Spatial Distribution Of Elements Research Articles

The use of LA-ICP-MS as an auxiliary tool to assess the pulmonary toxicity of molybdenum(IV) sulfide (MoS2) nano- and microparticles.

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has considerable applicative potential for both qualitative and quantitative analyses of elemental spatial distribution and concentration. It provides high resolutions at pg-level detection limits. These qualities make it very useful for analyzing biological samples. The present study responds to the growing demand for adequate analytical methods which would allow to assess the distribution of nanostructured molybdenum(IV) disulfide (MoS2) in organs. It was also motivated by an apparent lack of literature on the biological effects of MoS2 in living organisms. The study was aimed at using LA-ICP-MS for comparing micro- and nanosized MoS2 ditribution in selected rat tissue samples (lung, liver, brain and spleen tissues) after the intratracheal instillation (7 administrations) of MoS2 nano- and microparticles vs. controls. The experimental study, approved by the Ethics Committee for Animal Experiments was performed using albino Wistar rats. This was performed at 2-week intervals at a dose of 5 mg/kg b.w., followed by an analysis after 90 days of exposure. The MoS2 levels in control tissues were determined with the laser ablation system at optimized operating conditions. The parameter optimization process for the LA system was conducted using The National Institute of Standards and Technology (NIST) glass standard reference materials. Instrument parameters were optimized. The study found that molybdenum (Mo) levels in the lungs of microparticle-exposed rats were higher compared to nanoparticle-exposed rats. The opposite results were found for liver and spleen tissues. Brain Mo concentrations were below the detection limit. The LA-ICP-MS technique may be used as an important tool for visualizing the distribution of Mo on the surface of soft samples through quantitative and qualitative elemental mapping. Int J Occup Med Environ Health. 2024;37(1):18-33.

The influence of fluid inclusions, organics, and calcite fabric on trace element distributions in stalagmites

Trace elements and calcite fabrics in stalagmites are increasingly employed as indicators of past environmental conditions. The drivers of trace element concentrations and fabrics reflect a complex interplay of factors during crystal growth, and accurate interpretation of geochemical proxies requires a clear understanding of the incorporation of the proxy signal in the stalagmite. We employ a series of non-destructive techniques to compare the spatial distribution of water, organic components, and trace elements and in relationship with calcite fabrics, and evaluate if these distributions are consistent with recent hypotheses about controlling factors on crystal fabrics, fluid inclusions, and element incorporation. We use for the first time Fourier Transformation Infrared Focal-Plane Array (FTIR-FPA) imaging to show the distribution of molecular water (3,400 cm−1 absorbance) and organic matter (2,983 cm−1) in calcite. To test if entrapped water in speleothem calcite affects the abundance or distribution of trace elements, the element distribution (Na, Mg, Sr, U, Al, Y, and Zn) is mapped by Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS). Transmitted Light Microscope imaging constrains crystal fabrics. We find that stalagmite areas with strong Organic Matter fluorescence via Confocal Laser Scanning Microscopy coincide with areas of high Fourier Transformation Infrared absorbance at 2,983 cm−1, suggesting common co-location of multiple organic matter types in the stalagmite. While microscopic fluid inclusions visible in transmitted light are also detected by FTIR 3400 cm−1 absorbance, the FTIR additionally detects submicroscopic fluid inclusions, but not evident in transmitted light microscopy. In most samples, Na concentration is elevated in regions of high fluid inclusion density, suggesting that a significant portion of Na may be hosted in entrapped water rather than in the calcite. Only samples with 100-fold higher Y, feature Na concentrations which appear dominated by coupled Y-Na substitution and little influenced by fluid inclusion hosted Na. Our analysis provides new evidence of the influence of fluid inclusions on trace element content of stalagmites and illustrates the utility of several non-destructive imaging techniques to improve interpretations of proxy signals based on trace elements.

