Investigation of Soil Heavy Metal in Zhehai Town Huize County Yunnan Based on GIS- Approach and Geostatistics

2012 ◽  
Vol 610-613 ◽  
pp. 3067-3074
Author(s):  
Kun Shi ◽  
Dong Sheng Li ◽  
Bi Yun Zhao
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Heavy Metal ◽  
Principal Component Analysis ◽  
Correlation Matrix ◽  
Yunnan Province ◽  
Anthropogenic Activities ◽  
Principal Component ◽  
And Cluster Analysis ◽  
Soil Area

1144 sample points were collected using PXRF from an area of 99 square kilometers soil area Zhehai town Huizhe county of Yunnan province to acquire their concentrations and possible sources, and characterize their spatial variability for risk assessment. SPSS16.0 was used to deal the raw date and eliminate the outfits and perform Multivariate analysis (correlation matrix, principal component analysis, and cluster analysis). It discriminate distinct groups of heavy metals. From the Range of the semi-variorum models, it obtained elements spatial structure and the contamination resource caused mainly by natural resource or anthropogenic activities. The result of risk assessment attained the percentage of pollution accounts for whole investigate region, which provides the reference to deal with the soil pollution.

scholarly journals Heavy metal index and geographical information system (GIS) approach to study heavy metal contamination: a case study of north Chennai groundwater

2020 ◽  
Vol 10 (12) ◽  
Author(s):  
S. R. Mahapatra ◽  
T. Venugopal ◽  
A. Shanmugasundaram ◽  
L. Giridharan ◽  
M. Jayaprakash
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Principal Component Analysis ◽  
Information System ◽  
Principal Component ◽  
Geographical Information ◽  
Common Source ◽  
Groundwater Samples ◽  
Metal Index ◽  
Drinking Purpose

AbstractFifty-four groundwater samples were collected from the highly industrialized area of north Chennai. These groundwater samples were tested for Fe, Mn, Cu, Ni, Pb, Zn and Cr in pre-monsoon and post-monsoon periods of 2015–2016. Most of the samples in the area were found to have high concentration of heavy metals. Geographical information system was used to develop contour maps for the analysis of heavy metals, and it has been found that most of the Ambattur area was affected by the heavy metals in both the seasons. ANOVA tests were carried out on the hydro-chemical data for both the monsoon periods, and it was found that there was a common source of origin for most of the heavy metals, which was also confirmed by the correlation and principal component analysis. T-test indicates that there was a common source of origin of heavy metals in the study area, viz. industrial and domestic pollutants, that were found to be the main source of heavy metals in both the monsoon periods. Principal component analysis gave three important factors (principal components) for both the seasons. Pre-monsoon groundwater samples showed a common cause of origin of heavy metals than the post-monsoon samples. Heavy metal pollution index indicates that almost all the samples were not fit for drinking purpose in both the monsoon periods and metal index also indicates the non-usability of the water for drinking purpose.

Application of Principal Component Analysis for the Estimation of Source of Heavy Metal Contamination in Sugarcane Soil

2014 ◽  
Vol 651-653 ◽  
pp. 1402-1409
Author(s):  
Gui Ping Xu ◽  
Xiao Fei Wang ◽  
Li Jun Chen
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Principal Component Analysis ◽  
Ecological Risk ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
Risk Index ◽  
Principal Component ◽  
Component Analysis ◽  
Potential Ecological Risk

Concentrations of heavy metals in sugarcane soil of Guangxi were determined and the potential ecological risk index was used simultaneously to evaluate the extent of heavy metals enrichment contamination. Results showed that the pollution extent of heavy metals in sugarcane soil by potential ecological risk followed the order: Cd>Pb>Cu>Zn, Cu and Zn were slightly polluted, with small potential ecological harm, while Pb and Cd were above moderately polluted, with heavy potential ecological harm. Principal component analysis was applied to estimate the sources of heavy metals contamination, the results indicated that the first two components accounted for 61.016% and 26.920% of the total variance respectively, 4 kinds of heavy metal elements had similar sources, tailing dam lead-zinc concentrator upstream along the coast was the main sources of heavy metal contamination.

