Multi-scale analysis of heavy metals sources in soils of Jiangsu Coast, Eastern China

Optimizing health risk assessment for soil trace metals under low-precision sampling conditions: A case study of agricultural soil

Cost limitations often lead to the adoption of lower precision grids for soil sampling in large-scale areas, potentially causing deviations in the observed trace metal (TM) concentrations from their true values. Therefore, in this study, an enhanced Health Risk Assessment (HRA) model was developed by combining Monte Carlo simulation (MCS) and Empirical Bayesian kriging (EBK), aiming to improve the accuracy of health risk assessment under low-precision sampling conditions. The results showed that the increased sampling scale led to an overestimation of the non-carcinogenic risk for children, resulting in potential risks (the maximum Hazard index value was 1.08 and 1.64 at the 500 and 1000 m sampling scales, respectively). EBK model was suitable for predicting soil TM concentrations at large sampling scale, and the predicted concentrations were closer to the actual value. Furthermore, we found that the improved HRA model by combining EBK and MCS effectively reduced the possibility of over- or under-estimation of risk levels due to the increasing sampling size, and enhanced the accuracy and robustness of risk assessment. This study provides an important methodology support for health risk assessment of soil TMs under data limitation.

Source apportionment and risk assessment of heavy metals in typical greenhouse vegetable soils in Shenyang, China

In this study, the concentrations of Cr, Cu, Ni, Pb, Zn, Cd, As, and Hg in the typical greenhouse vegetable soils in Shenyang, Northeast of China, were determined, and the pollution characteristics and primary sources of heavy mental pollution in soil were analyzed. Results showed that the sum of the mean values of eight typical heavy metals in the soil of the greenhouse soils was 219.79 mg/kg. According to the "Chinese Environmental Quality Evaluation Standard for Farmland of Greenhouse Vegetables Production" (HJ/T 333-2006), the concentrations of Cu (33.50 ± 11.99 mg/kg), Cd (0.246 ± 0.156 mg/kg), and Hg (0.214 ± 0.177 mg/kg) exceeded the limit values in 14.29%, 39.29%, and 39.29% of sampling points, respectively. The single factor pollution index and the Nemerow comprehensive pollution index of heavy metal elements showed that most greenhouse soils were at safety, alert, or light pollution levels. The potential ecological risk index (RI = 505.19) showed that 42.86% of the samples were at high or very high risk and Cd and Hg were the main ecological risk factors. Based on the result of correlation analysis, the Positive Matrix Factorization (PMF) differentiated sources of heavy metal pollution in the study area into four components, including fertilizer input, soil parent material, pesticide spraying and raw coal combustion, and plastic film mulching, which accounted for 36.76%, 22.64%, 20.89%, and 19.71%, respectively, of the total sources of heavy metals.

Spatial distribution of antibiotics and antibiotic resistance genes in tidal flat reclamation areas in China

Tidal flat areas are important resources for land development and are becoming antibiotic resistance receivers that trigger major health concerns. The spatial distributions of forty-nine antibiotics, nine antibiotic resistance genes (ARGs), one mobile gene element (MGE) gene, and nine available metals in the soils and sediments along the coastlines of the Yellow Sea in China were quantified. Hierarchical linear model analysis was used to explore relationships between the antibiotics and ARGs across multiple effects resulting from human activities and environmental factors. Fish farm sediments and farmland soils showed high levels of quinolones (QNs) (maximum 637 ng·g-1), sulfonamides (SAs) (maximum 221 ng·g-1), and corresponding ARGs. Significant positive correlations (P from 5.47 × 10-14 to 0.0487) were observed between the antibiotics (QNs, SAs, and chlortetracycline) and their corresponding ARGs (qnrA, qnrD, aac(6')-Ib-cr, dfrA, sul2, and tetA), indicating the selective pressure from antibiotics in soils and sediments. Nine available metals had positive correlations with at least one ARG, indicating heavy metal pollution could enhance the ARGs. Sheep and poultry husbandry and marine aquaculture contribute the most to the antibiotic resistance in the coastlines. In conclusion, antibiotic pollutions have promoting effects at sub-inhibitory concentrations and more attention should be given to inhibit the enrichment of ARGs during tidal flat reclamation processes. The study also suggests the induction effects from metal pollutions, MGE spread, and the antibiotic pollutions from the usage in livestock and aquaculture.

