Levels Of Heavy Metals In Soil Research Articles

Improved mapping of heavy metals in agricultural soils using machine learning augmented with spatial regionalization indices

The accurate spatial mapping of heavy metal levels in agricultural soils is crucial for environmental management and food security. However, the inherent limitations of traditional interpolation methods and emerging machine-learning techniques restrict their spatial prediction accuracy. This study aimed to refine the spatial prediction of heavy metal distributions in Guangxi, China, by integrating machine learning models and spatial regionalization indices (SRIs). The results demonstrated that random forest (RF) models incorporating SRIs outperformed artificial neural network and support vector regression models, achieving R2 values exceeding 0.96 for eight heavy metals on the test data. Hierarchical clustering for feature selection further improved the model performance. The optimized RF models accurately predicted the heavy metal distributions in agricultural soils across the province, revealing higher levels in the central-western regions and lower levels in the north and south. Notably, the models identified that 25.78 % of agricultural soils constitute hotspots with multiple co-occurring heavy metals, and over 6.41 million people are exposed to excessive soil heavy metal levels. Our findings provide valuable insights for the development of targeted strategies for soil pollution control and agricultural soil management to safeguard food security and public health.

Assessment of Heavy Metal Contamination in Irrigated Farmland and Associated Health Risks in Kano State, Nigeria: A Review

Study’s Excerpt/Novelty Soil pollution in Kano State is primarily caused by the use of contaminated irrigation water and household/industrial sludge as fertilizers, leading to heavy metal contamination in crops. The buildup of heavy metals in soil and crops poses significant health risks and potential food insecurity, necessitating multiple research projects to assess and address the situation. Implement regular monitoring of heavy metal levels in soils and crops, and establish guidelines for safe cultivation and consumption of vegetables grown on contaminated soils to mitigate health risks. Full Abstract The primary causes of soil pollution in Kano state, which leads to heavy metal contamination in crops grown from such soils, are using contaminated water for irrigation and household and industrial sludge as fertilizers. Along waterways where untreated wastewater flows, vegetables are planted. To determine the existing situation and potential preventative and remediation measures, it has become necessary to conduct multiple research projects on the levels of heavy metals in the soil and plants grown in Kano state, Nigeria. In light of this, this study has focused on the present and potential state of heavy metal buildup in soils and farmed crops and the potential health risks that may arise from this, including food insecurity. The main findings of the conducted research were that regular monitoring of the level of heavy metals in soils and crops should be established, and guidelines for the cultivation and consumption of leafy vegetables grown on contaminated soils should be set equally to avoid health risks.

Concentration levels and pollution status of selected heavy metals in active dumpsites in Port Harcourt, Rivers State, Nigeria

This study was carried out to assess the extent of concentration exposure of As, Cu, Cr, Ni and Mn in the soils of five active dumpsites located at (Eliozu, Oyibo, Eneka, Eleme and Woji) in the city of Port Harcourt Rivers State, Nigeria to evaluate the pollution indices of heavy metals. Soil samples were collected randomly at the quadrant from the dumpsite while control samples were collected from farmland 25 km away from the dumpsite. Some physiochemical parameters (pH, TOC and CEC) of the soils were evaluated using standard techniques, while the heavy metal concentrations were evaluated using Atomic Absorption Spectroscopy (AAS). The pollution levels of soil heavy metals were assessed using several pollution indices. The mean concentration of heavy metals (mg/kg) ranged between As (ND – 0.45), Cr (ND – 2.21), Cu (6.05 – 51.87), Mn (3.24 – 37.91), Ni (ND – 13.50) across the studied dumpsites. The heavy metal levels in soil samples observed were in the order of Cu > Mn > Ni > Cr > As (Eleme), Cu > Mn > As > Ni > Cr (Eliozu), Cu > Mn > Ni > Cr > As (Eneka), Cu > Mn > Cr (Oyigbo), Cu > Mn > Ni > Cr > As (Woji), Cu > Mn > Ni > Cr > As (Control Site). The pH results were relatively acidic across the studied dumpsites ranging from 5.7±0.58 to 6.63± 0.02, while the TOC levels were low to moderate showing no wide disparity in the values. The Cation exchange capacity (CEC) showed a range of 13.98±0.186 (Eneka) to 20.98±0.061 cmol/kg (Woji) across the studied dumpsites. The Igeo values except for Ni, Cu and Mn at Eneka dumpsite, Cr and As in all the studied dumpsites revealed moderate to heavy contamination. Pollution load index (˃ 1) was in the studied dumpsites which implies that there is heavy metal pollution across the studied dumpsites. Anthropogenicity indicates that human activity is mostly responsible for the increase in metals in the studied area. Low ecological risk indices for the heavy metals (Ni, Cu, Cr, Mn, As) were found in all the sampling locations except for copper in Oyibo dumpsite. According to the findings, there is a low to moderate level of heavy metal pollution in the soils from the dumpsite, which can deteriorate the food ecosystem if adequate measures are not put in place.