scholarly journals The Risk Characteristics of Heavy Metals in Urban Soil

2021 ◽  
Author(s):  
Yan Li ◽  
Dike Feng ◽  
Meiying Ji ◽  
Zhanpeng Li ◽  
Ruocheng Zhang ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Heavy Metal ◽  
High Risk ◽  
Human Health ◽  
Rapid Development ◽  
Risk Index ◽  
Principal Component ◽  
Research Area ◽  
Assessment Model

Abstract With the rapid development of China's industrial economy, heavy metals and other pollutants continue to accumulate in the environment, which has created serious threats for the ecological environment and human health. To comprehensively evaluate the ecological risks from heavy metals in the soil in Nanjing, China, as well as the status of the risks to human health, this study randomly collected 50 surface soil samples, and the contents of Al, Ca, Fe, Mg, Mn, Ni, Ti, Cd, Cr, Cu, Pb and Zn in the samples were determined, combined with the ecological risk index and the USEPA health risk assessment model for a comprehensive risk assessment of soil heavy metals in Nanjing. The results show that there has been heavy metal enrichment of Mn, Pb, Zn and other heavy metals in the research area in Nanjing city, and the variation coefficients of Pb and Cu are distinctly large; that is, the distribution of Pb and Cu in the research area shows a great fluctuation. These elements are all slightly polluting, among which the Cu heavy metal pollution degree is different, and Pb element pollution is the most serious. Children are at a high risk of exposure in various ways, among which Pb and Cu elements have a high risk of causing non-carcinogenic issues. Overall, Pb and Cu in Nanjing are important risk elements that should be monitored and controlled. The results of the correlation analysis showed that the content changes of Pb, Zn and Cu; Ni, Ti and Fe; and Zn and Pb had extremely significant correlations, indicating that they may have the same source; while Ti and Ca, Ti and Cu, and Pb and Zn showed opposite changes, indicating that their concentrations were inversely related. The results of the principal component analysis showed that industrial sources in Nanjing contributed the most heavy metals, reaching 34.4%. The second largest source was from parent material and fertilizer, which contributed 32.3% and 19.6%, respectively. The sources with the lowest contributions were from weathering and deposition, which reached 13.7%.

Assessment of Heavy Metals in Relation to Soil Pollution at Mewat, Haryana, India

2018 ◽  
Vol 13 (3) ◽  
pp. 299-306 ◽  
Author(s):  
GOPAL KRISHAN ◽  
S.K. CHANDNIHA ◽  
A.K. LOHANI ◽  
BRIJESH KUMAR YADAV ◽  
NARESH KUMAR ARORA ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Principal Component Analysis ◽  
Metal Pollution ◽  
Principal Component ◽  
Anthropogenic Sources ◽  
Soil Profiles ◽  
Agricultural Crops ◽  
Heavy Metals In Soils ◽  
Typical Soil

Assessment of heavy metals in soils is important in context of human health as these may either pollute the agricultural crops or may move deeper into the groundwater. There has been no such work been carried out in the soils of Mewat district. In the present study, to investigate the soil heavy metal pollution characteristics 15 samples and 3 typical soil profiles were collected from 2 blocks of Mewat district, Haryana and were analyzed for contents of Arsenic (As), copper(Cu), cadmium (Cd), zinc(Zn), iron (Fe), manganese (Mn) and nickel(Ni). Concentrations of As, Cd and Ni in soils are less than their toxicity levels while concentrations of Fe, Mn, Zn and Cu are found exceeding the toxicity levels. Based on the results, soil in the study area are polluted by heavy metals viz. Fe, Mn, Zn and Cu. According to principal component analysis, distinct groups of heavy metals were discriminated between natural or anthropogenic sources.

scholarly journals Multivariate statistical characterization of groundwater quality in Fesdis, East of Algeria

2018 ◽  
Vol 37 (1) ◽  
pp. 65-74 ◽  
Author(s):  
Safia Khelif ◽  
Abderrahmane Boudoukha
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Anthropogenic Activities ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Component Analysis ◽  
Data Sets ◽  
Multivariate Statistical ◽  
Statistical Characterization ◽  
And Cluster Analysis

