Application of statistical methods to study seasonal variation in the mine contaminants in soil and groundwater of Goa, India

 Soil and groundwater samples were collected during two seasons, premonsoon (April 1990) and postmonsoon (December 1990), and analyzed for major elements (Na, Mg, Al, Si, P, K, Ca, Ti, Mn and Fe), trace elements (Ni, Pb, Co, Cr and Zn) and water parameters (pH, conductivity, acidity, alkalinity, hardness, Cl and SO₄). All the data were subjected to linear discriminant analysis and partial correlation analysis in order to understand the seasonal variation in the data. It was observed from the Mahalanobis generalized distance that in both soil and groundwater samples there was a large difference in the concentration level of premonsoon and postmonsoon data. Linear discriminant functions were calculated to distinguish between premonsoon and postmonsoon samples. From the partial correlation coefficient analysis of soil samples, dominance of chemical weathering and precipitation of atmospheric fallout during monsoon were inferred. In the case of the water samples, high conductivity and high hardness in the postmonsoon samples as well as atmospheric fallout of Pb and Ni during the premonsoon period was suggested from partial correlation of water samples. Received: 19 September 1995 · Accepted: 12 December 1995     

江都市土壤重金属分布特征及污染评价

江都市土壤重金属含量分布及污染现状评价结果显示,江都市土壤环境质量总体良好,但局部地区土壤污染严重,其中通扬运河以北地区土壤环境质量优于通扬运河以南地区。土壤中镉、汞、锌含量空间分布不均匀,局部土壤含量超过国家土壤二级标准,由点源污染所致,其中镉、汞为江都市土壤主要致污染因子,导致局部土壤严重污染。建议对不同污染程度土壤土地采取不同利用方式,需进行合理调整规划。     

Relationship between aquatic insects and heavy metals in an urban stream using multivariate techniques

In the study, the relationship between some aquatic insect species (Ephemeroptera, Plecoptera, Trichoptera and Odonata) and some heavy metals (cadmium, lead, copper, zinc, nickel, iron and manganese) and boron were assessed using data obtained from the Ankara Stream, which flows through Ankara, the capital city of Turkey and receives high organic and industrial wastes. Sampling was carried out monthly along the Ankara Stream in 1991. environmental data were used to explain biological variation using multivariate techniques provided by the program canonical correspondence analysis ordination. The ordination method canonical correspondence analysis was applied to evaluate the relationships between environmental variables and distribution of aquatic insect larvae. Data sets were classified by two way indicator species analysis. In this study, aquatic insecta communities have been shown by canonical correspondence analysis ordination as related to total hardness, pH, cadmium, lead, copper, zinc, nickel, iron, manganese and boron. Cadmium, lead, copper and boron exceeded limits of the United States Environmental Protection Agency criteria for aquatic life. Trichopteran, Dinarthrum iranicum was an indicator of two way indicator species analysis and was placed close to the arrow representing copper. Odonate, Aeschna juncea was an indicator of two way indicator species analysis in site 10 and was placed close to the arrows representing manganese, lead, and nickel. Trichopteran, Cheumatopsyche lepida and odonate, Platycnemis pennipes were indicators of two way indicator species analysis for sites 6, 7, 11, 14, 15, 18 and were placed close to the arrows representing cadmium, boron, iron and total hardness.     

Contamination and distribution of heavy metals in urban soil in Zhangzhou City, Fujian, China

The urban environment quality is of vital importance as the majority of people now live in cities. Due to the continuous urbanization and industrialization with rapidly increasing economy in China, metals are continuously emitted into soils, imposing a great threat on human health. Urban soils might be affected by industrial activities, transport, agricultural practice, and waste disposal. An extensive survey was conducted in the highly urbanized Zhangzhou City （Fujian Province, China） using a systematic sampling strategy. Concentrations of Hg, Cd, Pb, Zn, Cu, As, Cr and Ni were measured on 108 topsoil samples collected from parks （0-15 cm）, residential areas and suburban agricultural soils. Statistic approach （cluster analysis） was adopted for identification of natural and anthropogenic influence on heavy metal contents. The maps of metal concentrations in surface soils were made based on geographical information system （GIS） data. All of these aim at assessing the distribution of these heavy metals in the urban environment.     