Evaluation of the heavy metal levels in soil and water from coal mining communities of Enugu State, Nigeria

Water and soil from Akwuke, Ngwo and Udi were analyzed for their heavy metal content using the atomic absorption spectrometry (AAS). All the well water samples were found to be higher in heavy metal concentration when compared with the WHO permissible limit, except nickel in drinking water. The soil samples in the three communities were found to have lower concentration of Mn, Cr, Pb, Cd, and Ni when compared to the WHO permissible limit in soil. This study has revealed high concentration of manganese, lead, chromium, cadmium and nickel in water samples in the three studied area Akwuke, Ngwo and Udi, all in Enugu State. Though the concentrations of these heavy metals were not high in any of the soil samples, but high concentration of these heavy metals, compared to WHO/FAO in well water was observed, especially in Udi and Ngwo community. Keywords: Heavy metal, levels, soil and water.

Spatial Distribution of Soil Heavy Metals and Regional Control Strategies in China at Province Level

It is important to understand the spatial distribution characteristics and health risks of soil heavy metals for the implementation of soil pollution control measures in different levels and regions. Based on the data of 706 core studies in the last 20 years, the spatial distribution characteristics, accumulation degree, and health risks of soil heavy metals in China were analyzed at the provincial level. The results showed that the soil heavy metals had obvious spatial differences on the provincial scale, with an overall trend of "high in the south and low in the north and high in the east and low in the west." The content of heavy metals in the soil of agricultural land and construction land was high, and the rate of exceeding the standard was higher than that of other land types. Soil heavy metal concentrations in most areas of China were higher than the regional background values and were highly cumulative. The accumulation indices were:Cd(1.80)>Pb(0.23)>Cu(0.17)>Zn(-0.05)>As(-0.56)>Cr(-0.69), with more than 85% of the provincial soils reaching moderate levels of Cd pollution. Non-ferrous metal resource-based provinces such as Yunnan, Guizhou, Guangxi, Hunan, and Jiangxi generally had higher soil heavy metal levels than those in other provinces, and local children faced higher cancer risks. Soil pollution in coastal areas such as Fujian, Zhejiang, Jiangsu, and Tianjin mainly originated from industrial production and urbanization construction. High intensity agricultural utilization was an important cause of soil heavy metal accumulation in Henan, Shandong, and Anhui.

Geranium robertianum L. tolerates various soil types burdened with heavy metals.

