Identification of Soil Heavy Metal Sources in a Large-Scale Area Affected by Industry

Temporal and Spatial Variation of Toxic Metal Concentrations in Cultivated Soil in Jiaxing, Zhejiang Province, China: Characteristics and Mechanisms

The toxic metal (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) pollution in 250 agricultural soil samples representing the urban area of Jiaxing was studied to investigate the temporal and spatial variations. Compared to the early 1990s, the pollution level has increased. Industry and urbanization were the main factors causing toxic metal pollution on temporal variation, especially the use of feed containing toxic metals. The soil types and crop cultivation methods are the main factors causing toxic metal pollution on spatial variation. Although the single-factor pollution indices of all the toxic metals were within the safe limits, as per the National Soil Environmental Quality Standard (risk screening value), if the background values of soil elements in Jiaxing City are used as the standard, the pollution index of all the elements surveyed exceeds 1.0, reaching a level of mild pollution. The soil samples investigated were heavily contaminated with toxic metal compounds, and their levels increased over time. This situation poses potential ecological and health risks.

Effect of environmental factors on accumulation of trace metals in a typical shale gas exploitation area: A comprehensive investigation by machine learning and geodetector models

Whether a certain relationship is exist between shale gas exploitation and accumulation of trace metals in soil is a controversial issue in recent years. To date, few study clearly reveal the intrinsic contributions of natural and anthropogenic factors to accumulation of trace metals in soil. In this study, machine learning and geodetector models were integrated to investigate to contribution of environmental factors to variations of trace metals concentration. Before modeling, there are 10.33%-25.87% of soil considered as metal pollution, and the value of Pn further suggest that the Ba contribute the most to the comprehensive pollution index of trace metals in soil. The initial prediction of trace metals concentration by machine learning models is less effectively indicating the need for alternative approaches. To address this problem, post-constraints approach was used, and the post-constraint MSLR model demonstrates superior performance (R2 = 0.81) Additionally, through the utilization of geodetector model, the explanatory power (q) of CEC and SOM were identified as dominant natural factors with value of 0.055 and 0.089. respectively. Moreover, distance from working sites and working status were identified as the dominant anthropogenic factors associating to the spatial heterogeneity of trace metals in soil. The interaction between natural and anthropogenic factors showed a siginifacnt nonlinear enhancement effect on accumulation of Cr, Ba and Sr, and the highest value of q was 0.38 for SOM and distance. This study indicated that the potential metal contamination was related to shale gas exploitation and provide reference for controlling soil pollution in shale gas exploitation area and making management strategy.

Modeling and identification of affective parameters on cadmium's durability and evaluating cadmium pollution indicators caused by using chemical fertilizers in long term

Soil contamination by anthropogenic heavy metals has become a global issue. This study aimed to investigate cadmium (Cd) concentration, mobility, and contamination indices of Cd in soils in the Hamadan province, west of Iran. To investigate the concentration of Cd in soil, one hundred soil samples from wheat farms and five samples from control lands were collected. Pollution indexes, including Cd mobility, enrichment factor, geoaccumulation index, contamination index, and availability ratio, were investigated. The structural equation model was also used to evaluate effective parameters on cadmium durability in soil. Results showed that mean values of available phosphorus (P) were 83.65, 129, and 65 (mg kg-1) in three land-use types rainfed, irrigated, and controlled, respectively. The mean values of Cd in different land-use types of rainfed, irrigated, and controlled were 0.15, 0.18, and 0.08 (mg kg-1), respectively. The results indicated that the amount of Cd in both forms (available and total) in ones that received fertilizer, especially P fertilizers, was higher than in the controlled one. Other pollution indexes revealed that the study area had been slightly contaminated due to anthropogenic activities. Lime, clay, lead, and OM were identified as affective parameters on cadmium durability. Finally, the results demonstrated that the mobility rate was high. Cd had a higher potential mobility in soil samples in the rain-fed and irrigated land than in the controlled land, and Cd had a low retention time.

