Identification of heavy metal sources by multivariable analysis in a typical Mediterranean city (SE Spain)

Problems associated with heavy metal characterization in the majority of sites are often due to multiple sources of pollution. This work presents the results through the use of advanced statistical techniques to identify sources of soil heavy metals in a typical Mediterranean city. The multivariable analysis performed on seven metals identified four sources controlling their variability. Cr, Mn, and Ni contents were associated to soil parent materials; Cd and Pb contents were related to anthropogenic activities, specifically industrial activities and traffic; Cu content is controlled by long-term application of inorganic fertilizers in agricultural areas. Finally, zinc concentration is associated to commercial and outdoor activities in the area. These results were supported by the fact that metals associated to parent material (Cr, Mn, and Ni) were better correlated with soil lithogenic properties, while anthropogenic metals were correlated with more variable soil constituents.     

Analysis of mosses and topsoils for detecting sources of heavy metal pollution: multivariate and enrichment factor analysis

In order to assess the contribution of emission sources to the pollution of areas remote from industrial facilities, a combined approach of enrichment factor analysis and multivariate statistics was used for detecting the origin of heavy metal pollution in the Zlatibor ecosystem, in Serbia. Samples of moss (Pleurozium schreberi, Hylocomium splendens, Scleropodium purum, Hypnum cupressiforme and Thuidum delicatulum) and of topsoil (0-5 cm) were collected in 2005. The concentrations of seven heavy metals (Cd, Cr, Cu, Mn, Ni, Pb and Zn) were determined in moss and soil samples by atomic absorption spectrometry. The results obtained by enrichment factor analysis and two multivariate statistical methods, principal component analysis and cluster analysis, enabled discrimination of the lithologic and anthropogenic sources of heavy metals in the mosses. Enrichment factors, calculated to evaluate the contribution to the metal content in moss from anthropogenic sources, revealed pollution of the investigated area by Cd and Pb, originating from long-range transport and fossil fuel burning.     

Application of multivariate statistical techniques in hydrogeochemical studies—a case study: Brahmani–Koel River (India)

This study presents the usefulness of multivariate statistical techniques, such as correlation matrix, cluster analysis, and factor analysis, for the evaluation and interpretation of complex water quality data sets of Brahmani–Koel river along the Rourkela Industrial Complex, India, and the apportionment of pollution sources/factors. The correlation study suggests that dissolved heavy metals, biochemical oxygen demand (BOD), and chemical oxygen demand (COD) are contributed by anthropogenic sources. The results of R-mode factor analyses revealed that anthropogenic contributions are responsible for increase in metals of the river water, which is mainly responsible for contamination of the river. It also reflected that the level of pollution in the river was very high. The factor score plot and loading plot have been drawn, which indicate that the polluted stations are identified by the heavy metals. The relationships among the stations are highlighted by cluster analysis, represented in dendograms to categorize different levels of contamination. An attempt has been made to study the degree of contamination of the river waters by using a tool like enrichment ratio (ER). The ER for heavy metal concentrations concluded that metals like Ni, Co, Cr, and Fe are showing high enrichment with respect to global background and metal ions like Fe, Mn, Cu, and Zn show high enrichment with respect to local background.     

Characterization of soil heavy metal contamination and potential health risk in metropolitan region of northern China

Soil in metropolitan region suffers great contamination risk due to the rapid urbanization especially in developing countries. Beijing and Tianjin, together with their surrounding regions, form a mega-metropolitan region in northern China. To assess the soil environmental quality, a total of 458 surface soil samples were collected from this area. Concentrations of Cr, Cu, Pb, Zn, As, Cd, and Hg were analyzed and compared to the Chinese environmental quality standards for soil. Multivariate analysis was carried out to identify the possible sources and Geographic Information Systems techniques were applied to visualize the spatial data. It was found that the primary inputs of As were due to pedogenic sources, whereas Hg was mainly of anthropogenic source. Other elements including Cr, Cu, Pb, Zn, and Cd were from both lithogenic and anthropogenic origins. Health risk assessment based on the maximum heavy metal concentration indicated that As derived from sewage irrigation area can result in carcinogenic lifetime risk due to ingestion and/or dermal contact of soil. The potential non-carcinogenic risk for children is significant for Pb and the cumulative effect of multiple metals is of concern for children in the vicinity of mining site. The results increased our knowledge for understanding natural and anthropogenic sources as well as health risk for metals in metropolitan soil.     

