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1
Sun, Jianwei, Mengchan Chen, Jingrou Xiao, et al. "Exploring the Spatial Distribution Characteristics of Urban Soil Heavy Metals in Different Levels of Urbanization." Agronomy 15, no. 2 (2025): 418. https://doi.org/10.3390/agronomy15020418.
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With the development of urbanization and industrialization worldwide, soil heavy metal pollution has become a critical and pressing environmental problem in urban areas. Soil heavy metals exhibit complex and varying spatial aggregation and diffusion processes within diverse urban landscapes, especially in different urban areas with varying urbanization levels. However, many existing experimental methods and conventional models overlook the crucial aspects of spatial autocorrelation and heterogeneity between soil heavy metals and influencing factors. This neglect poses significant environmental concerns, as rapid monitoring of soil heavy metals and accurate identification of their determinants become imperative. This study investigated four environmentally sensitive and potentially harmful soil heavy metals, arsenic (As), cadmium (Cd), copper (Cu), and lead (Pb), in two urban areas in China with varying urbanization levels. Enshi (a prefecture-level city) and Wuhan (a provincial capital city) were selected for comparison of the spatially variable relationships between soil heavy metals and their influencing factors. We employed a global stepwise linear regression (STR) model and a local spatial model-geographically weighted regression (GWR) to map the spatial distribution of soil heavy metals based on 121 auxiliary variables, including terrain, geophysical, socioeconomic factors, and remote sensing data. Our results showed that: (1) soil heavy metals exhibited strong spatial aggregation in the prefecture-level city (Enshi) but, nonetheless, have strong spatial heterogeneity in the provincial capital city (Wuhan) due to elevated anthropogenic disturbances; (2) GWR accurately mapped the spatial distributions of As (r = 0.47 and 0.66), Cd (r = 0.74 and 0.53), Cu (r = 0.60 and 0.54), and Pb (r = 0.44 and 0.50) based on auxiliary variables in different cities and also can clearly reveal the spatially variable relationships with main influence factors; (3) human activities were the primary driving factors influencing As and Pb, while natural environment variables were identified as the main potential sources of Cd and Cu. This study demonstrates a methodology to explore spatially variable characteristics of soil heavy metals and their spatial varying relationships with influence factors. The comparative analysis between two cities provides insights that can greatly enhance quantitative source apportionment and support sustainable management strategies for controlling soil heavy metal pollution across varied urban environments.
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Dabaibeh, Reem Naser. "Spatial Distribution of Heavy Metals in Al-Zarqa, Jordan." Indonesian Journal of Chemistry 21, no. 2 (2021): 478. http://dx.doi.org/10.22146/ijc.58304.
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Al-Zarqa is experiencing challenges in industry conversion and extensive urbanization. The environmental quality of soil in the Al-Zarqa region was analyzed by Spatial analysis for the identification of sources and estimation of the concentration of heavy metals, which helped in the assessment of soil quality and heavy metal pollution. The reason for the elevation of heavy metal pollution is increased urbanization, industrialization, traffic, oil refinery emissions, and mixed anthropogenic sources in that region. The main objective of this research was to assess the ecological impact of heavy metals pollutants in the Al-Zarqa region. The concentrations of (Cd, Cr, Cu, Mn, Ni, Pb, Zn, and Fe) were estimated and compared with the existing literature. The distribution pattern of each metal was identified by spatial distribution analysis. Results revealed that metals concentration (Cd, Cr, and Ni) is higher, and the concentration of Pb, Zn, and Cu is less than the maximum allowed limits. Factor analysis identified the potential sources of heavy metals in the investigated area, and spatial distribution showed the geographical distribution of heavy metals over the study area. Consequently, it is better than showing only the individual point concentration without identifying their potential sources and their geographical variations.
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Tian, Mi, Xueqiu Wang, Jian Zhou, et al. "Temporal–Spatial Distributions and Influencing Factors of Heavy Metals As, Cd, Pb, and Zn in Alluvial Soils on a Regional Scale in Guangxi, China." Minerals 13, no. 8 (2023): 1107. http://dx.doi.org/10.3390/min13081107.
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Understanding the temporal–spatial distribution and influencing factors of heavy metals on a regional scale is crucial for assessing the anthropogenic impacts and natural variations in elemental geochemical behavior. This study evaluated the spatial distributions of the heavy metals As, Cd, Pb, and Zn as well as the driving mechanisms over the past 31 years in Guangxi, China, using three geochemical baseline projects (the Environmental Geochemical Monitoring Network Project (EGMON) project 1992–1996; the Geochemical Baseline (CGB) 1 project 2008–2012; and the CGB2 project 2015–2019). By calculating the variable importance using the random forest algorithm, it was found that natural factors are the primary drivers of the spatial distribution of heavy metals in the EGMON project, especially precipitation for As, the digital elevation model (DEM) for Cd and Pb, and temperature for Zn. Surface alluvial soils showed obvious heavy metal enrichment in the CGB1 project, with the gross domestic product (GDP) driving the spatial distribution of all heavy metals. In addition, the anomalous intensity and range of heavy metals in the CGB2 project decreased significantly compared with the CGB1 project, especially owing to the normalized difference vegetation index (NDVI) as a positive anthropogenic factor that improves the degree of rocky desertification, thus reducing the heavy metal contents of As and Pb, and the precipitation promoting the decomposition of Fe–Mn concretions and thus the migration of Cd and Zn. This research promotes an understanding of anthropogenic and natural influences on the spatiotemporal distribution of heavy metals and is of great significance for environmental monitoring and governance.
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Daniel Maramis, Stefan, Rika Ernawati, and Waterman Sulistyana Bargawa. "Distribution Analysis of Heavy Metal Contaminants in Soil With Geostatistic Methods; Paper Review." Eduvest - Journal Of Universal Studies 1, no. 7 (2021): 620–28. http://dx.doi.org/10.36418/edv.v1i7.111.
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Heavy metal contaminants in the soil will have a direct effect on human life. The spatial distribution of naturally occurring heavy metals is highly heterogeneous and significantly increased concentrations may be present in the soil at certain locations. Heavy metals in areas of high concentration can be distributed to other areas by surface runoff, groundwater flow, weathering and atmospheric cycles (eg wind, sea salt spray, volcanic eruptions, deposition by rivers). More and more people are now using a combination of geographic information science (GIS) with geostatistical statistical analysis techniques to examine the spatial distribution of heavy metals in soils on a regional scale. The most widely used geostatistical methods are the Inverse Distance Weighted, Kriging, and Spatial Autocorrelation methods as well as other methods. This review paper will explain clearly the source of the presence of heavy metals in soil, geostatistical methods that are often used, as well as case studies on the use of geostatistics for the distribution of heavy metals. The use of geostatistical models allows us to accurately assess the relationship between the spatial distribution of heavy metals and other parameters in a map.
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Daniel Maramis, Stefan, Rika Ernawati, and Waterman Sulistyana Bargawa. "Distribution Analysis of Heavy Metal Contaminants in Soil With Geostatistic Methods; Paper Review." Eduvest - Journal of Universal Studies 1, no. 7 (2021): 620–28. http://dx.doi.org/10.59188/eduvest.v1i7.111.
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Heavy metal contaminants in the soil will have a direct effect on human life. The spatial distribution of naturally occurring heavy metals is highly heterogeneous and significantly increased concentrations may be present in the soil at certain locations. Heavy metals in areas of high concentration can be distributed to other areas by surface runoff, groundwater flow, weathering and atmospheric cycles (eg wind, sea salt spray, volcanic eruptions, deposition by rivers). More and more people are now using a combination of geographic information science (GIS) with geostatistical statistical analysis techniques to examine the spatial distribution of heavy metals in soils on a regional scale. The most widely used geostatistical methods are the Inverse Distance Weighted, Kriging, and Spatial Autocorrelation methods as well as other methods. This review paper will explain clearly the source of the presence of heavy metals in soil, geostatistical methods that are often used, as well as case studies on the use of geostatistics for the distribution of heavy metals. The use of geostatistical models allows us to accurately assess the relationship between the spatial distribution of heavy metals and other parameters in a map.
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Erbes, S. "Heavy metals spatial distribution in soil ecosystem components roadside territories." Bulletin of Science and Practice 4, no. 7 (2018): 179–83. https://doi.org/10.5281/zenodo.1312205.