Many heavy metals (HMs) are essential micronutrients for the growth and development of plants. However, human activities such as mining, smelting, waste disposal, and industrial processes have led to toxic levels of HMs in soil. Fortunately, many plant species have developed incredible adaptive mechanisms to survive and thrive in such harsh environments. As a widespread and ruderal species, Geranium robertianum L. inhabits versatile soil types, both polluted and unpolluted. Considering the ubiquity of G. robertianum, the study aimed to determine whether geographically distant populations can tolerate HMs. We collected soil and plant samples from serpentine, an anthropogenic heavy metal contaminated, and a non-metalliferous site to study the physiological state of G. robertianum. HMs in soil and plants were determined using flame atomic absorption spectrometry. Spectrophotometric methods were used to measure the total content of chlorophylls a and b, total phenolics, phenolic acids, flavonoids, and proline. Principal component analysis (PCA) was used to investigate the potential correlation between HMs concentrations gathered from various soil types and plant samples and biochemical data acquired for plant material. A statistically significant difference was observed for all localities regarding secondary metabolite parameters. A positive correlation between Ni and Zn in soil and Ni and Zn in plant matter was observed (p<0.0005) indicating higher absorption. Regardless of high concentrations of heavy metals in investigated soils, G. robertianum displayed resilience and was capable of thriving. These results may be ascribed to several protective mechanisms that allow G. robertianum to express normal growth and development and act as a pioneer species.

A method for heavy metal estimation in mining regions based on SMA-PCC-RF and reflectance spectroscopy

Heavy metal contamination has long been a concern of intense research within the field of environmental protection. The exacerbation of heavy metal pollution due to mineral resource over-exploitation and the implementation of agricultural modernization has further emphasized the need for rapid monitoring. Although traditional geochemical survey methods have been deemed reliable, they lack the ability to conduct non-destructive and rapid surveys of large areas due to their high cost, low real-time capability, and cumbersome operations. We collected 120 soil samples in the field using Xin'an County, Henan Province as the research region, and obtained hyperspectral curves and contents of the samples using the spectrometer and chemical analysis. After preprocessing the spectral curves, we used the slime mold algorithm (SMA) to preselect feature wavebands, and then the mathematically transformed method was used to improve their correlation. Next, we calculated the correlation coefficients of these wavebands with six heavy metals, and the final modeled wavebands were obtained through precise feature selection based on the criterion that the correlation coefficient’s absolute value exceeded 0.298. The inversion model was also established by using adaptive boosting (AdaBoost), gradient boosted decision tree (GBDT), random forest (RF), and partial least squares (PLS). The results indicated that SMA-PCC can effectively downscale the high-dimensional hyperspectral data and obtain the feature wavebands with a high contribution to the modeling. We also observed that the mathematical transformation method improved the relevance between heavy metal elements and spectra. Among the four models, RF showed better overall inversion accuracy for all heavy metals (i.e., Zn: RAdaBoost2=0.85,RGBDT2=0.56,RRF2=0.89,RPLS2=0.57). This paper showcases that the algorithm presented can provide meaningful technical guidance for the large-scale investigation and assessment of heavy metal levels in soil.

Spatial Distribution and Associated Risk Assessment of Heavy Metal Pollution in Farmland Soil Surrounding the Ganhe Industrial Park in Qinghai Province, China

The farmland around the industrial areas in the Upper Yellow River is crucial for agricultural production but is vulnerable to contamination from the surrounding industries. This research focused on analyzing the spatial distribution and environmental risks of heavy metal pollution in the farmland around the Ganhe Industrial Park in the Qinghai–Tibet Plateau. A total of 138 surface soil samples were collected, and the concentration of seven heavy metals (Cd, As, Pb, Cr, Cu, Ni, and Zn) was analyzed using the random forest (RF) model. Pollution indicators, including the pollution index and Nemero index, were used to evaluate the pollution levels of soil heavy metals. The human health and ecological risks were estimated using the hazard index (HI) and the potential ecological risk index (RI). Cd and Zn were identified as the primary soil pollutants in the study area, with Cd being more concentrated than other heavy metals. Heavy metal contamination was most severe in the central–eastern region of the study area, with a ring-shaped distribution, which correlated with the presence of zinc smelting and chemical plants. Furthermore, the study revealed that soil heavy metal contamination posed a health threat to the local population, with children being particularly vulnerable to non-carcinogenic risks when the HI was 1.21 and to potential carcinogenic risks when the CR was 2.27 × 10−5. Additionally, heavy metal pollution caused a moderate to high ecological risk in 56.4% of the samples. The results highlighted the severe impact of soil heavy metal pollution on the delicate ecosystem of the Upper Yellow River and Qinghai–Tibet Plateau. The government should take action to improve soil environment management and prevent heavy metal pollution to protect the health of the local population and the ecological environment.