黄石市城市边缘区土壤重金属分布特征、风险评价及溯源分析

为掌握黄石市城市边缘区农用土壤环境质量现状,在高密度表、深层土壤采样的基础上,重点分析了土壤重金属元素的分布规律和特征,对其进行了生态环境风险评价,并对重金属元素成因进行了溯源分析。结果表明:研究区土壤中的重金属元素As、Pb、Hg、Cd、Zn、Ni、Cu和Cr含量范围分别为(5.2~155.9)×10-6 、(19.2~426.1)×10-6 、(0.012~1.823)×10-6 、(0.03~4.59)×10-6 、(34.8~529.6)×10-6 、(8.5~86.2)×10-6 、(16.52~104.39)×10-6 和(51.2~145.5)×10-6,平均含量均超过区域土壤环境背景值,且Cd超过农用地土壤风险筛选值。重金属污染物主要集中在表层40 cm以上土壤中,土地类型中以水田和旱地污染为主,污染物中以Cd、As和Pb为主要特征。水田中As、Pb、Cu和Zn为轻度污染,Cd和Hg为中度污染,而Cr和Ni无污染;旱地和林地中As、Pb和Hg为轻度污染,Cd为中度污染,而Cr、Cu、Ni和Zn无污染。多元统计分析表明,研究区土壤中Cr和Ni为自然源成因,与成土母质相关;Cd和Pb、As和Hg主要为人为源污染,与黄石市高强度工矿业生产和硫化物矿物酸化释放有关;而Cu和Zn为混合源成因,部分来源于土壤环境背景,部分来源于人类活动和工业生产排放。     

Identification of influencing factors for groundwater quality variation using multivariate analysis

This paper reports the results of multivariate analysis on the major-ions data present in groundwater collected in a hydrogeochemical survey of a hard rock terrain in Andhra Pradesh, India. The use of factor analysis is proposed, as a first step, for identifying the processes influencing the hydrogeochemical variations in groundwater. As a result of the application factor analysis, three factors were obtained, which explained characterization of groundwater quality and identified the sources for the presence of ions and its variations in concentrations and their geochemical processes. The natural dissolution of existing rocks of granites and granitic gneisses is the common influencing source for its hydrogeochemical character in the study area, but at some localized zones, the human-influenced sources of agricultural, industrial and urbanization are the dominating factors. The spatial and seasonal variation of the hydrogeochemical processes associated with the factor variables in the groundwater quality of the study area were analysed and evaluated.     

Evaluation of the processes affecting vertical water chemistry in an alluvial aquifer of Mankyeong Watershed, Korea, using multivariate statistical analyses

Vertical variations of redox chemistry and groundwater quality were investigated in an alluvial aquifer beneath an agricultural area, in which deep groundwaters are free of NO₃, Fe, and Mn problems that are frequently encountered during the development of alluvial groundwaters. This study was performed to identify and evaluate vertical chemical processes attenuating these chemical species in the study area. For this study, the processes affecting groundwater chemistry were identified by factor analysis (FA) and the groundwater samples collected from six multilevel samplers were hierarchically classified into three different redox zones by cluster analysis (CA) based on the similarity of geochemical features. FA results indicated three major factors affecting the overall water chemistry: agricultural activities (factor 1), redox reactions (factor 2), and remnant seawater (factor 3). The groundwater quality in the study area was revealed to be controlled by a series of different redox reactions, resulting in different redox zones as a function of depth. It was also revealed that the low Fe and Mn levels in the groundwater of the deeper part are associated with sulfate reduction, which led to precipitation of Fe as iron sulfide and adsorption of Mn on it.     

Source and distribution of metals in bed sediments of Subarnarekha River, India

The study was taken up to establish the distributions of metals as well as to assess the extent of anthropogenic inputs into the Subarnarekha River. Bed sediments were collected; analyzed for metals; and assessed with the index of geo-accumulation (I _geo), enrichment factor (EF) value, concentration factor (CF) and pollution load index (PLI). Metals in the sediment were variable in the river and there are major pollution problems at certain locations. The average concentrations of Fe, Cu, Cr, Pb, Mn, Ni, Zn, Co and Ba in mg/kg was found to be 30,802 ± 11,563, 69 ± 57, 111 ± 74, 75 ± 61, 842 ± 335, 42 ± 22, 100 ± 39, 15 ± 4 and 698 ± 435, respectively. The I _geo, EF, CF and PLI indices showed that the contamination of Pb and Cu was more serious than that of Ni, Zn, Co and Ba, whereas the presence of Fe, Mn and Cr might be primarily from natural sources. The contamination of the sediments with metals at few locations is attributed to mining, industries and other anthropogenic causes. Principal component analysis was employed to better comprehend the controlling factors of sediment quality. The statistical analysis of inter-metallic relationship revealed the high degree of correlation among the metals indicated their identical behaviour during transport. PCA outcome of three factors together explained 83.8 % of the variance with >1 initial eigenvalue indicated both innate and anthropogenic activities are contributing factors as source of metal profusion in Subarnarekha River basin.The overall study reveals moderately serious pollution in the river basin principally in some locations under the anthropogenic influences.     