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The accumulation and spatial distribution of some heavy metals in the soil is the component of the ecosystems of roadside territories. The processes of accumulation and spatial distribution are considered taking into account the buffer capacity of the traffic flow. Analysis of the buffer capacity of soils in relation to the accumulation of heavy metals is performed using the parameters of the particle size distribution, humus content, pH level. Chemical methods of investigation were used, description of roadside phytocenoses was performed. The analysis of the vertical and horizontal distribution of a number of heavy metals is performed, which showed certain regularities, which are reflected in the conclusion of the work. The greatest differences between the values in the content of mobile forms of heavy metals are the ones for zinc and lead.
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Li, Shuang, Yi Ming Liu, and Yuan Yuan Sun. "Spatial Distribution and Pollution Evaluation of Heavy Metals of Surface Sediments in Nansi Lake." Applied Mechanics and Materials 587-589 (July 2014): 804–7. http://dx.doi.org/10.4028/www.scientific.net/amm.587-589.804.
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The heavy metals contents of 29 samples were tested in Nansi Lake which was divided into 5 parts. The heavy metals included Hg, Cd, Cr, Pb, Ni, Cu, Zn and As. The spatial distribution of heavy metals of 5 Lakes region has been received. The pollution of heavy metals was with evaluated with Igeo and RI. The results showed that: Nasi Lake has been polluted by heavy metals in middle level, and As, Hg, Cd and Pb were more serious. The heavy metals pollution of the part in north were more serious than in south, except the As and Cd. Overall, the heavy metals pollution in the north Zhaoyang Lake was the most serious, followed by the Nanyang Lake, Weishan Lake, Dushan Lake and the south Zhaoyang Lake.
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Chi, Yangyang, Jiayi Wang, Jiale Bi, et al. "Heavy Metals in Sediments of the Yangtze River, Poyang Lake and Its Tributaries: Spatial Distribution, Relationship Analysis and Source Apportionment." Water 17, no. 9 (2025): 1295. https://doi.org/10.3390/w17091295.
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The concentration, spatial distribution characteristics, river–lake relationship analysis and source apportionment of heavy metals in the sediments of the Yangtze River, Poyang Lake and its tributaries were studied in this work. Heavy metals were detected more frequently in the sediments of the Yangtze River compared with the sediments of Poyang Lake and its tributaries. V, Cr, Pb and Ni were the dominant heavy metals in Poyang lake, with V being the most abundant in the lower Yangtze River, Poyang Lake and its tributaries. As, Cu, Ni and V showed similar distribution patterns, with a fan-shaped increasing trend in the southwestern area of Poyang Lake. The spatial distribution of Cr, Hg, Pb and Cd showed a large spatial variability with a decreasing distribution from the northwest to the southeast of the lake. The heavy metals in the sediments of Poyang Lake are related to those in its tributaries. The organic matter, oxidation-reduction potential and depth of sediments are correlated with the heavy metals in sediments. Mining, industrial and road traffic sources were the main sources of heavy metals in the study area. Except for Cd and Hg, most heavy metals in Poyang Lake exhibited a low ecological risk in an environmental evaluation. The results of this study might guide future studies on heavy metals in the sediments of Poyang Lake.
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Magno, J. L., and W. Budianta. "Spatial distribution and pattern of heavy metals in urban soils of Yogyakarta, Indonesia." IOP Conference Series: Earth and Environmental Science 1071, no. 1 (2022): 012032. http://dx.doi.org/10.1088/1755-1315/1071/1/012032.
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Abstract Heavy metals contamination is becoming a global problem in urban areas. With that, understanding spatial distribution and pattern of heavy metals in urban soils is a crucial step toward sustainable urban development. This study intends to assess the spatial distribution and pattern of four heavy metals (Pb, Cu, Zn, and Cd) in Yogyakarta City outward in the boundaries of Sleman and Bantul Regencies. In relation, we utilized geostatistical method Empirical Bayesian Kriging (EBK) then correlated to Land Cover/Use data for the spatial analysis of heavy metals concentration. The degree of contamination was quantified using indices - PI (Pollution Index), Igeo (Geo-accumulation Index), and PLI (Pollution Load Index). We show that by analysing the Pb, Cu, Zn, and Cd elements of 168 urban soils samples collected, Yogyakarta City, a densely populated area, serves as a place of heavy metals contamination hotspots. Pb and Cu is posed as moderately contaminated, whereas Zn and Cd is considered as uncontaminated (as majority of Zn and Cd values does not exceed the background values). But in overlapping consideration of four heavy metals contamination, they are classified as moderately contaminated (PLI=1.10). In summary, heavy metals contamination in soils varies as a function of urbanization.
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Nurcholis, Mohammad, Dwi Fitri Yudiantoro, Darban Haryanto, and Abdurrachman Mirzam. "Heavy Metals Distribution in the Artisanal Gold Mining Area in Wonogiri." Indonesian Journal of Geography 49, no. 2 (2017): 133. http://dx.doi.org/10.22146/ijg.15321.
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Artisanal and small gold mining activity in Wonogiri Regency has long been done with problems on environmental quality. This study was aimed to analyze the levels and spatial distribution of heavy metals in the mining area. Survey of mining and amalgamation sites, sampling the soil and tailings had been conducted. There were 66 samples of soil and tailing were collected, analysis of heavy Fe, Mn, Pb, Hg, As and Co, using X-ray fluorescence (XRF). Normal distribution test of data was conducted using the Kolmogorov-Smirnov and Shapiro Wilk. The spatial distribution of heavy metals was described using Krigging method. Contents of most heavy metals in the area studied were high, except for Co. According to the distribution pattern of heavy metals indicated that the contamination caused by the mining.
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Jin, Mengting, Hao Yuan, Bo Liu, Jiajia Peng, Liping Xu, and Dezheng Yang. "Review of the distribution and detection methods of heavy metals in the environment." Analytical Methods 12, no. 48 (2020): 5747–66. http://dx.doi.org/10.1039/d0ay01577f.
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Li, Qiong, Chun Ming Hao, and Hui Lin Liu. "Spatial Distribution of Heavy Metals in Surface Soil of Zhejiang Pinghu." Applied Mechanics and Materials 130-134 (October 2011): 3773–75. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.3773.
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In this paper, the spatial structure of heavy metals were quantitatively described to soil in Zhejiang Pinghu City based on statistical methods, and the main factors of the spatial structure of heavy metals were discussed in the study region. The results showed that the soil experimental variogram model fitted better in the study area in the 7 heavy metals of As, Cr, Cd, Cu, Ni, Pb, and Zn. Principal component analysis reflected the elements Pb, Zn, Cu, As, Cr and Ni distribution in a same component; and elemental Hg and Cd each a separate component.
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Nie, Shunqi, Honghua Chen, Xinxin Sun, and Yunce An. "Spatial Distribution Prediction of Soil Heavy Metals Based on Random Forest Model." Sustainability 16, no. 11 (2024): 4358. http://dx.doi.org/10.3390/su16114358.
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Mastering the spatial distribution of soil heavy metal content and evaluating the pollution status of soil heavy metals is of great significance for ensuring agricultural production and protecting human health. This study used a machine learning model to study the spatial distribution of soil heavy metal content in a coastal city in eastern China. Having obtained six soil heavy metal contents, including Cr, Cd, Pb, As, Hg, and Ni, environmental variables such as precipitation, soil moisture, and population density were selected. Random forest (RF) was used to model the spatial distribution of soil heavy metal content. The research findings indicate that the RF model demonstrates a robust predictive capability in discerning the spatial distribution of soil heavy metals, and environmental factor variables can explain 60%, 52.3%, 53.5%, 63.1%, 61.2%, and 51.2% of the heavy metal content of Cr, Cd, Pb, As, Hg, and Ni in soil, respectively. Among the chosen environmental variables, precipitation and population density exert notable influences on the predictive outcomes of the model. Specifically, precipitation exhibits the most substantial impact on Cr and Ni, whereas population density emerges as the primary determinant for Cd, Pb, As, and Hg. The RF prediction results show that Cr and Ni in the study area are less affected by human activities, while Cd, Pb, As, and Hg are more affected by human industrial and agricultural production. Research has shown that using RF models for predicting soil heavy metal distributions has certain significance.
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Li, Xiu Xia. "Spatial Distribution of Heavy Metal in Urban Soil of China." Advanced Materials Research 989-994 (July 2014): 454–57. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.454.
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There are significant regional differences of the heavy metals contents in urban soils in China. The heavy metals contents in urban soils of the eastern, central and western regions are quite different, and the pollution of capital cities and prefecture-level cities are different. The study about spatial variability, time differences, pollution levels and environmental risks of heavy metals from China's urban soil show that the heavy metal contents in Chinese cities are over the soil background value in China, especially the contents of Cd and Pb , which were 91.37 times and 41.91 times to the Chinese soil background value. And the content of Ni l is only 1.59 times to the Chinese soil background value.There are also obvious differences among different functional areas the city. Meanwhile, the metal content of urban soils change with the length of time of urban development. Nemero comprehensive pollution index of China's urban soil heavy metal was 45.404, which is heavily polluted. The potential ecological risk index of China's urban soil heavy metal is 71.56, which is high potential ecological risk. Different levels of urban pollution with development degrees cause the different environmental risks.