Lithological mapping of geological remote sensing via adversarial semi-supervised segmentation network

Geological remote sensing interpretation (GRSI), which aims to recognize multiple geological elements based on their characteristics on satellite remote sensing images, is vital in large-scale regional lithological mapping. However, due to the influence of long-term geological movements, the spatial distribution of geological elements (such as lithology, glaciers, and soils) on the image is often complex and highly fragmented. In addition, the characteristics of high inter-class similarity and severe homogenization make the annotation of geological element samples require significant cost and expert knowledge. These lead to insufficient interpretation accuracy and limited annotation samples in GRSI. To alleviate the dependence of labeled samples and promote the performance of GRSI, we propose an adversarial semi-supervised segmentation network with object-context and global-attention (AdvSemi-OCGNet) for the GRSI, which achieves effective segmentation results in the case of limited labeled samples. Under the architecture of adversarial learning, a proposed baseline network OCGNet and a full convolution discriminator (FCD) are integrated to conduct semi-supervised segmentation. OCGNet, as the generator, aims to confuse FCD by predicting probability maps. Then FCD selects trustworthy regions with high-confidence of unlabeled sample to generate pseudo-labels for semi-supervised segmentation of OCGNet. Iterative adversarial learning is employed to simulate the process of expert interpretation of geological elements through continuous discrimination and correction. Finally, a fully connected conditional random field eliminates holes and isolated areas of segmented results caused by misclassification. Two study areas are selected, which include various geological elements such as multiple lithologies, soils, rock glaciers, and surface water. Numerous experiments have revealed the superiority of the proposed model in GRSI with limited annotation samples.

Study of demixing in C–F plasma produced in a capillary discharge

The spatial distribution of chemical elements in plasma produced by a pulsed discharge in a capillary made of polytetrafluoroethylene has been studied by methods and means of optical spectroscopy. It has been found that the ratio of the molar fractions of fluorine and carbon differs significantly from that in the polymer wall and varies nonmonotonically along the radius of the plasma jet emerging from the capillary. The performed qualitative analysis of the intensity and direction of a number of competing diffusion fluxes involving C, C+, F, and F+ indicates both the possibility of the slowdown in the fluorine and carbon demixing, which start from the peripheral zone, and a change in the direction of some of these fluxes in the central zone of the discharge, which is reflected in the measured mole fraction profiles of these elements.

Spatial and Temporal Evolution of the Characteristics of Spatially Aggregated Elements in an Urban Area: A Case Study of Wuhan, China

Urban spatial elements present agglomeration and dispersion geographic processes in the urban development. Identifying the characteristics of their distribution changes and accurately capturing the evolution of the urban spatial structure is of great significance to urban construction and management. This study takes Wuhan as a case study and focuses on the spatial agglomeration distribution of urban elements. Point of Interest (POI) data from 2017 to 2021 were collected, and the Block2Vec model was employed to extract the comprehensive geographic information from various elements within the traffic analysis zones (TAZs). Subsequently, identification and division were carried out to access the level of urban spatial element agglomeration. Finally, the spatial–temporal evolution characteristics of urban aggregated elements in the Wuhan metropolitan development area over five years were compared and analyzed. The results indicate the following: (1) urban elements present an obvious circle structure in their spatial agglomeration, with distinct differences observed among different element types; (2) from 2017 to 2021, the Wuhan urban development zone experienced obvious expansion in urban space; (3) increased agglomeration of spatial elements mainly occurred in the surrounding areas of the city, while some areas in the city center displayed weaker element agglomeration and a reduction in various service facilities. The results demonstrate that the method used in this study could effectively identify the spatial agglomeration distribution of urban elements, as well as accurately distinguishing regions with distinct development characteristics. This approach could provide robust support for optimizing land use and urban spatial planning.