Source apportionment and distribution of atmospheric mercury in urban Beijing,China

The concentration of gaseous elemental mercury (GEM) in the atmosphere of urban Beijing was measured from October 2003 to September 2004 to investigate the origins and spatial-temporal variations of atmospheric Hg. The mean value of Hg concentration is 17.1 ng·m-3 (n=653). The atmospheric Hg data showed spatial-temporal variations throughout the duration of our observation. The maximum GEM concentration (53.7 ng·m-3) was observed at Gucheng in the western area of urban Beijing. The GEM concentrations increased from the north to the south of the studied area, and were higher in winter than in summer. The highest and lowest monthly averages of GEM concentrations were measured to be 23.3 and 4.1 ng·m-3 in January and July, respectively. In addition, GEM concentrations are higher in the daytime than at night in Autumn and from 14 March to 15 April, but daily GEM variation showed an inverse pattern from 22 April to 22 May. In winter, two peak values of GEM concentrations occurred at 13:30 and 21:30. Daily variation of GEM concentrations in summer was the lowest in the four seasons. Mercury from coal combustion was estimated to be the main source of anthropogenic emissions in Beijing from October 2003 to September 2004. Additionally, Hg emission from natural gas burning was estimated to be another dominant source of atmospheric Hg in Beijing.     

Assessment of groundwater quality using multivariate statistical techniques in Hashtgerd Plain, Iran

Multivariate statistical techniques, such as cluster analysis (CA), factor analysis (FA), principal component analysis (PCA), and discriminant analysis (DA), were applied for the evaluation of variations and the interpretation of a large complex groundwater quality data set of the Hashtgerd Plain. In view of this, 13 parameters were measured in groundwater of 26 different wells for two periods. Hierarchical CA grouped the 26 sampling sites into two clusters based on the similarity of groundwater quality characteristics. FA based on PCA, was applied to the data sets of the two different groups obtained from CA, and resulted in three and five effective factors explaining 79.56 and 81.57% of the total variance in groundwater quality data sets of the two clusters, respectively. The main factors obtained from FA indicate that the parameters influencing groundwater quality are mainly related to natural (dissolution of soil and rock), point source (domestic wastewater) and non-point source pollution (agriculture and orchard practices) in the sampling sites of Hashtgerd Plain. DA provided an important data reduction as it uses only three parameters, i.e., electrical conductivity (EC), magnesium (Mg²⁺) and pH, affording more than 98% correct assignations, to discriminate between the two clusters of groundwater wells in the plain. Overall, the results of this study present the effectiveness of the combined use of multivariate statistical techniques for interpretation and reduction of a large data set and for identification of sources for effective groundwater quality management.     

Identification of the origin of salinization in groundwater using multivariate statistical analysis and geochemical modeling: a case study of Kaohsiung,Southwest Taiwan

The study of brine aquifers in southern Taiwan is highly complicated by hybrid geochemical reactions, which obscure important geochemical information. Using multivariate analysis on major and minor ion compositions normalized by Cl⁻ content, chemical constituents were combined into two principal components representing brine mixing and mineral precipitation. Comparing to multivariate analysis on the original data, this procedure reveals more geochemical information. It demonstrates that the brine groundwater of the region is primarily composed of highly evaporated seawater. The evaporation ratio is >70%; a point at which calcite, dolomite and gypsum precipitate. Oxygen and hydrogen isotopic compositions confirm this inference; and further, geochemical modeling quantitatively determined the evaporation ratio to be about 85%. Natural boron contamination is a consequence of brine groundwater. Two evolutionary trends in the plotting of the Cl/B ratio versus Cl⁻ can be identified: (1) Cl/B ratio decreases with boron being released from clay minerals when brine aquifers are flushed with freshwater; and (2) Cl/B ratio increases when seawater of a high Cl/B ratio infiltrates coastal aquifers.     

