Soil Heavy Metal Concentrations Research Articles

Spatial Distribution of Soil Heavy Metal Concentrations in Road-Neighboring Areas Using UAV-Based Hyperspectral Remote Sensing and GIS Technology

Monitoring and restoring soil quality in areas neighboring roads affected by traffic activities require a thorough investigation of heavy metal concentrations. This study examines the spatial heterogeneity of copper (Cu) and chromium (Cr) concentrations in a 0.113 km² area adjacent to Jin-Long Avenue in Wuhan, China, using Unmanned Aerial Vehicle (UAV)-based hyperspectral remote sensing technology. Through this UAV-based remote sensing technology, we innovatively achieve a small-scale and fine-grained analysis of soil heavy metal pollution related with traffic activities, which represents a major contribution of this research study. In our approach, we generated 4375 spectral variates by transforming the original spectrum. To enhance result accuracy, we applied the Boruta algorithm and correlation analysis to select optimal spectral variates. We developed the retrieval model using the Gradient Boosting Decision Tree (GBDT) regression method, selected from a set of four regression methods using the LOOCV method. The resulting model yielded R-square values of 0.325 and 0.351 for Cu and Cr, respectively, providing valuable insights into the heavy metal concentrations. Based on the retrieved heavy metal concentrations from bare soil pixels (17,420 points), we analyzed the relationship between heavy metal concentrations and the perpendicular distance from the road. Additionally, we employed the universal kriging interpolation method to map heavy metal concentrations across the entire area. Our findings reveal that the concentration of heavy metals in this area exceeds background values and decreases as the distance from the road increases. This research significantly contributes to the understanding of spatial distribution characteristics and pollution caused by heavy metal concentrations resulting from traffic activities.

Heavy Metal Contamination Status of Water, Agricultural Soil, and Plant in the Semiarid Region of Kandahar, Afghanistan

Agricultural irrigation using wastewater containing heavy metals (HM) might impose risks in bioaccumulation in foods. The current study was performed to assess the status of HM in terms of water-soil–plant systems in Kandahar, Afghanistan, where industrial and domestic wastewater was partially reused for irrigation. Water, soil, and plant samples were collected from wastewater sites in Haji-Arab (HA), Bala-Karz (BKZ), and Mahal-e-Nejat (MN) in comparison with those from a freshwater-irrigated site in Char-Bagh (CB). The HM levels in unfiltered water samples remained lower than the World Health Organization (WHO) and Food and Agriculture Organization (FAO) permissible values, but the HM concentrations in soil and crops were higher at the HA, BKZ, and MN (wastewater-irrigated sites) than those at the CB site (freshwater-irrigated site). Lead (Pb) levels were high in soils (43–83 mg/kg) and crops (18–36 mg/kg) and extremely exceeded the safe limits even for those crop samples cultivated in the freshwater-irrigated site. Continuous wastewater irrigation increased the HM concentration in water, soil, and plants, but the Pb pollution was found to be ascribed to the minerals in that area since the underground water was showing high Pb levels. The bioaccumulation of HM in the studied sites was related to the cultivated crops and correlated with the land use in the watershed area. This study is important in understanding the risks associated with HM and exercising prudence when applying various irrigation resources in Afghanistan.

Incorporation of source contributions to improve the accuracy of soil heavy metal mapping using small sample sizes at a county scale

Estimating heavy metal (HM) distribution with high precision is the key to effectively preventing Chinese medicinal plants from being polluted by the native soil. A total of 44 surface soil samples were gathered to detect the concentrations of eight HMs (As, Hg, Cu, Cr, Ni, Zn, Pb, and Cd) in the herb growing area of Luanping County, northeastern Hebei Province, China. An absolute principal component score-multiple linear regression (APCS-MLR) model was used to quantify pollution source contributions to soil HMs. Furthermore, the source contribution rates and environmental data of each sampling point were simultaneously incorporated into a stepwise linear regression model to identify the crucial indicators for predicting soil HM spatial distributions. Results showed that 88% of Cu, 72% of Cr, and 72% of Ni came from natural sources; 50% of Zn, 49% of Pb, and 59% of Cd were mainly caused by agricultural activities; and 44% of As and 56% of Hg originated from industrial activities. When three-type (natural, agricultural, and industrial) source contribution rates and environmental data were simultaneously incorporated into the stepwise linear regression model, the fitting accuracy was significantly improved and the model could explain 31%–86% of the total variance in soil HM concentrations. This study introduced three-type source contributions of each sampling point based on APCS-MLR analysis as new covariates to improve soil HM estimation precision, thus providing a new approach for predicting the spatial distribution of HMs using small sample sizes at the county scale.