Spatial patterns of heavy metals in soil under different geological structures and land uses for assessing metal enrichments

One hundred and thirty composite soil samples were collected from Hamedan county, Iran to characterize the spatial distribution and trace the sources of heavy metals including As, Cd, Co, Cr, Cu, Ni, Pb, V, Zn, and Fe. The multivariate gap statistical analysis was used; for interrelation of spatial patterns of pollution, the disjunctive kriging and geoenrichment factor (EF_G) techniques were applied. Heavy metals and soil properties were grouped using agglomerative hierarchical clustering and gap statistic. Principal component analysis was used for identification of the source of metals in a set of data. Geostatistics was used for the geospatial data processing. Based on the comparison between the original data and background values of the ten metals, the disjunctive kriging and EF_G techniques were used to quantify their geospatial patterns and assess the contamination levels of the heavy metals. The spatial distribution map combined with the statistical analysis showed that the main source of Cr, Co, Ni, Zn, Pb, and V in group A land use (agriculture, rocky, and urban) was geogenic; the origin of As, Cd, and Cu was industrial and agricultural activities (anthropogenic sources). In group B land use (rangeland and orchards), the origin of metals (Cr, Co, Ni, Zn, and V) was mainly controlled by natural factors and As, Cd, Cu, and Pb had been added by organic factors. In group C land use (water), the origin of most heavy metals is natural without anthropogenic sources. The Cd and As pollution was relatively more serious in different land use. The EF_G technique used confirmed the anthropogenic influence of heavy metal pollution. All metals showed concentrations substantially higher than their background values, suggesting anthropogenic pollution.     

Soil heavy metal contamination in an industrial area: analysis of the data collected during a decade

Soil contamination by heavy metals has become a serious problem mainly because, above certain concentrations, all metals have adverse effects on human health. In particular, the accumulation of heavy metals in agricultural soils leads to elevated uptake by crops and affects food quality and safety. In this paper, we present the results of a study carried out over a decade for evaluating the impact of a new industrial settlement in an area geared to agriculture and livestock and far from urban sites. We focus our study on the bioavailable fraction of Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn in soil samples. Heavy metal concentrations in soil are analysed with both univariate and multivariate statistical procedures. The main goal of this paper is the development of a statistical procedure, based on a mix of multivariate analysis, able to compare field surveys carried out during different years and to characterize spatial and temporal changes in soil heavy metals concentrations.     

Statistical source identification of major and trace elements in groundwater downward the tailings dam of Miduk Copper Complex, Kerman, Iran

Identifying the possible sources of potential harmful metals in groundwater systems plays a crucial role in evaluating the potential risks to residents and local plant cover. An attempt was made to define the origin of Al, Cd, Cu, Fe, Mo, Ni, and Pb in groundwater using multivariate statistic approaches [principal component analysis (PCA), hierarchical cluster analysis], and tailings sequential extraction by the method of Tessier et al. The concentrations of studied elements were measured in 42 samples collected from 15 stations surrounding and downward the tailings dam of Miduk Copper Complex, central province of Kerman, Iran. According to the PCA results, confirmed by cluster dendrogram and metal content measurement of tailings sequential extracts, two components accounting for nearly 73% of the total variance, controlled the heavy metal variability and classified the possible source of groundwater contamination into two categories: (1) upper seepage which controls the variability of Cd, Cu, Fe, Ni, and Pb and (2) toe seepage of tailings dump affecting on Mo and Al concentration in downstream groundwater.     