Spatial and temporal distribution characteristics of antibiotics and heavy metals in the Yitong River basin and ecological risk assessment

Due to rapid socioeconomic development, antibiotic pollution and heavy metal pollution are receiving increasing amounts of attention. Both antibiotics and heavy metals in the environment are persistent and toxic, and the interactions between the pollutants create potential long-term hazards for the ecological environment and human health as mixed pollutants. In this study, the surface water of the Yitong River in Changchun was used as the research object, and the hazards associated with antibiotics and heavy metals in the surface water were assessed by analyzing the spatial and temporal distribution characteristics of antibiotics and heavy metals and by using ecological risk assessment and human health risk assessment models. The results showed that ofloxacin (OFL) and norfloxacin (NOR) varied seasonally according to the seasonal climate, with total concentrations ranging from 17.65 to 902.47 ng/L and ND to 260.49 ng/L for OFL and NOR, respectively, and from 8.30 to 120.40 μg/L, 1.52 to 113.41 μg/L and 0.03 to 0.04 μg/L for copper (Cu), zinc (Zn) and cadmium (Cd), respectively. In terms of spatial distribution, the concentration of antibiotics in the urban sections, which had intensive human activities, was higher than that in the suburban sections, while the concentration of heavy metals in the suburban sections, which had intensive agricultural operations, was greater than that in the urban section. Ecological risk evaluation showed that NOR and OFL were present in the water bodies at a high-risk level, Cd was at a low pollution level, and the heavy metal Cd was the primary pollutant associated with health risks toward for adults and children, and it was mainly at a medium risk level. Additionally, both antibiotics and heavy metals posed higher health risks for children than for adults.

Assessment of Heavy Metal Content in Soil and Lycopersicon esculentum (Tomato) and Their Health Implications

In this study, the content of lead (Pb), cadmium (Cd), chromium (Cr) and manganese (Mn) was evaluated in soils and tomatoes (Lycopersicon esculentum) collected from rural areas of Dobrogea province, South-East of Romania. The risk to human health due to the heavy metal exposure via tomato consumption was also assessed.The results suggest that based on the contamination factor, the soils are moderately contaminated with Cd and Mn (Cf values of 1.266. and 1.40) and poorly contaminated with Pb and Cr. The bioconcentration factor (BAF) was below 1 and indicated that the studied species of Lycopersicon esculentum did not accumulate the monitored elements. Person's correlation analysis showed that there were significant relations between soil pH and BCF values of Cd, Pb, Cr and Mn in analysed tomatoes. The estimated daily intake of each metal was below the oral reference dose. The hazard quotient (HQ) and hazard index (HI) were below the acceptable level (< 1), and the cancer risk (CR) for Pb, Cd and Cr was found within acceptable levels (1.0 × 10^-6-1.0 × 10^-4). Based on health guidance values, it may be concluded that the analysed tomatoes do not present health risks to consumers in terms of content and accumulation of heavy metals. It is important to monitor the other toxic metals as well, in order to evaluate the heavy metal accumulation variation and the toxicity value of each metal in agricultural soils from both rural and industrial areas.

Research on health risk assessment of heavy metals in soil based on multi-factor source apportionment: A case study in Guangdong Province, China

Environmental problems caused by heavy metal pollution in soil have attracted widespread attention worldwide. Identifying and quantifying the heavy metal pollution sources and risks is crucial for subsequent soil management. In this study, an integrated source-risk method for source apportionment and risk assessment based on the PMF model, the geodetector model and the health risk assessment model (HRA) was proposed and applied. Analysis of Hg, As, Pb, Cd, Cu, Ni, Cr, and Zn in 208 topsoils showed that the average contents of eight heavy metals were 1.87-5.86 times greater than corresponding background values, among which Cd and As were relatively high, which were higher than the specified soil risk screening values, high-value areas of heavy metals are mainly concentrated in the central part of the study area. The source apportionment showed that the accumulation of heavy metals was affected by five sources: atmospheric deposition (16.3 %), natural sources (33.1 %), industrial activities dominated by metal mining (15.1 %), industrial activities dominated by metal smelting (12.6 %) and traffic sources (22.9 %). The results of the health risk assessment showed that the carcinogenic risks (adult: 4.74E-05, children: 7.41E-05) of heavy metals in soil to the study population were both acceptable, the non-carcinogenic risk of adult (THI = 0.277) was within the limit, while the non-carcinogenic risk of children (THI = 1.70) was higher than the limit value. Ingestion (89.5 %-95.9 %) contributed the greatest health risk among all exposure routes. Source 3 (arsenic-related industrial activities dominated by metal mining) contributed the most to the HI and CRI of adults and children (all above 50 %), therefore, in the formulation stage of soil management strategy in this area, priority should be given to the control and management of this pollution source. These results can provide more detailed support for environmental protection departments to propose targeted soil pollution control measures.

Influence of soil inorganic amendments on heavy metal accumulation by leafy vegetables

The present study aims to assess the effect of four inorganic soil amendments, such as lime (CaCO3), red mud consisting of 75% hematite (Fe2O3), gypsum (CaSO4·2H2O), and Al oxide (Al2O3), of an alkaline heavy metal-contaminated soil. For this purpose, a pot experiment was conducted by physically mixing individual six subsamples of a soil sample collected from Thessaly area with four inorganic soil amendments along with two leafy plants, spinach and lettuce. Al oxide causes the maximum reduction of the water-soluble Cu concentration, as its concentrations is no longer detectable. The Cu availability index decreases when aluminum oxide was used. The use of gypsum and red mud caused almost equal reduction while the smallest decrease was caused by the use of lime. The Zn availability index decreased equally when aluminum oxide and gypsum were mixed with the soil sample. The highest reduction of Cu and Zn transfer coefficient (TC) was observed when the Al2O3 was used. In spinach, Zn TC reduction was 39.8% and Cu TC reduction was 41.0%. In lettuce, the addition of Al2O3 led to Cu TC reduction of over 37.3% and Zn TC reduction of up to 38.7%. Generally, Al2O3 nanoparticles may function as suitable sorbents for the removal of Zn and Cu from soil samples, with an increasing effectiveness in spinach rather than lettuce. Liming materials seem to increase the soil alkalinity and promote the complexation of soluble heavy metals with hydroxide ions leading to immobilization of heavy metals in soil and reduce their amount in leafy vegetables. Remediation of contaminated soils is considered necessary to reduce environmental risks and to achieve the means available to increase agricultural production of safe and quality food.

Identifying sources and transport routes of heavy metals in soil with different land uses around a smelting site by GIS based PCA and PMF

Identifying sources and transport routes of heavy metals in soil is necessary for pollution control. This study integrated principal component analysis (PCA), positive matrix factorization (PMF), and geographic information system (GIS) mapping to identify the sources, transport routes, and apportion heavy metals in soil based on land uses around a smelting site. The results revealed that the mean concentrations of As, Hg, Cd, Pb, Zn, and Cu in the soil exceeded their background values except for Cr, Mn, and Fe, which were slightly higher. According to the mean I_geo values, the soils were most polluted with As, Cd, Pb, and Cu, followed a decreasing order of grassland (1.71, 2.38, 2.10, and 1.73) > agricultural land (0.632, 2.32, 1.19, and 1.08) > forestland (0.255, 0.952, 0.654, and 0.148). Smelter emissions and soil parent materials were the primary sources of heavy metals. The PCA and PMF factor hotspots visualized by GIS were mostly distributed within the smelting site, slag and wastewater runoff areas, and in the dominant wind direction. The GIS based PCA and PMF results confirmed that As, Cd, Pb, Cu, and Zn were transported mainly by surface runoff and atmospheric deposition, while Hg was mostly from atmospheric deposition. Grassland and agricultural land soils received heavy metals from surface runoff and atmospheric deposition, while forestland soils only received from atmospheric deposition. The integrated approach was useful in identifying the sources, transport routes, and contributions of the heavy metals among different land uses, thereby assisting policymakers in understanding the sources and transport routes of heavy metals in the soil around smelting areas.

Soil parameters affecting the levels of potentially harmful metals in Thessaly area, Greece: a robust quadratic regression approach of soil pollution prediction

The behavior and possible contamination risk due to the presence of potentially harmful metals (PHM) were studied based on 2250 soil samples that were collected in a 5-year period (2013-2017) from the plain of Thessaly (prefectures of Karditsa, Trikala, and Larissa). The vertical distribution of metals was also investigated from sample profiles at three depths 0-30, 30-60, and 60-90cm. The soils of the sampling belong to four taxonomy soil orders that are dominant in the studied area (Alfisols, Inceptisols, Endisols, and Vertisols). In a novel approach, robust quadratic regression analysis on multiple variables was used to define prediction models of the concentrations of two metals: Fe which is an essential metal and the toxic Cd. Linear and quadratic regression formulae were estimated based on the iteratively reweighted least squares robust regression approach in an effort to eliminate the impact of the outliers. These formulae define how several soil properties affect the distribution of the considered metals in each soil order. The evaluation of the estimated regression equations based on the R² metric indicates that they constitute a useful, reliable, and valuable tool for managing, describing, and predicting the pollution in the studied area.

Heavy Metal(loid)s Pollution of Agricultural Soils and Health Risk Assessment of Consuming Soybean and Wheat in a Typical Non-Ferrous Metal Mine Area in Northeast China

During mining, some of the essential metal(loid)s for plants or humans are discharged into the environment with non-essential metal(loid)s. Thus, comprehensive investigations of their distribution and the health risk of consuming food crops near mines are significant. A total of 26 soils and 25 food crops (soybean grains and wheat grains) were sampled to investigate arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), lead (Pb), zinc (Zn), selenium (Se), molybdenum (Mo), and manganese (Mn) in soils and crops in a typical non-ferrous metal mine area in Northeast China. The distribution patterns of soil heavy metal(loid)s and principal component analysis (PCA) results indicated that Cd, Cu, Zn, Mo, and Mn in soils were significantly affected by mining activities and were mainly or partly derived from the mines. Moreover, these soil heavy metal(loid)s (except Se) in the Tongshan copper mine area were attenuated with distance in the downstream direction. The BCF (bioconcentration factor) values of non-essential elements (Se, Hg, Cr, As, Cd, Pb) were relatively lower and positively related to soil nutrients. On the contrary, higher BCF values of essential elements (Cu, Zn, and Mo) and a weak relationship between the BCF of essential elements and soil nutrients were found. The mean Igeo values of soil heavy metal(loid)s indicated that As and Cu were at an unpolluted-to-moderately-polluted level (Igeo > 1), while other heavy metal(loid)s all presented an unpolluted level (Igeo < 1). Nevertheless, some soil samples were obviously polluted (Igeo > 1), such as KQ, D1, D3, D5, D6, and T1. The HQ (hazard quotient) and HI (hazard index) values of As and Mn both exceeded 1, indicating the higher potential health risks of consuming soybean grains and wheat grains for all people groups.

Prediction of high-risk areas of soil heavy metal pollution with multiple factors on a large scale in industrial agglomeration areas

Heavy metals in soil are a great threat to ecosystems and human health. The rapid development of industrialization has created a serious risk of heavy metal pollution in soil. The study took the industrial-intensive Dahetan subbasin as the typical area. The factors and interactions that affected the distribution of soil heavy metals (Cd, Hg, As, Pb and Cr) in the typical area were explored based on the Geodetector model. The analysis results were extended to predict high-risk areas of heavy metal pollution in the soil in the Xiangjiang River basin. The results showed that Cd, As and Pb were significantly affected by local industrial and mining activities, and Hg and Cr were primarily affected by natural factors, such as pH and soil type. Compared to a single factor, the interaction between factors had a greater impact on the concentration of heavy metals. The high-risk areas of soil heavy metal pollution in the Xiangjiang River basin were primarily concentrated in the upper reaches and middle reaches.Significant overlapping of high-risk areas of multiple heavy metals occurred in the west, middle and south of the basin. The spatial visualization of the high-risk areas was realized, and the influence of several factors was integrated via layer superposition. This study proposes a new idea to predict the high-risk areas of soil pollution in large-scale areas to provide a reference for the regional prevention and control of soil pollution.

Contamination Assessment and Source Apportionment of Metals and Metalloids Pollution in Agricultural Soil: A Comparison of the APCA-MLR and APCA-GWR Models

Metals and metalloids accumulate in soil, which not only leads to soil degradation and crop yield reduction but also poses hazards to human health. Commonly, source apportionment methods generate an overall relationship between sources and elements and, thus, lack the ability to capture important geographical variations of pollution sources. The present work uses a dataset collected by intensive sampling (1848 topsoil samples containing the metals Cd, Hg, Cr, Pb, and a metalloid of As) in the Shanghai study area and proposes a synthetic approach to source apportionment in the condition of spatial heterogeneity (non-stationarity) through the integration of absolute principal component scores with geographically weighted regression (APCA-GWR). The results showed that three main sources were detected by the APCA, i.e., natural sources, such as alluvial soil materials; agricultural activities, especially the overuse of phosphate fertilizer; and atmospheric deposition pollution from industry coal combustion and transportation activities. APCA-GWR provided more accurate and site-specific pollution source information than the mainstream APCA-MLR, which was verified by higher R2, lower AIC values, and non-spatial autocorrelation of residuals. According to APCA-GWR, natural sources were responsible for As and Cr accumulation in the northern mainland and Pb accumulation in the southern and northern mainland. Atmospheric deposition was the main source of Hg in the entire study area and Pb in the eastern mainland and Chongming Island. Agricultural activities, especially the overuse of phosphate fertilizer, were the main source of Cd across the study area and of As and Cr in the southern regions of the mainland and the middle of Chongming Island. In summary, this study highlights the use of a synthetic APCA-GWR model to efficiently handle source apportionment issues with spatial heterogeneity, which can provide more accurate and specific pollution source information and better references for pollution prevention and human health protection.

Trees and shrubs from a post-industrial area high in calcium and trace elements: the potential of dendroremediation

That is probably the first study to date of trees and shrubs differing in age and growing on post-industrial soil contaminated with calcium (Ca) and selected toxic metals/metalloids. The obtained results show that an alkaline reaction (less than 9) of soil and an unusually high Ca concentration may help the studied tree species to adapt/survive in unfavorable habitat conditions (high concentration of toxic elements). The efficiency of phytoextraction of toxic elements was so high that, especially for forest animals (roe-deer) that consume, e.g., willow shoots, it could pose a serious threat to health and life, both for them and potentially for humans.

Heavy metal accumulation by roadside vegetation and implications for pollution control

Vehicular emissions cause heavy metal pollution and exert negative impacts on environment and roadside vegetation. Wild plants growing along roadsides are capable of absorbing considerable amounts of heavy metals; thus, could be helpful in reducing heavy metal pollution. Therefore, current study inferred heavy metal absorbance capacity of some wild plant species growing along roadside. Four different wild plant species, i.e., Acacia nilotica L., Calotropis procera L., Ricinus communis L., and Ziziphus mauritiana L. were selected for the study. Leaf samples of these species were collected from four different sites, i.e., Control, New Lahore, Nawababad and Fatehabad. Leaf samples were analyzed to determine Pb2+, Zn2+, Ni2+, Mn2+ and Fe3+ accumulation. The A. nilotica, Z. mauritiana and C. procera accumulated significant amount of Pb at New Lahore site. Similarly, R. communis and A. nilotica accumulated higher amounts of Mn, Zn and Fe at Nawababad and New Lahore sites compared to the rest of the species. Nonetheless, Z. mauritiana accumulated higher amounts of Ni at all sites compared with the other species included in the study. Soil surface contributed towards the uptake of heavy metals in leaves; therefore, wild plant species should be grown near the roadsides to control heavy metals pollution. Results revealed that wild plants growing along roadsides accumulate significant amounts of heavy metals. Therefore, these species could be used to halt the vehicular pollution along roadsides and other polluted areas.