646
Author(s):  
Francesco Caridi ◽  
Giuseppe Acri ◽  
Alberto Belvedere ◽  
Vincenza Crupi ◽  
Maurizio D’Agostino ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Metal Contamination ◽  
Inductively Coupled Plasma ◽  
Heavy Metal Contamination ◽  
Specific Activity ◽  
Single Type ◽  
Multivariate Statistical ◽  
Inductively Coupled

Flour investigation, in terms of physical and chemical pollutants and mineral content, is of great interest, in view of its high consumption for nutritional purposes. In this study, eleven types of flour (five samples for each one), coming from large retailers and employed by people for different cooking food purposes, were investigated through high-purity germanium (HPGe) gamma spectrometry, in order to estimate natural (40K) and anthropogenic (137Cs) radioisotope specific activity and thus, to assess the radiological risk due to the flour ingestion. Inductively-coupled plasma mass spectrometry (ICP-MS) and inductively-coupled plasma emission spectroscopy (ICP-OES) were also employed to evaluate any possible heavy metal contamination and the mineral composition, and to perform multivariate statistical analysis to deduce the flour authenticity. The evaluation of dose levels due to flour ingestion was performed, for the age category higher than 17 years, taking into account the average yearly consumption in Italy and assuming this need to be satisfied from a single type of flour as a precaution. All obtained results are under the allowable level set by Italian legislation (1 mSv y−1), thus excluding the risk of ionizing radiation effects on humans. As far as heavy metal contamination is concerned, Cd and Pb concentrations turned out to be lower than the threshold values, thus excluding their presence as pollutants. Finally, the multivariate statistical analysis allowed to unambiguously correlate flour samples to their botanical origin, according to their elemental concentrations.

Statistical Analsysis to Evaluate Heavy Metal Pollution in the Air Obatained by Moss Technique in Hanoi and its Surrounding Region

2019 ◽  
Vol 29 (3SI) ◽  
pp. 411
Author(s):  
N. H. Quyet ◽  
Le Hong Khiem ◽  
V. D. Quan ◽  
T. T. T. My ◽  
M. V. Frontasieva ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Statistical Analysis ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Principal Component ◽  
Multivariate Statistical ◽  
Five Factors ◽  
Heavy Metal Elements ◽  
Surrounding Areas ◽  
Potential Pollution

The aim of this paper was the application of statistical analysis including principal component analysis to evaluate heavy metal pollution obtained by moss technique in the air of Ha Noi and its surrounding areas and to evaluate potential pollution sources. The concentrations of 33 heavy metal elements in 27 samples of Barbula Indica moss in the investigated region collected in December of 2016 in the investigated area have been examined using multivariate statistical analysis. Five factors explaining 80% of the total variance were identified and their potential sources have been discussed.

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

scholarly journals Heavy metal levels in drinking water sources of Chingola District, Zambia

2020 ◽  
Author(s):  
Francis Hamwiinga ◽  
Chisala D. Meki ◽  
Patricia Mubita ◽  
Hikabasa Halwiindi
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Drinking Water ◽  
Ground Water ◽  
Water Samples ◽  
Tap Water ◽  
Water Sources ◽  
Wet Season ◽  
Drinking Water Sources ◽  
Metal Levels