Impact of industrial waste effluents on river Damodar adjacent to Durgapur industrial complex, West Bengal, India

The present study deals with the characterization of industrial effluents released from various industries and distribution of heavy metals in effluent discharge channel and its impact on the river Damodar. The effluent of tamlanala, a natural storm water channel, is extensively used for irrigation for growing vegetables in and around the study area. The heavy metals in water of the study area are in the order of Fe > Mn > Pb >?Cd and sediments follow similar trends too. The enrichment of heavy metals in the sediments are in the order of Cd (39.904) > Pb (33.156) > Mn (0.164) > Fe (0.013). The geoaccumulation index values reveal effluent channel is subjected to moderate to high pollution with respect to Cd (4.733) and Pb (4.466). The analyzed data for enrichment factors and the pollution load index (1.305) show that effluent channels have suffered from significant heavy metal contamination following industrialization and urbanization. Compared to baseline values, the surface sediment layers show high enrichment across the channel and at its discharge point. The factor analysis reveals three factors—industrial sources, surface runoff inputs, and background lithogenic factors which clarify the observed variance of the environmental variables. Metal pollution assessment of sediments suggests that pollution from the heavy metals observed is high in the tamlanala which in turn affects the downstream of the river system.     

Use of the land snail Helix aspersa for monitoring heavy metal soil contamination in Northeast Algeria

The objective of this study was to investigate the impact of anthropogenic activities on soil quality using the land snail Helix aspersa as a bioindicator. Soil samples and snails were collected from several sites in Northeast Algeria during the summer and winter of 2010. All of the sites were chosen due to their proximity to industrial factories—a potential source of soil pollution via heavy metal contamination. The concentration of heavy metals (Pb, Cd, Mn, and Fe) in soil samples was analyzed using atomic absorption spectrophotometry. Activity levels of glutathione S-transferase (GST) and acetylcholinesterase (AChE), indicators of oxidative stress and neurotoxicity, respectively, were measured in snails collected from each site. GST and AChE activity were found to vary between sites and by season. The highest levels of GST activity were registered during the summer at sites closest to potential sources of pollution. AChE activity levels also peaked during the summer with the highest values recorded at the site in El Hadjar. These increased levels of bioindicative stress response correlated with increasing metal concentration in soil samples collected at each site.     

Distribution and Environmental Risk Assessment of Heavy Metal in Surface Sediments and Red Mullet (<Emphasis Type="Italic">Mullus barbatus</Emphasis>) from Algiers and BouIsmail Bay (Algeria)

BouIsmail (BIB) and Algiers (AB) are the most important bays in Algeria, where busy shipping activities and various industry complexes introduce different pollutants including heavy metals to the aquatic environment. The main goal of this study was to assess the contamination levels of heavy metals (Cd, Cr, Cu, Fe, Hg, Mn, Pb, Zn) in surface sediments and red mullet (Mullus barbatus) of the BIB and AB and to examine the possibility of the use of their enrichment factors (EFs) to track down the sources of metals (natural processes or human activity). The geoaccumulation index (I _geo) was calculated as a criterion to indicate the contamination level for each heavy metal. Moreover, geographical information systems based on spatial analysis methods (inverse distance weighting (IDW)) and statistical approaches (the principal component (PCA)) were performed to assess the spatial influences of multiple anthropogenic sources in different sampled areas. The results of both EF and I _geo revealed that the study area is exposed to various anthropogenic activities. The pollution load index (PLI) values of sediment samples in the different sites of Algiers and BIB ranged from 0.2 to 3.4 illustrating highly contaminated sediments. Significant bioaccumulation of Cd, Cu, Hg, Pb, and Zn (bioaccumulation factor >100%) were observed in muscle and liver of red mullet, suggesting potential health risks through consuming this fish species.     