Sources and spatiotemporal variations of nitrogen and phosphorus in Liaodong Bay, China

Excessive discharge of N and P pollutants results in deterioration of marine environment quality and reduction of sustainability and safety of marine ecology. Spatiotemporal variations characteristics and sources of N and P pollutants were determined based on the long-term monitoring data in Liaodong Bay. Results indicated that an evident spatiotemporal variation was investigated for nutrients. The highest concentrations of NH₃-N, NO₂-N, NO₃-N and PO₄-P were in spring (25.32 μg/L), summer (20.67 μg/L) and autumn (222.07 μg/L, 11.08 μg/L), respectively. The hot-spots of pollutants were mainly concentrated in estuarine and aquaculture areas. The hot spot of PO₄-P gradually extended to the middle of Liaodong Bay in autumn. In addition, pollution sources in each marine functional zone were different, the main pollution source was aquaculture wastewater, river input, domestic sewage. This study provided reasonable suggestions for effectively reducing N and P pollution in Liaodong Bay, and elsewhere.

Influence of local geological data and geographical parameters to assess regional health impact in LCA. Tomsk oblast', Russian Federation application case

The research paper is aimed to modify the human health impact assessment of Cr in soils. The current article presents the input of several critical parameters for the human health Impact Score (IS_hum) assessment in soils. The modification of the IS_hum is derived using geological data - results of neutron activation analysis of soils are used in the IS_hum calculation; research area is divided using the watersheds and population size and density. Watersheds reflect the local environmental conditions of the territory unlike the administrative units (geographical areas of the studied region) due to their geological independence. The calculations of the characterization factor value underestimate the influence of the population size and density on the final result. Default characterization factor values cannot be considered during the assessment of the potential human health impact for the big sparsely inhabited areas. In case of very low population density, the result will be overrated and underestimated in the opposite case. The current approach demonstrates that the geographical separation in the USEtox model should be specified. The same approach can be utilized for other geo zones due to the accessibility of this information (area size, population size, and density, geological, and landscape features).

Pollution assessment, source identification, and health risks of heavy metals: a case study in a typical wheat-maize rotation area of eastern China

Winter-wheat-summer-maize rotations are important cropping patterns in China, and the quality of the food produced from these systems can affect human health. However, the effects of heavy metal pollution on both crops remain unclear. We analyzed soil-wheat and soil-maize samples from eastern China for their Cd, Cu, Zn, Cr, Ni, and Pb contents. The concentrations of these metals in the soils analyzed were found to be lower than those recommended by the national guidelines, but the Cd, Cr, Cu, and Ni concentrations were higher than the natural soil background values in China. Quality indices showed that subpollution was predominant in wheat/maize (95.00%/81.25%) samples. Positive matrix factorization model data revealed that the contributions from natural sources, agricultural activities, and traffic to the heavy metal pollution levels were 30.40-43.07%, 34.67-26.63%, and 34.92-30.27%, respectively, in the wheat-maize rotations. Although the health hazard quotient values for wheat were higher than those for maize, there were no health risks for children or adults.

A Multi-Medium Analysis of Human Health Risk of Toxic Elements in Rice-Crayfish System: A Case Study from Middle Reach of Yangtze River, China

Rice-crayfish system has been extensively promoted in China in recent years. However, the presence of toxic elements in soil may threaten the quality of agricultural products. In this study, eight toxic elements were determined in multi-medium including soil, rice, and crayfish from the rice-crayfish system (RCS) and conventional rice culture (CRC) area. Crayfish obtained a low level of toxic element content, and mercury (Hg) in rice from RCS showed the highest bioavailability and mobility. Health risk assessment, coupled with Monte Carlo simulation, revealed that the dietary exposure to arsenic (As) and Hg from rice and crayfish consumption was the primary factor for non-carcinogenic risk, while Cd and As were the dominant contributors to the high carcinogenic risk of rice intake for adults and children, respectively. Based on the estimated probability distribution, the probabilities of the total cancer risk (TCR) of rice intake for children from RCS were lower than that from CRC.