Levels of Heavy Metals in Grapevine Soil and Leaf Samples in Response to Seasonal Change and Farming Practice in the Cape Winelands

Heavy metal toxicity is a major threat to the health of both humans and ecosystems. Toxic levels of heavy metals in food crops, such as grapes, can have devastating effects on plant health and the market value of the produce. Two important factors that may influence the prevalence of heavy metals in grapevines are seasonal change and farming practices. The objectives of this study were (i) to conduct a detailed pioneer screening of heavy metal levels in soils and grapevine leaf tissues in selected wine farms and (ii) to study the influence of season and farming on heavy metal levels in soils and grapevine leaf tissues. Soil and grapevine leaf samples were collected from demarcated areas in selected vineyards in the Cape Winelands region of South Africa. The sampling was conducted in winter and summer from the same sites. The soil and leaf samples were analysed using inductively coupled plasma mass spectrometry (ICP-MS) techniques. The pooled data from the farms practising conventional or organic farming showed that seasonal variation had no significant effect (DF = 1, 22; p > 0.05) on the heavy metal contents in the soil. When the soil data from the winter and summer months were compared separately or pooled, the influence of agricultural practice was well-pronounced in As (DF = 1, 22, or 46; p < 0.05) and Cu (DF = 1, 22, or 46; p <0.05). The agricultural practice greatly influenced (DF = 1, 22; p< 0.05) Cu, As, Cr, and Hg uptake, with little effect on Ni, Co, Cd, and Hg leaf contents. Generally, the heavy metals studied (Cr, Co, Ni, Zn, As, Cd, Hg, and Pb) were substantially below the maximum permitted levels in plant and soil samples, per the recommendations of the WHO and Er indices, respectively. However, moderate contamination of the soils was recorded for Cr, Ni, Zn, and Pb. Remarkably, the Cu levels in the organic vineyard soils were significantly higher than in the conventional vineyards. Furthermore, based on the Igeo index, Cu occurred at moderate to heavy contamination levels.

Heavy metal pollution characteristics and potential ecological risk assessment of soils around three typical antimony mining areas and watersheds in China

China is the largest antimony resource globally. The mining and smelting of antimony will inevitably have a significant impact on the surrounding and downstream farmlands of the mining area, Therefore, it is necessary to understand the pollution characteristics of antimony and evaluate its potential environmental risks. In this paper, three typical antimony mining areas were used as research districts to analyze the contents of heavy metals in soils of the mining areas and watersheds. The single-factor pollution index method, Nemerow comprehensive pollution index method, geo-accumulation index method, and potential ecological risk index method were used to comprehensively evaluate the pollution status and ecological risk of heavy metals in soils around the mining areas. The soil around the Lengshuijiang tin mine was polluted by As, Cd, Zn, and Sb, it was a heavily polluted soil and at a high ecological risk level. The arable soil around the Nandan tea mountain antimony mine was polluted by As, Cd, Cu, Pb, Sb, and Zn, and it was a heavily polluted soil with very high ecological risk level. The soil around the Xunyang antimony mine was mainly polluted by Sb and it was a moderately polluted soil with moderate ecological risk level. The results revealed that the overall soil heavy metal levels in the Lengshuijiang mining area and the Nandan mining area were in a high-risk state, most likely due to the mining and smelting of metal ores and the weathering of mineralised rocks. showing a high-potential ecological risk in these mining areas. We expect to provide a scientific basis for the safe utilization of farmland and pollution control around the antimony mining areas and watersheds in China.

