Spatial Distribution Of Trace Elements Research Articles

Distribution, source identification, water quality, and risk assessment of trace elements in the surface-groundwater-sediments multifunctional system in Guohe River Basin

Within the Huaihe River Basin, Guohe River, as its second-largest tributary, serves as a critical water supply source. Recent industrial and agricultural advancements have led to increased trace element contamination, adversely impacting the water quality within Guohe River Basin. Therefore, this study aimed to investigate the distribution characteristics, sources, water quality and risk assessment of trace elements in the surface water, groundwater, and sediments across the basin. The results showed that the spatial distribution of trace elements in the surface water and groundwater of Guohe River Basin was that most of the high concentrations appeared in Qiaocheng District of Bozhou City, the mean concentration of Fe in Guohe River sediments was the highest, the mean concentration of Sb was the lowest. The PMF source analysis results showed that the main source of trace elements in Guohe River Basin was natural geological processes, followed by human activities. The sodium adsorption ratio (SAR) indicated that the surface water samples of Guohe River in two seasons had high sodium and salinity hazards. The water quality index (WQI) showed that surface water and groundwater samples in the northwestern of Guohe River Basin had poor water quality. The results of the risk assessment showed that As and Mn posed great ecological risks to surface water and groundwater, respectively, and that F− was the pollutant with the most potential health risk hazard in the basin. The Geo-accumulation index (Igeo) results showed that Cd, Se and As should be taken seriously as the main contaminants of the sediments in Guohe River Basin. KeywardsTrace elements; Source analysis; Sodium adsorption ratio; Water quality index; Risk assessment; Geo-accumulation index.

“Hidden” mineralogical-geochemical zonality revealed by the laser microanalysis of sulfides at the Kyzyk-Chadr deposit, Republic of Tyva

A comprehensive study of the Kyzyk-Chadr porphyry copper deposit included determination of the composition and spatial distribution of trace elements in ore-forming sulfide minerals over the ore- hosting rock volume. The study was carried out using the mass spectrometric analysis with laser ablation of the analyzed material. Steady qualitative and quantitative elements of a “hidden” mineralogical and geochemical zonality have been identified, that are expressed in variations in the concentration of trace elements and their ratios in pyrites and chalcopyrites over the volume of the ore-bearing porphyry copper stockwork. The identified regularities correlate with the established centrifugal vector and concentric pattern of the mineralogical ore-metasomatic zonality of the ore deposit.

Evaluate the spatial distribution of trace elements in soil of a karst terrain

Evaluate the spatial distribution of trace elements in soil of a karst terrain

Spatial distribution of trace elements and potential contamination sources for surface sediments of the North-Western Black Sea, Romania

It is essential to determine the concentrations of metals/metalloids in marine sediments and their contamination status to develop appropriate pollution control strategies and/or improve existing ones. Spatial distribution of aluminum (Al) and some trace elements, i.e., arsenic (As), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn), accumulated in surface sediments of the north-western (NW) Black Sea (Romanian zone) was evaluated. Sediment samples were collected in 2019 from 32 stations located at water depths in the range of 12.7–149 m. The mean values ± standard deviations (SD) of element concentrations were as follows: 3.9 ± 1.6% for Al, 11.2 ± 10.2 mg/kg for As, 64.8 ± 27.0 mg/kg for Cr, 32.7 ± 15.0 mg/kg for Cu, 0.10 ± 0.09 mg/kg for Hg, 45.3 ± 23.8 mg/kg for Ni, 24.6 ± 9.6 mg/kg for Pb, and 68.0 ± 28.0 mg/kg for Zn. These values are not significantly different (p > 0.05) from those found in a previous study on surface sediments collected in 2018 from 22 stations located in the same area, but at lower water depths (13.5–67 m). Contamination factor (CF) was used to assess the contamination status of surface sediments. The mean values of CF (0.26–1.23) reveal low to moderate contamination with Pb and low contamination with the other elements. Principal component analysis (PCA) and correlation analysis indicated that As, Cu, Ni, Hg, Pb, and Zn were associated with clay, silt, and organic matter, suggesting that these elements mainly came from the Danube discharges and also from local anthropogenic sources, whereas Al, Cr, and partly Hg, Pb, and Zn originated from rock/soil weathering and erosion. The concentration levels of As, Cu, Hg, Ni, Pb, Zn, TOC, silt, and clay were higher in sediments collected from stations generally located at higher water depths (up to 118 m), suggesting that the TEs associated with the finer carriers were transported offshore by currents and waves, whereas the concentration levels of Al, Cr, Hg, and Zn were higher in sediments with lower levels of CaCO3 content (10.1–24.3%), collected from shallower stations (water depths of 12.7–42.0 m).