Heavy Metal Pollution and Its Prior Pollution Source Identification in Agricultural Soil: A Case Study in the Qianguo Irrigation District, Northeast China

Heavy metals are the primary pollutants in agricultural soil and have hindered the sustainable development of agriculture. To control heavy metal pollution, it is essential to identify the pollution sources, particularly the prior source, in agricultural soils. In the current study, Qianguo Irrigation District, a typical agricultural region in Northeast China, was selected to be investigated for the source apportionment of soil heavy metals and identify the prior pollution source. The results showed that the study area was at a moderate pollution level with considerable ecological risk, while Hg and Cd were the main pollutants. Human-health risk assessment indicated that the non-carcinogenic risk for all populations was acceptable (HI < 1), and the carcinogenic risk was not negligible (10−6 < TCR < 10−4). The main pollution sources were concluded to be of lithogenic origin (35.5%), livestock manure (25.4%), coal combustion (21.5%), and chemical fertilizers (17.7%). Coal combustion was identified as the prior pollution source, accounting for 47.69% of the RI contribution. This study can provide scientific support for environmental management and pollution control of soil heavy metals in agricultural regions.

Composition, environmental implication and source identification of elements in soil and moss from a pristine spruce forest ecosystem, Northwest China

The environmental quality of remote alpine ecosystem has been drawn increasing attention owing to the increasingly severe atmospheric pollution. This study investigated the composition and sources of elements in the soil and moss collected from a pristine spruce forest in the Qilian Mountains, Northwest China. The order of mean concentrations of elements investigated in soil was Fe > K > Na > Mg > Ca > Mn > Cr > Zn > Pb > Ni > Cu > As > Cd > Hg, and that of moss was Ca > Fe > Mg > K > Na > Mn > Cr > Zn > Pb > Ni > Cu > As > Cd > Hg. The concentrations of trace metals (except for As) in soil were greater than the soil background values, with Pb contamination more serious than the other elements. The Nemerow integrated pollution index (NIPI) values indicated that the soils were heavily polluted by Pb, Cd and Ni. The potential ecological risk index (PERI) suggested that the soils were at moderate risk. In particular, Hg and Cd were the most critically potential factors for ecological risk. According to the bioaccumulation factors (BAF), the accumulated concentrations of Ca, Hg, Cd, Pb, Ni, Mg, Cr and Zn in moss were higher than those in soil. By performing the multivariate analyses, natural sources (airborne soil particles) were identified to be the major contributors for all elements, whereas anthropogenic sources also contributed to the accumulations of Pb and Cd in the soil and moss in this region.

Spatiotemporal variation and sources of soil heavy metals along the lower reaches of Yangtze River, China

Excessive accumulation of soil heavy metals (HMs) result in the deterioration of soil quality and reduction of agricultural productivity and safety. The accumulation status, temporal change, and sources of soil HMs were determined by large-scale field surveys in 2014 and 2019 in rapid urbanization and industrialization area along the lower reaches of the Yangtze River, China. Eighty-two surface soil samples were collected in 2014 and ninety-five surface soil samples and seven soil profiles (0-100 cm) were collected in 2019. The mean concentrations (in, mg kg^-1) of As (10.17), Cd (0.33), Cr (86.38), Cu (38.22), Hg (0.11), Ni (37.67), Pb (43.95), and Zn (113.15) were greater than the corresponding background values. The concentrations of these 8 HMs significantly varied with site-specific distributions depending on nearby landscape patterns with decreasing order: agricultural soil around industrial > agricultural soil > fallow soil. Cd and Hg were found to be priority pollutants due to their greater accumulations in this study area. Combined analyses of principal component analysis and positive matrix factorization model addressed source apportionment of soil HMs. Industrial activities, parent materials, and agricultural and traffic activities were three major sources and their contributions were 35.56%, 35.20%, and 29.23%, respectively. The concentrations of soil As, Cd, Cr and Pb increased with time. This study elucidates how changes in land uses and time affect soil HMs and provides reasonable suggestions for the effective reduction of HM contamination in economically and industrially developed areas of China, and elsewhere.

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.