AbstractThis study is a contribution to the knowledge of hydrochemical properties of the groundwater in Fesdis Plain, Algeria, using multivariate statistical techniques including principal component analysis (PCA) and cluster analysis. 28 samples were taken during February and July 2015 (14 samples for each month). The principal component analysis (PCA) applied to the data sets has resulted in four significant factors which explain 75.19%, of the total variance. PCA method has enabled to highlight two big phenomena in acquisition of the mineralization of waters. The main phenomenon of production of ions in water is the contact water-rock. The second phenomenon reflects the signatures of the anthropogenic activities. The hierarchical cluster analysis (CA) in R mode grouped the 10 variables into four clusters and in Q mode, 14 sampling points are grouped into three clusters of similar water quality characteristics.

scholarly journals Elemental composition of surface soils in Nature Park Shumen Plateau and Shumen City, Bulgaria

2018 ◽  
Vol 5 (2) ◽  
pp. 68-76
Author(s):  
Vanya Koleva ◽  
Teodora Koynova ◽  
Asya Dragoeva ◽  
Nikolay Natchev
Keyword(s):  
Heavy Metals ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Elemental Composition ◽  
Principal Component ◽  
Component Analysis ◽  
Soil Samples ◽  
Surface Soils ◽  
Nature Park ◽  
And Cluster Analysis

Abstract Anthropogenic activities cause environmental pollution and alter biogeochemical cycles. Soils in cities and their vicinity are exposed to different pollutants. Nature Park Shumen Plateau is a protected area situated in the proximity of Shumen (Bulgaria). The aim of this research was to compare elemental composition of surface soil samples from Nature Park with two areas in Shumen city. Soil samples from seven sites on the territory of Nature Park and from two urban sites were collected. The elemental composition of the samples was determined using Energy Dispersive X-Ray Fluorescence technique. Principal component analysis and cluster analysis were performed to interpret the complex data. The content of 24 elements was determined: Br, Y, Zr, Mo, Ag, Cd, Sn, Sb, I, Cs, Ba, La, Ce Si, K, Ca, Ti, Mn, Fe, Cu, Zn, Rb, Sr, and Pb. Results presented here and previously showed that concentrations of heavy metals Cu, Zn, Cd and Pb are below the upper limit according to Bulgarian legislation. Concentrations of Mn and Fe in samples from Nature Park were comparable to the literature data reported for unpolluted areas. Principal component analysis and cluster analysis show similarity of the content of 24 elements between samples from Nature Park and from Shumen city. These findings are in accordance with our previous positive results from Allium-test: cytogenetic endpoints showed a presence of harmful compounds in Nature Park soils. The content of heavy metals in the surface soils studied show a lack of environmental risk for Nature Park. However, a similar distribution pattern of the investigated elements in the park and two anthropologically influenced areas in Shumen city indicated a potential hazard in Nature Park.

scholarly journals Heavy metal contents in Latosols cultivated with vegetable crops1

2016 ◽  
Vol 46 (4) ◽  
pp. 391-400 ◽  
Author(s):  
Laércio Santos Silva ◽  
◽  
Izabel Cristina de Luna Galindo ◽  
Clístenes Williams Araújo do Nascimento ◽  
Romário Pimenta Gomes ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Principal Component Analysis ◽  
Agricultural Practices ◽  
Principal Component ◽  
Soil Samples ◽  
Vegetable Crops ◽  
Chemical Analyses ◽  
Analysis Techniques ◽  
Metal Contents

ABSTRACT Heavy metals are naturally found in soils, but their levels may increase as a result of anthropogenic actions. This study aimed at determining the concentrations of Cd, Cu, Mn, Ni, Pb and Zn in Yellow Latosol from vegetable crops areas, as well as the influence of the cultivation and position in the landscape on the accumulation of these elements. Soil samples were collected from five farming areas and four areas with natural vegetation, which served as a reference. Soil was collected along the planting rows from three transect positions (upper, middle and lower sections of the slope), as well as from the upper portion of forest areas, at three depths (0.0-0.10 m, 0.10-0.30 m and 0.30-0.60 m). The results from the chemical analyses indicated that Cd, Cu, Mn, Pb and Zn levels in the soil increased as a result of cultivation. Only Cd and Cu concentrations were above the quality reference values for the Pernambuco State. The multivariate analysis techniques used were efficient at separating the environments and at differentiating the origin of the metals. Soils from forest areas were clearly separated from croplands, demonstrating the effect of agricultural practices on the metal contents in the soils. The principal component analysis indicated a predominantly anthropogenic origin (phosphate fertilizing) for Cd, in more superficial soil samples.