Investigating Heavy Metal Contamination Extent of Soil and Plant from Urban Gardens in Jinju

In Korea, 90% of the population lives in urban areas, so urban agriculture is commonly carried out. However, research on the safety of urban soils for growing food still needs to be done. Thus, this study was conducted to evaluate the suitability of urban soil for crop cultivation by investigating the heavy metal concentration of soil and plant from urban gardens in Jinju. Soils and crop leaves were collected from 23 urban gardens, and the concentrations of As, Cd, Cr, Cu, Ni, Pb, and Zn were analyzed. The average concentrations of garden soils in Jinju were As 5.31, Cd 0.59, Cr 30.09, Cu 33.05, Ni 21.14, Pb 23.28, and Zn 121.68 mg kg-1, which did not exceed the Korean guidelines except for Zn in one study site. Geoaccumulation Index, calculated using the background values of heavy metals in Korean soil, showed that contamination of Cd, Cu, Pb, and Zn was in progress. The inflow of Cu and Zn into the garden soils would be from the atmosphere and direct entry into the soil by adding livestock manure. Differently, the other elements were more predominantly introduced from the atmosphere. Particularly, a significant amount of Pb was introduced into the soils from the atmosphere in a couple of gardens. Overall, the results from this study indicated that continuous monitoring for heavy metals in urban garden soils is required for food safety.The number of urban gardens at each level of soil contamination by Geoaccumulation Index. Level of soil contamination As Cd Cu Ni Pb Zn Practically uncontaminated 19 1 1 12 12 1 Uncontaminated to moderately contaminated 3 12 10 8 8 12 Moderately contaminated 1 10 9 3 2 8 Moderately to heavily contaminated 0 0 3 0 1 2 More than heavily contaminated 0 0 0 0 0 0

Urban Microplastic Pollution Revealed by a Large-Scale Wetland Soil Survey.

Microplastics (MPs), as a new persistent pollutant, can be emitted and accumulated in urban environments, but there is no detailed information on the driving factors of MP pollution. In this study, through a large-scale wetland soil survey, the features of MPs were characterized in each urban area. The results showed an average abundance to be 379 n/kg in wetland soil. Polypropylene, fiber or fragment, and black color were common composition, shape, and color, respectively. The spatial distribution information showed that MP abundance was significantly relevant to the distance from the urban economic center. Furthermore, the correlation and regression analysis revealed that MP abundance was related to soil heavy metal and atmospheric particle (PM10 and PM2.5) concentrations (P < 0.05), while the promotion of socioeconomic activities (urbanization level, population density, etc.) may aggravate the pollution degree. Additionally, by using structural equation modeling, it was found that the urbanization level was the dominant factor driving the MP pollution degree, with a total effect coefficient of 0.49. Overall, this work provides multi-sided environmental information regarding MP pollution in urban ecosystems, which is significant for follow-up studies of MP pollution control and restoration.

Comparison of magnetic susceptibility probes relevantly used in soil contamination applications.

Magnetic susceptibility (MS) technology can achieve the efficient rough measurement, mapping, and pollution assessment of soil heavy metal concentrations in topsoil due to atmospheric dust contamination. However, previous studies of commonly used MS field probes (MS2D, MS2F, and MS2K) have not dealt with the range of magnetic signal detection and the attenuation characteristics of the signal with respect to distance. In this study, the vertical and horizontal measurement ranges of the MS2D, MS2F, and MS2K probes were explored through laboratory and field experiments, and the intensity of their magnetic signals was further compared and analyzed in the field. The results showed that the magnetic signal intensity of the three probes decreased exponentially with distance. The penetration depths of the MS2D, MS2F, and MS2K probes were 8.5, 2.4, and 3.0cm, respectively, and the horizontal detection boundary lengths of their magnetic signals were 32, 8, and 6.8cm, respectively. In the field surface soil MS detection, the magnetic measurement signals of the MS2F and MS2K probes showed a weak linear correlation with the MS2D probe (R2 of 0.43 and 0.50, respectively), while the MS2F and MS2K probes had a significantly better correlation (R2 = 0.68) with each other. In general, the MS2D probe and MS2K probe correlation had a slope close to unity, meaning MS2K probes had good mutual substitution. Furthermore, results of this study improve the effectiveness of the MS evaluation of heavy metal pollution in urban topsoil.