Racial Disparities in the Heavy Metal Contamination of Urban Soil in the Southeastern United States.

(1) Background: Field monitoring data for addressing the disproportional burden of exposure to soil contamination in communities of minority and low socioeconomic status (SES) are sparse. This study aims to examine the association between soil heavy metal levels, SES, and racial composition. (2) Methods: A total of 423 soil samples were collected in the urban areas of eight cities across six Southern states in the U.S., in 2015. Samples were analyzed using inductively coupled plasma–mass spectrometry (ICP–MS) for eight heavy metals. The association was examined with mixed models with the log-transformed metal concentrations as the dependent variables and rankings of low-income or minority percentages as the explanatory variables. (3) Results: Model results showed that soil metal concentrations were significantly associated with rankings of poverty and minority percentages. The cadmium concentration significantly increased by 4.7% (p-value < 0.01), for every 10 percentiles of increase in poverty rank. For every 10 percentiles of increase in minority rank, the soil concentrations were significantly up (p-values < 0.01) for arsenic (13.5%), cadmium (5.5%), and lead (10.6%). Minority rank had significant direct effects on both arsenic and lead. (4) Conclusions: The findings confirmed elevated heavy metal contamination in urban soil in low-income and/or predominantly minority communities.

Preliminary Assessment of Heavy Metals in Soil along the Vaisigano River in Samoa

The contamination of heavy metals in various environmental matrices is a major concern to many researchers and requires attention due to their detrimental impacts on the environment and humans as well. This research was carried out to investigate heavy metal levels in soils of some selected sites along the Vaisigano river in Upolu, Samoa. The soil samples were also analysed for physicochemical parameters such as pH, Electrical Conductivity, Moisture Factor, Cation Exchange Capacity (CEC), Organic Carbon, Nitrogen, Phosphorus, and Soil texture. The mean concentrations of heavy metals at the Lelata site were 0.19 ± 0.05 mg/kg (Pb), 0.37 ± 0.45 mg/kg (Mn), 0.15 ± 0.02 mg/kg (Zn) and 0.56 ± 0.42 mg/kg (Cu). The mean concentrations of heavy metals at the Alaoa site were 0.13 ± 0.03 mg/kg (Pb), 0.42 ± 0.51 mg/kg (Mn), 0.16 ± 0.03 mg/kg (Zn) and 0.45 ± 0.43 mg/kg (Cu). The heavy metal concentrations from both sites were lower than the permissible levels given by the World Health Organization (WHO). The Geo-accumulation pollution index (I(geo)) of heavy metals in the Lelata site was Cu > Mn > Pb > Zn and from the Alaoa site was Cu > Pb > Zn > Mn.

MOLECULAR ASPECTS OF HEAVY METAL STRESS- AN OVERVIEW

Anthropogenic activities like contemporary agricultural methods, and the effects of industrialization on our environment are long-term and harmful. As a result of all of these variables, heavy metal levels in soil, water and air rise. Metals have the potential to be hazardous to plants only when, they are found in bioavailable forms in large quantities. Cadmium, zinc, mercury, lead, chromium, copper, cobalt, nickel, manganese, arsenic and iron are among the elements. Hence, plants have also evolved some of the detoxifying mechanisms to mitigate the harmful effects of heavy metal exposure, its build-up and the studies regarding these have been covered in this overview.

Assessment of Heavy Metals in Agricultural Soils and Plant (Vernonia amygdalina Delile) in Port Harcourt Metropolis, Nigeria

This study assessed the concentration of heavy metal, such as lead (Pb), cadmium (Cd), Chromium (Cr), iron (Fe), Nickel (Ni), and Silver (Ag), in Vernonia amygdalina Delile and agricultural soils of three university farms located in Port Harcourt, Nigeria. The soils and plants were taken randomly to form composite samples and analyzed for heavy metals by the use of atomic absorption spectroscopy (AAS) and X-ray fluorescence (XRF). The study stations were agricultural soils and Vernonia amygdalina Delile from the Ignatius Ajuru University of Education (I), River State University (R) and University of Port Harcourt (U). The soil samples recorded mean concentration ranges for Fe as 19.71 ± 1.77 (I)–27.24 ± 3.56 mg/kg (R) in soils and 12.95 ± 1.68 (R)–18.18 ± 2.02 mg/kg (U) for the bitter leaf samples. The mean range for Pb concentration in the soil and bitter leaf were 4.35 ± 0.87–6.80 ± 0.86 mg/kg and 0.24 ± 0.64–2.19 ± 0.74 mg/kg, while Cd concentration in the soil and bitter leaf were 0.46 ± 0.28–1.42 ± 0.40 mg/kg and 0.17 ± 0.22–0.42 ± 0.08 mg/kg, respectively. The respective mean ranges for Cr concentration in the soil and bitter leaf were 5.91 ± 1.14–8.77 ± 0.88 mg/kg and 4.04 ± 0.64–5.92 ± 0.69 mg/kg, while Ni in soil and bitter leaf were 0.54 ± 3.38–10.26 ± 3.50 mg/kg and 0.042 ± 1.42–3.30 ± 0.88 mg/kg, while Ag was negligible. Heavy metal levels in soils and Vernonia amygdalina followed the order Fe &gt; Cr &gt; Pb &gt; Ni &gt; Cd and Fe &gt; Cr &gt; Ni &gt; Pb &gt; Cd, respectively, and were lower than WHO/FAO and EPA, except Cd, which was higher in soil and in Vernonia amygdalina. The ecological risk factor (ErF) was comparatively lower in soils than in the plant, while pollution load index (PLI) showed high heavy metal retention capacities in Vernonia amygdalina due to more anthropogenic influences. The metal transfer factor (TF) was highest in Fe, followed by Cr &gt; Cd &gt; Ni &gt; Pb, while Pb had the highest chances of cancer risks from the incremental lifetime cancer risk (ILCR), especially in both soil and plant (mean ILCR, 2.07 × 10−2 and 2.45 × 10−3), while Cd had the least (mean ILCR, 9.64 × 10−5 and 3.36 × 10−5). Anthropogenic activities must be regulated and monitored by government relevant agencies to reduce heavy metal inputs into soils and avoid excessive accruals in food chain.

Deciding Heavy Metal Levels in Soil Based on Various Ecological Information through Artificial Intelligence Modeling

ABSTRACT The aim of this paper is to decide on heavy metal levels based on ecological parameters by effectively eliminating common disadvantages such as high cost and serious time-consuming laboratory procedures via an effective artificial intelligence approach. Therefore, this study is hinged on an artificial intelligence technique, ANN, because of its low cost and high accuracy in overcoming the mentioned limitations and obstacles in the determination process of the amounts of elements. The ANNs have thus been employed to determine essential heavy metals, such as Fe, Mn, and Zn depending on Ca, K, and Mg concentrations of soil samples obtained from different altitudes in Mount Ida. To the best knowledge of the authors, this is the first study in the literature in which altitude was considered as a parameter in the prediction of nutrient heavy metals. The computed relative errors are significantly low for each of the considered elements (Fe, Mn, and Zn); and are found to be between 1.0–4.1%, 1.0–4.2%, 1.5–7.1%, respectively, for the training, testing, and holdout data. The findings indicate that the relative errors could still be decreased further by assuming the altitude as a factor variable.