Assessment of trace element contamination in sediment cores from the Pearl River and estuary,South China: geochemical and multivariate analysis approaches

Twenty-four major and trace elements and the mineralogical composition of four sediment cores along the Pearl River and estuary were analyzed using ICP-AES, ICP-MS, and X-ray diffraction (XRD) to evaluate contamination levels. The dominant minerals were quartz, kaolinite, and illite, followed by montmorillonite and feldspars, while small amounts of halite and calcite were also observed in a few samples. Cluster analysis (CA) and principal component analysis (PCA) were performed to identify the element sources. The highest metal concentrations were found at Huangpu, primarily due to wastewater treatment plant discharge and/or the surreptitious dumping of sludge, and these data differed from those of other sources. Excluding the data from Huangpu, the PCA showed that most elements could be considered as lithogenic; few elements are the combination of lithogenic and anthropogenic sources. An antagonistic relationship between the anthropogenic source metals (K, Ba, Zn, Pb, Cd, Ag, Tl, and U) and marine source metals (Na, Mg, Ti, V, and Ca) was observed. The resulting normalized Al enrichment factor (EF) indicated very high or significant pollution of Cd, Ag, Cu, Zn, Mo, and Pb at Huangpu, which may cause serious environmental effects. Conflicting results between the PCA and EF can be attributed to the background values used, indicating that background values must be selected carefully.     

Assessment of some heavy metals in surface sediments of the Aqaba Gulf, Egypt

Aqaba Gulf is an economically important marine environment in Egypt. Its coastal area was subjected to anthropogenic impact of urbanization and economic development during the last decades. The study was oriented to investigate the distribution as well as assess the heavy metal pollution status (Fe, Mn, Zn, Ni, Co, Cr, Cu, and Cd) in its surface sediment. Large heavy metals fluctuations were detected along the studied area. The results pointed out to the highly significant correlations among Fe, Cu, Ni, and Co heavy metals and their similar lithogenic origin beside their input sources. The sediment quality was performed by using the geo-accumulation index (I (geo)) and different sediment criteria guidelines; China State Bureau of Quality and Technical Supervision (CSBTS), and Canadian guidelines. Among the studied heavy metals, Cd was the only metal that showed moderate pollution for I (geo) as well as it exceeded the primary and the secondary criteria of CSBTS and the threshold effect level of the Canadian guidelines (TEL). On the other hand, the other heavy metals were within the natural background levels.     

Heavy metals partitioning in sediments of the Kabini River in South India

Cu, Cr, Fe, Mn, Ni, Pb, and Zn in the sediments of the Kabini River, Karnataka, India was studied to determine the association of metal with various geochemical phases by sequential extraction. The variations of heavy metal concentration depend on the lithology of the river basin and partly on anthropogenic activities. The Kabini River sediments are dominated by Sargur supracrustals with amphibolites, gneisses, carbonates, and ultrabasic rocks weathering into gneissic and serpentine soils carrying a natural load of cationic heavy metals. The source of heavy metals in the Kabini riverbed sediments is normally envisaged as additional inputs from anthropogenic over and above natural and lithogenic sources. Geochemical study indicates the metals under study were present mostly in the least mobilizable fraction in the overlying water and it is concluded that heavy metals in these sediments are to a great extent derived from multisource anthropogenic inputs besides geochemical background contributions The results show that lead and chromium have higher potential for mobilization from the sediment due to higher concentration at the exchangeable ion and sulfide ion bounded, also Cu and Pb have the greatest percentage of carbonate fraction, it means that the study area received inputs from urban and industrial effluents. Association of the Fe with organic matter fraction can be explained by the high affinity of these elements for the humic substances. Further, Zn and Ni reveal a significant enrichment in sediment and it is due to release of industrial wastewater into the river. These trace metals are possible contaminants to enter into aquatic and food chain.     

A 100 year sedimentary record of heavy metal pollution in a shallow eutrophic lake, Lake Chaohu, China

This study has worked on the evaluation of the temporal and spatial evolution of heavy metal contamination in sediment taken from a shallow eutrophic lake, Lake Chaohu, China, over the last 100 years, and thereby used (137)Cs and (210)Pb dating, a PIRLA procedure, statistical analysis, geochemical normalization and a enrichment factor calculation (EF). Concentrations of 5174, 29?325, 10.7, 36.4, 20.4, 386.0, 21.1 and 38.4 mg kg(-1) for Ti, Fe, Co, Cr, Cu, Mn, Pb and Zn, respectively, are proposed as natural background values for the Lake Chaohu based on a PIRLA procedure. The contamination history from the last 100 years can be divided into two periods. Before the 1960s, heavy metal contamination did not occur and there was no spatial difference for heavy metal distribution. Since the 1960s, heavy metal enrichment and contamination has occurred, and the west half of the lake region showed a higher degree of contamination than the east half to various intensified anthropogenic activities. In the east half of the lake region, the anthropogenic source of heavy metals mainly originated from agricultural intensification, whereas in the west half of the lake it originated from city runoff and industry as well as agriculture. In all anthropogenic heavy metals, Co is only from industry.     