Estimation of Pb and Cd Content in Soil Using Sentinel-2A Multispectral Images Based on Ensemble Learning

With the increasing economic growth in developing nations, soil heavy metal pollution has become a growing concern. Monitoring the heavy metal concentration in soil through remote sensing is crucial for safeguarding the ecological environment. However, the current indoor spectral measurement method has limitations, such as the discrete soil sampling space and weak spectral characteristics of soil heavy metals, leading to a poor robustness of remote sensing inversion models. This study presents a novel approach to address these challenges by incorporating a spatial feature of pollution sources and sinks to evaluate the spatial factors affecting pollutant diffusion and concentration. An integrated learning model, combining spatial and spectral information, is developed to estimate heavy metal content in soil using Sentinel-2A satellite data. A total of 235 soil samples were collected in Jiyuan, China, and the effective spectral transformation characteristics of Sentinel-2A data were screened. The impact of spectral characteristics, topographic characteristics, and spatial characteristics on retrieving soil heavy metal lead (Pb) and cadmium (Cd) content were analyzed. The optimal inversion method was determined through various integrated learning models, and the spatial distribution of heavy metals Pb and Cd was mapped. The results indicate that the accuracy of the inversion model was significantly improved by incorporating terrain features and spatial features of pollution sources. The Blending integrated learning method showed a 65.9% and 73.2% reduction in the RMSE of Pb and Cd, respectively, compared to other regression models. With R2 values of 0.9486 and 0.9489 for Pb and Cd, respectively, and a MAPE less than 0.2, the Blending model demonstrated high prediction accuracy.

Cassava Processing and Heavy Metal Concentrations in Soils of the Riverine Community Toru-Ebeni, Bayelsa State, Nigeria.

Cassava Processing and Heavy Metal Concentrations in Soils of the Riverine Community Toru-Ebeni, Bayelsa State, Nigeria.

Prediction of Cr and Ni contents in soil from hyperspectral data combined with Al-Fe minerals

ABSTRACT Hyperspectral analysis is useful in monitoring and evaluating soil heavy metal pollution. The difficulty in estimation of heavy metals by hyperspectral analysis is to extract the spectral features related to soil heavy metal concentration which may be interfered by signals resulting from other soil components. In this study, we established a comprehensive framework for prediction of Cr and Ni from hyperspectral data combined with soil Al-Fe minerals using advanced machine learning methods. The Al-Fe minerals were measured in laboratory and predicted from the spectral data, respectively. The results show that (1) from the original hyperspectral data, the model performances for Cr (R2 = 0.61, RMSE = 16.96) and Ni (R2 = 0.34, RMSE = 6.92) are not satisfactory. (2) With the incorporation of the measured Al-Fe minerals as the predictors, the optimal machine learning method for prediction of Cr and Ni is XgBoost, and the model performances are improved obviously (Cr: R2 = 0.85, RMSE = 10.67; Ni: R2 = 0.71, RMSE = 4.55). (3) With the incorporation of the Al-Fe minerals predicted from the spectral data, the optimal machine learning method for prediction of Cr and Ni is GdBoost, and the model performances are acceptable (Cr: R2 = 0.74, RMSE = 13.93; Ni: R2 = 0.68, RMSE = 4.79). This study provides a preliminary analysis for mapping soil heavy metal content and monitoring heavy metal pollution over a large spatial extent.