Spatial distribution and human health risk assessment of soil heavy metals based on sequential Gaussian simulation and positive matrix factorization model: A case study in irrigation area of the Yellow River

The content of Cd, Cu, Pb, Zn, Cr, Ni and As from 250 soil samples was measured in agricultural soil of Ningxia section of the Yellow River. Positive matrix factorization (PMF) was to identify the main sources of these heavy metals; Sequential Gaussian Simulation (SGS) was to identify their spatial distribution and high-risk areas; and Human Health risk (HHR) model was to measure the health risk. Results showed that the average content of Cd and As exceeds the risk screening value of "Soil Environmental Quality-Agricultural Land Soil Pollution Risk Control Standard" (GB 15618-2018), which belongs to slight-level pollution. Although the content of other types of HMs (Cu, Pb, Zn, Cr, Ni) is below the risk screening value, they are still included heavily in the soil (except Cr). PMF indicated that mixed sources of agriculture and industry accounted for 27.06%, natural sources accounted for 14.12%, industrial sources accounted for 23.04%, traffic sources accounted for 21.50%, and Yellow River sedimentary sources accounted for 14.28%. PMF-HHR showed that the mixed sources of agriculture and industry are the most important factor causing non-carcinogenic risk (HI) to children (accounting for 55.75%). Industrial sources and traffic sources were the two main factors that cause HI to adults (industrial sources accounted for 25.16%, and traffic sources accounted for 28.78%). Mixed sources of agriculture and industry and natural sources were the two main factors that cause carcinogenic risk (CR) (mixed sources of agriculture and industry account for 35.34%, and natural sources account for 33.23%). SGS indicated that 0.64% and 9.32% of the total areas were posing as higher HI areas to children and adults respectively; in particular, 0.68% and 1.12% of the areas were identified as higher HI of As and Cr areas at a critical probability of 0.9.

Interactive effects of natural and anthropogenic factors on heterogenetic accumulations of heavy metals in surface soils through geodetector analysis

The rapid socioeconomic development has led to severe pollution of urban soils by heavy metals. It is vital to identify and quantify the factors that affect trace-element pollution for better preventing and managing soil pollution. In this study, we collected 179 surface soil samples from Zhangzhou City in a coastal area of south China to determine the concentration of seven heavy metals (As, Cr, Cu, Hg, Ni, Pb, and Zn) and used the Nemerow Pollution Index (P_n) to estimate the level of heavy metal pollution in soils. Eighteen environmental factors, including six natural factors (e.g. soil properties, surface topography) and twelve anthropogenic factors (e.g. industry, road network, land use types and landscape pattern), were evaluated with the geodetector statistical method. The results indicate that the heavy metal contamination of soils in Zhangzhou City was highly heterogeneous. We found that the primary influencing factors for heavy metal concentrations were soil organic matter content, agriculture activities, and landscape pattern. Furthermore, the nonlinear relationship between the primary factors and their interaction factors enhanced soil contamination by the heavy metals. Among the anthropogenic factors, landscape pattern enhanced P_n the most when interacting with natural factor. In addition, the buffer zone should be considered when evaluating the effects of factors such as land use and landscape pattern, because the interactions between landscape pattern and slope aspect produce a maximum effect, accounting for 31.0% of the P_n value on the scale of 800 m. Based on this analysis, we identified the key factors of heavy metal pollution in the soils of Zhangzhou City and proposed strategic procedures for effective soil pollution prevention and treatment in the future.

A simple method to determine the sampling numbers in decision-making units with unknown variations of soil cadmium

Sampling number is one critical issue to achieve credible results when surveying soil contamination and making remediation decisions. Traditional methods based on a normal distribution for determining numbers of samples are not always optimal because most distributions of soil heavy metal concentrations followed a log-normal distribution. Moreover, the variation of soil heavy metal concentrations is a prerequisite for previous methods to determine sampling numbers. Unfortunately, the variation is often unknown before soil sampling. Therefore, a simple method under the log-normal distribution without relying on variation to determine quickly the sampling number (QSN) was developed for soil cadmium and compared with other methods based on classical statistics and Chebyshev inequality. Results showed that an equation as a function of sampling areas could be used to determine QSN (QSN = 18.44 × A^0.54 + 8.69, A is sampling areas, km²), with acceptable errors ranging from 13 to 33% at the sampling areas of 0.03-10 km². The developed simple method for QSN was easy to use and cost-effective without prerequisite on the estimation of variation. Moreover, when the sampling cost was enough and the improved accuracy was requested, the increased sampling numbers were recommended as 1.53 times as the number calculated by the simple method. Therefore, the proposed method is believed as a simple and cost-effective method to determine the sampling numbers of soil Cd in decision-making units with unknown variations.