Heavy metal and polycyclic aromatic hydrocarbons in Ebrié lagoon sediments, Côte d’Ivoire

Surface sediments throughout Ebrié lagoon, Côte d’Ivoire were collected in 2001 and analyzed for their heavy metal and polycyclic aromatic hydrocarbons (PAH) contaminant content. Geochemical maps of heavy metals (Cd, Cu, Zn, Fe, and Mn) in the surface sediment were produced based on geographical information system (GIS) technology. Heavy metals and PAH were detected at high concentration and provide evidence for several anthropogenic inputs to the lagoon. A significant spatial relationship was found for Fe, Zn, and Cu in the sediment using a GIS-based analysis, suggesting that these metal contaminants in the sediments of the Biétri bay had common sources.     

Distribution, speciation, and risk assessment of selected metals in the gold and iron mine soils of the catchment area of Miyun Reservoir, Beijing, China

In order to investigate the metal distribution, speciation, correlation and origin, risk assessment, 86 surface soil samples from the catchment area around the Miyun Reservoir, Beijing, including samples from gold and iron mine areas, were monitored for fractions of heavy metal and total contents. Most of the metal concentrations in the gold and iron mine soil samples exceeded the metal background levels in Beijing. The contents of most elements in the gold mine tailings were noticeably higher than those in the iron mine tailings. Geochemical speciation data of the metals showed that the residual fraction dominated most of the heavy metals in both mines. In both mine areas, Mn had the greatest the acid-soluble fraction (F1) per portion. The high secondary-phase fraction portion of Cd in gold mine samples indicated that there was a direct potential hazard to organisms in the tested areas. Multivariate analysis coupled with the contents of selected metals, showed that Hg, Pb, Cr, and Ni in gold mine areas represented anthropogenic sources; Cd, Pb, and Cr in iron mine areas represented industrial sources. There was moderate to high contamination of a few metals in the gold and iron soil samples, the contamination levels were relatively higher in gold mine than in iron mine soils.     

Risk assessment of heavy metals in road and soil dusts within PM2.5, PM10 and PM100 fractions in Dongying city, Shandong Province, China

15 road and 14 soil dust samples were collected from an oilfield city, Dongying, from 11/2009-4/2010 and analyzed by inductively coupled plasma-mass spectroscopy (ICP-MS) for V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd and Pb within PM(2.5), PM(10) and PM(100) fractions synchronously. Metal concentrations, sources and human health risk were studied. Results showed that both soil and road dust exhibited higher values for Mn and Zn and lower values for Co and Cd for the three fractions. Mass concentration ratios of PM(2.5)/PM(10) and PM(10)/PM(100) for metals in road and soil dust indicate that most of the heavy metals tend to concentrate in fine particles. Geoaccumulation index and enrichment factors analysis showed that Cu, Zn and Cd exhibited moderate or heavy contamination and significant enrichment, indicating the influence of anthropogenic sources. Vanadium, Cr, Mn and Co were mostly not enriched and were mainly influenced by crustal sources. For Ni, As and Pb, they ranged from not enriched to moderately enriched and were influenced by both crustal materials and anthropogenic sources. The conclusions were confirmed by multivariate analysis methods. Principle component analysis revealed that the major sources were vehicle emission, industrial activities, coal combustion, agricultural activities and crustal materials. The risk assessment results indicated that metal ingestion appeared to be the main exposure route followed by dermal contact. The most likely cause for cancer and other health risks are both the fine particles of soil and road dusts.     