Spatial Distribution of Trace Elements in Sub-Surficial Marine Sediments: New Insights from Bay I of the Mar Piccolo of Taranto (Southern Italy)

Contaminated marine and coastal sediments represent the main source of secondary pollution for the aquatic environment and marine fauna, affecting, directly and indirectly, ecosystems and human health. The assessment of the distribution of chemical pollutants in marine sediments can therefore be considered a preliminary step for understanding the possible circulation of pollutants in the marine environment and planning any targeted and efficient reclamation activity. This study provides new insights on the environmental status of Bay I of Mar Piccolo basin (Southern Italy) by proposing an integrated investigation approach to define the distribution of trace metals and evaluate the thickness of the sediments potentially affected by pollution. To this aim, the concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, Sn, and Zn are estimated for sediment samples collected from 19 cores, and specific environmental indices are calculated. Due to its remarkable environmental and economic relevance, the area of Taranto has been selected as a case study to evaluate the effectiveness of the proposed method in supporting the identification of hotspot areas for which priority remediation activities are needed.

Evaluation of trace elements in the sediments of intertidal zone around Mahin-Ugbo Area, southwestern Nigeria

This study assessed the spatial distribution of Trace Elements (TE) in the muddy sediments of the Mahin-Ugbo coastal area of Southwestern Nigeria, using Inductively Coupled Plasma-mass spectrometry, (ICP-MS). The physicochemical parameters (pH, EC and TDS) of the sediments were also determined. Results showed that the mean values for pH, E.C and TDS were 5.09, 153.6 μs/cm and 76.8 mg/L, respectively. Further, there was a varying distribution pattern of TE concentrations: Mn> Zn > Ba > Cr > V > Sr > Pb > La > Cu > Ni > Co > As > Th > Sc > Ga. The As, Pb, and Zn concentrations in the sediment with mean values of 11.2, 40.4 and 122.1 ppm, respectively, were significantly higher than the average concentrations of As (10 ppm), Pb (20 ppm) and Zn (90 ppm) in natural shale, suggesting anthropogenic TE enrichment in the study area. To corroborate this, the TE source apportionments in the sediments using correlation coefficient, bi-variant plots and principal component analyses showed that the TE enrichment may have been anthropogenically induced. Pollution status assessments using I-geo, contamination factors and pollution load index indicated that the study area's sediments is slightly to moderately polluted. These findings suggest that although the area is not heavily polluted, increasing human activities, from inland rivers to the coastal area, in the study area will in no time be a cause for concern.

Spatial distribution of trace elements in coastal sediments of Ha Tinh province, Vietnam

Sediment compositions and trace element (Cu, Pb, Zn, Cr, Fe, Mn, As, and Hg) concentrations were analyzed to assess the sediment quality and the factors affecting the trace elements’ concentration in Ha Tinh province’s coastal sediments. Results revealed that the concentration of trace elements in the coastal sediments was generally lower than in other coastal areas in Vietnam. The significantly positive correlation of the fine sediment composition with Cu, Pb, Zn, Cr, and Fe indicated that the silt and clay sediments could absorb these trace elements. The highly positive correlation among Cu, Pb, Zn, Cr, and Fe suggested that the trace elements likely originated from similar sources. The sediment quality assessment showed that trace element concentrations were lower than the limited values in the sediment quality guideline (QCVN 43:2017/BTNMT). According to the Igeo index, the sediments were not polluted by Cu, Pb, Zn, Cr, Fe, and As but were likely polluted by Hg and Mn in some sampling sites. Therefore, it is necessary to invest the future studies to assess the Hg and Mn concentration levels in these sites to protect the marine environment.