The Monitoring of Selected Heavy Metals Content and Bioavailability in the Soil-Plant System and Its Impact on Sustainability in Agribusiness Food Chains

This study assisted in identifying and preventing the increase in heavy metals in soil and winter wheat. Its accumulation can affect cultivated crops, quality and crop yields, and consumers’ health. Selected heavy metals were analyzed using the GTAAS method. They were undertaken on selected heavy metals content (Cd, Cu, Pb, and Zn) in arable soils at three sites in Slovakia and their accumulation in parts of cultivated winter wheat. Our study showed that the limit value of Cd in soil samples was exceeded in the monitored arable soils from 2017–2019. The average content values of Cu and Zn did not exceed the limit values, even in Pb values (except for the spring period). The analyses also showed that the heavy metals content for plants bioavailable in soil did not exceed the statutory critical values for Cd, Cu, and Zn’s average content values. However, Pb content exceeded permitted critical values. Heavy metals bioaccumulation (Zn, Cu) was within the limit values in wheat. Analyzed Cd content in wheat roots and Pb content were determined in all parts of wheat except grain. The study showed that grain from cultivated winter wheat in monitored arable soils is not a risk for consumers.

An Integrated Multi-Approach to Environmental Monitoring of a Self-Burning Coal Waste Pile: The São Pedro da Cova Mine (Porto, Portugal) Study Case

The São Pedro da Cova waste pile (Porto, Portugal) is composed of coal mining residues that have been self-burning since 2005 and is located close to an inhabited area and social infrastructures, further adding to effects on the environment and human health. Therefore, there is a great interest in the environmental monitoring of this waste pile. This work describes an integrative multi-approach that allows the environmental monitoring of several parameters of the waste pile, applying several technologies. The temperature measurements were obtained by a thermal infrared (TIR) sensor on board an unmanned aerial vehicle (UAV) and supplemented with field measurements. In order to evaluate the altimetric variations, for each flight, a digital elevation model (DEM) was generated considering a multispectral sensor also on board the UAV. The hydrogeochemical characterization was performed through the analysis of groundwater and surface water samples, with and without the influence of mine drainage. The soil monitoring included the analysis of waste material as well as the surface soil in the surrounding area of the waste pile. All the data were analyzed and integrated in a geographical information system (GIS) open-source application. The adopted multi-approach methodology, given its intrinsic interdisciplinary character, has proven to be an effective way of encompassing the complexity of this type of environmental problem.

Contamination assessment, health risk evaluation, and source identification of heavy metals in the soil-rice system of typical agricultural regions on the southeast coast of China

To quantitatively assess heavy metal accumulation and potential ecological and human health risks as well as analyze the sources of metals in a typical soil-rice system located on the southeast coast of China, 120 topsoil samples and corresponding rice grain samples were collected across the study area. The concentrations of As, Cd, Pb, Cr, Hg, Zn, Cu, and Ni were analyzed. The results revealed that Hg, Cd, and Cu were the main pollutants in soils. Besides, according to geo-accumulation value of Hg, 18.3% of samples were at or above moderate contamination levels. Additionally, the soil was in moderate ecological risk from combined heavy metal pollution, and 49.7% and 27.0% of this risk could be attributed to Hg and Cd pollution, respectively, due to their high toxic-response factors. For the rice samples, Cd content showed the highest biological accumulation coefficient value (40.8%) in rice grains and was slightly greater than its maximum allowable value (MAV) (0.2 mg/kg) in 7.5% of samples, whereas the other metals were all lower than their corresponding MAVs. Heavy metal exposure (especially As exposure) via rice consumption causes significant carcinogenic and non-carcinogenic risks to adults, and non-carcinogenic risk to children, while the carcinogenic risk to children was at tolerable level. Greater rice consumption might be responsible for the greater health risk to adults than children. Natural sources (loaded heavily with Cr and Ni) such as lithogenic components and soil parent materials, agricultural activities (loaded heavily with Cd, Cu, and Zn), especially excessive use of pesticides and fertilizers, and industrial activities (loaded heavily with Hg, Pb, and As) including vehicle emissions, coal combustion, and those of the textile and chemical industries were identified as the main sources. Effective regulations should be enforced to guarantee the safety of farm produce and protect ecological and human health in the study area.