Abstract Background: One of the factors impeding access to safe water is water pollution. Of particular concern is heavy metal contamination of water bodies. This study was aimed at determining the levels of heavy metals in drinking water sources of Chingola District of Zambia. Methods: A cross sectional study was employed. A total of 60 water samples were collected. Thirsty (30) samples were collected in the dry season in the month of October 2016 and another 30 in the wet season in the months of February and March, 2017. For each season 10 water samples were collected from each of the three water sources. i.e. Tap water, Urban ground water sources and Rural ground water sources. Heavy metal analysis was done using Atomic Absorption Spectrophotometer (AAS).Results: This study revealed that the concentrations of Iron, Manganese, Lead, Nickel and Arsenic were beyond maximum permissible levels in various water sources. Combined averages for both dry and wet seasons were as follows: Iron: 2.3, Copper: 0.63, Cobalt: 0.02, Manganese: 0.36, Lead: 0.04, Zinc:3.2, Nickel: 0.03, Arsenic: 0.05. Chromium and Cadmium were below detection limit in all water samples. The median concentrations of iron, arsenic, copper, manganese in drinking water from the Tap, rural and urban ground water sources were different, and this difference was statistically significant (p<0.05). The median concentrations of arsenic, nickel, manganese and cobalt were different between dry and wet season, and this difference was statistically significant (p<0.05).Conclusions: Sources of heavy metals in water seems to be both natural and from human activities. The concentration of heavy metals in different water sources in this study was found to be above the recommended levels. This calls for improvement in water monitoring to protect the health of the public. Therefore, there is need for continuous monitoring of heavy metals in drinking water sources by regulatory authorities.

scholarly journals Metalliferous content of drinking water and sediments in storage tanks of some schools in Erbil city, Iraq

2020 ◽  
Vol 9 (3) ◽  
Author(s):  
Hawraz Sami Khalid ◽  
Hoshyar Saadi Ali ◽  
Dhary Almashhadany
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Heavy Metal ◽  
Drinking Water ◽  
Water Samples ◽  
World Health ◽  
Storage Tanks ◽  
Quality Indices ◽  
Toxic Heavy Metals ◽  
Water Quality Indices

The present study was conducted to evaluate the quality of drinking water in randomly selected schools in Erbil city, Kurdistan Region, Iraq. The water quality indices such as the Heavy metal Pollution Index (HPI) and Heavy metal Evaluation Index (HEI) were applied to characterize water quality. Eighteen schools were incorporated and sampled for their water storage tanks available to students. Water samples and sediment samples from tanks floor were analyzed by Inductively Coupled Plasma Optical Emission Spectrometer for the determination of twenty-two metal elements. In drinking water samples, all detected metals did not exceed the permissible limits of the World Health Organization. The results of this study showed that the average values of HPI and HEI for As, Cd, Cr, Cu, Fe, Pb, Mn, Ni, and Zn were 54.442 and 0.221, respectively. According to data of the water quality indices, the schools drinking water quality are good and suitable for drinking in terms of heavy metals. However, sediments samples contained high concentrations of all elements including the toxic heavy metals (As, Cd, Cr, and Pb). Re-suspension of sediments into water column after refilling storage tanks can pose a serious threat to students drinking water from such vessels. It is therefore recommended that proper storage tanks are provided to the schools accompanied by continuous sanitation and hygiene practice to mitigate the corrosion of tanks to avoid health risks of toxic metal

scholarly journals Assessment of Some Heavy Metals in Drinking Water Samples of Tunceli, Turkey

2011 ◽  
Vol 8 (1) ◽  
pp. 276-280 ◽  
Author(s):  
Olcay Kaplan ◽  
Nuran Cikcikoglu Yildirim ◽  
Numan Yildirim ◽  
Nilgun Tayhan
Keyword(s):  
Heavy Metals ◽  
Drinking Water ◽  
Water Samples ◽  
World Health ◽  
Environment Protection ◽  
Protection Agency ◽  
Supply Networks ◽  
Health Organization ◽  
The City ◽  
Drinking Water Samples

The drinking water quality is associated with the conditions of the water supply networks, the pollution and the contamination of groundwater with pollutants of both anthropogenic and natural origin. In this study, water samples were taken from four different waterworks in Tunceli, Turkey and heavy metals concentrations (As, Cu, Cd, Cr, Pb, Ni and Hg) were measured. Four sampling sites were pre-defined in different locations of the city. The obtained results showed that, the heavy metals concentrations in water samples did not exceed the values of WHO (World Health Organization), EC (Europe Community), EPA (Environment Protection Agency) and TSE-266 (Turkish Standard) guidelines.

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