安徽省宣城市南部地区土壤重金属元素地球化学特征

利用1∶25万土地质量地球化学调查数据分析和研究了安徽省宣城市南部地区土壤中As、Cd、Cr、Cu、Hg、Ni、Pb、Zn 8种重金属元素的地球化学特征以及重金属异常来源。调查发现地质背景是土壤元素含量的主控因素,调查区表、深层土壤重金属元素含量空间分布特征与地质背景、沉积环境表现出显著的空间一致性,重金属高含量成土母岩(荷塘组、皮园村组、蓝田组等地层)是土壤重金属元素高异常的主要影响因素,此外矿山开采、大气干湿沉降也是土壤重金属高异常的影响因素之一,土壤中Pb、Hg、Cd、Cr元素具有大气干湿沉降的输入来源。调查区土壤重金属污染风险主要影响指标为Cd,土壤Cd超过农用地土壤污染风险管制值的样品比例为2.56%,形态分析结果显示土壤Cd以离子交换态为主,结合农作物调查发现在土壤Cd高异常区存在一定的生态风险。     

Water pollution sources assessment by multivariate statistical methods in the Tahtali Basin,Turkey

In this study, multivariate statistical methods including factor, principal component and cluster analysis were applied to surface water quality data sets obtained from the Tahtali River Basin, Turkey. Factor and principal components analysis results revealed that surface water quality was mainly controlled by agricultural uses and domestic discharges. Cluster analysis generated two clusters. Based on the locations of the sites consisted by each cluster and variable concentrations at these stations, it was concluded that agricultural discharges strongly affected north and northeast part of the region. These methods are believed to assist water managers to understand complex nature of water quality issues and determine priorities to improve water quality.     

Source and distribution of trace metals and nutrients in Narmada and Tapti river basins,India

The study was designed to establish the distributions of trace metals, dissolved organic carbon, and inorganic nutrients as well as to assess the extent of anthropogenic inputs into the Narmada and Tapti rivers. Water and sediment qualities are variable in the rivers, and there are major pollution problems at certain locations, mainly associated with urban and industrial centers. The metal concentrations of samples of the aquatic compartments investigated were close to the maximum permissible concentration for the survival of aquatic life, except for higher values of Cu (5–763 μg l⁻¹), Pb (24–376 μg l⁻¹), Zn (24–730 μg l⁻¹), and Cr (70–740 μg l⁻¹) and for drinking water except for elevated concentrations of metals such as Pb, Fe (850–2,060 μg l⁻¹), Cr, and Ni (20–120 μg l⁻¹). In general, the concentrations of trace metals in the rivers vary down stream which may affect the “health” of the aquatic ecosystem and may also affect the health of the rural community that depends on the untreated river water directly for domestic use. The assessment of EF, I _geo, and PLI in the sediments reveals overall moderate pollution in the river basins.     

Spatial variation assessment of groundwater quality using multivariate statistical analysis(Case Study: Fasa Plain,Iran)

Groundwater is considered as one of the most important sources for water supply in Iran. The Fasa Plain in Fars Province, Southern Iran is one of the major areas of wheat production using groundwater for irrigation. A large population also uses local groundwater for drinking purposes. Therefore, in this study, this plain was selected to assess the spatial variability of groundwater quality and also to identify main parameters affecting the water quality using multivariate statistical techniques such as Cluster Analysis (CA), Discriminant Analysis (DA), and Principal Component Analysis (PCA). Water quality data was monitored at 22 different wells, for five years (2009-2014) with 10 water quality parameters. By using cluster analysis, the sampling wells were grouped into two clusters with distinct water qualities at different locations. The Lasso Discriminant Analysis (LDA) technique was used to assess the spatial variability of water quality. Based on the results, all of the variables except sodium absorption ratio (SAR) are effective in the LDA model with all variables affording 92.80% correct assignation to discriminate between the clusters from the primary 10 variables. Principal component (PC) analysis and factor analysis reduced the complex data matrix into two main components, accounting for more than 95.93% of the total variance. The first PC contained the parameters of TH, Ca²⁺, and Mg²⁺. Therefore, the first dominant factor was hardness. In the second PC, Cl^-, SAR, and Na⁺ were the dominant parameters, which may indicate salinity. The originally acquired factors illustrate natural (existence of geological formations) and anthropogenic (improper disposal of domestic and agricultural wastes) factors which affect the groundwater quality.