Spatial variability and hotspot prediction of heavy metal pollution in soil-rice system: based on a new geostatistical method

ABSTRACT The goal of this research was to better understand the spatial characteristics and hot areas of heavy metal concentrations in the soil-rice system, which was critical for implementing heavy metal pollution prevention and control strategies. The amounts of heavy metals in soil-rice were determined using high-precision testing methods such as XRF, ICP-MS, and AFS based on the systematic collection of 285 pairs of soil-rice samples from Wanjiang Economic Zone, China. The Getis-Ord index, Kriging method, and geostatistical method were used to reveal the spatial distribution of heavy metal contamination hot spots in the soil-rice system. The results revealed that the average concentration of heavy metals in soil was Zn>Cr>Cu>Pb>Ni>As>Cd>Hg, whereas it was Zn>Cu>Ni>Cr>Cd>As>Pb>Hg in rice. The average concentrations of heavy metals in the soil were all well below the maximum allowable limit, except for Cd, which was slightly above the allowable limit. Only Cd and Ni concentrations in rice exceeded the maximum permitted limits. In soil, Cd, Hg, Pb, and Zn pollution hotspots were mostly found in the southeast, while Cr and Ni were mostly found in the northeast. An intriguing discovery was that there was a weak relationship between heavy metal concentrations in soil and rice and the spatial pattern of their distribution. The study’s findings offer a scientific foundation for establishing a long-term agricultural development strategy for the soil-rice system in the Wanjiang Economic Zone.

Estimation of heavy metal soil contamination distribution, hazard probability, and population at risk by machine learning prediction modeling in Guangxi, China

Due to superposition of diverse pollution sources, soil heavy metal concentrations have been detected to exceed the recommended maximum permissible levels in many areas of Guangxi province, China. However, the heavy metal contamination distribution, hazard probability, and population at risk of heavy metals in the entire Guangxi province remain largely unclear. In this study, machine learning prediction models with different standard risk values determined according to land use types were used to identify high-risk areas and estimate populations at risk of Cr and Ni based on 658 topsoil samples from Guangxi province, China. Our results showed that soil Cr and Ni contamination derived from carbonate rocks was relatively serious in Guangxi province, and that their co-enrichment during soil formation was associated with Fe and Mn oxides and alkaline soil environment. Our established model exhibited excellent performance in predicting contamination distribution (R2 > 0.85) and hazard probability (AUC>0.85). Pollution of Cr and Ni exhibited a pattern of decreasing gradually from the central-west areas to the surrounding areas with the polluted area (Igeo>0) of Cr and Ni accounting for approximately 24.46% and 29.24% of total area in Guangxi province, respectively, but only 10.4% and 8.51% of total area was classified as Cr and Ni high-risk regions. We estimated approximately 1.44 and 1.47 million people were potentially exposed to the risk of Cr and Ni contamination, which were mainly concentrated in the Nanning, Laibin, and Guigang. These regions are main heavily-populated agricultural regions in Guangxi, and thus heavy metal contamination localization and risk control in these regions are urgent and essential from the perspective of food safety.

Maden Sahasından Ağır Metallerin (Cd, Zn, Pb) Ayçiçeği (Helianthus annuus) Bitkisiyle Fitoekstraksiyonu

Aim of study: The aim of this study was to determine the phytoremediation capacity of sunflower (Helianthus annuus L.), which can also be used as a bioenergy plant, in soils contaminated with copper (Cu), zinc (Zn) and lead (Pb) from the waste dumping sites during the mining operations. Area of study: Phytoremediation study was carried out in Artvin Coruh University Research greenhouse environment. Material and Methods: Plants were grown by mixing clean and contaminated soil at the rates of 0%, 50% and 100%. Bioaccumulation (BAF) and translocation (TF) factors were calculated by measuring heavy metal concentrations in soil and plant samples. The bioaccumulation factor is calculated by dividing the metal concentration in the shoots with the metal concentration in the soil. The translocation factor expresses the ratio of the metal concentration in the plant green parts to the root metal concentration. Main results: The sunflower plant has accumulated the highest Zn in the shoots, while Cu and Pb have accumulated the highest in the roots. The mean BAF values of the plants were determined as 0.72 for Zn, 0.5 for Pb and 0.28 for Cu, while the mean TF values were determined as 1.25 for Zn, 0.97 for Pb and 0.52 for Cu. Highlights: The findings show that the sunflower plant can be used in the phytostabilization of Cu metal and in the phytoextraction of Zn and Pb metal to reclaim heavy metal contaminated soils.