Sources and the distribution of heavy metals in the particle size of soil polluted by gold mining upstream of Miyun Reservoir,Beijing: implications for assessing the potential risks

Mining has been carried out upstream of Miyun Reservoir, Beijing, for several decades, and has caused metal emissions to the environment, threatening human health. We conducted a soil survey to assess metal contamination in this area and to determine distribution of heavy metals in the particle size. We attempted to determine the possible sources of the metals and the significance of metals in the fine particle fractions to soil risk assessments. Thirty-four soil samples were collected, and eight samples were partitioned into seven size fractions. Most of the metal concentrations in the soils were higher than the background levels in Beijing, and the metal concentrations and total organic matter (TOC) contents generally increased as the particle size decreased. Each metal except Hg significantly positively correlated with the TOC. The metals in the coarse-grained soils were mainly derived from parent materials, but the metals in the fine fractions were mostly anthropogenic. Statistical analyses showed that there were three metal sources: Cd, Cu, Hg, Pb, and Zn had anthropogenic sources; Co, Cr, Ni, and V had mixed anthropogenic and natural sources; and As and Be had natural sources. The trace metals were primarily in the clay and fine silt fractions, and they might pose health risks through the inhalation of resuspended soil particles (PM10 and PM2.5). The elevated accumulation factors, enrichment factors, and ecological risk indices for the metals in the fine fractions suggest that risk assessments should be based on the fine particle size.     

Heavy metals concentration in soils of southeastern part of Ranga Reddy district, Andhra Pradesh, India

There is a growing concern over the potential accumulation of heavy metals in soils owing to rapid industrial and urban development and increasing reliance on agrochemicals in the last several decades. These metals can infiltrate through the soil thereby causing groundwater pollution. Surface soil samples (5 to 15 cm) collected from southeastern part of Ranga Reddy district were analyzed for 14 heavy metals (As, Ba, Co, Cr, Cu, Mo, Ni, Pb, Rb, Sr, V, Y, Zn and Zr) using Philips PW 2440 X-ray fluorescence spectrometer. Results for heavy and trace elements are reported for the first time in soils for this region. The contamination of the soils was assessed on the basis of enrichment factor (EF), geoaccumulation index (I (geo)), contamination factor and degree of contamination. The results reveal that variations in heavy element concentrations in the soil analyzed have both geogenic and anthropogenic contribution, due to the long period of constant human activities in the study area. The concentration of the metals Ba, Rb, Sr, V, Y and Zr were interpreted to be mainly inherited from parent materials (rocks) and the As, Co, Cr, Cu, Mo, Ni, Pb and Zn concentrations show contribution from geogenic and anthropogenic sources. The major element variations in soils are determined by the composition of the parent material predominantly involving granites.     

Multivariate statistical analysis of heavy metals in soils of a Pb–Zn mining area, India

Surface soil samples collected from a Pb and Zn mining area in India were subjected to multi-elemental analysis by using inductively coupled plasma-atomic emission spectrometry. Multivariate statistical methods such as principal component analysis and cluster analysis, coupled with correlation coefficient analysis, were used to analyze the data and to apportion the possible sources of elements in soils of a metal mining area. Soils in this area have elevated heavy metal concentrations especially Pb, Zn, Mn, Cu, As, and Tl. Using principal component (PC) analysis, six components were extracted, out of which two PCs explaining 50.12% of total variance are more important. The first principal component with a high contribution of Ag, As, Be, Cd, Co, Cu, Mg, Mn, Ni, Pb, and Zn was deemed to be technogenic/anthropogenic component, and the second principal component, with high loadings for the five discerning variables (Al, Be, Cr, K, Li), was considered as lithogenic component. The third component having strong loadings of Ba, Ca, K, and Na is supposed to have a mixed origin (lithogenic as well as technogenic). Electrical conductivity and total organic matter were not correlated with any element and also have a strong loading in the fifth component which is probably the biomass and ions present in these soils. The findings of the principal component analysis were also substantiated by the cluster analysis. The present study would not only enhance our knowledge regarding the soil pollution status in the study area but would also provide us information to manage the sources of these elements in the study area.