Predictive geochemical mapping using machine learning in western Kenya

Digital soil mapping techniques represent a cost-effective method for obtaining detailed information regarding the spatial distribution of chemical elements in soils. Machine learning (ML) algorithms using random forest (RF) models have been developed for classification, pattern recognition and regression tasks, they are capable of modelling non-linear relationships using a range of datasets, identifying hierarchical relationships, and determining the importance of predictor variables. In this study, we describe a framework for spatial prediction based on RF modelling where inverse distance weighted (IDW) predictors are used in conjunction with ancillary environmental covariates. The model was applied to predict the total concentration (mg kg−1) and assess the prediction uncertainty of 56 elements, soil pH and organic matter content using 466 soil samples in western Kenya; the results of iodine (I), selenium (Se), zinc (Zn) and soil pH are highlighted in this work. These elements were selected due to contrasting biogeochemical cycles and widespread dietary deficiencies in sub-Saharan Africa, whilst soil pH is an important parameter controlling soil chemical reactions. Algorithm performance was evaluated determining the relative importance of each predictor variable and the model's response using partial dependence profiles. The accuracy and precision of each RF model were assessed by evaluating out-of-bag predicted values. The models R2 values range from 0.31 to 0.64 whilst CCC values range from 0.51 to 0.77. The IDW predictor variables had the greatest impact on assessing the distribution of soil properties in the study area, however, the inclusion of ancillary environmental data improved model performance for all soil properties. The results presented in this paper highlight the benefits of ML algorithms which can incorporate multiple layers of data for spatial prediction, uncertainty assessment and attributing variable importance. Additional research is now required to ensure health practitioners and the agri-community utilise the geochemical maps presented here for assessing the relationship between environmental geochemistry, endemic diseases and preventable micronutrient deficiency.

Spatial and temporal distribution of geochemical elements and their processes in different size fractions–Miri River (NW Borneo)

The toxicity, persistence, and propensity for accumulation of metals in aquatic environments have raised significant concerns globally. Expansion of urbanization with the growth of industrial and agricultural sectors in Miri City results in a high concentration of pollutants that flow directly into the Miri River. Hence, this study provides a comprehensive analysis of the Miri River water quality, focusing on spatial and temporal variations. River water samples were collected in two different time periods and analysed for physico-chemical parameters includes major ions, nutrients, metals and isotopes. Particularly, the metals were analysed in different size fractions (particulate and colloid) of the suspended solids. Geochemical plots, pollution index, geochemical modelling and factor analysis were used for the data analysis. Interpretation of data reveals that the mean concentration of metals in river water were increased from downstream to the upstream of the river irrespective of the seasons. Major ions were mostly derived from the chemical weathering of source rocks, which was supported by the Gibbs plot. Piper plot indicates the seasonal shifting of water types from Ca–Mg to Na–Cl. Isotopic signatures reveal direct atmospheric precipitation and evaporation were the major origins of river water. Fe was the dominant metal concentration in river water irrespective of the seasons (mean concentration 1.05 mg/L). Fe and Zn were the dominant metal concentration observed in all the 3 size fractions of suspended solids. Industrial activities and seawater influx dominate in the downstream, whereas weathering and agricultural inputs are significant in the upstream of the river. Particulate and colloidal fractions are the major contributors for the metal transport in the midstream and downstream of the river. The outcome of this study offer a thorough understanding of the seasonal elemental distribution at different size fractions, geochemical behaviour and the pollution status of the Miri River. With this knowledge, sustainable management strategies can be developed for this crucial water resource to the benefit of Miri community.

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.

Concentration, Spatial Distribution, and Source Analysis of Trace Elements in the Yarlung Zangbo River Basin and Its Two Tributaries

The Yarlung Zangbo River (YZR) is the longest plateau river in China and has famous tributaries, the Lhasa River and the Nianchu River. A total of 75 water samples were collected from the Yarlung Zangbo River Basin (YZRB) in this study to investigate the dissolved concentration, spatial distribution, and source of trace elements (Fe, V, Be, Ti, Mo, Se, Cd, Zn, Cu, Ni, Co, Mn, Cr, Ba, Tl, Pb, Hg, As, and Sb). The results indicate that only Cr and Tl contaminate water, while the other trace elements were in an unpolluted state. In addition, correlation analysis showed that there was a highly significant positive correlation between the concentrations of As, Sb, and Mo; there was also a highly significant positive correlation between the concentrations of Fe, Mn, Ti, Pb, Ni, Co, and Ba. The results of Positive Matrix Factorization (PMF) showed that there were four sources of trace elements in the YZRB, including the resuspension and dissolution of sediments (16.283%), agricultural source (11.436%), lithological source (47.418%), and soil-forming rocks (6.374%). Cluster analysis combined with PMF normalized contribution analysis, which showed that the trace elements found in the YZR’s mainstream were predominantly influenced by the surrounding rocks composition. Meanwhile, both the discharge of mining wastewater and sediments were marked in the Lhasa River. Additionally, agricultural activities were the chief contributors to the trace elements in the Nianchu River. Furthermore, the entire basin was subjected to the influence of soil-forming rocks. This study comprehensively analyzed and evaluated the physicochemical properties of water, the spatial distribution, and the pollution degree, and performed source analysis of trace elements in the YZRB. This research provides a foundational reference for further investigation of the spatial distribution and origins of trace elements in the rivers of the Qinghai–Tibet Plateau (QTP).