Spatial assessment models to evaluate human health risk associated to soil potentially toxic elements

Quantifying source apportionment of potentially toxic elements (PTEs) in soils and associated human health risk (HHR) is essential for soil environment regulation and pollution risk mitigation. For this purpose, an integrated method was proposed, and applied to a dataset consisting of As, Cd, Cr, Cu, Hg, Ni, Pb, Se, and Zn in 273 soil surface samples. Positive matrix factorization (PMF) was used to quantitatively examine sources contributions of PTEs in soils; and the HHR arising from the identified source was determined by combining source profiles and health risk assessment; at last, sequential Gaussian simulation (SGS) was used to identify the areas with high HHR. Four sources were identified by PMF. Natural and agricultural sources affected all 9 PTEs contents with contributions ranging from 19.2% to 62.9%. 41.9% of Cd, 40.8% of Pb, 58.6% of Se, and 29.8% of Zn were controlled by industrial and traffic emissions. Metals smelting and mining explained 35.5%, 30.5%, and 24.9% of Cr, Cu, and Ni variations, respectively. Hg was dominated by atmospheric deposition from coal combustion and coking (58.7%). The mean values of the total non-carcinogenic risks of PTEs were 1.55 × 10^-1 and 9.40 × 10^-1 for adults and children, and the total carcinogenic risk of PTEs had an average value of 8.86 × 10^-5. Based on source-oriented HHR calculation, natural and agricultural sources were the most important factor influencing HHR, explaining 51.0% and 49.1% of non-carcinogenic risks for children and adults, and 44.2% of carcinogenic risk. SGS indicated that 1.1% of the total area was identified as hazardous areas with non-carcinogens risk for children.

Evolution of groundwater chemistry in coastal aquifers of the Jiangsu, east China: Insights from a multi-isotope (δ2H, δ18O, 87Sr/86Sr, and δ11B) approach

Groundwater salinization is currently a very serious and challenging issue in many parts of the world. With an increasing demographic pressure and remarkable changes of water and land uses over the last decades, the multilayer coastal aquifer system of Jiangsu province, east China, was affected by increasing salinization. In this study, we investigate the groundwater salinization process and the salinity sources of the aquifer system in Nantong area (southern part of the Jiangsu coastal plain) using a multi-isotope (δ²H, δ¹⁸O, ⁸⁷Sr/⁸⁶Sr, and δ¹¹B) approach. The results show that the TDS (total dissolved solids) values in most deep groundwater samples are generally lower than those of the shallow groundwater samples. The TDS of both shallow and deep groundwater increase from western Nantong (inland) to the eastern coastal region of the Yellow Sea. The chemical types transform from Ca-Mg-HCO₃ or Mg-Ca-HCO₃ to NaCl. The stable hydrogen and oxygen isotopes signatures of the groundwater samples indicate that local precipitation likely acts as the main recharge source of both the shallow and deep confined groundwater systems. The deep groundwater shows more depleted isotopes, suggesting recharging by the precipitation under a cold climate before the Holocene period. The shallow groundwater features heavier water isotopes, indicating recharging source from recent precipitation under a warm climate. The variations in δ¹¹B and ⁸⁷Sr/⁸⁶Sr of groundwater samples can be explained by the changes of solute sources. In the inland region (western Nantong), shallow groundwater with higher TDS is mainly caused by evaporation-induced concentration, whereas in coastal areas, seawater intrusion exerts a major influence on the chemical composition of the shallow groundwater. Our results show that that seawater intrusion mainly occurs in eastern and southeastern Nantong area. We also find that hydraulic connection between shallow and deep groundwater is strengthened by continuous overexploitation, and deep groundwater is mixed with shallow groundwater at some points. The mixing between upper saline water and deep freshwater, together with water-rock interactions, likely explain the observed low salinity in deep groundwater in coastal areas. Overall, with growing observations of salty seawater intrusion in the estuary region of the Yangtze River, future efforts are needed to prevent further seawater intrusion as sea level rises and groundwater table declines. In this context, our findings provide key information for groundwater management in other coastal aquifers, east China.

Heavy metal pollution and the risk from tidal flat reclamation in coastal areas of Jiangsu, China

Tidal flat is an important supplementary land resource. However, increasing tidal flat reclamation in China has resulted in severe environmental issues. Using single-metal pollution index and multi-metal Nemerow pollution index, this study aimed to evaluate the risks of heavy metal pollution among different tidal flat use types, including fish farm, farmland, pastoral land, industrial land, forest and unutilized land. The results indicated that, concentrations of all elements were higher than geochemical values; Cd posed the highest risk, followed by As and Ni. Fish farm created the highest risk, followed by farmland. Every one year increase in fish farming led to increases in sediment concentrations of Cu, Cr, Ni, Pb, Zn and As by 0.73, 1.25, 0.68, 0.41, 1.22 and 0.20 mg.kg^-1, respectively. Tidal flat reclamation in Jiangsu Province creates the risk of heavy metal pollution, and specific attention should be paid to the fodders and additives used in fish farming.