Spatial distribution, impact factors, and potential health implications of trace elements in human hair from capital residents in China

We analyzed the levels, spatial distribution, impact factors, source apportionment, and potential health implications of trace elements (V, Zn, Cu, Mn, Ni, Mo, and Co) in 1202 human hair samples of urban residents aged 4–55 from 29 cities in China. The median values of seven trace elements in hair were found in the following increasing order: Co (0.02 μg/g) < V (0.04 μg/g) < Mo (0.05 μg/g) < Ni (0.32 μg/g) < Mn (0.74 μg/g) < Cu (9.63 μg/g) < Zn (157 μg/g). The spatial distribution of these trace elements in the hair from the six geographical subdivisions varied depending on the exposure sources and impact factors. Principal component analysis (PCA) revealed that Cu, Zn, and Co in the hair samples of urban residents were primarily derived from food, whereas V, Ni, and Mn were attributed to industrial activities and food. Majority of the hair samples (up to 81%) from North China (NC) exceeded the recommended value for V content, whereas up to 59.2%, 51.3%, and 31.6% samples from Northeast China (NE) exceeded the recommended values for Co, Mn, and Ni contents, respectively. The levels of Mn, Co, Ni, Cu, and Zn were significantly higher in female hair than those in male hair, whereas the levels of Mo were higher in male than in female hair (p < 0.01). Furthermore, significantly higher Cu/Zn ratios were observed in the hair of male residents than those in the female residents (p < 0.001), indicating a higher health risk for male residents.

Geochemistry and geostatistics for the assessment of trace elements contamination in soil and stream sediments in abandoned artisanal small-scale gold mining (Bétaré-Oya, Cameroon)

Soil and stream sediment contamination from abandoned artisanal mines is of prime importance due to the associated potential for heavy metal and metalloid contamination. Indeed, mine wastes are an evident source of soil and stream sediment contamination. The aim of the current study is to propose a conceptual approach to assess the contamination degree and the spatial distribution of trace elements in soils and stream sediments around mine sites. The abandoned artisanal gold mine of Bétaré-Oya in Cameroon was considered as a case study. In order to separate anthropogenically contaminated soils and stream sediments from the un contaminated ones, representative soil, stream sediment and mine wastes samples were collected and analyzed for the pH, Electrical Conductivity (EC), mineralogical paragenesis, major elements and trace elements. Very acidic pH values and high EC values ranging from 3.2 to 5.8 and from 44 to 315 μs cm−1, respectively were obtained for the analyzed samples. Based on the enrichment factor (EF) calculation, four elements of interest (Co, Cd, Cu and As) were selected for soils and seven elements of interest (Co, Cd, Cu, As, Cr, Pb and Zn) were selected for stream sediments. The Geochemical Background (GB) of these elements was determined with the normal Q-Q plot, the Geo-accumulation index (Igeo) was calculated and the geochemical maps for soils and stream sediments were elaborated using geostatistics in Geographic Information System (GIS) environment.The obtained results show that Bétaré-Oya soils and stream sediments are contaminated with metals and metalloid that exceed the established GB values for soil (Co ≈ 17.73 mg/kg, Cd ≈ 0.36 mg/kg, Cu ≈ 146.81 mg/kg and As≈48.82 mg/kg) and GB values for stream sediments (Co ≈ 30.90 mg/kg, Cd ≈ 0.24 mg/kg, Cu ≈ 173 mg/kg, As≈51.59 mg/kg, Cr ≈ 137 mg/kg, Pb ≈ 7.56 mg/kg, and Zn ≈ 39.48 mg/kg). The Igeo calculation revealed that soils and stream sediments were highly influenced by anthropogenic activity. The maximum values of the Igeo, especially for Cd ≈ 4.59, Pb ≈ 2.83, and Zn ≈ 2.97, highlighted the highly contaminated samples and therefore quantify accurately the contamination degree. Finally, geochemical maps of soils and stream sediments show clearly that mine wastes are the main source of trace elements contamination in the study area.