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Yona, Defri, Mochamad Arif Zainul Fuad, and Nurin Hidayati. "Spatial Distribution of Heavy Metals in the Surface Sediments of the Southern Coast of Pacitan, Indonesia." Indonesian Journal of Chemistry 18, no. 1 (2018): 137. http://dx.doi.org/10.22146/ijc.22400.
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This study was conducted to analyze the spatial distribution of heavy metals from four different coastal areas in southern Pacitan, Indonesia: Pantai Watu Karung (WK), Pantai Teleng Ria (TL), Pantai Pancer (TP) dan Pantai Soge (SG). Data collected in this study included: temperature, salinity, DO, pH, sediment, organic matter and heavy metals in the sediments (Pb, Hg and Cd). The results showed different distribution patterns of heavy metals. Heavy metal concentrations, especially Pb and Hg, were found to be higher in Pantai Soge, while the concentration of Cd was higher in Pantai Pancer. An ANOVA test showed the distributions of Pb and Cd were significantly different (p < 0.01) between sampling sites. Variability of the physicochemical parameters influenced the variabilities of heavy metal concentrations among sampling sites. Overall, heavy metal concentrations in the study areas are rather low; however, attention is still needed due to heavy activities in the coastal areas of southern Pacitan that can contribute to heavy metal pollution.
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Fatima, Rukshana, Nayan Chandra Ghosh, Moniruzzaman Md., et al. "SPATIAL AND TEMPORAL DISTRIBUTION OF HEAVY METALS IN THE BURIGANGA RIVER." Technical Journal 15, no. 1 (2020): 48–58. https://doi.org/10.5281/zenodo.7780928.
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This article represents the spatial distributions of heavy metals in water at sixteen different sites spread over the whole stretch of the Buriganga River (27km). The concentrations of seven metals, Cr, Cd, Pb, Ni, Fe, Zn, and Cu, were analyzed using an Atomic Absorption Spectrophotometer (Thermo-Scientific, 3000 series) in the RRI laboratory. The concentrations were compared with several standard guidelines provided by organizations like WHO, DoE, FAO, and CCME. The visualization of the spatial pattern of individual metal throughout the Buriganga was primed using ArcGIS 10.3 software. The result showed that these heavy metals severely polluted the surface water of the whole stretch of the Buriganga in the dry season except Cu and Zn. The statistical analysis showed a wide variation of concentrations among Cr, Cd, Pb, Ni, Fe, Zn, and Cu but slightly differed among the locations. Anthropogenic activities are mainly responsible for elevated levels of the measured metals in river water. A lower heavy metal concentration was found in the post-rainy season compared to the dry season. Even though the concentration has decreased post rainy season, some severe toxic heavy metals like Cr and Cd concentrations are far above the safe recommended values.
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Wang, Zhao, and Xubo Sun. "Spatial Distribution Characteristics of Heavy Metals and Pollution Analysis Methods." Scientific Journal of Technology 4, no. 10 (2022): 14–18. http://dx.doi.org/10.54691/sjt.v4i10.2399.
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With the rapid development of urban economy and the continuous increase of urban population, the discharge and improper disposal of a large number of industrial wastes, urban domestic garbage, sludge and other pollutants have led to the continuous accumulation of heavy metals in the soil, which has increased the pollution load of heavy metals in the soil, leading to the increasingly serious heavy metal pollution of urban topsoil in China. Heavy metal pollution of urban soil is one of the important indicators that can effectively reflect the status of urban environmental pollution. Therefore, the verification of urban soil environment anomalies and the application of verification data to urban environmental quality assessment, as well as the study of the evolution model of human activities affecting urban soil environment, have increasingly become the focus of attention. Based on the analysis of a large number of relevant documents and previous work, the sources, hazards and pollution status of soil heavy metal pollution in some regions of China are briefly summarized, and the characteristics of five commonly used assessment methods of soil heavy metal pollution (single pollution index method, comprehensive pollution index method, geo accumulation index method, potential ecological risk index method, principal component analysis method) are briefly analyzed and summarized, It is expected to provide some reference for the investigation and treatment of soil pollution.
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Wang, Junlei, Chunyu Dong, Sijing Sun, Liyuan Mu, Naiming Zhang, and Li Bao. "Characteristics and Correlation Analysis of the Spatial Distribution of Heavy Metals in Arable Soils with Different Soil-Forming Matrices." Sustainability 16, no. 23 (2024): 10338. http://dx.doi.org/10.3390/su162310338.
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The problem of the contamination of soils with high background values of heavy metals has attracted increasing attention. In this paper, the contents, spatial distribution characteristics and correlations of five heavy metals in seven types of arable soils with different soil-forming matrices were analyzed by using Kriging spatial interpolation, descriptive statistics and correlation analysis to clarify the spatial distribution of heavy metals in different soil-forming matrices, and to explore the influence of parent rocks on the spatial distribution and concentration of heavy metals. The results showed that the Cd contents of the seven soil-forming parent materials exceeded the background values recorded for soils in Yunnan Province and that metamorphic rocks such as mudstone, argillaceous rock, purple rock, and carbonate rock exceeded the risk screening values. The average Pb, Cu, and As contents were lower than the background values recorded for soils in Yunnan Province and smaller than the risk screening values for agricultural land. Carbonate areas have a large area of contamination, while metamorphic mudstone areas have a relatively small percentage of contamination. The correlations of heavy metals in different soil-forming matrices varies, and the source of each element and its correlation can be further analyzed and verified by means such as the source analysis method. The results of this study are crucial for pollution prevention and the analysis of the source of heavy metal soil contamination.
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G.M., Shikhaleyeva, Ennan A.A., Chursina O.D., Shikhaleyev I.I., and Yurchenko Yu.Yu. "ECOLOGICAL AND GEOCHEMICAL ASSESEMENT OF KUYALNIK ESTUARY." Біологія та валеологія, no. 19 (December 12, 2017): 199–207. https://doi.org/10.5281/zenodo.1109597.
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The long-term investigations of Kuyalnik liman bottom sediments during the period of 2002-2012 years showed that the pollution levels in this estuary by heavy metals (Pb, Cd, Cu, Zn, Cr, V, Mn) and their spatial distribution depend on the location of the local anthropogenic contamination sources and the mechanical composition and types of sediments. The small depth, the limited water exchange and silt structure contribute to the accumulation of heavy metals in bottom sediments of Kuyalnik estuary. This research yields the data on the spatial distribution of heavy metals in the surface (0-20 cm) layer of bottom sediments of Kuyalnik estuary and made it possible to estimate the current level of pollution. All the sediment samples are shown to contain heavy metals (V, Zn, Pb, Cd, Mn, Cu). In particular, the high concentrations of metals that belong to the first class of hazard (Cd, Zn, Pb) are registered. The average concentration for all studied metals except cadmium and zinc do not exceed the geochemical background. The maximum concentration of Pb, Zn, Cd, V exceed the limit values for soil. The level of technogenic pollution was established to be quite equal with the natural clarkes of lithosphere levels.
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Augustine, Abah Odeh, Ali Alwadood Jasini, Nnaemeka Ihenacho Michael, et al. "A GIS-based analysis of heavy metals around Otukpo rice mill in Benue state." World Journal of Advanced Research and Reviews 22, no. 1 (2024): 036–42. https://doi.org/10.5281/zenodo.14187467.
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Heavy metals are primarily sourced from natural pedo-geochemical backgrounds and anthropogenic occurrences like composting, sewage sludge, aerosol deposition, and waste animal manure. The study aims to determine the heavy metals within the rice mill in Otukpo to understand the spatial distribution with the objectives to examine the heavy metals within the identified activity areas in the Otukpo rice mill, to determine the spatial distribution of heavy metals within the study area and to compare heavy metal values with the acceptable limits. Soil samples were collected from ten locations at Otukpo Rice Mill to analyze heavy metal concentrations. The samples were collected using sterile bottles and a stainless trowel, and the soil samples were analyzed for the concentrations of Cadmium, Copper, Lead, Nickel, Zinc, Mercury, Iron, Arsenic, and Chromium using the Atomic Absorption Spectrophotometry method. The result was analyzed using interpolation to see the variation of the Heavy metals within the various activity areas. The result of the study reveals that Iron has the highest concentration at the Entrance point and lowest at the Generator house with a range value of 3.92 – 1.12mg/kg respectively. The highest concentration of Zinc was recorded at the Mechanic workshop while the lowest is at the Drying point with a range value of 0.135 – 0.872mg/kg respectively. The Husk dumpsite recorded the highest concentration of Copper (0.666mg/kg) with the Drying point recording the least (0.088 mg/kg). The study reveals uneven concentrations and highlights the effectiveness of the Geographic Information System in mapping heavy metal concentrations.