Comparison of the concentrations, sources, and distributions of heavy metal(loid)s in agricultural soils of two provinces in the Yangtze River Delta, China

Jiangsu and Zhejiang provinces, located in the Yangtze River Delta (YRD) core region, are the most economically developed regions in China, as well as the areas with serious soil pollution. The concentrations, sources, and distributions of heavy metal(loid)s in agricultural soils of the two provinces were studied; positive matrix factorization model (PMF) analysis and kriging interpolation were combined to compare the pollution characteristics of heavy metal(loid)s. The results showed that the degree of accumulation might be more serious in Zhejiang province than in Jiangsu province, especially in terms of Cd, Hg, and Pb. PMF results showed anthropogenic activities were the dominant factors affecting the concentrations of soil heavy metal(loid)s. The contributions of the three sources in Jiangsu province were 40.28% natural and traffic sources, 37.49% agricultural sources, and 22.22% industrial and coal combustion sources. The contributions of the three sources in Zhejiang province were 43.45% agricultural and industrial sources, 32.15% natural sources, and 24.40% industrial sources. The kriging interpolation results of the two provinces showed that the concentrations of As, Cr, and Ni were significantly higher in Jiangsu province than in Zhejiang province; the concentrations of Cu were similar in the two provinces, while other heavy metals had higher concentrations in Zhejiang province. These accumulations of heavy metal(loid)s in agricultural soil in both provinces cannot be ignored. This work will contribute to the development of effective policies aimed at protecting the soil environment from long-term accumulation of heavy metal(loid)s.

Accumulation of potentially toxic elements in agricultural soil and scenario analysis of cadmium inputs by fertilization: A case study in Quzhou county

Fertilizer application has greatly increased crop yield, however impurities in mineral or organic fertilizers, such as heavy metals, are being added to agricultural soils, which would pose a high risk for soil and crop production. 115 soil samples were collected from Quzhou, a typical agricultural county in the North China Plain, to investigate the total content of cadmium (Cd), arsenic (As), lead (Pb), nickel (Ni), copper (Cu), zinc (Zn) and chromium (Cr) in soils. The contamination levels and source apportionment of studied elements were explored by the pollution indices, multivariate statistical approaches and geostatistical analysis. The ranges of Cd, As, Pb, Ni, Cu, Zn and Cr were between 0.08 and 0.35, 5.34-15.9, 7.34-38.9, 12.9-61.3, 7.80-27.0, 31.4-154, and 17.0-50.5 mg/kg and with the mean values 0.16, 9.20, 16.0, 24.7, 17.6, 61.1, and 29.5 mg/kg, respectively. The studied area was slightly polluted mainly by Cd, and higher pollution was found in soils under vegetable crops. The application of mineral phosphate fertilizer and livestock manure were the main source of Cd and Zn, and other elements (As, Pb, Ni and Cu) might originate from soil parent materials. Scenario analyses were performed using the R programming language, based on the cadmium contents in mineral phosphate fertilizers and livestock manures. The results showed that the long-term application of phosphate fertilizers would lead to some Cd enrichment in soil without risk of substantial pollution. Compared to pure mineral fertilizers, the long-term application of blended fertilizers (30% livestock manures and 70% phosphate fertilizers) or livestock manures would incur a higher Cd pollution risk within a short period, with a maximum probability of Cd risk of 55.21%. Mitigation measurements and scientific agronomic practices should be developed to minimize the risk of potential toxic elements in agricultural soil.

Heavy metal concentrations of soils near the large opencast coal mine pits in China

Mining is a common industrial activity and significant source of soil heavy metal (HM) pollution. However, nearly all studies on the effects of mining activities on soil environmental quality have entailed field monitoring of small regions or bibliometric analyses. This study therefore investigated the pollution of surface soils surrounding 135 large opencast coal mining pits in China. A total of 1772 surface soil samples were collected, and the concentrations of eight major HMs were determined. The HM concentrations in this study were relatively lower than the published HM concentrations of coal mine soils from 50 typical Chinese coal mines. However, pollution assessments indicated that Cd, Cu, and As concentrations were concerning. