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Multivariate Statistical and GIS-based Approach to Identify Heavy Metal Sources in Soils
Abstract
The knowledge of the regional variability, the background values and the anthropic vs. natural origin for potentially harmful elements in soils is of critical importance to assess human impact and to fix guide values and quality standards. The present study was undertaken as a preliminary survey on soil contamination on a regional scale in Piemonte (NW Italy). The aims of the study were: (1) to determine average regional concentrations of some heavy metals (Cr, Co, Ni, Cu, Zn, Pb); (2) to find out their large-scale variability; (3) to define their natural or artificial origin; and (4) to identify possible non-point sources of contamination. Multivariate statistic approaches (Principal Component Analysis and Cluster Analysis) were adopted for data treatment, allowing the identification of three main factors controlling the heavy metal variability in cultivated soils. Geostatistics were used to construct regional distribution maps, to be compared with the geographical, geologic and land use regional database using GIS software. This approach, evidencing spatial relationships, proved very useful to the confirmation and refinement of geochemical interpretations of the statistical output. Cr, Co and Ni were associated with and controlled by parent rocks, whereas Cu together with Zn, and Pb alone were controlled by anthropic activities. The study indicates that background values and realistic mandatory guidelines are impossible to fix without an extensive data collection and without a correct geochemical interpretation of the data.
... This process involves assessing the soil heavy metal vertical distribution and their speciation by examining heavy metal speciation and content within soil profiles at diverse depths [27,28]. By comparing the heavy metal speciation across different soil layers, an initial evaluation of anthropogenic pollution in soils can be identified [29][30][31]. Using isotopes for source identification has become popular recently [31][32][33]. ...
... This observation could be attributed to the following: first of all, Cu, Zn, As, Cd, and Pb of natural origins, such as geological formations, weathering of rocks, and soil mineralization, resulting in similar geochemical behaviors and distributions [7].It was also obtained three components, including industrial sources (Cd, Zn and Pb), nature sources (Cr and Ni) as well as agricultural sources (As and Cu) by using PCA analysis methods [51]. Secondly, human activities like mining, emissions from fossil fuel combustion, industrial processes, and agricultural practices can introduce these metals to the environmental systems through similar pathways, like air deposition, water runoff, and soil contamination [25,29,34]. Additionally, Hg exhibited a different contamination source due to its distinct behavior and sources of release. ...
... It was also obtained three components, including industrial sources (Cd, Zn and Pb), nature sources (Cr and Ni) as well as agricultural sources (As and Cu) by using PCA analysis methods [51]. Secondly, human activities like mining, emissions from fossil fuel combustion, industrial processes, and agricultural practices can introduce these metals to the environmental systems through similar pathways, like air deposition, water runoff, and soil contamination [25,29,34]. Additionally, Hg exhibited a different contamination source due to its distinct behavior and sources of release. ...
Heavy metal pollution in agricultural soil has been tightly associated with anthropogenic emissions. Although there are many studies that focus on a regional scale, the source identification of heavy metal contamination on a field scale around industrial areas remains unclear. The average concentrations in topsoils of Hg, Cd, As, Pb, Cr, Ni, Zn, and Cu were 2.07, 0.13, 8.56, 42.3, 81.1, 37.3, 105, and 43.8 mg kg⁻¹, respectively. The enrichment of Hg was particularly presented on topsoils, with the highest single pollution index (Pi) (9.00) and ecological risk index (Eri) (922) values. An integrated methodology was employed in source identification of heavy metals contamination, especially for Hg, including Pearson’s and PCA analysis, soil profile morphology, mathematical modeling, and Hg isotope analysis. Results revealed that the concentrations of Hg decreased as a function of depth, suggesting Hg contamination was an anthropogenic source and can be supported by Hg isotope analysis. The negative Δ¹⁹⁹Hg values of the residual Hg (F4-Hg) and soil profile in 80–100 cm deviate from those of the soil profiles in 0–80 cm, indicating exogenous input of Hg occurred in the study area. According to the UNMIX model, the contribution of coal combustion, agricultural activities, parent material, and industrial/traffic emissions to Hg accumulation in soils were 66.2%, 16.9%, 9.81%, and 7.0%, respectively. However, the contribution rates calculated with the PMF model of mixed industrial source, traffic emissions, and parent material were 71.4%, 27.8%, and 0.8%, respectively. This study can accurately quantify and identify the factors contributing to heavy metal contamination in agricultural soil on a field scale.
... Heavy metals are generally present in soils in cationic forms and therefore they may show low availability even at high total concentrations, since they interact with the soil matrix. However, they can become mobile as a result of changing environmental conditions or by saturation exceeding the buffering capacity of a soil, a situation referred to as "chemical time bomb" (Facchinelli et al. 2001). ...
... Therefore, factor and principal component analyses (FA and PCA) have been widely used to reveal variable redundancy, and combine variables into single factors (Wilcke et al. 1998;Chen et al. 1999;Kumru and Bakac 2003;Navas and Machin 2002;Bretzel and Calderisi 2006). Cluster analysis (CA) is often coupled to FA and PCA to provide groupings of individual variables according to distances or similarity indices (Facchinelli et al. 2001;Granero and Domingo 2002;Manta et al. 2002;Wang et al. 2005;Han et al. 2006). The interpretation of the above data processing aids to identify pollution sources and apportion natural vs. anthropic contribution. ...
... Usually, the ratio of metal concentration in the studied soils divided by the respective mean value for the world unpolluted soils or for the background soils of the region is used (Manta et al. 2002;Cemek and Kizikkaya 2006;. Another common way to express an EF of topsoils, presented as TEF (top enrichment factor) by Facchinelli et al. (2001), is to divide the metal concentration in the surface soil by the respective concentration in the subsurface sample(s). ...
... Distribution of potentially toxic elements (PTE) including heavy metals and metalloids in agricultural soils depends on both geogenic and anthropogenic factors, which act jointly at different spatial and temporal scales (Hu et al. 2017;Liu et al. 2020). Through chemical weathering, erosion and pedogenic processes, PTE of geogenic origin are accumulated in soils and remain there for a long time (Facchinelli et al. 2001;Dai et al. 2018Dai et al. , 2019Bastami et al. 2015). The rate of these physico-chemical processes and that of PTE accumulation in soils are controlled by the local geology, climate and topography (Sollitto et al. 2010). ...
... As a result, univariate statistics would not allow a full characterization of soil PTE. Alternatively, multivariate statistical techniques such as R-mode factor analysis (FA) and hierarchical cluster analysis (HCA) that reduce large datasets into a few interpretable factors or groups without losing important information have been popularly used in environmental studies to characterize soil geochemistry (Facchinelli et al. 2001;Grunsky 2010;Sierra et al. 2014). These techniques also allow identification of natural or anthropogenic sources of pollution in the soil environment (Hernández-Pellón et al. 2018). ...
... Since each PTE might have its own distinctive spatial distribution pattern, it is necessary to characterize spatial correlations of several features simultaneously. As a consequent, a combination of univariate geostatistical techniques with FA has been successfully used to differentiate the relative contribution of anthropogenic inputs and pedogeochemical background levels to element abundance in soils (Facchinelli et al. 2001;Chowdary et al. 2005;Ali et al. 2016). Thus, a geostatistical technique can be applied to factor scores, which reflect the importance of each factor, or processresponse relationships at given sampling points. ...
Burkina Faso faces a major challenge of environmental degradation due to a booming of gold mining. To date, there is no available information regarding soil geochemical status of this rapidly transitioning land use from merely subsistence agriculture to market gardening and artisanal gold mining. Therefore, this case study investigates distribution of 13 potentially toxic elements in soil exposed to different land-uses. For that purpose, 226 topsoil samples were collected in a grid of 200 m × 200 m, and their pseudototal concentrations were determined by inductively coupled plasma mass spectrometer. Univariate statistics, multivariate and geostatistical techniques showed that chemical weathering of parent bedrocks contributed to La, Tl, Th, U and Ti distribution in the soil, whereas that of Au, Hg and Te were controlled by artisanal gold mining. Laterization of basaltic rocks appeared to be the main source of V, Ga and Sc. In contrast, spatial distribution of Sr and Ba might be attributed to application of inorganic fertilizers and agrochemicals and, to lesser degree, parent materials. The results of multivariate analyses were corroborated by the interpolated factor score maps. The high concentrations of V, Sc, Bi, Hg and Sb above the mean upper continental crust composition and world-average soil concentrations are likely to pose serious threats to human. The study showed that the soil geochemistry is affected by both geogenic and anthropogenic sources. Thus, understanding geochemical status of the soil is vital for developing sustainable agricultural practices and environmental protection schemes in the area.
... The contamination of rivers with Zn, Pb, and Cu in river systems is largely attributed to anthropogenic sources (Qiao et al. 2013;Xia et al. 2018). Additionally, Pb in soil is predominantly linked to human activities, as demonstrated by a study in North-West Italy (Facchinelli et al. 2001). The transport of Pb-laden soil through surface runoff further contributes to sediment contamination in the rivers. ...
... Factor scores are indirect estimates of contamination obtained from PCA for the respective PCs, where higher factor score indicate a deterioration in environmental quality (Wan et al. 2013;Prieto-Amparán et al. 2018). To understand the spatial distribution of the factor scores, and their multivariate relationships and to make the essential comparison, it was interpolated in the entire watershed (Facchinelli et al. 2001;Yang et al. 2020). IDW interpolation of factor scores revealed that the heavy metals on PC1 (Cr, Ni, Cu partly) exhibited a higher accumulation of the factor scores (> 1) in the lower Chao Phraya River sediment (Fig. 3). ...
Purpose
Sediment contamination by heavy metals, and nutrients has been evident in the riverine ecosystems, while their source apportionment, and spatial distribution are complicated to understand. This study aimed to identify the sources, and spatial heterogeneity of heavy metals and nutrients through the adoption of integration approaches that could analyze their patterns, improve understanding of dynamics, and provide insights to enhance decision-making in conserving rivers.
Materials and methods
Surface sediment samples (n = 184) were collected and analyzed from the eight different rivers in the Great Chao Phraya River network, Thailand. Principal Component Analysis (PCA) was employed in identifying the sources, while its integration with Inverse Distance Weighting (IDW), and Geographically Weighted Regression (GWR) were executed in exploring the spatial heterogeneity of contaminants. A large pool of explanatory variables, including natural and anthropogenic factors were utilized in the geospatial regression using a multiple GWR model.
Results and discussion
The PCA revealed that Cr, Ni, and Cu (partly) were potentially sourced from natural/lithogenic origin; Cu, Cd, Zn, and Pb from anthropogenic sources; Hg and As from mining and industries; and the nutrients (TC, TN and TP) from domestic activities and agriculture. An integration approach of PCA with IDW showed that the loadings of the sediment-associated heavy metals, and nutrients increased towards the downstream (0 ~ 4), which aligns with the degree of anthropogenic influences. The local explanatory power of GWR was highest for PC4 (< 0.4), and PC1 (< 0.37), followed by PC2 (< 0.21) and PC3 (< 0.2). Clear spatial patterns of higher local R² values in the lower Chao Phraya were detected, except for PC4 (Hg, As). Although comparatively lower local R² values were noted, the random distribution of the local residuals underscored the good performance of the GWR model. The linear relationships of the local coefficients along the urbanization gradient demonstrate that urban land use is a dominant factor impacting sediment quality.
Conclusions
This study illustrated that the integration of multivariate analysis, and geospatial approaches provides meaningful insights into understanding the sources, spatial dynamics of sediment contaminants, and the influencing factors. Moreover, the higher performance of the GWR model with increasing levels of urbanization possibly implied the better suitability of using the GWR model in developed watersheds. Future studies should test the different integration approaches, which could offer valuable insights into understanding the spatial characteristics of sediment quality.
... Principal component analysis (PCA) is commonly used to reduce the dimensionality of multivariate data, identifying significant patterns and relationships among heavy metal variables [16][17][18][19][20]. However, conventional PCA may overlook spatial heterogeneity, limiting its effectiveness. ...
... A regional-scale soil contamination survey conducted in Piemonte, Italy, utilizing PCA and cluster analysis, identified heavy metal sources and assessed their natural or artificial origin. The study found that parent rocks influenced Cr, Co, and Ni, while Cu, Zn, and Pb were primarily linked to human activities [20]. ...
This study investigates spatial distribution and chemical elemental composition screening in soils in Rome (Italy) using X-ray fluorescence analysis. Fifty-nine soil samples were collected from various locations within the urban areas of the Rome municipality and were analyzed for 19 elements. Multivariate statistical techniques, including nonlinear mapping, principal component analysis, and hierarchical cluster analysis, were employed to identify clusters of similar soil samples and their spatial distribution and to try to obtain environmental quality information. The soil sample clusters result from natural geological processes and anthropogenic activities on soil contamination patterns. Spatial clustering using the k-means algorithm further identified six distinct clusters, each with specific geographical distributions and elemental characteristics. Hence, the findings underscore the importance of targeted soil assessments to ensure the sustainable use of land resources in urban areas.
... These sources encompass mining, the combustion of fossil fuels, extensive utilization of phosphate fertilizers and certain pesticides, wastewater irrigation, as well as the involvement of industries like paints and dyes, cement and printing, and leather tanning. Additionally, the improper disposal of electronic wastes (e-wastes) such as batteries and circuit boards further contributes to HMs pollution (Facchinelli et al. 2001);Al-Khashman and Shawabkeh 2006;Su et al. 2014 andTopalidis et al. 2017). ...
... Coatings containing lead in soil, as well as lead-containing fuels, engine oils, pesticides and incinerators contribute to lead pollution [8]. Facinelli et al. (2001) clarified that naturally occurring and continuously low heavy elements resulting from weathering and pedogenic processes in the parent rocks [9,10]. Lead Pb melts at 327.5°C [11]. ...
The experiment was conducted in the laboratories of the University of Agriculture in Basra University. The study included investigating the behavior of lead adsorption in soil samples at equilibrium conditions and factors affecting adsorption by organic residues (animal and plant) Soil samples were taken from two different locations in Basra State (Al-Zubair and Kutayban). A laboratory experiment was conducted in which five volumes of mg L -1 of lead (20-40-80-160-200) were added to each soil sample, with three modified for the Langmuir and Freundlich equations of the adsorption system was used to describe the nature of lead adsorption in the soil sample under investigation. The study concluded that the rate of adsorption increased with increasing amount of lead added, and the change in soil adsorption capacity was responsible for differences in chemical and physical properties of experimental soil of the species, represented by calcium carbonate concentration, organic matter, clay content and type, pH, and ionic strength. EDN: OIJERN
... Whereas they are of benefits to plants in certain amounts and toxic beyond certain thresholds and disadvantages of their non-biodegradability and a tendency to persist in the soil [1]. Some heavy metals like lead and cadmium are likely to cause adverse effects to plants, animal and humans" life especially on long time exposure [2], [3] and through the food web of plants; [4], [5]. Heavy metals in soil may cause a probable threat that may negatively impact sustainable crop production globally. ...
This study assessed the levels of lead, zinc, copper, chromium, cadmium, nickel, iron, and manganese in soil samples from ten specific sites within the Athi-Thwake River catchment area in November 2021 and January 2022, representing the wet and dry seasons respectively in Makueni County. The samples were analyzed using an Atomic Absorption Spectrophotometer (AAS) and data by IBM SPSS 20. The metal levels ranged from 0.10 ± 0.03 mg/kg - 188.02 ± 3.69 mg/kg. In the dry season, the order of metal levels was iron > lead > zinc > manganese > copper > chromium > cadmium > nickel these values were compared with the World Health Organization (WHO) recommended limits for soil quality. Zinc and copper levels were within the WHO limits of 5.0 mg/kg and 10 mg/kg, respectively. However, the mean levels of lead, cadmium, nickel, iron, and manganese in both the wet and dry seasons showed significant differences (p<.05) and exceeded WHO limits of 0.1 mg/kg, 0.1 mg/kg, 0.003 mg/kg, 0.05 mg/kg, 55 mg/kg, and 0.5 mg/kg, respectively, while copper and chromium showed no statistical significance (p>.05). The study revealed the importance of conducting thorough soil analysis, specifically focusing on heavy metals in the ten selected sites. The study showed the presence of high levels of these metals in soil in the catchment area and this could be impacting negatively on the ecosystem health of the area.
... SPSS version 23 statistical package and software Excel 2010 were used for data analysis. Analyses of the experimental data were carried out by using Pearson correlation matrix, Hierarchical Cluster Analysis, Principal Component Analysis (PCA) and Factor Analysis (FA) methods (22,23) . ...
... Additionally, hydrothermal activities related to Red Sea rift tectonics have further enriched localized zones with these metals [2,4,11]. Conversely, PC2 revealed inverse relationships between Fe, Pb, and Cd with Co and, to a lesser extent, Zn, suggesting differing environmental behaviors or anthropogenic sources [47]. The weaker positive loadings of Zn and Co on PC2 may indicate distinct geochemical processes or secondary sources contributing to their presence. ...
This study provides a comprehensive assessment of environmental and human health risks associated with potentially toxic elements in the coastal sediments of the Gulf of Aqaba. A total of 33 sediment samples were analyzed using inductively coupled plasma mass spectrometry, revealing Fe (1,526–5,123 mg/kg), Zn (16.8–32.0 mg/kg), Pb (3.5–9.1 mg/kg), Co (2.2–6.4 mg/kg), and Cd (0.05–0.18 mg/kg). The concentrations detected were within acceptable limits and below the Interim Sediment Quality Guidelines, indicating minimal environmental risk. Environmental indices, including the pollution index, modified contamination degree, pollution load index, hazard index, and lifetime cancer risk indicate no contamination or health risks for adults or children through ingestion and dermal contact pathways. Principal component and correlation analysis suggest that Fe, Zn, and Co primarily originate from natural geological processes due to their strong association with elements typically derived from bedrock weathering, while minor anthropogenic contributions may arise from tourism and coastal activities. The findings confirm that the sediments pose no environmental or health risks, providing a baseline for future monitoring and pollution management in the Gulf of Aqaba.
... Defining the distribution of chemical elements and their anomalies, as well as understanding the nature of the factors controlling their spatial variability, is essential for those committed to environmental management, particularly when addressing the effects on ecosystems and living beings to target the development of remedial actions. In this framework, it is crucial to understand the apportionment of inputs [6] to focus on multi-elemental associations, which could be used as practical markers for mineralized areas [32,33] and to highlight geochemical anomalies related to the geology and mineralization of the underlying bedrock [34]; it also helps identify and distinguish the different origins of specific minerals based on their chemical composition, allowing one to trace the provenance and therefore identify potential hidden mineralized areas [35]. Also, the study of geochemical processes that regulate the compositional evolution of magma has benefited from the application of PCA [36]. ...
Environmental risks often stem from contamination driven by chemical stressors introduced from multiple sources, either geogenic or anthopogenic. Differentiating between anthropogenic chemical anomalies and those inherent to the environment is crucial. This distinction is essential for defining feasible remediation objectives. This study applied univariate and multivariate statistical techniques to analyse geochemical data from over 7000 topsoil samples in Campania (Southern Italy), over an area of approximately 13,600 km². A key step in the methodology was applying Normal Score Transformation (NST), which stabilized the variance of the dataset, pulling the extreme outliers back to normal ranges, making it more suitable for multivariate analysis. Principal Component Analysis (PCA) was performed, and four components were selected; the spatialization of their scores revealed four primary independent sources controlling geochemical variability across the region. Specifically, two distinct volcanic districts were identified, plus a siliciclastic and an anthropogenic component. The integration of RGB composite maps further refined this differentiation, emphasising the coexistence or the predominance of one component over the other. The methodological approach demonstrated here provides valuable insights for environmental risk assessment and remediation planning in geochemically complex and anthropized regions.
... Heavy metal pollution has become a crucial issue in soil (Facchinelli et al. 2001), and one of the most exposed regions to this problem is the soil in the protected forest areas, such as National Parks (NPs), biosphere reserves (Ratko et al. 2011;Toma skin et al. 2013), etc. This leads to a decline in soil quality, functioning, and property (Lang et al. 2017;Huang et al. 2019), which is harmful to living biota, mainly via their impacts on the soil-plant-atmosphere continuum and soilcrop-food web (Shen et al. 2017). ...
Soil forms an integral component of terrestrial ecosystems and regulates its well-being. Despite the abundant literature on the concentration of metals in several soil types in India, their values in the forests are mostly unreported. To address this knowledge gap, in this study, we assessed the vertical proBles of several metals including lead (Pb), potassium (K), boron (B), manganese (Mn), iron (Fe), nickel (Ni), cadmium (Cd), chromium (Cr), cobalt (Co), zinc (Zn), magnesium (Mg), mercury (Hg), silver (Ag), copper (Cu) and arsenic (As), in a pristine forest using the ICP-OES technique. Our study site is the Kaziranga National Park, a major forest in northeast India, the region with above-average forest cover in the country. For a comprehensive understanding, we have computed multiple indices, including the elemental enrichment factor (EF), geo-accumulation index (I geo), contamination factor (C f), pollution load index (PLI), and ecological risk. We find a significant accumulation of heavy metals in the topsoil, several times higher than the deeper layers, due to a high amount of undecomposed soil organic matter, which binds well with heavy metals. The estimated mean potential ecological risk index shows the forest floor to be highly polluted by several heavy metals.
... The Box-Cox transformation was used to obtain normal distributions. Multivariate R-mode factor analysis was used to reveal the relationships between the chemical elements (Facchinelli et al., 2001). Factor analysis was performed with variables standardised to a mean of zero and a standard deviation of one unit (Reimann et al., 2002). ...
... The study of the spatial distribution of both heavy metals and potentially toxic elements in soil samples is extremely valuable in order to identify hot-spot areas and assess the potential sources of pollutants [16][17][18]. Therefore, the purpose of this research was to investigate, through discriminant analysis, the spatial variability and pollution sources of potential toxic elements in Ulaanbaatar surface soil in order to identify hot-spot areas and assess the potential sources of pollutants. ...
In this work we investigated, through discriminant analysis, the spatial variability and pollution sources of potential toxic elements in Ulaanbaatar surface soil. The total concentration of potential toxic elements in urban surface soil samples, collected depending on pollution sources, were determined by using a rational scheme of chemical analysis of urban soils for ecological monitoring. It was found that the average concentration of B, Cr, Pb, Sn, Zn, Cu, Bi, Ag and Sb were all higher than their background values, while average concentration of Li, Ni, Co, V and Cd were comparatively lower. Urban surface soil samples had varying concentration levels of Ag, B, Bi, Cd, Cr, Cu, F, Ge, Mo, Pb, Sb, Sn and Tl, and identical levels of concentration of As, Co, Ni, Zn, Li, V and Mn. As per the results of the Kruskal–Wallis rank test, the surface soil in the ger (traditional round felt dwelling) area (A) and the main road (B) is highly polluted with Pb, Cu, Zn, Cr, MO, Sn, Bi, Ag and Sb. A stepwise selection of the spatial discriminant analysis shows that, Cr, Cu, Ge, Mo, Pb, Sb, Tl and V are most significant variables. These selected variables clearly discriminates the soil groups of the ger area (A) such as Khailaast, Chingeltei and Bayanzurkh, the main road (B) namely, along the central transport routes and in the vicinity of the bus stations and around the power plant and industrial area (C) with 71 per cent total success rate of classification.
... The cracking and withering of paint on roadside structures releases lead into the soil and atmosphere, creating health risks for both humans and animals. Studies have shown a direct link between the close proximity of roadways with Pb-painted structures and increased Pb concentrations in nearby soil [86,87]. Contact with Pb-contaminated air and soil near these structures has extremely serious health consequences. ...
One major environmental concern is the lead (Pb) pollution from automobile traffic, especially in highway-side grazing areas. Sheep grazing in Pb-contaminated areas are particularly vulnerable because Pb exposure from soil, water, and feed can have harmful effects that impair their general health, reproductive capability, and immune systems. Long-term hazards to cattle from persistent Pb exposure include neurotoxicity, hematological abnormalities, reproductive health problems, and immunosuppression. These can have serious consequences, such as reduced productivity and even mortality. Additionally, through the food chain, Pb bioaccumulation in lamb tissues directly endangers human health. Pb poisoning is caused by a variety of intricate mechanisms, including disturbances in calcium-dependent processes, oxidative stress, and enzyme inhibition. To mitigate these risks, an interdisciplinary approach is essential, combining expertise in environmental science, toxicology, animal husbandry, and public health. Effective strategies include rotational grazing, alternative foraging options, mineral supplementation, and soil remediation techniques like phytoremediation. Additionally, the implementation of stringent regulatory measures, continuous monitoring, and community-based initiatives are vital. This review emphasizes the need for comprehensive and multidisciplinary methodologies to address the ecological, agricultural, and public health impacts of Pb pollution. By integrating scientific expertise and policy measures, it is possible to ensure the long-term sustainability of grazing systems, protect livestock and human health, and maintain ecosystem integrity.
... Various sources of environmental pollutants and heavy metals enter aquatic ecosystems through industrial and agricultural processes, acid rain, and human and animal waste [19,41]. Pollution of the aquatic environment with heavy metals has become a critical global issue and scientific concern due to their degradability, toxic effects, persistence, and longterm accumulation in living organisms [30,42]. ...
Contamination of aquatic ecosystems with heavy metals poses a significant global issue due to its hazardous effects and persistent accumulation in living organisms. This study analyzed 51 fish samples from two species of Black Fish, Capoeta saadii and Capoeta trutta, collected from Iran’s Khorramroud River during the summer and fall of 2022 to assess heavy metal accumulation in their gill, liver, and muscle tissues. After biometry, the studied tissues of each fish were isolated to measure the concentration of heavy metals (cadmium (Cd), zinc (Zn), chromium (Cr), lead (Pb), copper (Cu), and nickel (Ni)). The tissue concentration of the studied metals was obtained by measuring in the inductively coupled plasma optical emission spectroscopy (ICP-OES) device after chemical digestion. Based on the results of this study, muscle and liver tissues had the lowest and highest accumulation of heavy metals, respectively, with zinc concentration in the liver of C. saadii reaching 118.557 mg/kg, which exceeds the permissible limit of 75 mg/kg. Also, there was no significant correlation between the amount of absorption of heavy elements and the biometric indicators of body weight and length. Although C. saadii accumulated higher levels of Zn, Cu, Cd, and Cr than C. trutta, statistical analysis (ANOVA and PCA) revealed no significant differences in heavy metal accumulation between the two species (P > 0.05). Comparisons with international standards indicated that chromium (2.10–9.97 mg/kg) and zinc concentrations (41.72–118.557 mg/kg) exceeded permissible limits, while Ni, Cu, Pb, and Cr levels remained below the allowable thresholds. These findings underscore the need for strategic planning, management, and continuous environmental monitoring to mitigate heavy metal pollution in aquatic ecosystems and safeguard the health of fish populations in the Khorramroud River.
... With the relentless pace of global urbanization and economic expansion, environmental contamination by heavy metals has escalated, particularly in agricultural, industrial, and mining regions (Facchinelli et al., 2001;Shi et al., 2024;Solgi et al., 2012;Xie et al., 2024aXie et al., , 2024b. These pollutants primarily originate from solid waste landfills, industrial activities, transportation, mining and smelting operations, sewage irrigation, chemical fertilizers, and pesticides (Murtaza et al., 2017). ...
The accelerating pace of global industrialization has intensified the prevalence of heavy metals in various environments, presenting a substantial threat to human health. This comprehensive review synthesizes findings from existing studies on human health risk assessments at heavy metal contaminated sites, mainly spanning 2013–2023. It reveals a concentrated focus on specific heavy metals, predominantly Pb, Cd, Cu, Zn, Cr, Ni, and As, and common exposure pathways, such as soil ingestion, dermal contact, and inhalation. This trend may inadvertently overshadow other significant contaminants and exposure routes, indicating a research bias towards certain metals and pathways. We observe a lack of justification in selecting these metals and pathways in existing research, which raises concerns about potential oversight of other significant contaminants and exposure pathways. This review also sheds light on the varying health risks of different site types, with higher risks observed in e-waste-related areas, mines, landfills, and waste incinerators. By conducting an in-depth analysis of existing literature, this review illuminates the imperative to evolve current risk assessment methods to more accurately mirror the complex and variable nature of environmental contaminants. The findings suggest a need for more diversified and comprehensive approaches in selecting pollutants and exposure pathways in heavy metal risk assessments, aiming to protect vulnerable populations better and inform future research and policy decisions.
... Pearson 相关系数分析重金属元素之间的相关性, 可为判断其是否具有同源性提供一定依据 [13] ;主成分 分析结果可通过将多个变量转变为几类综合因子,有 效判断土壤重金属元素的分类与来源 [35][36] .聚类分析 ...
... Once urban soil becomes polluted, the pollutants often bind with soil organic matter or minerals, rendering them resistant to degradation and artificial removal, complicating recovery efforts. Heavy metals in soil primarily harm the human body through direct exposure, such as skin contact or inhalation [23][24][25][26][27][28][29][30]. Additionally, these metals can enter the human body indirectly through the food chain, thereby posing a significant threat to human health. ...
Urban soil samples were collected from the major heavy industrial city of Baotou in Inner Mongolia, China, to investigate the concentration, spatial distribution, and pollution levels of heavy metals. The study employed the geoaccumulation index (Igeo), ecological risk index, and spatial interpolation methods to comprehensively assess urban soil pollution. The results indicated that apart from arsenic (As) and nickel (Ni), the concentrations of heavy metals such as cadmium (Cd), chromium (Cr), manganese (Mn), mercury (Hg), copper (Cu), zinc (Zn), and lead (Pb) were significantly higher than the corresponding background values in the study areas. According to the geoaccumulation index (Igeo), the overall pollution level in the study area ranged from uncontaminated to low pollution. However, variations existed among different urban districts. Among Baotou’s four main urban areas, the soil pollution level in Kundulun District was notably higher compared to the other three urban areas. Mercury (Hg), lead (Pb), zinc (Zn), and copper (Cu) exhibited relatively higher pollution levels across the four district sites. The observed pollution characteristics are closely linked to the distinct industrial attributes of the urban districts: the Kundulun District of Baotou, Inner Mongolia, is renowned for its significant presence of industrial activities such as steel manufacturing, power generation, and coal combustion. These industries play a crucial role in the local economy but also contribute substantially to heavy metal emissions, leading to notable environmental impacts. Similar to the Kundulun District, the Qingshan District of Baotou, Inner Mongolia, is significantly influenced by industrial activities, which have led to elevated concentrations of certain heavy metals and formed higher potential ecological risk index (PERI) hotspots. Implications and Recommendations. The disparity in industrial activities across the four urban districts of Baotou is a principal factor contributing to variations in pollution levels and ecological risks. In conclusion, this research highlights the necessity of aligning industrial zoning with effective environmental management strategies to combat heavy metal pollution in urban soils. By implementing these integrated approaches, Baotou can safeguard its environment and public health, paving the way for a sustainable future.
... Determining the geochemical background value of Cr is crucial in both environmental science and mineral resource exploration [5,37,38]. In mineral resource exploration, accurately defining the Cr background value is essential for identifying geological anomalies and assessing potential resource deposits [39][40][41]. ...
The geochemical background value of chromium (Cr) serves as a pivotal factor in environmental assessments and mineral exploration endeavors. Traditionally, geochemical background values have been determined using statistical parameters derived from dataset analysis, though this method may possess inherent limitations. In this study, we introduce a novel equation to calculate the geochemical background value of Cr, based on the premise that major elements can effectively delineate the geochemical background for trace elements. Using a dataset encompassing 791 abundance records from rocks, soils, and sediments, we derived and fitted the equation. Our findings revealed that when treating these 791 records as representative of background samples, approximately 95% of the records lie within a logarithmic error of ±0.2 from the calculated values. Based on this observation, we propose adopting a logarithmic error threshold of ±0.2 as a criterion for identifying background samples. To further validate the equation, we tested background samples from diverse regions with varying degrees of weathering. Among the 138 samples analyzed, only two exhibited background values with a logarithmic error exceeding ±0.2 from the measured values, although all samples fell within a ±0.3 error margin. We subsequently applied this equation to the orthopyroxenite and dunite zones within the Pados-Tundra complex, located in the western Kola Peninsula, Russia. According to the ±0.2 logarithmic error criterion, mildly altered orthopyroxenite samples could be deemed as background Cr samples, where certain altered orthopyroxenite samples exhibited a logarithmic error in the ±0.2–±0.3 range. In contrast, altered and mineralized samples in the dunite zone showed a significant deviation beyond the ±0.2 error range, indicating that they should be classified as anomalous Cr samples. This innovative methodology offers a refined approach for background determination and anomaly identification, thereby enhancing mineral exploration and Cr environmental quality assessments.
... It is essential to assess the presence and occurrence possibility of organic and inorganic contaminants within the soil (Sapcanin et al., 2017). Also, the soil may pollute both groundwater and surface water resources, sediments, living organisms, and oceans (Facchinelli et al., 2001;Kumari & Mishra, 2021). Heavy metals are highly nonbiodegradable. ...
Publisher: University of West of England (UWE) Publication year: 2022 Abstract The present study was conducted for the spatial distribution and concentration evaluation of heavy metals, including Cu, Cd, Mn, Fe, Zn, and Pb, within 102 soil samples collected from Kushk Mine in Bafgh, Iran. This work employed hierarchical clustering analysis (HCA), principal component analysis (PCA), and spatial distribution patterns, to perform element distribution evaluation within the area. The distributions of heavy metals in the entire area were exhibited in the form of maps. The average concentrations of Cd, Cu, Mn, Fe, Zn, and Pb were found to be 0.39, 0.26, 5.3, 4.1, 51.9, and 40.9 mg.kg −1 , respectively. Based on the PCA and HCA findings, the heavy metals were divided into two groups. The first group included Pb, Cd, Zn, and Cu. In the first group, altered threshold-surpassing anthropogenic and lithogenic pollution was found to be the main factor accounting for Pb and Zn. The second group involved Fe and Mn, which could be impacted by either anthropogenic and lithogenic factors. Furthermore, the geo-statistical results demonstrated higher contents of the heavy metals in the south of the mine and in the vicinity of the mine tailings. It may be concluded from the results that the heavy metal contents of the area are impacted by anthro-pogenic and lithogenic factors. K E Y W O R D S heavy metals, Latin hypercube, lithogenic, pollution source, Solonchaks, spatial distribution
... In that case, the distribution of this variable is skewed to the right, known as positive skewness, and the skewness value is positive. If it's [58]. Kurtosis measures the peak probability distribution of real-value random variables in comparison to the usual distribution. ...
Using a high-purity germanium detector (HPGe), the natural and artificial radioactivity in soil samples taken from agricultural regions near the Al-Kasak oil refinery were examined. According to estimates, the average specific activities of 226Ra, 232Th, 40K, and 137Cs were 20, 15, 283, and 3.6 Bq kg−1, respectively. The specific activities of 226Ra, 232Th, 40K, and 137Cs in the soil samples were comparatively lower than the average values of these radionuclides worldwide. The investigation also analyzed several radiological hazard indices. The hazard indices calculated in this study were utilized to assess the potential health risks associated with radiation in the soil. The results indicate that these indices are significantly below their permissible limits. Therefore, the soil in the study area does not pose any excessive radiation exposure to the inhabitants and can be safely used as construction material without presenting an immediate radiological threat to the public.
... Multivariate R-mode factor analysis was used to reveal relationships among chemical elements. [29,30] The universal Kriging method with linear variogram interpolation was used to construct the area distribution maps of the analyzed elements and the obtained factor values using seven classes with the following percentile values: 0-10, 10-25, 25-40, 40-60, 60-75, 75-90, and 90-100. ...
A study was conducted to investigate the air deposition and explore the distribution of potentially toxic elements in the Mariovo region, North Macedonia, using moss samples as biomonitors of air pollution. The distribution of 44 chemical elements was detected in 20 moss samples collected in the area. The moss samples were analyzed after microwave digestion using inductively coupled plasma-atomic emission spectrometry (ICP-AES) and inductively coupled plasma-mass spectrom-etry (ICP-MS). It was found that atmospheric deposition for some potentially toxic elements in the moss samples in the study area was influenced only by lithogenic origin. R-mode factor analysis was used to identify and characterize elemental associations. Three factors were separated from the group of macroelements determined by ICP-AES: Factor 1 (Cr, Fe, Ni, V, Al, Zn, Pb, and Li), F2 (Li, Sr, and Ba), and F3 (P, and K); and two associations were separated from the group of trace elements determined by ICP-MS: Factor 1 (Ga, Sc, Ti, Co, Zr, Rb, As, Cs, Ge, Y, Sn, Mo, and rare earth elements-REEs) and Factor 2 (Br, B, Cd, I, and Sb).
... The accumulation risk level of TMs is not only related to their concentrations but also their sources [63]. PCA is usually used to identify the pollutant source [64][65][66]. The results showed that the first two principal components can explain 55.61% of the variable changes ( Figure 4A; Table S4). ...
The distribution of trace metals (TMs) in a continuous water body often exhibits watershed attributes, but the tidal gates of the coastal rivers may alter their transformation and accumulation patterns. Therefore, a tidal gate-controlled coastal river was selected to test the distribution and accumulation risks of Al, As, Cr, Cu, Fe, Mn, Ni, Sr, and Zn in the catchment area (CA), estuarine area (EA), and offshore area (OA). Associations between TMs and bacterial communities were analyzed to assess the feasibility of using bacterial parameters as ecological indicators. The results showed that As and Cr were the key pollutants due to the higher enrichment factor and geoaccumulation index, reaching slight to moderate pollution levels. The Nemero index was highest in EAs (14.93), indicating a higher pollution risk in sediments near tide gates. Although the TM dynamics can be explained by the metal-indicating effects of Fe and Mn, they have no linear relationships with toxic metals. Interestingly, the metabolic abundance of bacterial communities showed good correlations with different TMs in the sediment. These results highlight bacterial community characteristics as effective biomarkers for assessing TM pollution and practical tools for managing pollution control in coastal environment.
... The Spearman correlation analyses were used to indicate the existence of potential relationships among trace elements and basic properties of sediments. The high correlation between metals studied may indicate that the metals come from a similar pollution source and also their common migration [54,65]. The data obtained showed a strong positive correlation between Fe and Mn (r = 0.95, p < 0.01). ...
The enrichment of bottom sediments with trace elements due to anthropogenic factors is of growing concern worldwide. With the development of industry, agriculture, and urbanization, the risk of freshwater contamination with trace elements is increasing. As trace elements are poorly soluble in water, they have a tendency to accumulate in bottom sediments. The study focused on the evaluation of the trace element contents in the surface layer of bottom sediments of Lake Raczyńskie, located in Poland, and assessing the risks posed by these sediments. The pollution of bottom sediments was estimated based on the index of the geo-accumulation (Igeo), enrichment factor (EF), Nemerow multi-factor index (Pn), and pollution load index (PLI). The assessment of environmental risk was evaluated by the potential ecological risk index (RI) and mean PEL quotient method. The results obtained showed that the average contents of Cd, Cu, Ni, Pb, and Zn exceeded the national geochemical background values (Bn), indicating possible enrichment of bottom sediments due to human activity. Only for Mn were the observed contents below the Bn. This evaluation was confirmed by the PLI and Pn values, which indicated sediment pollution from anthropogenic sources. However, the risk assessment by RI and mean PEL showed a low risk of contamination. The results of principal component analysis (PCA) and values of Igeo and EF suggested that Cd, Cu, Mn, and Zn mainly originate from geogenic sources, while Ni and Pb probably come from an unrecognized anthropogenic source. The distribution of Cd, Mn, and Ni depended on the contents of silt and clay fractions. Additionally, organic carbon influenced Cu, Mn, Ni, and Zn contents in bottom sediments.
... This analysis enables the grouping and optimization of similarities among data (Cruz-Cardenas et al., 2017) to understand the variations present within the data set (Kumar et al., 2018). Multivariate analysis is extensively used to interpret environmental data, including differentiation between natural inputs and anthropogenic activities (Facchinelli et al., 2001;Lucho-Constantino et al., 2005;da Silva et al., 2016;Filho et al., 2017), selection or determination of soil, sediment, and air characteristics (Araujo et al., 2013;Khwedim et al., 2015;Singh & Ramanathan, 2015;Junior et al., 2019), identification of sources of water pollution (Delshab et al., 2016;Ezraneti et al., 2021), and evaluation of the structure of mangrove community Efriyeldi et al., 2023). ...
The structure of the plant community significantly influences the equilibrium of the surrounding environment, affecting the trophic interactions within its ecosystem. The investigation of mangrove vegetation in Cut Mamplam village was carried out in September 2021 to determine the condition and structural characteristics of the mangrove ecosystem by multivariate analysis. The mangrove vegetation in Cut Mamplam Village was sampled at three observation stations by establishing a transect parallel to the coast. Subsequently, the community structure was examined and assessed using cluster analysis and nonmetric multidimensional scaling using the PRIMER v7 software. The study findings indicate that the mangrove forest vegetation in Cut Mamplam Village consists of five species from three families. Avicennia alba, A. lanata, Bruguiera gymnorrhiza, Rhizophora mucronata and Sonneratia alba. The highest density of mangrove vegetation was observed in A. alba in all categories: trees (616.67 ind/ha), seedlings (833.33 ind/ha) and saplings (66666.67 ind/ha). Additionally, the highest important value index (IVI) was recorded in A. alba for all categories: trees (232.16%), seedlings (102.40%), and saplings (228.43%). A similarity of mangrove density between species was noted at 60%, resulting in the formation of two distinct groups. Regarding the basal area, the vegetation stands of A. alba and A. lanata exhibited the highest values (280.61 and 266.03 m2/ha, respectively). The similarity of basal area among the observed species was 20%, resulting in the formation of two distinct groups. Additionally, Station II, classified as having mature vegetation, demonstrated a maturity similarity of 80% between observation stations.
... These sources encompass mining, the combustion of fossil fuels, extensive utilization of phosphate fertilizers and certain pesticides, wastewater irrigation, as well as the involvement of industries like paints and dyes, cement and printing, and leather tanning. Additionally, the improper disposal of electronic wastes (e-wastes) such as batteries and circuit boards further contributes to HMs pollution (Facchinelli et al. 2001);Al-Khashman and Shawabkeh 2006;Su et al. 2014 andTopalidis et al. 2017). ...
Resistance mechanisms through tissue culture
... The principal component analysis (PCA), which is a statistical tool commonly used in geochemical studies to simplify the number of variables and to facilitate interpretation of the data (Facchinelli et al., 2001. Liu et al., 2002. ...
The development of the right side of the Senegal River can lead to the degradation of the soils around the neighboring countries. That's the reasons why this study was conducted on the soils of the plain of M'Pourié. A sampling of the soil was done by zig zag method, and carried out on three depths (20, 40 and 60 cm) in the South East area of the plain of M'Pourié. This sample has hydromorphic soils (type pseudo-gley), red brownish color with a granular structure. The study done on this sample is about some physico-chemical parameters (pH, organic matter and texture), major elements and metal traces elements (MTE). The results show that these soils have a silty clay texture and a low average of organic content (1.14%). PH has an acid tendency and this acidity increases with depth (6.74 6.15 and 5.7 respectively for 20, 40 and 60 cm). The major elements have an abundance of aluminum and iron with low concentration of carbonates. The highest MTE are Cr V and Ni while the lowest are Cd, Pb and As. The vertical dynamics of the majority of elements shows a low variability, yet the Cd, Pb and As are more concentrated near the surface (20 cm) the principal component analysis (PCA) shows that most of the MTE is controlled by the aluminum, iron, phosphorus, and calcium, which induces a lithogenic origin. Whereas Cd, Pb and As show a correlation with the organic material assuming, at least in part, a anthropogenic origin (fertilizers). The comparison of the values of ETM soils plain M'Pourié with environmental quality standards TEC and PEC shows contamination by Cd and Ni accompanied by Cr pollution.
... The commercial statistics software package SPSS (v.23.0 for Windows) was used to conduct the data treatment and histogram generation, employing both conventional and 32 Principal component analysis (PCA) is a widely utilized method for summarizing patterns within a multivariate dataset, enabling the identification of underlying patterns among variables and representing data in a manner that emphasizes their similarities and differences. PCA's key advantage is its capacity for data compression by reducing the number of dimensions once the patterns have been identified, while still preserving a substantial amount of information. ...
This investigation assessed the baseline levels of radioactivity in the soil of Daquq district, Iraq, using the GR-460 radiation detection system. ²³⁸ U, ²³² Th, and ⁴⁰ K’s specific activities were measured and the hazard indices’ values determined. The average values of the absorbed dose, annual effective dose equivalent, annual gonadal equivalent dose, and lifetime cancer risk radiological risk factors were estimated. It is important to note that some of these results exceeded the global average levels. Various multivariate statistical techniques were employed to explore the relationships between the radioactive variables and identify potential correlations amongst them. Cluster analysis was utilized to identify clusters or groups of variables that shared similar characteristics. The study aimed to gain insights into the relationships between the radioactive variables and identify any correlations between them. These analyses provided valuable information regarding the associations and patterns within the data, thus contributing to an improved understanding of the radioactive variables and their potential implications.
... Metals are always present at natural non-anthropogenic levels. Their introduction into ecosystem can be from processes as simple as the weathering of parent rocks and pedogenesis, inputting metals into soils and up trophic levels [100]. Wren et al. [101] for example, found different tissue metal concentrations in wild animals such as mink and river otter that can be attribute to natural geological and regional differences. ...
This manuscript reviews the rise of environmental awareness since WWII and the resulting scientific and technological developments implemented since then to ensure healthy populations and a sustainable environment. Essential and non-essential metals are discussed in relation to their positive and negative impacts and their relationship to ecotoxicology, anthropogenic impacts, and natural sources. Metals originating from the environment are re-introduced, often in bioavailable forms from anthropogenic activities. Their movement throughout our natural systems is not always visible, making them difficult to study and understand. Although the effects of individual metals has been studied extensively, the amalgamated effects of multiple metals on individuals are not well understood. There are very few studies on the effects of many metals from multiple trophic levels. Understanding this level of ecotoxicology can be useful in understanding the in-situ effects that urban development and industries such as mining and forestry have on the local environment.
... This concept includes the geogenic natural content (background level) and the anthropogenic contribution to soils (Salminen and Gregorauskiene, 2000;Cicchella et al., 2005;Frattini et al., 2006;Albanese et al., 2007;Galan et al., 2008). Calculating the geochemical baseline is indeed a more practical approach for assessing soil trace element concentrations, in the context of the current global environmental impact, and provide guidelines and quality standards in legislation and policy-making environment (Chen et al., 1999;Facchinelli et al., 2001;Wei and Wen, 2012;Sappa et al., 2020). Despite its importance, there is currently no accepted methodology that determines the background and baseline values, therefore various approaches are used depending on the specific context and objectives of the study (Matschullat et al., 2000;Gałuszka and Migaszewski, 2011). ...
Soil heavy metal contamination is highly persistent and toxic, posing a serious threat to ecological and public health. The objective of this study was to assess the spatial distribution and ecological risks of heavy metals under varied land-use types in Nowshera District, Pakistan. Methods: Seventy-six surface soil samples were systemically collected and analyzed for 14 heavy metals from industrial, urban, rural, and agricultural regions using spectro photometric methods. Mapping and geospatial analyses as utilized by GIS tools uncovered specific contamination hotspots, especially present among both industrial and urban areas, whereby both rural and agricultural regions, showed lower levels of contamination. Industrially associated (lead (Pb), zinc (Zn), and copper (Cu)) and urban-associated activity pollutants (asbestos, Cr, and Pb) enriched their particular areas of the urban area, whereas agricultural soils were enriched in localized black spots of Mn and Cr from agri-chemical usage in the urban-rural transition. The study determined industrial zones as high-risk areas using risk assessment indices, such as the Geo-accumulation Index, Pollution Load Index, and Ecological Risk Index, among others. Moreover, the study showed that the primary contributing elements for ecological toxicity were Cd and Pb. In addition, multivariate studies demonstrated unique groupings, highlighting the source of the metals from industrially produced, lithogenic, and agrochemical origins. Pb was among the metals in industrial soils that outmatched global technological intervention. The study highlights the necessity for focused endeavors to Gul et al., 2025 mitigate risks for heavy metals. Specifically, industrial sites are required to regulate emissions, while urban areas need to manage their waste and traffic. Agricultural regions are required to implement sustainable agrochemicals. Finally, integrating geospatial tools with risk indices can create feasible solutions for targeted policy implementation.
Toxic metal pollution is ubiquitous in soils, yet its worldwide distribution is unknown. We analyzed a global database of soil pollution by arsenic, cadmium, cobalt, chromium, copper, nickel, and lead at 796,084 sampling points from 1493 regional studies and used machine learning techniques to map areas with exceedance of
agricultural and human health thresholds. We reveal a previously unrecognized high-risk, metal-enriched zone in low-latitude Eurasia, which is attributed to influential climatic, topographic, and anthropogenic conditions. This feature can be regarded as a signpost for the Anthropocene era. We show that 14 to 17% of cropland is affected by toxic metal pollution globally and estimate that between 0.9 and 1.4 billion people live in regions of heightened public health and ecological risks.
Mining is undoubtedly an important economic activity in Morocco but it can be related to many environmental and health problems. The current study is a review of previous research between 2005 and 2023 on the level of pollution by 7 heavy metals (Cd, As, Cu, Cr, Zn, Ni, and Pb) from 14 mining soils in Morocco and the related health risks. The mean average concentration varies in the following order Zn > Pb > Cr > Cu > Cd > As > Ni. In index of geological accumulation (Igeo) terms, the most serious heavy metal contaminations were associated with Zn, Pb, Cu, as well as Cd. Furthermore, the analysis of the carcinogenic and non-carcinogenic risks showed that the Hazard Quotient (HQ), The Lifetime cancer risk (LCR) and the Hazard Index (HI) were extreme for children than for adults. As for the child population, in most mining soils the risks of non-carcinogenicity for Cd, Pb, Zn, As and Cu, as well as the carcinogenic risks for Pb, were found above the tolerable range for adults. This study provided valuable background data to better understand the heavy metals environmental impact and their potential health risks.
Heavy metal pollution reduces the community of soil microorganisms, including fungi from the genus Trichoderma , which are plant growth promotors and biological control agents. Because of potential effects on crop productivity, the toxic effects of heavy metals (HMs) in Trichoderma are of interest. However, there have been few studies on the biochemical and molecular response to oxidation caused by exposure to copper (Cu), chromium (Cr), and lead (Pb) and whether this antioxidant response is species-specific. In this study, we compared the tolerance of Trichoderma asperellum and Trichoderma longibrachiatum to Cu, Pb, and Cr and evaluated the expression of genes related to the antioxidant response, including glutathione peroxidase ( GPX ), catalase ( CAT ), and cysteine synthase ( CYS ) as well as the activity of peroxidase and catalase. The isolates of Trichoderma were selected because we previously reported them as promotors of plant growth and agents of biological control. Our results revealed that, with exposure to the three HMs, the Trichoderma cultures formed aggregates and the culture color changed according to the metal and the Trichoderma species. The tolerance index (TI) indicated that the two Trichoderma species were tolerant of HMs (Cu > Cr > Pb). However, the TI and conidia production revealed that T. longibrachiatum was more tolerant of HMs than T. asperellum . The three HMs caused oxidative damage in both Trichoderma species, but the enzyme activity and gene expression were differentially regulated based on exposure time (72 and 144 h) to the HMs and Trichoderma species. The main changes occurred in T. asperellum ; the maximum expression of the GPX gene occurred at 144 h in response to all three HMs, whereas the CAT gene was upregulated at 72 h in response to Cu but downregulated at 144 h in response to all three HMs. The CYS gene was upregulated in response to the three metals. The peroxidase activity increased with all three HMs, but the catalase activity increased with Cu and Pb at 72 h and decreased at 144 h with Pb and Cr. In T. longibrachiatum , the GPX gene was upregulated with all three HMs at 72 h, the CAT gene was upregulated only with Pb at 72 h and was downregulated at 144 h with HMs. Cr and Cu upregulated CYS gene expression, but expression did not change with Pb. The peroxidase activity increased with Cu at 144 h and with Cr at 72 h, whereas Pb decreased the enzyme activity. In contrast, catalase activity increased with the three metals at 144 h. In conclusion, T. longibrachiatum was more tolerant of Cu, Cr, and Pb than was T. asperellum , but exposure to all three HMs caused oxidative damage to both Trichoderma species. Peroxidases and catalases were activated, and the expression of the genes GPX and CYS was upregulated, whereas the CAT gene was downregulated. These findings indicate that the antioxidant response to HMs was genetically modulated in each Trichoderma species.
The aim of this study was to assess soil fertility and heavy metal contamination in soil on reclaimed land in two sample areas. Area R1, trees are difficult to grow and R2, trees can grow. This investigation was conducted to reveal the level of soil fertility, concentration and enrichment of various heavy metals in contaminated soil. Twenty-two samples, twelve sampling positions in R1 and ten sampling positions in R2. Inductive study combined ICP-MS (Inductively Coupled Plasma Mass Spectrometry) and ICP-OES (Inductively Coupled Plasma-Optically Emission Spectrometry) methodologies to determine the concentration levels of Cu, Pb, Zn, Ni, Co, Mn, As, Cd and Cr. A total of four R1 soil samples and four R2 soil samples were measured by XRD to determine the mineralogy and study the flame emission photometry method, extraction and Walkley-Black to determine the soil physicochemistry: texture, pH, K⁺, Na⁺, Ca, Mg, Available Phospor, K, organic carbon, base saturation and cation exchange capacity (CEC). Correlation coefficient analysis and cluster analysis, coupled with principal component analysis, were used to analyze the data and to identify possible sources of these heavy metals. Overall, the levels of heavy metal enrichment are arranged in the following EF order: Cr R1 < Cr R2 ; Mn R1 > Mn R2; Zn R1= Zn R2. Heavy metals Mn, Cr, Co, Ni generally exceed moderate pollution and even strong pollution (2 < Igeo < 3; 3 < Igeo < 4; 5 < Igeo), and Zn, Cu low to moderate pollution levels (0 < Igeo < 1; 1 < Igeo < 2), but Pb, Cd, As low pollution levels (0 < Igeo). The results showed that the difficulty of tree growth in all places in R1 was indicated by the physicochemical properties of soil texture and CEC which were in line with mineralogy in influencing soil fertility and even distribution of heavy metals. Compared to R2, the presence of tree growth was related to a positive correlation between soil texture and organic carbon which played an important role in fertilizing the soil and mineralogy support to control the uneven distribution of heavy metals.
Wetlands serve as significant sinks and sources of heavy metals. In this study, surface sediment samples (0–25 cm) were collected from 15 sampling sites across the wetlands in the Ningxia reach, Henan reach, and delta reach of the Yellow River to investigate the contents, distributions, and ecological risks of heavy metals such as As and Cd in the wetland sediments. Our assessment revealed that the sediments were alkaline in upper and lower reaches compared to the middle reach and that the alkaline sediments were more conducive to heavy metal enrichment. There was no significant spatial distribution pattern of the heavy metals across the wetlands in the whole Yellow River basin. The contents of the heavy metals decreased with increasing sediment depth at each sampling site. Geoaccumulation index (Igeo) analysis revealed that heavy metals had a negative Igeo value at each sampling site, except for the following metals and sampling sites: in the upper reaches, the Igeo values for Cd, Mn, and Ni were 0.71, 0.17, and 0.04, respectively; in the middle reaches, the Igeo value for Cd was 0.28; and in the lower reaches, the Igeo value for Sb in the delta wetlands was 0.21. Pollution load index analysis and enrichment factor (EF) analysis revealed the occurrence of severe Cd contamination in Ningxia reach, with an EF greater than 3, indicating a high degree of anthropogenic impact. There was a strong correlation (r > 0.8) among the various heavy metals in the wetlands of both the Ningxia and delta reaches, suggesting that these two reaches have the same source for such heavy metal pollutions.
This research addresses the global challenge of waste management, focusing on a regional non-sanitary municipal solid waste landfill. Over a 2018–2019 monitoring period, the study conducted an extensive environmental impact assessment by analyzing leachate, groundwater, surface water, and soil quality. The aim was to identify and understand crucial environmental threats, laying the groundwork for the development of a robust site selection methodology. The study reveals substandard groundwater quality (LWPI=2.03–4.20) due to uncontrolled landfilling. Despite a relatively low LPI values (8.84–10.48), the leachate exhibits heavy contamination with organic matter and heavy metals, highlighting inadequate leachate management. Surface water analysis indicates a significant adverse impact both upstream and downstream of the landfill with eutrophication evidence found in elevated organic matter and nutrient levels with low dissolved oxygen in the canal. Heavy metal distribution in soil varies spatially, with specific concern for Cr concentrations (80.02–462.1 mg/kg) in active landfill areas. To aid future sanitary landfill site selection, the study employs the FUCOM SAW method, considering nine criteria with weight values calculated using FUCOM algorithm and input of 5 decision-makers, resulting in highest collective weight value (wc j =0.2162) obtained for groundwater vulnerability as a criterion. Location A emerges as the most preferable choice, with highest final score (0.769). Sensitivity analysis identifies groundwater vulnerability and distance to residential areas as critical criteria. The study concludes recommending the closure and remediation of the existing landfill, ongoing monitoring, and the adoption of the proposed site selection methodology for future sanitary landfills.
This study assessed human health risks due to exposure to potentially toxic elements (PTES) in soil and river water in eastern Serbia. Concentrations of As, Cu, Cd, Zn, Pb, Ni, and Cr were measured in soil and river water from the Vlasina watershed area. The concentrations of Cl-, SO42- and NO3- were also measured in the river water. According to the Regulation of the Republic of Serbia, the water quality of the investigated rivers corresponds to the surface water quality Class I and II. The content of PTEs in soil was below soil guideline values. Children were more sensitive than adults when exposed to PTE in water and soil. Arsenic was the dominant contributor to the total non-carcinogenic and carcinogenic risks for exposure to PTE in water. For PTE in soil, As had the dominant contribution to non-carcinogenic risks, and Ni to carcinogenic risks. All hazard index (HI) values for adults and children are less than 1, which indicates that the impact of PTEs in the examined river water and soil on human health is insignificant. Ingestion route is a major contributor to both total non-carcinogenic and carcinogenic risks.
This study analysed forty-six soil samples from the top 15 cm (6 in.) of urban soil in Tripoli, Libya for heavy metal contamination using atomic absorption spectrometry. The metals assessed included cadmium (Cd), lead (Pb), zinc (Zn), copper (Cu), nickel (Ni), cobalt (Co), iron (Fe), manganese (Mn) and chromium (Cr), with average concentrations of 3.94±1.93, 38.17±11.67, 170.94±62.68, 29.67±8.00, 19.70±8.75, 30.38±10.68, 27.444.52±8,739.15, 233.82±48.24, and 195.92±61.37 mg.kg-1.dwt (1.4E-4±7.0E-5, 1.35E-3±4.1E-4, 6.03E-3±2.21E-3, 1.05E-3±2.8E-4, 6.9E-4±3.1E-4 ,1.07E-3±3.8E-4, 0.97±3.08E-1, 8.25E-3±1.7E-3 and 6.91E-3±2.16E-3 oz.lb.-1.dwt), respectively. Most of these levels exceeded the permissible limits set by the World Health Organization and typical background values. Pollution indices suggested that the soil ranged from unpolluted to moderately polluted, with Cd, Co, Cr, and Zn being of particular concern. Cadmium was found to be the primary contributor to ecological risk, mainly from anthropogenic sources. Principal component analysis identified four key components: PC1 was dominated by Cd, Pb, and Zn with moderate contributions from Cu, related to human activities; PC2 was dominated by Fe and Cr; PC3 by Ni and Mn; and PC4 by Co and Cu, primarily from natural sources.
The consumption of heavy metal-contaminated vegetables poses a threat to human health and the environment. This study assessed the level of heavy metals in selected leafy vegetables collected from wastewater-irrigated agricultural land located at Jalkuri Union of Siddhirganj Upazila in Narayanganj district of Bangladesh. The mean concentrations of metals were decreasing in the following order: Fe > Mn > Zn > Pb> Cr> Cu > Ni > Cd in wastewater, Fe> Mn > Cr > Zn > Ni > Pb> Cu> Cd in irrigated soil, and Fe > Zn > Mn> Cu> Pb > Cr> Ni > Cd in leafy vegetables. The contamination factor (CF) showed that the soils were moderate to highly contaminated by Cr and Cd. The pollution load index (PLI) and geo-accumulation index (Igeo) values of the analyzed samples revealed that the soils were non-polluted to moderately polluted. The target hazard quotients (THQ) for most of the metals were <1, suggesting non-carcinogenic health hazards for humans. The target carcinogenic risk (TCR) of heavy metals, except for Pb, was above the safe standard, suggesting a carcinogenic risk (CR) for their consumption. It is a matter of concern that regular intake of contaminated leafy vegetables in the area would increase health risk, as the hazard index (HI) was greater than 1. The study observed that vegetables should not be irrigated with contaminated water, and industrial wastewater must be properly treated before discharging into the environment.