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Chang, Jing-Song, Kuang-Chung Yu, Li-Jyur Tsai, and Shien-Tsong Ho. "Spatial distribution of heavy metals in bottom sediment of Yenshui river, Taiwan." Water Science and Technology 38, no. 11 (1998): 159–67. http://dx.doi.org/10.2166/wst.1998.0459.
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Distribution of heavy metals in bottom sediments from heavily polluted section of Yenshui river, located in the southern Taiwan, are presented. Sediment cores of seven sites were separated into several cuts and analyzed with both sequential extraction procedure (SEP) to realize the heavy metal contents (including Cr, Co, Zn, Ni, Pb, Cu and Cd) among binding fractions of different sediment depth and multivariate analysis (MA) to conduct the correlations of heavy metal variation in depth profile. Results show that distribution of heavy metals in depth profile of sediment is not identical among different sites. Levels of Zn, Cr, Cu and Ni were higher than other metals, and within the ranges of 30–200 mg/Kg, 8–160 mg/Kg, 5–130 mg/Kg, 10–100 mg/Kg, respectively. The major binding forms of Zn, Cr and Cu in sediment were ‘bound to carbonates’, ‘bound to Fe oxides’ and ‘bound to organic matter’ respectively. And, the percentages of different heavy metal binding forms were not significantly varied in depth profile. Results of principal component analyses (PCA) demonstrate that Cr, Ni and Cu were clustered, which indicate these metals had similar loadings in sediment profile, and might be discharged from the same pollution source of electroplating industry.
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Wang, Shi Xu, Zu Lu Zhang, and Xue Wang. "Heavy Metal Environmental Assessment of Surface Soil in Rizhao Tea-Planting Areas." Advanced Materials Research 807-809 (September 2013): 1397–401. http://dx.doi.org/10.4028/www.scientific.net/amr.807-809.1397.
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Analysis about contents and distributions of heavy metal elements in soil is one of the primary matters in surveying geochemical environmental quality in Rizhao tea-planting areas. By using 1km×1km sampling data of surface soil in Rizhao tea-planting areas, Geostatistics method is adopted to analyze spatial distribution of heavy metal elements, and nemerow synthetic index method is adopted to assess environmental qualities of heavy metals and show the result out by Kriging interpolation. The assessment results are as follows: the distribution of all the heavy metals besides Cd, Pb is comparatively uniformity; From the result of the single pollution index, the gross part of research areas is clean, only Cd, Ni pollution existed in finitude areas; From the spatial distribution of nemerow synthetic pollution index, 88.41% of the research areas soil belongs to level I, and 6.44% belongs to level II, and 5.14% level III, while no area belongs to level IV and level V.
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Zhu, He, Haijian Bing, Huapeng Yi, Yanhong Wu, and Zhigao Sun. "Spatial Distribution and Contamination Assessment of Heavy Metals in Surface Sediments of the Caofeidian Adjacent Sea after the Land Reclamation, Bohai Bay." Journal of Chemistry 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/2049353.
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Land reclamation can significantly influence spatial distribution of heavy metals in inshore sediments. In this study, the distribution and contamination of heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn) in inshore sediments of Bohai Bay were investigated after the land reclamation of Caofeidian. The results showed that the concentrations of Cd, Cr, Cu, Ni, Pb, and Zn in the sediments were 0.20–0.65, 27.16–115.70, 11.14–39.00, 17.37–65.90, 15.08–24.06, and 41.64–139.56 mg/kg, respectively. These metal concentrations were generally higher in the area of Caofeidian than in other Chinese bays and estuaries. Spatially, the concentrations of Cd, Cr, Cu, Ni, and Zn were markedly lower in the sediments close to Caofeidian compared with other regions, whereas the concentrations of Pb showed an opposite case. Hydrodynamic conditions after the land reclamation were the major factor influencing the distribution of heavy metals in the sediments. Grain sizes dominated the distribution of Cu and Zn, and organic matters and Fe/Mn oxides/hydroxides also determined the distribution of the heavy metals. Multiple contamination indices showed that the inshore sediments were moderately to highly contaminated by Cd and slightly contaminated by other heavy metals. Similarly, Cd showed a high potential ecorisk in the sediments, and other metals were in the low level. Chromium contributed to higher exposure toxicity than other metals by the toxicity unit and toxic risk index. The results of this study indicate that after the land reclamation of Caofeidian the contamination and ecorisk of heavy metals in the sediments markedly decreased in the stronger hydrodynamic areas.
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Liu, Yi-Jian, and Zi-Yu Li. "Research on Locating Model of Heavy Metal Pollutants Source Based on SFPI Method and 2D Convection-Diffusion Equation." Environment and Natural Resources Research 7, no. 2 (2017): 68. http://dx.doi.org/10.5539/enrr.v7n2p68.
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As an important field in environmental science, the research on the locating issue of heavy metals pollutants source has increasingly attracted attention of scholars and society. In order to locate the pollutants source, we should firstly figure out the spatial distribution of heavy metals pollutants and pollution degree of different subareas in a limited area. Based on the datasheets from CUMCM 2011, we obtain the spatial distribution figures of heavy metals on MATLAB platform. Then, we introduce SFPI method to build an evaluation model of pollution degree in different subareas, with analyzing of the result of which, we can approximately conclude that the location of heavy metals pollutants source may be located in Industrial Area and Traffic Area. Further analyzing, to position the pollutants source more precisely, we introduce 2D convection-diffusion equation to describe the pollutant pathway of heavy metals, solve the equation with FDM algorithm on Maple platform, and obtain the propagation function of heavy metals concentration. Finally, we furtherly modify the propagation function and then figure out the precise coordinates of the pollution source and the corresponding subareas.
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Du, Jiaxu, Fu Liao, Ziwen Zhang, Aoao Du, and Jiale Qian. "Spatial Heterogeneity and Controlling Factors of Heavy Metals in Groundwater in a Typical Industrial Area in Southern China." Water 17, no. 13 (2025): 2012. https://doi.org/10.3390/w17132012.
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Heavy metal contamination in groundwater has emerged as a significant environmental issue, driven by rapid industrialization and intensified human activities, particularly in southern China. Heavy metal pollution in groundwater often presents complex spatial patterns and multiple sources; understanding the spatial heterogeneity and controlling factors of heavy metals is crucial for pollution prevention and water resource management in industrial regions. This study applied spatial autocorrelation analysis and self-organizing maps (SOM) coupled with K-means clustering to investigate the spatial distribution and key influencing factors of nine heavy metals (Cr, Fe, Mn, Ni, Cu, Zn, As, Ba, and Pb) in a typical industrial area in southern China. Heavy metals show significant spatial heterogeneity in concentrations. Cr, Mn, Fe, and Cu form local hotspots near urban and peripheral zones; Ni and As present downstream enrichment along the river pathway with longitudinal increase trends; Zn, Ba, and Pb exhibit a fluctuating pattern from west to east in the piedmont region. Local Moran’s I analysis further revealed spatial clustering in the northwest, riverine zones, and coastal outlet areas, providing insight into potential source regions. SOM clustering identified three types of groundwater: Cluster 1 (characterized by Cr, Mn, Fe, and Ni) is primarily influenced by industrial pollution and present spatially scattered distribution; Cluster 2 (dominated by As, NO3−, Ca2+, and K+) is associated with domestic sewage and distributes following river flow; Cluster 3 (enriched in Zn, Ba, Pb, and NO3−) is shaped by agricultural activities and natural mineral dissolution, with a lateral distribution along the piedmont zone. The findings of this study provide a scientific foundation for groundwater pollution prevention and environmental management in industrialized areas.
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Zhang, Yong, Jing Xia Chen, Jun Qiu Zhang, and Ying Te Wang. "Spatial Distribution and Sources of Heavy Metal Pollution of Surface Dust in Taiyuan, China." Applied Mechanics and Materials 737 (March 2015): 503–7. http://dx.doi.org/10.4028/www.scientific.net/amm.737.503.