Assessment of Heavy Metal Levels in Soil and Vegetables in Some Farms Around Mining Sites in Mangu Local Government Area Plateau State, Nigeria

When the mining process is not properly controlled, it can be a source of heavy metals pollution in the environment. The uptake of these heavy metals in edible parts of vegetables can be a direct source of the metals into the human food chain. This study assessed the concentrations of lead (Pb), manganese (Mn), zinc (Zn), copper (Cu), nickel (Ni) and chromium (Cr) in soil and vegetables obtained from nine (9) farms around mining sites in Mangu LGA. Concentrations of heavy metals in soil and vegetables were determined using atomic absorption spectrophotometer (AAS). The results revealed the concentrations of the heavy metals at the farms to be within the recommended maximum levels of world soils but were higher than their respective controls. This implies that the artisanal mining contributed to the increased values of these heavy metals in the environment. Also, the mean concentrations of the heavy metals at Mangu Halle mining site decreased in the order Mn &gt; Zn &gt; Cr &gt; Cu &gt; Ni &gt; Pb &gt; Cd whereas at Alogwom it decreased in the order Mn &gt; Zn &gt; Pb &gt; Cu &gt; Ni &gt; Cr &gt; Cd. The enrichment factor (EF) of the elements showed deficiency to minimum enrichment for all the heavy metals whereas the pollution index (PI) of the metals indicated very slight contamination to moderate pollution. The results of the heavy metals in the vegetables showed that the bioaccumulation of the metals followed a pattern: Zn &gt; Cu &gt; Pb &gt; Cr &gt; Cd &gt; Ni. Levels of Cd, Pb and Ni in the vegetables were observed to be higher than the recommended limit for vegetables whereas Cu, Cr and Zn exhibited lower values than recommended standards. Thus, their consumption might pose health risk to consumers and therefore there is the need for proper monitoring of the illegal mining activities to reduce health risk and the extent of heavy metals contamination.

Heavy metal contamination and ecological risk assessment of the agricultural soil in Shanxi Province, China.

To assess contamination levels and ecological risks of heavy metals in agricultural soil from Shanxi Province of China, a total of 33 samples in the surface soil were collected from 11 cities in Shanxi. The soil samples were digested by a mixed acid of nitric acid and hydrofluoric acid on a microwave digestion system, then the levels of eight heavy metals were analysed using an inductively coupled plasma mass spectrometer. The pollution levels of soil heavy metals were evaluated using a geo-accumulation index and their ecological risks were assessed using risk index calculated by Hakanson's method. As a result, the average concentrations of the heavy metals As, Cd, Cr, Cu, Hg, Ni, Pb and Zn were 12.9 ± 4.8, 0.35 ± 0.23, 43 ± 14, 27 ± 19, 0.25 ± 0.14, 21.7 ± 5.7, 17 ± 13 and 89 ± 53 mg kg−1, respectively. By comparison to the Chinese soil environmental quality (GB15618-2018), only 9% of Cd samples and 3% of Cu samples exceeded their corresponding screening criteria. Subsequently, the results of geo-accumulation indices suggested that Shanxi's soil suffered from moderate to heavy contamination posed by Cd and Hg, and risk indices exhibited a similar trend that Cd and Hg were the main contributors for considerable to very high ecological risk. Finally, the analysis of variance indicated that the mean levels of Cd significantly occurred at Yuncheng areas among the 11 cities (n = 3, p < 0.05), but Hg concentrations did not have significantly statistical differences. This study demonstrated that metals Cd and Hg had higher levels and ecological risks for agricultural soil in Shanxi, especially, Yuncheng City suffered from heavy Cd contamination. The findings of the present study will provide basic information on management and control of the agricultural soil contamination in Shanxi Province, China.