Cadmium alters whole animal ionome and promotes the re-distribution of iron in intestinal cells of Caenorhabditis elegans.

The chronic exposure of humans to the toxic metal cadmium (Cd), either occupational or from food and air, causes various diseases, including neurodegenerative conditions, dysfunction of vital organs, and cancer. While the toxicology of Cd and its effect on the homeostasis of biologically relevant elements is increasingly recognized, the spatial distribution of Cd and other elements in Cd toxicity-caused diseases is still poorly understood. Here, we use Caenorhabditis elegans as a non-mammalian multicellular model system to determine the distribution of Cd at the tissue and cellular resolution and its effect on the internal levels and the distribution of biologically relevant elements. Using inductively coupled plasma-mass spectrophotometry (ICP-MS), we show that exposure of worms to Cd not only led to its internal accumulation but also significantly altered the C. elegans ionome. Specifically, Cd treatment was associated with increased levels of toxic elements such as arsenic (As) and rubidium (Rb) and a decreased accumulation of essential elements such as zinc (Zn), copper (Cu), manganese (Mn), calcium (Ca), cobalt (Co) and, depending on the Cd-concentration used in the assay, iron (Fe). We regarded these changes as an ionomic signature of Cd toxicity in C. elegans. We also show that supplementing nematode growth medium with Zn but not Cu, rescues Cd toxicity and that mutant worms lacking Zn transporters CDF-1 or SUR-7, or both are more sensitive to Cd toxicity. Finally, using synchrotron X-Ray fluorescence Microscopy (XRF), we showed that Cd significantly alters the spatial distribution of mineral elements. The effect of Cd on the distribution of Fe was particularly striking: while Fe was evenly distributed in intestinal cells of worms grown without Cd, in the presence of Cd, Fe, and Cd co-localized in punctum-like structures in the intestinal cells. Together, this study advances our understanding of the effect of Cd on the accumulation and distribution of biologically relevant elements. Considering that C. elegans possesses the principal tissues and cell types as humans, our data may have important implications for future therapeutic developments aiming to alleviate Cd-related pathologies in humans.

Spatial distribution of major and trace elements in artificial lakes in Serbia: health risk indices and suitability of water for drinking and irrigation purposes

Lakes and reservoirs are the main water resources for household, irrigation, and industrial use. Hence, it is necessary to control water pollution and have reliable information on water quality, which refers to its suitability for a particular purpose. The main objective of this study was to evaluate the suitability of water for drinking and irrigation purposes from ten artificial lakes on the territory of the Republic of Serbia. The physicochemical parameters were determined using standard analytical methods, whereas the optical emission spectrometry with inductively coupled plasma, ICP-OES, was used to determine the concentrations of 23 macro-, micro-, and trace elements in water. Health risk indices of drinking water and its suitability for irrigation purposes were evaluated. The results of physicochemical parameters, except for total organic matter, indicated that most samples were within the recommended values. Among analyzed elements, the concentration of Mg was elevated in the water of the lakes Srebrno and Prvonek. The results of health risk assessment clearly showed that there was no acute health risk (HQA < 1), whereas long-term risk (HQL) in the studied lakes was observed with respect to As (lakes Grlište and Srebrno), Mn (lakes Srebrno and Prvonek), Ni (Lake Vrutci), and Sr (Lake Grlište). The irrigation criteria indicated that the water from the examined lakes had satisfactory quality for this purpose, except for residual sodium carbonates (RSC). This criterion indicated low quality or unsuitability of the water in 7 lakes. The main outcomes provided valuable information on the suitability of water from the artificial lakes for intended uses.