Effects of anthropogenic and natural environmental factors on the spatial distribution of trace elements in agricultural soils

The concentrations of trace elements in agricultural soils directly affect the ecological security and quality of agricultural products. A comprehensive study aimed at quantitatively analyze the effects of anthropogenic and natural environmental factors on the spatial distribution of heavy metals (HMs) and selenium (Se) in agricultural soils in a typical grain producing area of China. Factors considered in this study were parent rock, soil physicochemical properties, topography, precipitation, mine activity, and vegetation. Results showed that the median values of Zn, Cd, Cr, and Cu of 111 topsoil samples exceeded the background values of Guangxi province but were lower than the relevant national soil quality standards, and 85% of soil samples were classified as having rich Se levels (0.40 −3.0 mg kg−1). The potential ecological risk index of soil heavy metals as a whole was low, with Cd in 9% of the samples posing moderate ecological risk. The concentrations of heavy metals and Se were relatively high in soils from shale rock. Soil properties, mainly Fe2O3 and Mn played a dominant role on soil HMs and Se concentrations. Based on GeoDetector, we found that the interaction effects of two factors on the spatial differentiation of soil HMs and Se were greater than their sum effect. Among the factors, Mn enhanced the explanatory power of the model the most when interacting with other factors for soil Zn; the greatest interactive effect was between distance from mining area and Mn for Cd (q = 0.70); Fe2O3 significantly promoted the spatial differentiation of soil Cr, Cu and Se when interacting with other factors (q > 0.50). These findings contribute to a better understanding of the factors that drive the distribution of HMs and Se in agricultural soils.

Geographically Optimal Similarity

Understanding geographical characteristics of distribution patterns and spatial association is essential for spatial statistical inference such as factor exploration and spatial prediction. The geographical similarity principle was recently developed to explain the association between geographical variables. It describes the comprehensive degree of approximation of a geographical structure instead of explicit relationships between variables. However, there are still challenges for geographical similarity-based methods. For instance, all samples are used for prediction, leading to increased calculation burden and reduced prediction accuracy due to the noise and unrelated data in large spatial data sets. This study develops a geographically optimal similarity (GOS) model for accurate and reliable spatial prediction based on the geographical similarity principle. In GOS, the geographical configurations are first characterized, and similarities between unknown and known observation locations are assessed. Next, an optimal threshold is determined to select a small number of observations with optimal similarities for the prediction at each unknown location. Finally, a reliable uncertainty assessment approach is developed to assess and map uncertainties of GOS predictions. A new R package “geosimilarity” is developed to conduct GOS models. In this study, GOS is implemented in predicting spatial distributions of trace elements in a mining region in Australia. Results show that GOS can use a small number of observations to derive more accurate and reliable spatial predictions than linear regression and basic configuration similarity models. In addition, pattern characteristics of predictions can be improved by GOS by eliminating the phenomenon wherein predictions are clustered near mean values and contain striped textures. Therefore, GOS demonstrates greater potential for implementing the geographical similarity principle in spatial predictions by bringing information from samples with relatively high similarities at any location across space for more accurate and effective predictions in broader fields and practice.

Trace elements in public drinking water in Chinese cities: Insights from their health risks and mineral nutrition assessments.

The trace elements in the public drinking water have a duality: on the one hand, trace elements play an important role in maintaining human metabolism; on the other hand, high trace elements levels lead to significant health risks. To determine the impacts of trace elements in the public drinking water on physical health in China, water samples were collected from 314 Chinese cities to analyze the concentrations and spatial distributions of trace elements on a national scale. On this basis, the non-carcinogenic health risk assessments and the nutrient-based scores of trace elements (NSTEs) were applied to evaluate the public drinking water quality in terms of safety and nutrition. Most of the water samples were weakly alkaline: pH values fell in the range of 6.62-8.54, with a mean of 7.80. The results indicated that Sr and F- had the highest concentrations in public drinking water, with averages of 0.3604mg/L and 0.2351mg/L, respectively. Moreover, hazard index (HI) values in different regions followed the order: northwest China (NWC)>northern China (NC)>Qinghai-Tibetan Plateau (QT)>southern China (SC). The percentages of water samples with HI>1 in SC, NC, NWC, and QT were 5.49%, 16.82%, 25.81%, and 16.67%, respectively, indicating that the public drinking water in some cities had significant non-carcinogenic health risks. In addition, the intakes of Mn, Fe, Cu, and Rb through public drinking water made negligible contributions to their recommended nutrient intakes. In contrast, trace elements like Sr, F, B, Li, Mo, etc., contributed a lot. The NSTEs in NWC and most parts of NC were relatively high with averages of 8.0300 and 11.2082, respectively; however, the NSTEs in SC and the northeast part of NC were low with averages of 3.3284 and 5.2106, respectively. The results from this study provide a reference for establishing the public drinking water standards and improving drinking water quality.