scholarly journals Heavy metal pollutants and their spatial distribution in surface sediments from Thondi coast, Palk Bay, South India

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Karthikeyan Perumal ◽  
Joseph Antony ◽  
Subagunasekar Muthuramalingam
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Principal Component Analysis ◽  
Spatial Distribution ◽  
South India ◽  
Surface Sediments ◽  
Principal Component ◽  
Component Analysis ◽  
Pollution Level ◽  
Palk Bay

Abstract Background The concentration of heavy metals and their spatial distribution in surface sediments collected from the Thondi coast, Palk Bay, South India were analysed in this study. The sediment grain size, pH, EC, and major elements (Fe, and Al), heavy metal concentrations (Mn, Cr, Zn, Cd, Ni, Cu, and Pb) were determined and the values for the geoaccumulation index (Igeo), enrichment factor (EF), potential contamination index (Cp), potential ecological risk index (RI), contamination factor (CF), modified contamination degree (mCd), degree of contamination (Cd), and potential contamination factors (Cp) were calculated based on their background values to determine the pollution level of the study area. Multivariate analysis such as Pearson’s correlation coefficient, principal component analysis/factor analysis (PCA/FA), cluster analysis, and regression analysis are a versatile method for identifying heavy metal sources and determining the relationship between pollutants in marine sediment. Results The pollution indices, namely EF, CF, Cd, mCd, CP, RI, and Igeo, revealed that the heavy metal contamination was due to Cd, while a moderate level of contamination was caused by Cu, Zn, Pb, and Cr. The principal component analysis and correlation matrix analysis showed a strong positive loading for Cd due to its high level of contamination in the study area. Anthropogenic inputs such as municipal wastewater, domestic sewage discharge, fishing harbour activities, and industrial and aquaculture wastes led to the increased Cd concentration in the study area. Moreover, the pollution load index revealed that the sediments were polluted by heavy metals. Conclusion The findings of this study revealed that the increased concentration of heavy metals in the study area increases the toxicity in the marine environment, thus affecting the ecosystem.

scholarly journals Geochemical Mapping, Risk Assessment, and Source Identification of Heavy Metals in Road Dust Using Positive Matrix Factorization (PMF)

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 614
Author(s):  
Muhammad Faisal ◽  
Zening Wu ◽  
Huiliang Wang ◽  
Zafar Hussain ◽  
Chenyang Shen
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Matrix Factorization ◽  
Anthropogenic Activities ◽  
Contamination Factor ◽  
Road Dust ◽  
Positive Matrix Factorization ◽  
Prevention Measures ◽  
Positive Matrix ◽  
The City

Heavy metals in road dust pose a significant threat to human health. This study investigated the concentrations, patterns, and sources of eight hazardous heavy metals (Cr, Ni, Cu, Zn, As, Cd, Pb, and Hg) in the street dust of Zhengzhou city of PR China. Fifty-eight samples of road dust were analyzed based on three methods of risk assessment, i.e., Geo-Accumulation Index (Igeo), Potential Ecological Risk Assessment (RI), and Nemerow Synthetic Pollution Index (PIN). The results exhibited higher concentrations of Hg and Cd 14 and 7 times higher than their background values, respectively. Igeo showed the risks of contamination in a range of unpolluted (Cr, Ni) to strongly polluted (Hg and Cd) categories. RI came up with the contamination ranges from low (Cr, Ni, Cu, Zn, As, and Pb) to extreme (Cd and Hg) risk of contamination. The risk of contamination based on PIN was from safe (Cu, As, and Pb) to seriously high (Cd and Hg). The results yielded by PIN indicated the extreme risk of Cd and Hg in the city. Positive Matrix Factorization was used to identify the sources of contamination. Factor 1 (vehicular exhaust), Factor 2 (coal combustion), Factor 3 (metal industry), and Factor 4 (anthropogenic activities), respectively, contributed 14.63%, 35.34%, 36.14%, and 13.87% of total heavy metal pollution. Metal’s presence in the dust is a direct health risk for humans and warrants immediate and effective pollution control and prevention measures in the city.

Sign in / Sign up

Export Citation Format

Share Document