Discussion on Key Issues of Geochemical Monitoring of Soil Heavy Metal in Xiong'an New District

To build a soil environmental quality monitoring network and collect the systematic soil geochemical data of heavy metals before and after the construction of Xiong'an New District(XND), long-term variations in soil heavy metal levels during the XND construction were monitored based on the land quality geochemical survey monitoring data and the geochemical distribution of heavy metals. Parameters such as sampling density, sampling quantity, and sampling period were estimated to construct the geochemical monitoring network, which provides a reference for the future long-term monitoring of soil heavy metal geochemistry in XND. The results indicate that variations in the amount of heavy metals As, Cd, Cu, Hg, and Pb are greater than 36%, while the nugget coefficients of Cd, Cu, and Pb are greater than 75% because of the superposition of manmade sources on the high natural background levels. At the 95% and 90% confidence levels, while the allowable error Δ of the sample mean value is 5%, 10%, and 15% and heavy metals as As, Cd, Cu, Hg,Ni, Pb and Zn is monitored in soil environmental quality monitoring network, the proper numbers in the study area are 1077, 270, 120 and 767, 192, 86, respectively. The minimum detectable change(MDC)of each heavy metal species is between 0.0025 and 2.54 mg ·kg-1. Soil heavy metal monitoring requires different revisit intervals under different annual change rates, but in the study area, revisit intervals of soil monitoring are approximately two years under the current conditions of constant annual change rates.

Source identification and assessment of heavy metal contamination in urban soils based on cluster analysis and multiple pollution indices

To identify the sources and levels of contamination with anthropogenically derived heavy metals (HMs) for appropriate pollution control. We quantified anthropogenic influences with respect to HM pollution in soil, based on multiple pollution indices and cluster analysis derived from the results of an annual nationwide survey conducted in Korea. Contamination levels of HMs in soils were quantitatively evaluated using multiple pollution indices: contamination factor (CF), geo-accumulation index (Igeo), Nemerow’s integrated pollution index (NIPI), and pollution load index (PLI). Hierarchical cluster analysis was conducted to elucidate the correlations between HMs and contamination sources. A total of 2214 HM concentration data including six contamination sources were used to evaluate the pollution state of anthropogenic effects of HMs. The CFs for Zn and Cu revealed a broad enrichment of these HMs in all pollution sources. Scrap recycling sites (SRS) had the highest likelihood of pollutant distribution in soil surfaces. NIPI and PLI varied with the extent of anthropogenic activities or land use, especially in SRS, waste disposal sites (WDS), transport maintenance sites (TMS), and industrial sites (INS), and anthropogenic sources were divided into three discrete clusters: INS-TMS-LDS (land development sites), SRS-WDS, and vicinities of industrial sites (VIS). Our results confirmed that soil pollution indices combined with cluster analysis were useful to identify sources of anthropogenic HMs in urban soil, as well as to assess the levels of HM contamination.

Impact of Pb-Zn Mining on Heavy Metal Levels in Soil from Arufu Mine Field, Wukari, Nigeria

Analysis of soil around the vicinity of Arufu mine field was conducted in order to ascertain the impact of mining on the environment. Concentrations of trace metals associated with Pb – Zn – barite mineralization were determine in soils using atomic absorption spectrophotometer (AAS) Varian AA 240, after acid digestion with a mixture of 1:1 hydrofluoric acid and aqua regia. Mean concentrations (µg/g) of metals ranged from 5.72 (As) – 451.44 (Pb) in dry season and 1.32 (Cd) – 504.61 (Pb) in wet season. Index of geoaccumulation were in the following order of increasing magnitude: Cu &lt; Zn &lt; As &lt; Pb &lt; Ag for dry season and Cu &lt; As &lt; Zn &lt; Cd &lt; Pb for wet season. On the other hand, soil enrichment ratio ranged from Cu (1.06) – Ag (126.18) and Cu (1.35) – Pb (34.10) in dry and wet season respectively. Levels of metals measured were higher than their corresponding values reported for soil in the upper continental crusts. Toxic metal (Pb) has its mean concentration above maximum tolerance level while Zn and As levels were below the maximum tolerable levels. The presence of Pb above maximum tolerance level may render the soil unsuitable for agricultural practices, hence high impacts of Pb – Zn mining in the study area.