The second dimension of spatial association

• The concept of the second dimension of spatial associations (SDA) is proposed. • SDA can extract in-depth and multi-scale geoinformation outside sample locations. • SDA-based statistical, machine learning, and geostatistical models are developed. • Spatial prediction accuracy is critically improved by SDA models compared with FDA. • SDA models provide smooth, effective, and low-uncertainty spatial predictions. A reasonable and adequate understanding of spatial association between geographical variables is the basis of spatial statistical inference and geocomputation, such as spatial prediction. Most of the current models for exploring spatial association of variables are constructed using data at sample locations. In this study, approaches for exploring spatial association using observations at sample locations are defined as the first dimension of spatial association (FDA). However, geographical information outside sample locations is usually missing in current models. To address this issue, this study proposes the concept of the second dimension of spatial association (SDA), which is an approach that extracts geographical information at locations outside samples for exploring spatial association. Based on the concept of SDA, three SDA models, including SDA-based multivariate linear regression, machine learning (i.e., random forest), and geostatistical models (i.e., random forest kriging), are developed for examining spatial association and predicting spatial distributions of trace elements, including Cr and Cu, in a mining region in Western Australia. Model accuracy is evaluated by comparing with corresponding FDA models. A new R package “SecDim” is developed to conduct SDA models. Results show that SDA models have a series of advantages in examining spatial association compared with FDA models. First, the accuracy of spatial prediction can be critically improved by SDA compared with the FDA, although identical explanatory variables and models are used for the modeling and prediction. Second, SDA can effectively indicate the multi-scale effects and diverse information within explanatory variables of the geographical environment at local ranges using the second dimension variables. Third, SDA can avoid underestimating high values and overestimating low values in the general FDA-based statistical models, machine learning, and geostatistical models. Finally, SDA models provide more smooth spatial predictions across space than that predicted by FDA models and avoid massive fluctuations at local ranges. The concept of SDA provides new insight into geographical information-based spatial association. SDA and multiple types of SDA models have great potential for more accurate and effective spatial statistical inference and geocomputation in diverse fields.

LA-ICP-MS analysis of trace and rare-earth element distribution in calcite fracture fillings from Forsmark, Simpevarp and Laxemar (Sweden)

Concentrations and spatial distribution of trace elements in secondary minerals provide valuable information about mobility controlling processes in natural fractures. Important examples include rare-earth element contents that act as analogues for the retention of trivalent actinides such as Am/Cm or Pu(III). The secondary phases (carbonates) investigated in this study originate from exploration drilling bore cores of the Swedish Nuclear Fuel and Waste Management Company SKB (Forsmark, Simpevarp and Laxemar, Sweden).Here, high-resolution element analysis (Micro-X-ray Fluorescence-Spectrometry (µXRF) and Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS)) is applied to scan for Na and the trace elements Mn, Fe, Sr, Pb, Th and U as well as the rare-earth elements Y, La, Ce and Yb associated with carbonate fracture fillings. High resolution element maps highlight growth zones and microstructures within the samples, which are not detected by the usual point and line measurements. Evidence of phase-dependent partitioning is observed.The partition coefficients, D, determined from formation water and carbonate data were compared to experimentally generated coefficients and values derived from a 17-year precipitation experiment carried out at the Äspö Hard Rock Laboratory (HRL).Distribution coefficients of the light rare-earth elements La and Ce have been found to be relatively high in the studied samples, whereas the coefficients of distribution of Sr and U are remarkably low.Overall, the results of this work show that the secondary calcite formed in deep granitic fractures coprecipitated periodically with significant amounts of radionuclide analogues (i.e., rare-earth elements).

Ecological risks from trace elements in Quaternary agricultural soils of Lebanon- East Mediterranean.

Soil contamination by trace elements (TE) causes health and environmental risks. This work focused on arable lands of Central Bekaa of Lebanon, East Mediterranean. The spatial distribution of TEs in the cultivated soils was mapped. Results showed accumulation of Cr and Ni, in the soil-plant interface layer, exceeding the multifunctional land use (soil threshold I &lt;50 and &lt;40 mg kg-1 , respectively) and controlled land use (soil threshold II-100 mg kg-1 ). The index of geoaccumulation (Igeo) showed no hazards from Zn with moderate to strong contamination from Pb and moderate hazard from Ni, Cu, Cd and Cr. A cross sectional soil sampling from the Litani river to the eastern hill of Terbol showed accumulation of TEs at foot slopes and at river’s banks. Human activities within the plain contribute to further soil contamination with risk of pollutants transfer to food chain. Additional sampling of plant and corresponding soil in hot spots showed TE content in the plant leaves to be mostly within or slightly above the permissible values in wheat and potato. Considering the soil quality regarding chemical pollution is a necessary factor in land use planning for the elaboration of adapted to local soil conditions thresholds of TEs content in the soil for suitable land use, either in agriculture or alternative uses.

