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Статті в журналах з теми "Spatial distribution of heavy metals"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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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

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2

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

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3

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 calcul

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4

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 analys

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5

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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Анотація:

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 analys

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6

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 distributi

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7

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

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8

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-shap

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9

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

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10

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

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11

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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12

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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13

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

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14

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

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15

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 A

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16

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. Th

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17

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, t

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18

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 resu

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19

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

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20

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 Otu

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21

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 d

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22

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 comparati

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23

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 estu

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24

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 analyzin

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25

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

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26

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

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27

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-

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28

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 su

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29

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

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30

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 co

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31

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, Ii

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32

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 facto

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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 con

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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 Ri

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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 wer

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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 th

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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

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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 an

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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).

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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

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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 proces

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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 t

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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. Surfac

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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

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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 t

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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 concentrati

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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 a

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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

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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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