Because of their unbiquitous nature and potential chronic health effects, nonpoint source (NPS) pollutants have become a focal point of attention by the general public, particularly regarding pollution of surface and subsurface drinking water sources. The NPS pollutants pose a technical problem because of the areal extent of their contamination that increases the complexity and sheer volume of data far beyond that of point-source pollutants. The spatial nature of the NPS pollution problem necessitates the use of a geographic information system (GIS) to manipulate, retrieve, and display the large volumes of spatial data. This overview provides a brief introduction and review of the modeling of NPS pollutants with GIS and a brief discussion of some of the papers presented at the ASA-CSSA-SSSA 1995 Bouyoucos Conference entitled Applications of GIS to the Modeling of Nonpoint Source Pollutants in the Vadose Zone. 80 refs.
I intend to fill, with this book, a need that has long been felt by students and professionals in many areas of agricultural, biological, natural, and environmental sciences-the need for a comprehensive reference book on many important aspects of trace elements in the "land" environment. This book is different from other books on trace elements (also commonly referred to as heavy metals) in that each chapter focuses on a particular element, which in tum is discussed in terms of its importance in our economy, its natural occurrence, its fate and behavior in the soil-plant system, its requirement by and detriment to plants, its health limits in drinking water and food, and its origin in the environment. Because of long distance transport to pristine areas of cadmium, lead, copper, and zinc in relatively large quantities, these elements have an extra section on natural ecosystems. A blend of pictorial and tabular data are provided to enhance understanding of the relevant information being conveyed. Since individual chapters are independent of one another, they are arranged alphabetically. However, readers with weak backgrounds in soil science are advised to start with the chapter on zinc, since soil terminology is discussed in more detail here. Sections on sorption, forms and speciation, complexation, and transformations become more technical as soil physical-(bio )chemical phenomena are discussed. The less important "environmental" trace elements are discussed together in the "Other Trace Elements" chapter.
Historical records of the Golden Horn, so named in antiquity because of its shape, were examined to construct the pollution history of the area and to find out the past and present-day entries of pollutants and hence the impact of man. The pollution level of the Golden Horn by metals is presented by comparison which the continental soil and two other polluted water bodies: Savannah River Estuary and Narragansett Bay. Metals are distinguished as crustal and anthropogenic according to their enrichment factors. Information on how pollution level changes in time was shown using the concentration profiles of the elements between years 1913 and 1988. Li, Na, K, Rb, Be, Mg, Ca, Sr, Ba, Al, La, Ti, V, Mn, Fe, Co and P in the Golden Horn sediments are in levels comparable with those in continental soil. Cd, Cr, Ni, Cu, Zn, Ag, Pb, Mo, Ca, Sr, on the other hand, displayed enrichment through the surface strata. Elements were further grouped using factor analysis. As a result, an anthropogenic component, whose origin is mainly domestic, two crustal components, and a sea-salt component were found to be the main constituents of the Golden Horn sediments.
In the city area of Esslingen (Baden-Wurttemberg, Southwest-Germany) the outer bark layers of Aesculus hippocastuanum trees were analysed in 1988/89 for the contents of various trace elements. The results, received by means of X-ray fluorescence analysis, are assessed and presented on grid maps suitable for planning purposes using VISOR GIS (geographic Information System) connected to MICROSOFT ACCESS database via DDE (dynamic data exhange). The patterns of spatial distribution especially of the elements lead, bromium, zinc, and copper indicate traffic emissions as a main source of urban pollution. Raised contents of nickel, selenium, iron, titanium, and zirconium are also due to automobile exhausts and abrasion of wearing parts, whereas high concentrations of arsenium seem to originate from firing processes (coal). Additionally, various industrial sources contribute to the urban background pollution. In general, the concentrations of the elements decrease from the center of the city to the outskirts. They are also lower in greater green plots and quiet residential quarters, however significantly high along the main traffic lines.
This chapter discusses the aspects of environmental quality in which soils may serve as sources or sinks for potentially toxic substances in air, water, and the food chain. It describes the methods and concepts important in soil chemical monitoring. Soil monitoring procedures include methods and implementation programs to protect crop plants and the food chain from attaining harmful concentrations of the various environmental pollutants. The mineral composition of plants must be maintained at levels that do not harm the health of man and animals. The chapter deals with various soil pollution sources: (1) agricultural pollutants and soil erosion, (2) animal wastes, and (3) industrial and municipal wastes. Pollutants in the environment should be defined, monitored, and regulated on the basis of the following characteristics: (1) production and consumption within an area, (2) mode of transport into the environment, (3) persistence in a potentially hazardous form within the environment, (4) toxicity of poisonous concentrations by plants, animals, and human beings, (5) teratogenic effects of long-term exposure by animals and man to low concentrations, and (6) aesthetic considerations, such as eutrophication. The chapter further discusses the monitoring of macroelements and microelements.
Unplanned industrialization and urbanization are causing health hazard mainly in developing countries. It is essential to assess the magnitude of future hazard in an industrial town. The geographical information system is a special type of tool evolved to analyse geographic data for efficient planning. In India large-scale industrialization started after independence. New industrial towns have been established and Durgapur in West Bengal is one of them. In this study an indigenously developed GIS package GRAM has been used to assess air quality in Durgapur town. Using GIS, interpolated maps have been prepared showing the distribution of five pollutants, i.e. carbon monoxide, total oxidant, nitrogen-oxide, sulfur-dioxide and suspended particulate matter. The maps have been used to find the pollutant standard index of the area. The final map shows that the PSI index is high and ranges between the 'unhealthy' to 'very unhealthy' category. This map has been combined with a present landuse pattern. There are three pockets of extremely poor air quality zones which generally match with industrial units. Areas around these units are the potential zones of health hazard. Large numbers of patients admitted in hospitals here suffer from obstructive diseases. Most of them belong to the working age group. This may indicate that the main work force is exposed to the health hazard due to industrial pollution.
The objective of this study was to establish baseline concentrations for 15 potentially toxic elements (Ag, As, Ba, Be, Cd, Cr, cu, Hg, Ma, Mo, Ni, Pb, Sb, Se, and Zn) based on 448 representative Florida surface soils using microwave assisted HNOâ-HCl-HF digestion. Baseline concentrations of those elements were (mg kgâ»Â¹): Ag 0.07-2.50, As 0.02-7.01, Ba 1.67-112, Be 0.04-4.15, Cd 0-0.33, Cr 0.89-80.7, Cu 0.22-21.9, Hg 0.00075-0.0396, Mo 0.13-6.76, Ni 1.70-48.5, Pb 0.69-42.0, Sb 0.06-0.79, Se 0.01-1.11, and Zn 0.89-29.6, respectively. Upper baseline values for most elements corresponded with these reported in literature, except Ba, Hg, Mn, Sb, and Zn, which were 3 to 23 times lower. Soil properties, including pH, organic carbon (OC), particle size, cation-exchange capacity (CEC), available water, extractable base, extractable acidity, total Ca, Mg, P, K, Fe, and Al concentrations, were related to metal concentrations using factorial analysis. Eight factors were identified (total Fe and Al, CEC, pH, clay, OC, total Ni and Mo, total Sb and Pb, and total Hg) and accounted for 87% of the total variance, suggesting that metal concentrations were primarily controlled by soil compositions. Multiple regression of elemental concentrations against total Fe, total Al, clay, OC, CEC, and pH was significant for all elements. Partial correlation coefficients indicated that total Fe and/or Al explained most of the variance for Mn, Ni, Ba, Be, Hg, As, Cd, Cr, Cu, Mo, Pb, and Zn concentrations. Most of the variance in Se was related to clay, whereas those of Ag and Sb related to clay and total Al.
The St. Johns River Water Management District (SJR-WMD) is using a Geographic Information System (GIS) screening model to estimate annual nonpoint source pollution loads to surface waters and determine nonpoint source pollution problem areas within the SJRWMD. The model is a significant improvement over current practice because it is contained entirely within the district's GIS software, resulting in greater flexibility and efficiency, and useful visualization capabilities. Model inputs consist of five spatial data layers, runoff coefficients, mean runoff concentrations, and stormwater treatment efficiencies. The spatial data layers are: existing land use, future land use, soils, rainfall, and hydrologic boundaries. These data layers are processed using the analytical capabilities of a cell-based GIS. Model output consists of seven spatial data layers: runoff, total nitrogen, total phosphorous, suspended solids, biochemical oxygen demand, lead, and zinc. Model output can be examined visually or summarized numerically by drainage basin. Results are reported for only one of the SJRWMD's ten major drainage basins, the lower St. Johns River basin. The model was created to serve a major planning effort at the SJRWMD; results are being actively used to address nonpoint source pollution problems.
A method for reconstructing pore-water compositions from aqueous leachate data obtained from milled and dried drill core is described. The method uses principal component analysis (PCA) to construct an abstract model of the aqueous leachate data which separates out the contaminating components, arising from rock dissolution and drilling fluid contamination, from the pore-water residual solutes component. Iterative target factor analysis (TFA) is used to quantify this pore-water component based on the assumptions that halides in the aqueous leachate are mainly attributable to the pore-water and that the lithium tracer in the drilling fluid is not present in the pore-water. The method is tested on a simulated data set and on data obtained from a deep borehole in Sellafield, Cumbria. The results demonstrate that the proposed method, although requiring further development, has potential use as a powerful investigative tool in a wide range of environmental applications.
The paper presents the metal pollution assessment of Jacarepaguá basin rivers and lagoons based on statistical analysis of metal concentration in bottom sediments. It is demonstrated that Pavuna and Fundo Creeks are the main sources of anthropogenically introduced metals to the lagoons. Due to the weak process of water circulation in the lagoons the contamination is restricted to the discharge areas of both rivers. Metal concentration in river sediments appears to be highly dependent on rainfall events thus a seasonal (wet and dry seasons) variation in their concentration can be proposed. The examination of metal lognormal distribution plots indicates that concentration values, related to the curve inflexion(s), can be operationally used as thresholds between polluted and unpolluted areas. These values were; 0.92 μg g for Cd, 165 (μg gfor Zn, 15 μg g for Cr and 26 μg g for Ni. Factor analysis was used to examine the main sources of metals to the aquatic environment. It can be suggested that the steel and chemical industries would be the most important sources of metals released to the aquatic environment.
The construction of a new section of the M-40 ring road will give rise to a redistribution of traffic in the city of Madrid and its outskirts. The use of a geographical information system (GIS) has provided a suitable instrument for assessing and locating traffic effects before and after the new infrastructure enters service. Traffic information was used as basic input data for drawing up a pollution map, taking a standard day with unchanging weather conditions. The model chosen used several parameters to compute the concentrations of pollutants at ground level. Finally, the pollution map was cross-referenced with the standard maps in order to locate and quantify the population affected by the different pollution levels and the wildlife and historic and/or archaeological features at risk. The assessment was made before and after construction of the new road. The utilization of GIS methodology allowed the environmental changes to be automatically located with the use of a personal computer. This proved to be an effective tool for carrying out environmental impact assessments.
Introduces the concept of Geographic Information Systems (GIS) as an approach for integrating and synthesizing disparate information for use in the secondary geography and earth science curriculum. Reviews basic concepts and instructional approaches to familiarize teachers with the relative simplicity of GIS implementation. (Author/GEA)
From the Atlantic Ocean to the Ural Mountains, European soils are threatened by diffuse pollution from modem agriculture and increased atmospheric deposition. The vulnerability of the soil to diffuse pollution depends on land cover, topsoil features, net precipitation, aquifer type, groundwater recharge and age. The elaboration of the various elements was realized by applying Geographical Information Systems (GISs). Precipitation and the actual evapotranspiration were estimated using meteorological data. The resulting net precipitation is discharged by groundwater recharge and surfacial runoff, with the division of net precipitation in groundwater recharge and surfacial flow following from climate and soil features. The average groundwater age was based on aquifer depth, porosity and the recharge. The vulnerabilities of the soil and groundwater were estimated by establishing a ranking of the combined risks of a diffuse contamination for the topsoil and for groundwater in aquifers. Nitrogen compounds in soils are caused mainly by manuring and fertilization of agricultural lands and atmospheric deposition. The varying doses of fertilizer and manure and the atmospheric deposition of nitrogen compounds were assessed for an actual situation. Only part of the applied doses leached into the soil. The leaching of nitrate to a level of 1 m below land surface was estimated by applying empirical relations derived from the northwest European experience, based on land use, features of the topsoil and net precipitation. The subsequent leaching to deeper strata and a further denitrification also depend on groundwater recharge and aquifer type. The average nitrate concentration in the various aquifers was assessed by estimating the nitrogen doses to European soils in the course of time in combination with the groundwater age. Results, attained using GIS and presented in the form of maps, show the leaching of nitrate concentrations to a level of 1 m below land surface and also the average concentration in the upper aquifer system.
Baseline element concentrations are given for Spanish moss (Tillandsia usneoides), loblolly pine (Pinus taeda), and associated soils. Baseline and variability data for ash, Al, Ba, C, Ca, Cd, Ce, Co, Cr, Cu, Fe, K, La, Li, Mg, Mn, Na, Nb, Nd, Ni, P, Pb, S, Sc, Sr, Th, Ti, V, Y, and Zn are reported; however, not all variables are reported for all media because, in some media, certain elements were below the analytical detection limit. Spatial variation in element concentration among and within 0.5 km grid cells are given for each of the media. In general, only a few elements in Spanish moss showed statistically significant landscape patterns, whereas several elements in loblolly pine and in soils exhibited differences among sampling grids. Significant differences in the concentration of three elements in Spanish moss and eight elements (including total S) in loblolly pine were observed between two sampling dates (November and June); however, the absolute amount of these differences was small. Except for perhaps Ni and Pb concentrations in Spanish moss, element levels in all sample media exhibited ranges that indicate natural rather than anthropogenic additions of trace elements.
In the last decade, the Atlantic coast of south-eastern Brazil has been affected by increasing deforestation and anthropogenic effluents. Sediments in the coastal lagoons have recorded the process of such environmental change. Thirty-seven sediment samples from three cores in Piratininga Lagoon, Rio de Janeiro, were analyzed for their major components and minor element concentrations in order to examine geochemical characteristics and the depositional environment and to investigate the variation of heavy metals of environmental concern. Two multivariate analysis methods, principal component analysis and cluster analysis, were performed on the analytical data set to help visualize the sample clusters and the element associations. On the whole, the sediment samples from each core are similar and the sample clusters corresponding to the three cores are clearly separated, as a result of the different conditions of sedimentation. Some changes in the depositional environment are recognized using the results of multivariate analysis. The enrichment of Pb, Cu, and Zn in the upper parts of cores is in agreement with increasing anthropogenic influx (pollution).
The Holocene filling of the Tinto-Odiel Estuary comprises seven lithofacies over a Mio-Pliocene substrate. The sequence includes
three system tracts: lowstand system (10 000 to 8700 years BP), transgressive system (8700 to 7000 years BP), and regressive
system (7000 to Recent). Twenty sediment samples from the 50-m borehole were analyzed for their major components and minor
element concentrations. Two multivariate analysis methods, principal component analysis and cluster analysis, were performed
in the analytical data set to help visualize the sample clusters and the element associations. Samples corresponding to unpolluted,
pre-mining sediments are clearly separated by cluster analysis, mainly as a result of the low content in sulphide-associated
heavy metals such as Cu, Zn, As, Ag, and Pb. So, these sediments may be utilized as a background for geochemical analysis
(bulk sample) in other adjacent estuaries, both in sandy and silty-clayey sediments. As a consequence of large-scale mining
and smelting operations occurred since prehistoric times on the river banks, a rapid rise in the metal pollution was found
in the upper 2.5 m of the natural filling, with values exceeding up to ten times the natural background levels. In addition,
since the mid-1960s, large amounts of waste and pollutant effluents have been discharged from industries located around the
estuary, increasing the heavy metal content in the last 0.3 m of the natural sedimentation.
Simplification of a complex system of geochemical variables obtained from the soils of an industrialized area of Bombay is attempted by means of R-mode factor analysis. Prior to factor analysis, discriminant analysis was carried out taking rock and soil chemical data to establish the anthropogenic contribution of metals in soil. Trace elements (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) are expressed in terms of three rotated factors. The factors mostly indicate anthropogenic sources of metals such as atmospheric fallout, emission from different industrial chimneys, crushing operations in quarries, and sewage sludges. Major elements (Na, Mg, Al, Si, P, K, Ca, Ti, Mn, and Fe) are also expressed in terms of three rotated factors indicating natural processes such as chemical weathering, presence of clay minerals, and contribution from sewage sludges and municipal refuse. Summary statistics (mean, standard deviation, skewness, and kurtosis) for the particle size distribution were interpreted as moderate dominance of fine particles. Mineralogical studies revealed the presence of montmorillonite, kaolinite, and illite types of clay minerals. Thus the present study provides information about the metal content entering into the soil and their level, sources, and distribution in the area.
Pb isotope ratios and Pb concentrations of well-dated sediments of Lake Constance, Central Europe have been analyzed using thermal ion mass spectrometry. Sequential extraction studies indicated isotope homogeneity of the leachable Pb components within the investigated layers. Since the middle of the 19th century a significant anthropogenic Pb component appeared in the lake sediments, and rapidly approached concentration levels similar to that of the geogenic Pb background (20 ppm) at the beginning of the 20th century. Anthropogenic Pb was predominantly transferred to the lake sediments via the atmosphere. Pb sources were coal combustion, industrial ore processing and leaded gasoline. The flux of a fluvial Pb component to the lake sediments, additive to atmospheric Pb deposition, peaked in about 1960. This flux is attributed to (re)mobilization of Pb from polluted parts of the lake catchment, and indicates the change of catchment soils from a pollution sink to a heavy metal source. The strong reduction of anthropogenic Pb in the uppermost lake sediments since the 1960’s has been caused by advances of environmental protection.The lake sediments record the changing fluxes and the isotope composition of the deposited aeolian Pb pollution. During the 20th century aeolian Pb fluxes to the lake sediments were in the range of 1–4 μg/cm2/a. During peak emission periods of gasoline Pb to the atmosphere (1960–1990) the aerosol Pb isotope composition was rather constant (206Pb/207Pb: 1.12–1.13) and probably a mixture of Canadian and Australian with Russian and Central European Pb types. Aeolian Pb isotope and Pb flux trends in the lake sediments as a whole agree well with the trends found in Alpine glaciers and and in ombrotrophic peat bogs of Switzerland (Shotyk et al., 1996). However, different industrial Pb components were deposited in the archives of aeolian pollution during the early 20th century.
The atmospheric, edaphic, and vegetative components of the roadside ecosystem contain elevated levels of lead originating from the combustion of lead containing gasolines by motor vehicles. The size of this ecosystem approximates 3.04 X 10 hectares (118,000 square miles) in the United States. Recent evidence has greatly refined our understanding of the distribution and localization of lead in the roadside environment. This paper is a representative review of some of this recent evidence. Vehicles release approximately 80 mg of lead/km to the atmospheric compartment in the form of inorganic lead salts ranging in size from 1 to 5 µ. Lead content of roadside atmospheres may be elevated 2-20 times non-roadside atmospheres. Sedimentation from the atmospheric compartment results in lead contamination of the soil and vegetative compartments. Lead in the upper 5 cm of the soil profile may be elevated 30 times non-roadside soil within a few m of a street or highway. The soil lead is largely bound by organic matter exchange sites or present as the relatively insoluble lead sulfate. The increased lead burden of plants, largely due to surface deposition, may be 5-20,50-200, and 100-200 times baseline lead levels for unwashed agricultural crops, grass, and trees respectively. Invariably most plant studies demonstrate a strong inverse correlation between plant lead level and sampling distance normal to the highway and a less strong, but direct, correlation between lead burden and traffic volume. While our appreciation of the distribution of lead in the roadside ecosystem is good, our understanding of its chemistry and the effects on the biota are deficient. Acute and direct impacts of lead on components of the roadside biota are not apparent. The potential for interactive effects with other stress factors and for subtle impact is considerable, however, especially in regard to plant surface and soil microbiota, foraging insects and animals, and plant leaf and root metabolism.
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