Heavy Metal Concentrations in Roadside Soils on the Białystok-Budzisko Route in Northeastern Poland

Civilization development has contributed to environmental pollution. In recent years, the number of vehicles has increased significantly; according to the Central Statistical Office, the number of passenger cars in Poland in 2000 was nearly 10 million, while in 2020 it was slightly more than 25 million. The study aimed to determine the content and spatial distribution of trace elements (Fe, Mn, Cd, Pb, Cr, Ni, Zn and Cu) in the roadside topsoil along the trunk road Białystok–Budzisko on different types of land use (urban, rural, agricultural and forestal areas). Forty-five soil samples were collected from a 160 km road section, at intervals of approximately 4 km. Metal contents were analyzed by atomic absorption spectrometry. The concentrations of metals in roadside soils occurred in the following order: Fe &gt; Mn &gt; Zn &gt; Cr &gt; Cu &gt; Pb &gt; Ni &gt; Cd. The average contents of Cd, Zn, Cu, and Pb were higher than the geochemical background values of the Polish soils. Moreover, the values of the Igeo showed for Cd moderate to strong, while for Zn, Cu and Pb, moderate soil contamination. The study indicates that significant metal-binding factors in the studied roadside soils are Fe and Mn oxides. The crucial source of metals is road transport, depending on its intensity, which means amount, type, and speed of vehicles. Moreover, based on the analysis of the course of the factor values and their dynamics, it was observed that the areas where typical activities connected with the population take place (urban and agricultural areas) are additional sources of heavy metals. The results of this paper are relevant to the prevention and control of heavy metal pollution in roadside soils. The study can contribute to reducing the concentration of toxic elements in ecosystems due to vehicle emissions with appropriate land-use policies.

Spatial distribution of trace elements associated with organic carbon along the Beiyun River basin, Beijing, China

Pollution resulting from terrestrial and aquatic trace elements has become a severe problem across the world. Organic carbon (OC) content has a high affinity for metallic contaminants and it acts as a significant sink for trace elements. The decomposition of OC content directly influences the bioavailability of trace elements. The decomposition of OC content and OC distribution vary spatially, these processes affect the release of trace elements and need further research. In the current study, sediment samples from the surface sediment along Beiyun River (Section 1 to Section 4 from upper to lower reaches), which is situated in the rapidly urbanized Beijing metropolis, were measured for OC, moisture, hardness, and trace elements. The OC contents were found to have a substantial difference among all four river sections along the urbanized river gradient. Whereas the higher OC contents were found in Sections 2 (Urbanized uplands) and 3 (farmland) compared to those in Sections 1 (forest) and 4 (farmland and part of constructed areas). On the other hand, the highest value of the correlation coefficient was found among the different values of trace elements and OC content in the riverine zone of the Beiyun River basin. OC contents play a vital role in the transformation and origin of trace elements in the surface sediment of the Beiyun River basin. The One-way Analysis of Variance (ANOVA) was applied to compare the means of OC and trace elements at different sections indicating no significant difference. However, source identification of trace elements indicated that a geogenic source was responsible for higher contents of As and (69.95%). Simultaneously, the natural OC, agricultural activities, and industrial waste contributed about (21.10%) towards the Cd and Zn, and about 10% for Cr and Cu. The current study concludes that the absolute principle component analysis–multiple linear regression (APCA-MLR) method can be successfully used to investigate the trace elements (Zn, Ni, Pb, Mn, Cd, Cu, and As) interactions through OC content resulting in determination of the various sources of contamination to cause negative environmental impacts on the ecosystem and human health. So, the current study provides a baseline for a quantitative evaluation of trace elements under different sediment of OC contents.