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The concentrations of heavy metals (Cr, Cu, Ni, Pb and Mn) were determined using flame atomic absorption spectrophotometer after digested with four acids. The samples were collected from seven kinds of different functional areas in Taiyuan, China. The concentration of the heavy metals were found in Taiyuan is higher than the soil background values in Shanxi Province, which appeared different levels of accumulation. High concentrations of Cr, Ni, Mn were found in the samples from industrial area and Cu was noted from economic development area. The correlational analysis and principle component analysis showed that the heavy metals of surface dust in Taiyuan were mainly influenced by industrial activities.
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Toroyan, Ruben A., and Irina P. Takh. "SPATIAL DISTRIBUTION OF THE CONTENT OF HEAVY METALS IN THE BELAYA RIVER ECOSYSTEM." Ecologica Montenegrina 14 (October 30, 2017): 119–27. http://dx.doi.org/10.37828/em.2017.14.13.
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This paper presents the results of the research on the content and spatial distribution of heavy metals in the system of “water – bottom sediments” of the Belaya River. Quantitative data were obtained and the authors performed comparative analysis of the pollution of various abiotic environments of the river ecosystem. The pattern of vertical distribution of heavy metals in bottom sediments is shown to be linked to the level of pollution and conditions of the river flowage. Concentration of dissolved and suspended forms of the studied elements (the content of Fe, Mn, Cu, Pb, Zn, the oxidation-reduction potential, рН, turbidity and water temperature) in water samples from different gauge stations of the Belaya River is characterized by heterogeneity. There is a clear tendency for the increase of the content of Fe, Mn, Zn, and Cu down the river flow with the maximum concentrations in the foothill zone of the Republic. The studied heavy metals have prevalence of the suspended form of migration. Concentration of heavy metals in bottom sediments is considerably uneven in their distribution in different sites of the Belaya River. Bottom sediments are noticeably polluted with Zn and Pb at the village of Ministochnik, the aul of Bzhedugkhabl, and at the river mouth. In the lower watercourse of the Belaya River, contamination of bottom sediments with Cu prevails. In the gauge stations with low content of heavy metals, their vertical distribution is quite homogenous. In less polluted parts of the river, flowage plays an important role in vertical distribution of heavy metals. For example, with weak flowage (the part of the river from the village of Ministochnik to the aul of Bzhedugkhabl), the highest concentrations are in the surface layers of 0-10 cm in comparison to the layer of 10‒30 cm. With strong flowage (Dakhovskaya stanitsa), the lowest content of heavy metals is in the upper layer of 0‒10 cm, and the highest is in the layer of 10‒30 cm.
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Chen, Guoqing, Yong Yang, Xinyao Liu, and Mingjiu Wang. "Spatial Distribution Characteristics of Heavy Metals in Surface Soil of Xilinguole Coal Mining Area Based on Semivariogram." ISPRS International Journal of Geo-Information 10, no. 5 (2021): 290. http://dx.doi.org/10.3390/ijgi10050290.
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Heavy metal pollution is a major environmental problem facing humankind. Locating the source and distribution of heavy metal pollutants around mines can provide a scientific basis for environmental control. The structure effect and random effect of a semivariogram can be used to determine the reason for spatial differences in the heavy metal content in surface soil, and the coefficient of variation and regression analysis can be used to confirm that the verification accuracy meets the geostatistical requirements. According to the maximum difference method, the content of heavy metals in the surface soil of the mining area is higher than that of the surroundings, and Cu and Zn levels are higher than the background values for Inner Mongolia. In the present case, Zn, Mn, Pb, Cr, Ni, and Cu levels exceeded the background values for the surroundings of the study area by 65.10%, 53.72%, 52.17%, 46.24%, 33.08%, and 29.49%, respectively. The results show that human activities play a decisive role in the spatial distribution of heavy metals, leading to their spatial distribution in the form of “core periphery”. This distribution pattern was significantly affected by the slope, NDVI value, and the distance from the mining area, but the spatial distribution of Pb was significantly related to high-grade roads. The research methods and conclusions have reference significance for the sources and spatial distribution characteristics of heavy metal pollution in similar mining areas and provide a target for the prevention and control of environmental pollution in the study area.
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Li, Qi. "Spatial Distribution and Assessment of Soil Heavy Metals in Suburb Cropland, Suzhou City, Anhui, China." Advanced Materials Research 712-715 (June 2013): 457–60. http://dx.doi.org/10.4028/www.scientific.net/amr.712-715.457.
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In this paper, concentrations and spatial distribution of four heavy metals (Cu, Pb, Zn, As) in cropland soil from suburb area of Suzhou city were determined and analysed by X-Ray fluorescence spectrometer and interpolation analysis. Then based on integrated pollution index (IPI), pollution levels of the heavy metals were assessed. The results indicate that the mean concentrations of As was higher than the value of Anhui soil background, while the others were lower; Spatial distribution of Pb and Zn were affected by traffic pollution, Cu was related with the emissions of garbage and waste, As was came from the use of pesticides; The IPI of heavy metals belonged to light pollution levels, and As was higher than the others.
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Zhang, Yan, Shiqiao Liu, Li Zhang, et al. "Application of Singularity Theory to the Distribution of Heavy Metals in Surface Sediments of the Zhongsha Islands." Journal of Marine Science and Engineering 10, no. 11 (2022): 1697. http://dx.doi.org/10.3390/jmse10111697.
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This research aimed to use nonlinear theory and technology to describe the spatial distribution of heavy metals in the surface sediments of the Zhongsha Islands Sea region. The goal of this study is to explore the spatial distribution characteristics of heavy metals in the surface sediments of the Zhongsha Islands. The singularity theory and method were used to delineate heavy metal geochemical anomalies and the generalized self-similarity analysis method was used to decompose heavy metal geochemical anomalies and background concentrations. The results showed that there were abnormally high concentrations of heavy metals in the deep-sea plain area and in the western central sand trough area. The results of this study can inform priority areas for environmental monitoring. The element anomalies extracted by the singularity analysis method in this paper can be a guide to the next step in the investigation and provide the basis for the regional environmental assessment.
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Ma, Haotian, Zhilei Zhen, Meixia Mi, and Qian Wang. "Characteristics of nutrients pollution and ecological risk assessment of heavy metal in sediments of Fenhe River, Taiyuan section, China." Water Supply 22, no. 3 (2021): 2596–611. http://dx.doi.org/10.2166/ws.2021.453.
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Abstract This study aimed to reveal the characteristics of nutrients and heavy metals associated with ecological risks in the sediments of Fenhe River, Taiyuan section. The concentrations of nutrients (total nitrogen, total phosphorus, total organic matter) and heavy metals (As, Cu, Zn, Pb, Cr, Ni, Hg, Cd) were investigated. Spatial distribution, correlation analysis and source identification were facilitated to indicate nutrient and heavy metal pollution characteristics. Evaluations of heavy metals’ contamination degree were achieved by comprehensive ecological risk indexes including Igeo, Iin, Cf, pollution load index and risk index. The results showed that nutrients accumulated in the middle region and were mainly from embryophyte, zooplankton and phytoplankton or algae, based on C/N values. Large spatial variabilities existed in heavy metal distribution patterns; source identification for heavy metals revealed they were from natural sources and anthropogenic activities based on a principal component analysis model. Results of different ecological risk indexes showed that pollution associated with Hg was rated as a moderate ecological risk but was significant contamination, higher ecological risks mainly existed in the middle region.
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Niu, Jia Tian, Qin Kui Guo, Mei Guo, Yi Li, and Qun Hui Wang. "Spatial Distribution of Heavy Metals in Soybean Plantation Soils in Central Sanjiang Plain." Applied Mechanics and Materials 71-78 (July 2011): 3174–78. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.3174.
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Monitoring and analysis of the content of five heavy metals (i.e., Cd, Hg, As, Pb and Cr) in soybean plantation soils in central Sanjiang plain were conducted using the geographic information system (GIS). Statistical analysis indicated, strong intensities of spatial correlation among As, Cr, and Pb, whereas moderate intensities of spatial correlation were observed between Cd and Hg. Therefore, the content and the spatial distribution of the heavy metals are primarily affected by the parent material, topography, soil properties, and other internal factors. However, the effect of external factors, such as industrial pollution, farming methods, as well as the application of pesticide and fertilizer, should also be investigated.
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Ghaida Fathassabilla, Afra, and Wawan Budianta. "PENCEMARAN TANAH OLEH Pb DAN Cd DI SEKITAR TEMPAT PEMBUANGAN AKHIR (TPA) PUTRI CEMPO, KOTA SURAKARTA." KURVATEK 8, no. 1 (2023): 81–92. http://dx.doi.org/10.33579/krvtk.v8i1.3919.
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One of the impacts of rapid population growth is the problem of waste management. One of the impacts of waste disposal at the landfill is soil contamination due to heavy metals originating from waste disposed of. This study aims to determine the concentration and distribution of heavy metals in the soil laterally and vertically around Putri Cempo Landfill through spatial analysis. Sampling was carried out at 14 points with 3 different depths, namely 10 cm, 30 cm, and 60 cm. Data analysis was performed on 42 soil samples, including analysis of grain size, pH and organic content, heavy metal content, and distribution of heavy metals. The results showed that the concentrations of Pb and Cd at the three depths of the soil samples were mostly above the background values of each heavy metal. The distribution patterns of the two heavy metals laterally in the study area were relatively different, while the vertical distribution of contaminants decreased in concentration as the distance from the soil surface increased.
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Wu, Yao Qing, and Li Li. "Distribution Characteristics and Potential Ecological Risk Assessments and Heavy Metals in Surface Sediments and Water Body of the Yalu River Estuary China." Applied Mechanics and Materials 522-524 (February 2014): 88–91. http://dx.doi.org/10.4028/www.scientific.net/amm.522-524.88.
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Surface sediments and water body of the Yalu River estuary were monitored to evaluate the spatial distribution and the enrichment condition of heavy metals: As, Cu, Cd, Cr, Hg, Pb and Zn. Surface sediment samples and water samples were collected from 5 stations, at seven month intervals from May 2012 to November 2012. The correlation of the heavy metals in the surface sediments and the water body was analyzed by using Pearson method. And the method of potential ecological risk index presented by Hakanson was used to evaluate the potential ecological risk of heavy metal pollution in the Yalu River estuary. The results showed that, the order of heavy metals spatial fluctuation degree was Zn > Cr > Pb > Cu > total As > Cd > total Hg, the fluctuation degree of total contents of heavy metals was A1 > A3 > A2 ≈ A4 > A5. The evaluation of potential ecological risk showed that, total Hg reflected considerate ecological risk, total As and Cd reflected moderate ecological risk, and the rest of the heavy metals posed a low ecological risk.
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Si, Nianting, and Liang Qu. "Distribution characteristics and potential risk assessment of heavy metals in seawater and sediment of Liaodong Bay." E3S Web of Conferences 206 (2020): 02004. http://dx.doi.org/10.1051/e3sconf/202020602004.
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Distribution of heavy metals (Hg, Cu, Pb, Zn, Cd and Cr) in the seawater and sediments were studied based on data from two oceanographic surveys carried out in Liaodong Bay in May and October 2016. The results showed that the values of heavy metals in seawater represent a uniform distribution, while no trends were detected for spatial distribution. High values of heavy metals in sediment were generally distributed nearshore areas in October. Concentrations of Pb, Zn, Hg in seawater were higher than the national guideline values of Mar. sediment quality of China. Values of Cu, Zn, Cd and Hg were higher than the national guideline values of Mar. sediment quality of China in October, while quality was in good condition in May. Correlation analysis showed that TOC was mainly contributed for the variations of heavy metals. The potential ecological risk analysis of heavy metals indicates that Hg, Cd and Cu should be listed as the priority contaminant metals in Liaodong Bay.
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Zeng, Yunhui, Yuanbiao Zhang, Shusheng Huang, et al. "Analysis of Soil Pollution Degree and Causes Based on Mathematical Model." Journal of Environment and Ecology 9, no. 2 (2018): 16. http://dx.doi.org/10.5296/jee.v9i2.13655.
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Taking the heavy metal pollution in the urban surface soil as the object, this paper analyzes the degree of heavy metal pollution in different areas in the city and the main causes of pollution. Firstly, this paper uses Kriging interpolation method to increase the sample data together with Surfer software to draw the spatial distribution map of eight heavy metals, and then compares the single factor index method and the geological accumulation index-Nemero index method to make a comprehensive evaluation of the heavy metal pollution degree in different areas of the city. It is concluded that the pollution level in the area from slight to heavy is: mountain areas, park green areas, living areas, traffic areas, industrial areas. Then, the main comprehensive index of heavy metals is extracted by the principal component analysis, and the spatial distribution map of the main factors is drawn based on it. According to the spatial distribution map, the main cause of heavy metal pollution is the emission of automobile exhaust and industrial waste, which provides a reliable theoretical basis for the prevention and treatment of heavy metal pollution in the urban surface soil.
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Chen, Yunfei, Jinlong Zhou, Yinzhu Zhou, Yanyan Zeng, and Ying Sun. "Factors that influence the spatial distribution of heavy metals in soil of the Yutian County, Xinjiang, China." E3S Web of Conferences 98 (2019): 06002. http://dx.doi.org/10.1051/e3sconf/20199806002.
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In this study, 1165 surface soil samples for heavy metal analysis were collected in the Yutian County, Xinjiang, China. The factors that influence the spatial distribution of heavy metal elements in soils in the study area were analyzed by means of multivariate statistical analysis, geostatistics, spatial autocorrelation, spatial analysis and GIS technology. Results show that among 1165 soil samples, three of which had As contents greater than the risk screening values. The theoretical models for variation function of Cd and Pb were exponential model, while the theoretical models for variation function of Hg, As, Cr, Cu, Ni and Zn were spherical model. Nugget value of Cd was less than 25%, indicated a relatively strong spatial correlation. Nugget value of other elements ranged between 25% and 50%, indicated significant spatial correlations. The spatial autocorrelation Moran's I index of soil heavy metal contents in the Yutian County was greater than 0. There was a positive spatial correlation distribution in the county scale. The spatial distribution of soil heavy metal contents in the Yutian County showed a general decreasing trend from the center of the study area to surrounding areas. Distribution of soil heavy metal contents in the Yutian County varied in different parent materials, soil types and land use patterns. Hg, As, Pb, Cr, Cu, Ni and Zn in soil derived from the same source, contents of which were affected by soil texture.
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Li, Youwen, Jiangpeng Xue, Jixiang Cai, et al. "The Spatial Distribution and Influencing Factors of Heavy Metals in Soil in Xinjiang, China." Sustainability 15, no. 23 (2023): 16379. http://dx.doi.org/10.3390/su152316379.
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Heavy metal pollution has been a problem of concern in soil ecology in recent decades. This study investigated the spatial distribution of heavy metals and their pollution levels in the soil of Xinjiang, based on the data of heavy metals published in the literature in the past five years, by using a geostatistical method, pollution index method, and geographic information system (GIS)-based spatial analysis. Additionally, the effects of five economic development indicators, such as population and industrial activities on the accumulation of heavy metals in soil, were explored by correlation analysis. The results showed that the average contents of Cd, Cr, Cu, Ni, Pb, and Zn in the soils were 2.858, 1.062, 1.194, 1.159, 1.192, and 1.086 times higher than the background values in Xinjiang, respectively. The semi-variance functions indicated that the Cd and Pb block gold coefficients of soils were greater than 25% and less than 50%, with an obvious spatial correlation. The spatial patterns showed that the high values of Cd, Cr, Cu, Ni, Pb, and Zn were mainly distributed in Karamay, Changji, Tacheng, and Kashi areas, with an overall decreasing trend from north to south, and the pollution index showed that the pollution of heavy metal Cd in soil was the most serious. Furthermore, Karamay, Changji, and Kashi areas were at heavy pollution levels. Correlation analysis showed that heavy metal Pb in the soil was significantly positively correlated with the agricultural GDP in Xinjiang, while Cd was correlated significantly and positively with comprehensive energy consumption and more significantly with industrial GDP. Thus, this study could provide a scientific basis for local evaluation of soil environmental quality and prevention and control of soil heavy metal pollution, which is of great significance for understanding the impact of human activities.
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Zhang, Yibo, Yue Yu, Guanping An, Tao Huang, and Junhan Huang. "Spatial Distribution of Pollutants and Risk Assessment of Heavy Metals in Farmland Groundwater around a Traditional Industrial Park—A Case Study of Shifang City, Southwestern China." Sustainability 15, no. 20 (2023): 14903. http://dx.doi.org/10.3390/su152014903.
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In this paper, the groundwater environment in the farmland area around a traditional industrial park in Shifang City, southwest China, was taken as the research object. Geostatistical methods with GIS technology were adopted to analyze the spatial distribution of conventional pollutants and heavy metals in groundwater and to evaluate potential ecological risks. Chemical oxygen demand (CODMn) and ammonia nitrogen (NH3-N) distributions showed poor continuity and apparent spatial differentiation, which were primarily attributed to intensive anthropogenic activities (e.g., industrial discharges). The total relative hardness of (TH), SO42−, and Cl− were uniformly affected by external factors, with little spatial differentiation. Concentrations of total phosphorus (TP), TH, SO42−, and Cl− followed an approximately normal distribution; the peak values of detected concentrations appeared in the frequency distribution range, while CODMn and NH3-N did not. Groundwater showed enrichment for various heavy metals, mainly Zn and Cu, with apparent spatial differentiation in Cr and Cu, consistent with external interference. The correlation coefficients of Cr–Cu and Cu–Pb were 0.693 and 0.629 (p < 0.01), respectively, indicating similar pollution sources. The single-factor pollution index for groundwater was Ni > Pb > Mn > Zn > Cu > Cr. Cu had a moderate potential ecological risk. The six heavy metals’ average integrated potential ecological risk index (RI) revealed that mild pollution accounted for 96.2% of the investigation area. Overall, the traditional industrial park poses a mild ecological risk to the shallow groundwater in the surrounding farmland.
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Al-Dulaimi, Eman, Sufyan Shartooh, and Emad Al-Heety. "Concentration, Distribution, and Potential Sources of Heavy Metals in Households Dust in Al-Fallujah, Iraq." Iraqi Geological Journal 54, no. 2F (2021): 120–30. http://dx.doi.org/10.46717/igj.54.2f.11ms-2021-12-28.
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Household dust pollution with heavy metals attracted the attention of researchers and environmental managers due to the risk of the health of these metals. The study aims are to determine heavy metals concentrations (Cd, Cr, Cu, Ni, Pb, Zn), their spatial distribution, and their potential sources in the household dust of Al-Fallujah City, Iraq. The dust was sampled from 50 houses. The heavy metals levels in the dust were measured using the atomic absorption spectrophotometry method. The mean concentration of heavy metal was ordered as following: Zn (292.85 mg/kg) > Cr (289.45 mg/kg) > Ni (105.72 mg/kg) > Pb (75.57 mg/kg) > Cu (65.03 mg/kg) > Cd (14.77 mg/kg). The mean concentration of these metals exceeded the reference values. The areal distribution of the reported heavy metals showed specific and non-specific patterns indicating point and non-point pollution sources. The heavy metals potential sources in house dust in the study area were characterized using correlation, Principle components and cluster analyses. The potential sources for Cd, Cu and Pb were interior and exterior sources, while the Ni and Cr were derived from internal sources. This study provides the environmental protection managers and decision-makers with important information about heavy metals concentrations and their sources in indoor environments.
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Saber, Mohammed. "Vertical and Lateral Distribution of Heavy Metals in the Euphrates River Sediments between Heet and Fallujah, Western Iraq." Iraqi Geological Journal 54, no. 2A (2021): 112–25. http://dx.doi.org/10.46717/igj.54.2a.9ms-2021-07-30.
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In recent decades, significant attention has been paid to heavy metal contamination as a dangerous environmental problem because of the toxicity, abundance, persistence and bioaccumulation of these elements (Chen et al., 2016,) (Islam et al., 2017 and ) (Jin et al., 2019). In general, the contamination state of the environment is evaluated by the total concentration of heavy metals (Kanda et al., 2018). The riverine sediments are considered as the main basins for various pollutants following the largely uncontrolled discharge of contamination resulting from human activities and geogenic processes (Liu et al., 2018). The sediment contamination is an important indicator of environmental variation as a result of anthropogenic influence (Gao et al., 2019). River sediments serve as not only a major sink and carrier of heavy metals but also as potential sources of secondary pollution, which can reflect their contamination level (Tang et al., 2014 and ) (Hsu et al., 2016). The heavy metals are released into the aquatic environments from geogenic and anthropogenic sources. The geogenic sources include chemical leaching of bedrock, water drainage basins and runoff from banks (Raj et al., 2017). The anthropogenic sources of heavy metals pollution in aquatic systems include mining activities, industrial wastes disposal and pesticides use, (Chakravarty & Patgiri, 2009). The heavy metals pollution of sediments is an indicator of the aquatic systems water quality (Zhao et al., 2012). The heavy metal distribution in sediments and pollution levels supplies a base for consideration of sediments treatment methods and evaluation of the potential releasing of heavy metals into water and transport downstream (Nawrot et al., 2020). The vertical and spatial distribution of heavy metals and pollution levels have been evaluated in sediments of many world rivers, such as the Yinma River, China (Guan et al., 2018), the Voghji River, Armenia (Gabrielyan et al., 2018), the Barigui River, Brazil (Machado et al., 2017), the Harazdan River, Armenia (Petrosyan et al., 2019), the Thames River, the UK (Vane et al., 2020), the Yang River, China (Tang et al., 2020), and the Lu Lu River, China (Ye et al., 2020). The spatial distribution of heavy metals in sediments of the Euphrates River in Iraq has been investigated by many authors (Issa & Qanbar, 2016); (Al-Taher et al., 2020); and (Hussain & Al-Jaberi, 2020). The spatial variation of heavy metal concentrations in sediments of the Euphrates River along the studied area between Heet and Ramadi Cities has been studied by (Al-Bassam & Al-Mukhtar, 2008) and (Salah et al., 2012). The aim of the study is to investigate how heavy metals are laterally and vertically distributed in sediments of the given study area of Euphrates River between Heet and Fallujah Cities. This study represents the first attempt to investigate the vertical distribution of heavy metals in the Euphrates River sediments.
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Ganesan, Chinnaperamanoor Madhu, Chinnasamy Chinnaraju, A. R. Lavanya, and Kandasamy Prabakar. "Occurrence, Spatial Distribution and Ecological Impact of Heavy Metals in Rivers, Lakes and Marine Environments of Tamil Nadu, India." Asian Journal of Chemistry 34, no. 12 (2022): 3037–47. http://dx.doi.org/10.14233/ajchem.2022.24024.
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The importance of a clean environment is recognized as a “pillar” of sustainable development. There is, however, a serious public health threat associated with heavy metal releases into the environment. Aquatic environments in Tamil Nadu state of India lack heavy metals monitoring data. From year 2008 to 2022, research articles were assessed that focused at heavy metal concentrations in freshwater and marine ecosystems. It has been shown that elevated levels of heavy metals in sediments of aquatic ecosystems contribute to an increase in their abundance, which may further enter the food chain through bioaccumulation. In addition, intensifying human exploitation of the South East Coastal region (SEC) in Tamil Nadu state of India through industries, tourism, aquaculture and recreation further complicates the situation by providing ever-changing sources of contamination. As a result of analyzing all heavy metals, the levels of Cd in biota collected from ocean environments were higher. Rivers and lakes have shown increased levels of heavy metals such as Zn, Cu and Pb as a result of localized anthropogenic activities. In accordance with sediment guidelines and human health risk assessments, most of the heavy metals concentrations in sediments and aquatic biota exceeded the permissible limits. It is highly recommended that more monitoring studies are conducted to monitor the levels of heavy metals in organisms and in urban rivers, lakes and marine environments in the future, with extreme importance both for environmental health and economics. By identifying the sources of pollutants and implementing strict policies to abate pollution, local governments can implement better control measures to decrease pollution levels.
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Bao, Weimin, Weifan Wan, Zhi Sun, Mei Hong, and Haigang Li. "Spatial Distribution and Migration of Heavy Metals in Dry and Windy Area Polluted by Their Production in the North China." Processes 12, no. 1 (2024): 160. http://dx.doi.org/10.3390/pr12010160.
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We explored the migration and distribution of heavy metal pollution in a dry and windy area in northern China. We collected soil, atmospheric deposition, and water samples, and measured heavy metal concentrations. Cu, Zn, As, and Pb in the 0–10 cm soil layer had a fan-shaped distribution, consistent with their atmospheric deposition fluxes. This indicates that the distribution of these heavy metals was driven by strong winds. The concentration of Cd in the river increased from 0.257 mg/L upstream to 0.460 mg/L downstream, resulting in the same distribution trends as soil near the river. Surface runoff may therefore drive Cd migration. The concentration of Pb in the river exceeded the pollution threshold, resulting in accumulation in the 5–10 cm soil layer. Atmospheric deposition fluxes were consistent with the soil distribution results, and principal component analysis showed that the contribution of surface runoff was high. This suggests that the migration of Pb and Cr is driven by both wind and surface runoff. Six heavy metals showed different migration behaviors, suggesting specific control strategies should be implemented for individual heavy metals.
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Taghizadeh-Mehrjardi, Ruhollah, Hassan Fathizad, Mohammad Ali Hakimzadeh Ardakani, et al. "Spatio-Temporal Analysis of Heavy Metals in Arid Soils at the Catchment Scale Using Digital Soil Assessment and a Random Forest Model." Remote Sensing 13, no. 9 (2021): 1698. http://dx.doi.org/10.3390/rs13091698.