Effects of heavy metal pollution and soil physicochemical properties on the Sphagnum farmland soil microbial community structure in Southern Guizhou, China

Farmland soil pollution is a serious problem worldwide threatening environment and human health. Microbial communities plays a key role in soil function. The purpose of this study was to analyze the relationship between microbial structure and soil physicochemical properties under different heavy metal pollution levels, find out heavy metal tolerant species under different environmental conditions, then provide useful reference for the bioremediation of contaminated farmland. In this study, 16s rRNA high-throughput sequencing technology was used, multiple comparisons and correlation analyses of the data were performed using R software. The results showed that study area A was contaminated by heavy metal Cd, and study area A, B and C were contaminated by heavy metal Hg. From the analysis of the community structure of the samples, it can be seen that the dominant bacterial phyla were Proteobacteria, Acidobacteriota, Chloroflexi, Actinobacteria, and 10 others. Correlation and RDA analysis of samples showed that the heavy metals Hg and As in peat were related to dominant bacteria phyla, and the physicochemical properties of soil potential of hydrogen (pH), total nitrogen (TN), available nitrogen (AN), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM) were significantly positively correlated with the bacteria (Acidobacterta and Chloroflexi). Moreover, Chloroflexi was more tolerant to the heavy metals Hg and As. There was a significant correlation between bacterial community abundance and diversity in the four study areas. Soil heavy metal concentration and soil physicochemical properties affected the main phyla, bacterial community abundance and bacterial diversity of peat soil. These results indicate that some microorganisms have strong tolerance to heavy metal pollution and certain heavy metal digestion ability, which can create a good environment for farmland soil remediation.

Contamination characteristics, source analysis, and spatial prediction of soil heavy metal concentrations on the Qinghai-Tibet Plateau

Contamination characteristics, source analysis, and spatial prediction of soil heavy metal concentrations on the Qinghai-Tibet Plateau

Comparative Analysis of Heavy Metals Concentration in Soil and Vegetable (Vernonia amygdalina) Collected from Two Sampling Sites (Farmland and Dumpsite) and the Effect on Plant DNA

Different studies have shown that Vernonia amygdalina is enriched with proteins, fats, fibres, amino acids, minerals vitamins, and carbohydrates but no record yet on the level of heavy metals in Vernonia amygdalina collected from Ojota (dumpsite) and Badagry (control) in Lagos state. Samples of V. amygdalina were collected and analyzed for metals using standard method, while differences in concentrations were analyzed using t-test analysis at level of significance set at p=0.05. The results recorded in mg/100g for the metals content (Cd, Cr, Cu, Pb and Zn) in the plant across the two stations were not significantly different (p&gt;0.05). The Zn in leaf and stem (100.157 ±1.351, 45.743± 3.664) respectively from dumpsite were significantly higher than that of farmland (91.468 ± 2.386, 35.505 ±1.662). Also, Zn content in the root from farmland (73.671 ±2.205) was higher than that of dumpsite (69.515 ± 2.312). All the values of N, P and K recorded in the leaf, stem and roots of bitter leaf from both sites were different significantly (p&lt;0.05). The most frequent nutrient in the leaf, stem and root of the bitter leaf was K, followed by N while the least was P. In contrast, the root contained the highest K, followed by the leaf and then the stem. The DNA band of V. amygdalina from both sites showed no alteration. In conclusion, bitter leaves from both sites were rich in minerals (N, P, and K) though their values were higher at the dumpsites. However, heavy metals content in V. amygdalina at both sites being within standard permissible limits imply it is safe for human consumption.

Metal contamination in soil and vegetables around Savar tannery area, Dhaka, Bangladesh: A preliminary study for risk assessment

Monitoring of heavy metal concentrations in soil and their accumulation in vegetables grown in the newly shifted tannery area of Savar, Bangladesh, is crucial for human health. Heavy metals (i.e., Cr, Pb, Cu, Zn, Ni, and Cd) concentrations in soil and vegetable samples were determined by atomic absorption spectrophotometer (AAS). In soil, 3220 mg/kg Cr was observed, which was 32-fold greater than the WHO/FAO recommended limit. Ecological risk indices such as the contamination factor, enrichment factor, pollution load index, and geoaccumulation index showed metal levels as moderately to very highly contaminated. The non-carcinogenic risk (NCR) was found to be higher, and the carcinogenic risk (CR) exceeded the acceptable value 1 × 10−6 and posed greater risks to children than adults, especially for Cr in soil. The main exposure pathway for soil metals was 97.8–99.9% due to oral ingestion. The concentration of heavy metals especially Cr, Pb, Zn, and Cd, in vegetables was alarming as they crossed the safety limit. The calculated mean hazard index (8.71) for vegetable samples showed elevated levels of potential NCR, while CR for Cr and Cd, exceeded the acceptable limit of 1 × 10−6, indicating the probability of cancer risk to humans through the consumption of vegetables. This study revealed a to-and-fro analysis of the present scenario of the tannery area, giving importance to human health and the environment.

Plant material decomposition and bacterial and fungal communities in serpentine and karst soils of Japanese cool-temperate forests

ABSTRACT We aimed to reveal the plant material decomposition rate and abundance of bacteria and fungi in serpentine and karst sites of cool-temperate forests. Given the relatively higher soil pH, we hypothesized a higher decomposition rate of cellulose, lower decomposition rate of lignin-containing plant materials, and lower fungi-to-bacteria ratio in serpentine and karst sites than in neighboring non-serpentine/non-karst sites. This study was conducted on serpentine and mudstone sites in deciduous oak forests on Mount Oe and karst and sandstone sites on Mount Ibuki, Japan. We performed a decomposition experiment over 5 months using three chemically distinct materials: cellulose filter, lignin-containing coffee filter, and green tea leaves. These common materials enabled us to compare the in-situ utilization of different carbon substrates by microbial communities between sites. The abundance of bacteria and fungi and their ratio in topsoils and materials that decomposed for 1 month were assessed using quantitative PCR. In contrast to our hypothesis, the decomposition rate was higher in the mudstone site for cellulose and did not differ for the coffee filter compared to the serpentine site. Green teas with higher lignin content than coffee filters decomposed slower at the serpentine site only during the early period of decomposition. The serpentine site showed higher fungi-to-bacteria ratios in the decomposed materials and soil. The karst site also showed different decomposition patterns than our prediction, presenting no clear difference in the cellulose filter compared to the sandstone site. In the karst site, coffee filters decomposed faster at the early period; however, green teas decomposed slower as we expected, especially at the later period of decomposition. The karst site had a lower fungi-to-bacteria ratio in the topsoil, but similar fungi-to-bacteria ratios in the decomposed materials compared with the sandstone site. Our results suggest that the decomposition patterns in the serpentine and karst soils are not simply predicted based on soil pH and other distinct characteristics (e.g., soil moisture content and heavy metal concentration) would more strongly contribute to decomposition and microbial community composition in the study mountains.

Contributory science reveals insights into metal pollution trends across different households and environmental media

Heavy metals are prevalent in urban settings due to many legacy and modern pollution sources, and are essential to quantify because of the adverse health effects associated with them. Of particular importance is lead (Pb), because there is no safe level of exposure, and it especially harms children. Through our partnership with community scientists in the Marion County (Indiana, United States) area (n = 162 households), we measured Pb and other heavy metal concentrations in soil, paint, and dust. Community scientists completed sampling with screening kits and samples were analyzed in the laboratory via x-ray fluorescence by researchers to quantify heavy metal concentrations, with Pb hazards reported back to participants. Results point to renters being significantly (p ≤ 0.05) more likely to contain higher concentrations of Pb, zinc (Zn), and copper (Cu) in their soil versus homeowners, irrespective of soil sampling location at the home. Housing age was significantly negatively correlated with Pb and Zn in soil and Pb in dust across all homes. Analysis of paired soil, dust, and paint samples revealed several important relationships such as significant positive correlations between indoor vacuum dust Pb, dust wipe Pb, and outdoor soil Pb. Our collective results point to rental status being an important determinant of metal pollution exposure in Indianapolis, with housing age being reflective of both past and present Zn and Pb pollution at the household scale in dust and soil. Thus, future environmental pollution work examining renters versus homeowners, as well as other household data such as home condition and resident race/ethnicity, is imperative for better understanding environmental disparities surrounding not just Pb, but other heavy metals in environmental media as well.

Pollution Status of Dumpsites within Uyo Metropolis, Akwa Ibom State, Nigeria

The study evaluates the heavy metals, geo-accumulation index and contamination factor in soil around dumpsites in Uyo, Akwa Ibom State, Nigeria. Soil samples were collected, during rainy season, at depth of 0-15cm and 15-30cm from two study sites (A, B) and a control site (C). Soil samples were all analyzed for heavy metals (Pb, Ni, Cd and Cu) using Atomic Absorption Spectroscopy (AAS). The concentration of Lead at site A for depth 0-15 cm ranged from 13.71 -14.90 mg/kg with a mean value of 14.38 ± 0.61 mg/kg; Nickel varied from 2.35 – 3.22 mg/kg (2.74 ± 0.44 mg/kg); Cadmium ranged from 3.78 – 4.13 mg/kg (3.93 ± 1.18 mg/kg); Copper ranged from 27.84 – 28.34 mg/kg (28.14 ± 0.27 mg/kg). The heavy metals concentration in soil at sites A and B followed the sequence, Cu &gt; Pb &gt; Cd &gt; Ni while at the control site; Cu &gt; Cd &gt; Ni &gt; Pb. The calculated geo-accumulation index (Igeo) showed that the soil samples from sites A and B for Pb, Ni and Cu belong to class 2, which implies that the soil was moderately contaminated. The Igeo values for Cd at sites A and B were classified as 4, indicating a strongly contaminated soil. However, Igeo of Cd at the control site is class 3, implying moderately to strongly contaminated soil. Calculated contamination factor (CF) showed that Pb, Ni and Cu for sites A, B and control at depths 0-15cm were in class 1 (low contamination), while Cd contamination was class 4 except at control site (15 -30cm) which showed CF of class 3. The contamination degrees (CD) for the sampling sites A and B showed considerable contamination and their pollution load index (PLI) indicated a progressive deterioration of the sites; however, the control site recorded very minimal state of pollution. Generally, the results found that the top soil (0 – 15 cm) was more contaminated than the sub soil (15 – 30 cm) of all sample sites studied. The results of this study imply that the inhabitants around Sites A and B are exposed to Cadmium pollution and the soil is not suitable for agricultural practice, since plants can take up these toxic metals and bio-accumulate them in their tissues. Cadmium, at high concentration in plants, can cause serious clinical and physiological effects on humans when consumed as food.

Characteristics and Risk Assessment of Heavy Metals in the Soil Around Copper Smelting Sites

Copper smelting can cause heavy metal pollution in surrounding soil and threaten human health. This study examined the characteristics, distribution, and health risk of heavy metals in soil with different land uses around 40 copper smelting sites at home and abroad by collecting published literature data. The results showed that the mean values of ω(As), ω(Cd), ω(Cu), ω(Pb), and ω(Zn) in the soil around the copper smelting sites were 196, 10.5, 1948, 604, and 853 mg·kg-1, respectively. The order of Igeo was Cd(5.63)>Cu(3.88)>As(2.96)>Pb(2.30)>Zn(1.27), and the accumulation of Cd and Cu was the most serious. High Nemero index (NIPI) values were found in the soil around smelting sites with a long history of smelting, outdated process, and insufficient environmental protection measures. Significant correlations were found between the concentrations of heavy metals in the soil, which decreased with the sampling distance. The heavy metals mainly accumulated within 2-3 km from the smelting sites. Compared with the smelting history, scale, and process, land use type had a lower effect on soil heavy metal concentrations. The heavy metals in the soil around copper smelters may pose carcinogenic and non-carcinogenic risks on residents. The high health risks were mainly caused by As and Pb in smelting production areas, and Pb in woodland. These results may guide the risk prevention of heavy metal pollution in the soil around smelting sites.