Spatial distribution of trace elements in surface sediments of Hooghly (Ganges) river estuary in West Bengal, India

The spatial distribution of trace elements in surface sediments of the Hooghly estuary was studied over the monsoons in 2014–2017. As, Cd, Ni, Pb and U were two- to sixteen-fold the crust means with increasing levels toward the estuary, with Ni peak during the post-monsoon. Pearson’s correlation matrix, cluster analysis, enrichment factors and pollution index revealed the anthropic source and association of trace elements with Fe, Mn and Al and of Pb with U. Geoaccumulation index revealed for Ni an extremely contaminated situation at the estuary water during monsoon and for Cd a heavily contaminated situation at freshwater location. The potential contamination index was >6; thus, sediments were very severely contaminated by As, Cd and Ni with worst situation for As and Cd at fresh and brackish water and during post-monsoon. The overall ecological risk was severe, 300≤RI<600 at all sites and seasons, especially after the monsoon, at fluvial and brackish locations.

Metasomatism and cyclic skarn growth along lithological contacts: Physical and geochemical evidence from a distal Pb[sbnd]Zn skarn

Distal skarns form by the metasomatic reactions of a host rock induced by far-traveled hydrothermal fluids. Physical and structural characteristics and geochemical patterns of distal PbZn skarn bodies were studied at the Petrovitsa deposit in southern Bulgaria. Skarn bodies formed from the interaction of hydrothermal fluids with reactive host lithologies (marble and gneiss). These fluids were transported along sub-vertical feeder structures and lithological contacts. Epidote skarn developed in gneiss protolith, and pyroxene (johannsenite) skarn developed in marble. Detailed geological mapping, complimented by measurements of the internal structure of the skarn body using pyroxene growth versors, quantifies the propagation direction of the skarn body: 1) away from the major local fluid conduit (feeder structure), and 2) away from lithological contacts between aluminosilicate rock and marble. Such growth suggests that fluid flow was generally orthogonal to the skarn front propagation direction in the pyroxene skarn.Textural, mineralogical and geochemical data from skarn samples reveal multiple growth generations of major skarn calc-silicates epidote and pyroxene. The epidote skarn is characterized by limited spatial distribution and fine-grained epidote/clinozoisite growth associated with massive replacement and sulfide mineralization. The pyroxene skarn consists of acicular clinopyroxene crystals which form spheroidal aggregates with discrete growth banding. These bands are the physical representation of the cyclic fluid pulses which resulted in rhythmic skarn growth marked by geochemical banding. In situ geochemical analyses in the epidote skarn reveal early Al-rich epidote overprinted by Fe-rich epidote associated with higher Mn and Sr contents and irregular compositional banding. Clinopyroxene (Jo60–95) shows general increase in Na, Al, Mn, and REE + Y with distance from the feeder structure and lithologic contacts. These elements correlate with the distance traveled by the hydrothermal fluid from the feeder to the site of skarnification, which we define using a proxy based on the Al content of pyroxene crystals. This reflects an increasing degree of fluid “contamination” by interaction with the aluminosilicate host rocks and functions as a proxy for fluid transport distance. The spatial distribution of trace-elements in pyroxene on an outcrop scale is indicative of discrete pulses of hydrothermal fluid resulting in precipitation of skarn calc-silicates along the increasingly tortuous fluid pathway between the feeder structure and the skarn front, resulting in both the macro- and micro-scale chemical and textural variability of the skarn body.

Contamination of Trace Elements in River Ecosystem and Source Apportionment Based on Their Relationship with Landscape Patterns

Complex configuration of landscape types on different spatial scales and different slopes, such as entire basin and buffer zones, is a significant issue that affects contamination of trace elements in river ecosystem. Water and sediment samples were collected and analyzed to determine the concentration and spatial distribution of trace elements throughout various topographies and landscape types. The result demonstrated that landscape percentages (agricultural land, forest land, grassland, and built-up) would greatly affect concentration of trace elements in river, agricultural land and built-up percentage demonstrate significant positive correlation with concentration of trace elements. While forest land percentage appeared significant negative correlation with concentration of trace elements, but significant positive correlation areas are located on lower steepness slope and buffer zones with elevations of 0-500 m. As average slope steepness increases, more significant positive correlation exists between built-up percentage and trace elements concentration in river. Mining activities are a major potential source because the landscape types of mining land area in the upstream of the river are built-up on high steepness slope, and the relationships of built-up percentage in entire sub-basin with concentration of trace elements are more significant than that in river buffer zones.