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Predicting the spatio-temporal distribution of absorbable heavy metals in soil is needed to identify the potential contaminant sources and develop appropriate management plans to control these hazardous pollutants. Therefore, our aim was to develop a model to predict soil adsorbable heavy metals in arid regions of Iran from 1986 to 2016. Soil adsorbable heavy metals were measured in 201 samples from locations selected using the Latin hypercube sampling method in 2016. A random forest (RF) model was used to determine the relationship between a suite of geospatial predictors derived from remote sensing and digital elevation model data with georeferenced measurements of soil absorbable heavy metals. The trained RF model from 2016 was used to reconstruct the spatial distribution of soil absorbable heavy metals at three historical timesteps (1986, 1999, and 2010). Results indicated that the RF model was effective at predicting the distribution of heavy metals with coefficients of determination of 0.53, 0.59, 0.41, 0.45, and 0.60 for Fe, Mn, Ni, Pb, and Zn, respectively. The predicted maps showed high spatio-temporal variability; for example, there were substantial increases in Pb (the 1.5–2 mg/kg−1 class) where its distribution increased by ~25% from 1988 to 2016—similar trends were observed for the other heavy metals. This study provides insights into the spatio-temporal trends and the potential causes of soil heavy metal contamination to facilitate appropriate planning and management strategies to prevent, control, and reduce the impact of heavy metal contamination in soils.
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Wang, Shu Min, and Hui Yu. "Spatial and Temporal Distribution of Heavy Metals Concentration in Urban Stormwater Runoff." Advanced Materials Research 726-731 (August 2013): 1801–4. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.1801.
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In order to know the characteristic of spatial and temporal distribution of heavy metal concentrations in urban stormwater runoff, rainfall runoff from impervious underlying surfaces in urban region was observed during rain events. Results showed that during the precipitation process, heavy metal concentrations decreased gradually temporally (except Cd); concentrations of Fe, Cu and Zn meet Class III standard of Environmental Quality Standards for Surface Water in terminal runoff, but concentrations of Cd and Pb go beyond this standard far. Heavy metal concentrations in runoff from different types of landuses were significantly different. The arithmetic average concentrations of Fe, Cd, Cu and Zn in stormwater runoff from roof (e.g.,34.4mg/L, 0.15mg/L, 1.25mg/L and 1.23mg/L, respectively) were obviously higher than that in stormwater runoff from road (e.g., 11.8mg/L, 0.05mg/L, 0.13mg/L and 0.69mg/L, respectively).
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El Barjy, Meryem, Mehdi Maanan, Mohamed Maanan, Fouad Salhi, Ali Tnoumi, and Bendahhou Zourarah. "Contamination and environmental risk assessment of heavy metals in marine sediments from Tahaddart estuary (NW of Morocco)." Human and Ecological Risk Assessment 26, no. 1 (2020): 87–102. http://dx.doi.org/10.1080/10807039.2018.1495056.
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The distribution, contamination status, and ecological risks of heavy metals in Tahaddart estuary were investigated. 24 surface sediment samples and two cores were collected and analyzed for major (Al and Fe), heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn), and grain size composition. The heavy metals assessment was carried out using different environmental indices. The results indicated that the spatial distribution patterns of Al, Fe, and Zn were mainly determined by the distribution of the finer grained fraction (<63 μm) in the sediment. In contrast, As, Cd, Cr, Cu, Ni, and Pb concentrations were controlled by anthropogenic activities (vehicular traffic from Highway Bridge and thermal power plant). The distribution of heavy metals in sediment cores showed an upward enrichment in heavy metals with high concentration found in the uppermost may related to the increasing in human activities. The pollution indexes confirmed that the Tahaddart estuary sediment was considerably to high contaminated by heavy metals near to different anthropogenic inputs. Similarly, the potential ecological risk index and the biological risk index present 21% probability of toxicity posing potential risk to the aquatic organisms. These results provide basic information that can be used to protect and improve the quality of this ecosystem.
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Harmesa, Harmesa, Lestari Lestari, and Fitri Budiyanto. "Distribusi Logam Berat Dalam Air Laut Dan Sedimen Di Perairan Cimanuk, Jawa Barat, Indonesia." Oseanologi dan Limnologi di Indonesia 5, no. 1 (2020): 19. http://dx.doi.org/10.14203/oldi.2020.v5i1.310.
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<p><strong>Distribution of Heavy Metals in Seawater and Sediments in Cimanuk Estuary, West Java, Indonesia.</strong><strong> </strong>Increasing economic activities in the north coastal of Java have the potential to contribute to anthropogenic contaminants that threaten the water quality of Cimanuk coastal and estuary in Indramayu. Heavy metal which is one of the wastes from these activities has not been studied in detail. The aim of this study was to determine the distribution of Cu, Pb, Cd, Zn, and Ni in seawaters and sediments of the Cimanuk Estuary. Seawater and sediment samples were collected at 18 stations in May 2017. Seawater samples were extracted using the back extraction method while sediment samples were extracted using acids according to USEPA 3050B. Measurement of heavy metals from seawater extracts or sediments was carried out using Flame Absorption Spectrophotometry according to the USEPA 3050B method. The spatial distribution of heavy metals in seawater and sediments is modeled using ArcGIS® version 10.6.1. The results showed that ranges of metals in seawater : 0,0004 – 0,0038 mg/L (Cu), &lt;0,0001 – 0,0044 mg/L (Pb), 0,0002 – 0,0003 mg/L (Cd), 0,0005 – 0,0119 mg/L (Zn), and 0,0020 – 0,0052 mg/L (Ni). While the metal content in sediments are 12,36 – 54,08 mg/kg (Cu), 6,43 – 15,72 mg/kg (Pb), 0,07 – 0,37 mg/kg (Cd), 64,53 – 85,16 mg/kg (Zn), and 19,66 – 62,85 mg/kg (Ni). Spatial distribution models show that heavy metals in seawater and sediments show identical patterns. High level of metals are generally detected at the stations located closed to the mainland, indicating that heavy metals are enrichment from terrestrial anthropogenic activities.</p>
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Zhao, Huihui, Peijia Liu, Baojin Qiao, and Kening Wu. "The Spatial Distribution and Prediction of Soil Heavy Metals Based on Measured Samples and Multi-Spectral Images in Tai Lake of China." Land 10, no. 11 (2021): 1227. http://dx.doi.org/10.3390/land10111227.
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Soil is an important natural resource. The excessive amount of heavy metals in soil can harm and threaten human health. Therefore, monitoring of soil heavy metal content is urgent. Monitoring soil heavy metals by traditional methods requires many human and material resources. Remote sensing has shown advantages in the field of monitoring heavy metals. Based on 971 heavy metal samples and Sentinel-2 multi-spectral images in Tai Lake, China, we analyzed the correlation between six heavy metals (Cd, Hg, As, Pb, Cu, Zn) and spectral factors, and selected As and Hg as the input factors of inversion model. The correlation coefficient of the best model of As was 0.53 (p < 0.01), and of Hg was 0.318 (p < 0.01). We used the methods of partial least squares regression (PLSR) and back propagation neural network (BPNN) to establish inversion models with different combinations of spectral factors by using 649 measured samples. In addition, 322 measured samples were used for accuracy evaluation. Compared with the PLSR model, the BP neural network builds the model with higher accuracy, and B1-B4 combined with LnB1-LnB4 builds the model with the highest accuracy. The accuracy of the best model was verified, with an average error of 19% for As and 45% for Hg. Analyzing the spatial distribution of heavy metals by using the interpolation method of Kriging and IDW. The overall distribution trend of the two interpolations is similar. The concentration of As elements tends to increase from north to south, and the relatively high value of Hg elements is distributed in the east and west of the study area. The factories in the study area are distributed along rivers and lakes, which is consistent with the spatial distribution of heavy metal enrichment areas. The relatively high-value areas of heavy metal elements are related to the distribution of metal products factories, refractory porcelain factories, tile factories, factories and mining enterprises, etc., indicating that factory pollution is the main reason for the enrichment of heavy metals.
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Dewata, Indang, and Aprizon Putra. "Kriging-GIS model for the spatial distribution of seawater heavy metals." Periodicals of Engineering and Natural Sciences (PEN) 9, no. 2 (2021): 629. http://dx.doi.org/10.21533/pen.v9i2.1851.
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Yang, Yun mo, Moo Joon Shim, Da Yeon Oh, et al. "Spatial Distribution of Heavy Metals in Geum River after Weirs Construction." Korean Journal of Environmental Agriculture 34, no. 1 (2015): 64–68. http://dx.doi.org/10.5338/kjea.2015.34.1.06.
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