Grazing-emission X-ray fluorescence as a multiprobe tool for thin-film metrology

Recent research has demonstrated the high potential of grazing-emission X-ray fluorescence as a nanometrology tool for structures with complex 3D architecture. The technique now allows separate reconstruction of the spatial atomic distributions of different chemical elements both vertically and laterally, which opens up new and interesting applications in the nanofabrication industry. This study compares grazing-emission fluorescence with the well established grazing-incidence X-ray fluorescence method. The comparison uses a simple 1D thin-film structure. Reconstruction of the structure by both methods is performed and the statistical uncertainties of these reconstructions are compared by means of Monte Carlo Markov-chain simulations. For the forward model a semi-analytic approach is derived which allows simulation of the fluorescence intensity. This approach takes into account both grazing-incidence and grazing-emission cases. It also accounts for an even more complex physical phenomenon, the anomalous Kossel effect. Finally, using this semi-analytic approach, an experimental scheme combining grazing-incidence and grazing-emission X-ray fluorescence is studied theoretically.

MODELING OF THE SPATIAL DISTRIBUTION OF CHROME AND MANGANESE IN SOIL: SELECTION OF A TRAINING SUBSET

The selection of a method for dividing the raw data into training and test subsets in models based on artificial neural networks (ANN) is an insufficiently studied problem of continuous space-time field interpolation. In particular, selecting the best training subset for modeling the spatial distribution of elements in the topsoil is not a trivial task, since the sampling points are not equivalent. They contain a different amount of “information” in point of each specific model, therefore, when modeling, it is advisable to use most of the points containing information which is “useful” for this model. Incorrect data division may lead to inaccurate and highly variable model characteristics, high variance and bias in the generated results. The raw data included contents of chromium (Cr) and manganese (Mn) in the topsoil in residential areas of Noyabrsk (a city in Russian subarctic zone). A three-stage algorithm for extracting raw data with a division into training and test subsets has been developed for modeling the spatial distribution of heavy metals. According to the algorithm, the initial data set was randomly divided into training and test subsets. For each training subset, an ANN based on multilayer perceptron (MLP) was built and trained. MLP was used to model the spatial distribution of heavy metals in the upper soil layer, which took into account spatial heterogeneity and learning rules. The MLP structure was chosen by minimizing the root mean square error (RMSE). The networks with the lowest RMSE were selected, and the number of hits into the training subset of each point in space was calculated. By the number of hits in the training subset, all points were divided into three classes: “useful”, “ordinary” and “useless”. Taking this information into account, at the stage of the raw data division it possible to increase the accuracy of the predictive model.

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&gt; Zn &gt; Ba &gt; Cr &gt; V &gt; Sr &gt; Pb &gt; La &gt; Cu &gt; Ni &gt; Co &gt; As &gt; Th &gt; Sc &gt; 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 Al, Zn, Fe, As, Pb, Mn, Cr, and Cu in Surface Waters of the Urumqi River Basin, China, and Assessment of Risks to Ecosystems and Human Health

The study of pollution and risk assessment of surface water in watersheds is important for the use and management of surface water, as well as for the stability of ecosystems and human health. This study focused on a typical watershed in an arid zone, the Urumqi River basin; divided the basin into upper, middle, and lower reaches according to the main uses of the surface water in the region; and collected surface water samples from the basin. We collected 41 surface water samples from the upper, middle, and lower reaches of the Urumqi River Basin, a typical arid zone watershed. The characteristics and spatial distribution of metal elements in the surface waters of the basin were analysed, the pollution status was evaluated, and risk assessments of the effects of these metal elements on natural ecosystems and human health were carried out. The results showed that (1) the average concentration of the metal element Al in the surface water of the Urumqi River Basin was 663.73 µg·L−1, which was 3.3 times that of the standard limit value (200 µg·L−1), with an exceedance rate of 100%, and the standard deviation value was 136.05 µg·L−1, with a large difference in spatial distribution. Spatial distributions for Al, Cu, Cr, Fe, Mn, and Zn were higher upriver and midstream than downriver, and for Pb and As, they were higher upriver, midstream, and downriver than downriver. (2) The values of the single-factor pollution index of the metal elements Zn, As, Pb, Mn, Cr, and Cu in the upper, middle, and lower reaches of the watershed were all less than 1, which is within the safe range. The integrated pollution indexes of 0.03~0.27 were all less than 0.7, which is within the safe range, and the integrated pollution of the upper reaches was significantly greater than that of the middle and lower reaches. (3) The total ecological risk of the basin ranged from 0.09 to 13.72, which is much lower than the low-risk indicator value of 150, and the ecological risk of the upper reaches was higher than that of the middle and lower reaches. (4) The health risk assessment showed that the total health risks of the eight metal elements to adults and children showed an upstream &gt; downstream &gt; midstream pattern, all of which exceeded the ICRP recommended value (10−5). The average annual total health risks of the carcinogenic metal elements chromium and arsenic to adults and children were 10−6 and 10−5 a−1, respectively, with arsenic concentrations exceeding the ICRP recommended value (10−5). Arsenic and lead in the surface waters of the Urumqi River Basin are important indicators of health risk and need to be prioritised as indicators for environmental risk management.

Pb speciation and elemental distribution in leeks by micro X-ray fluorescence and X-ray absorption near-edge structure.

Vegetables are crucial to a human diet as they supply the body with essential vitamins, minerals, etc. Heavy metals that accumulate in plants consequently enter the food chain and endanger people's health. Studying the spatial distribution and chemical forms of elements in plant/vegetable tissues is vital to comprehending the potential interactions between elements and detoxification mechanisms. In this study, leek plants and soil from vegetable gardens near lead-zinc mines were collected and cultivated with 500 mg L-1 PbNO3 solutions for three weeks. Micro X-ray fluorescence was used to map the distribution of Pb and other chemical elements in leek roots, and X-ray absorption near-edge spectroscopy was used to assess the Pb speciation in leek roots and leaves. These findings demonstrated that Pb, Cu, Mn, Cr, Ti and Fe were detected in the outer rings of the root's cross section, and high-intensity points were observed in the epidermis. Zn, K and Ca, on the other hand, were distributed throughout the root's cross section. Leek root and leaf contained significant quantities of lead phosphate and basic lead carbonate at more than 80%, followed by lead sulfide (19%) and lead stearate (11.1%). The capacity of leek roots to convert ambient lead into precipitated lead and fix it on the root epidermis and other inner surfaces is a key mechanism for reducing the toxic effects of Pb.

Spatial Distribution of Heavy Element in Erbil's Municipal Landfills by Using GIS

Untreated municipal solid waste (MSW) release onto land is prevalent in developing countries. To reduce the high levels of harmful components in polluted soils, a proper evaluation of heavy metal concentrations in Erbil's Kani Qrzhala dump between August 2021 and February 2022 is required. The purpose of this research was to examine the impact of improper solid waste disposal on soil properties within a landfill by assessing the risks of contamination for eight heavy elements in two separate layers of the soil by using geoaccumulation index (I-geo) and pollution load index (PLI) supported. The ArcGIS software was employed to map the spatial distribution of heavy element pollution and potential ecological risks. The I-geo values in summer varied from -1.700 to 3.560 for Zn, 5.045 to 8.175 for Cd, 2.318 to 4.329 for Pb, 0 to 3.374 for Mn, 1.439 to 3.880 for Ni, 0.638 to 2.278 for Cu, -0.541 to 2.665 for Cr, and -2.495 to 0.778 for Hg. Based on the I-geo categorization, the contamination levels of Zn, Cd, Pb, Mn, Ni, Cu, and Hg ranged from uncontaminated to extremely contaminated. However, all metals were assessed as uncontaminated throughout winter, except I-geo (Cd) and I- geo (Ni) varied from -0.467 to 3.966 and -5.720 to 2.015 were classified from as uncontaminated to strong and uncontaminated to moderately/strongly contaminated respectively. According to the PLI category, most samples were rated as "highly polluted" during summer, but during the rainy season, all samples were rated as "unpolluted".

Application of two- and multiway chemometric strategies for describing elementomic changes in pepper plants exposed to cadmium stress by multielement determination

The objective of this work was to evaluate elemental changes in pepper exposed to Cd stress through different chemometric tools. For this purpose, pepper plants were grown under five different treatments with different Cd concentrations in the nutrient solution. Considering the hypothesis that pepper plants exposed to Cd stress during growth undergo changes in the macro- and microelemental distribution in leaves, stems, and roots, principal component analysis (PCA) and parallel factor (PARAFAC) analysis were applied to compare bidirectional and multivariate chemometric strategies to assess elemental changes in pepper plants. Since the number of variables and the data generated were large and complex, the application of chemometric tools was justified to facilitate the visualization and interpretation of results. The mineral composition, namely the Ca, Cd, Cu, Fe, K, Mg, Mn, N, and P contents, was assessed in 180 samples of leaves, stems, and roots of the cultivated peppers. Then, PCA and PARAFAC analysis were applied to compare bidirectional and multivariate chemometric strategies to assess elemental changes throughout pepper plants. The visualization of the trend on each sample and their intrinsic relationship with the variables were possible with the application of PCA. The use of PARAFAC analysis permitted the simultaneous study of all samples in a straightforward representation of the information that facilitated a quick and comprehensive understanding of the spatial distribution of elements in plants. Thus, macroelements (Ca, K, Mg, N, and P) that were found in higher concentrations in leaves did not present significant differences in the distribution along the plants under different treatment conditions. In contrast, a significant impact on the microelement (Cu, Fe, and Mn) distribution was produced between uncontaminated and contaminated samples. This analysis revealed a significant accumulation of Cd in roots and adverse effects on normal plant growth, demonstrating their level of phytotoxicity to pepper.

Opportunities and challenges in the application of single-cell and spatial transcriptomics in plants.

Single-cell and spatial transcriptomics have diverted researchers' attention from the multicellular level to the single-cell level and spatial information. Single-cell transcriptomes provide insights into the transcriptome at the single-cell level, whereas spatial transcriptomes help preserve spatial information. Although these two omics technologies are helpful and mature, further research is needed to ensure their widespread applicability in plant studies. Reviewing recent research on plant single-cell or spatial transcriptomics, we compared the different experimental methods used in various plants. The limitations and challenges are clear for both single-cell and spatial transcriptomic analyses, such as the lack of applicability, spatial information, or high resolution. Subsequently, we put forth further applications, such as cross-species analysis of roots at the single-cell level and the idea that single-cell transcriptome analysis needs to be combined with other omics analyses to achieve superiority over individual omics analyses. Overall, the results of this review suggest that combining single-cell transcriptomics, spatial transcriptomics, and spatial element distribution can provide a promising research direction, particularly for plant research.

THE BOTTOM RELIEF OF VYZYRKA POND (ODESSA REGION, ODESSA DISTRICT)

Problem Statement and Purpose. For arid conditions of southern Ukraine, the problem of preservation and use of the local water resources has been relevant for a long time. One of the types of adaptation of economic activity to the natural conditions of the area is artificial water bodies’ creation. Operation of ponds without repair work led to reduction of the water surface area of most of them, siltation, reduction of depths, overgrowth, as a result of which the ponds from water accumulators turned into evaporators. The publications review devoted to ponds and artificial reservoirs showed that their hydrochemical, hydrobiological regime, hydrological elements and ecological condition are mainly studying. The purpose of the research is to establish the regularities of the relief structure of the bottom of the pond in the village of Vyzyrka. Data &amp; Methods. Field research was conducted in July 2021–2022. From two reservoirs, located within the village of Vyzyrka, the larger one was investigated. Work in the water area was carried out from the rowing boat Kolibri. The depths were determined with a Garmin Echo 200 echo sounder a geodetic rail. The use of the echo sounder made it possible to visually trace the relief of the bottom changes on the tacks and choose typical underwater points during relief measurements (ND31– 7.002.-2005). The depths were determined at 60 points, located evenly across the water area. The coordinates of measurement points were determined using a Garmin GPS72H GPS receiver. The journal of points was exported to Garmin Base Camp software. Results. Vyzyrska Pond has existed as an artificial reservoir since 1923. The relief has a trough-like shape inherited from the beam relief. Three areas are distinguished in the structure of the bottom relief: flat bottom of the northern part; underwater continuation of concave coastal slopes; the central depression stretches along the axis of the reservoir from southeast to northwest. The creation and use of artificial reservoirs leads to the development of geomorphological processes associated with the interaction of the native relief, which was formed in other physical and geographical conditions, with the water environment. Further studies of the pond are aimed at establishing the spatial distribution of hydrological elements in the water area of the pond in order to establish patterns of their change, which are important for the aquatic biota development.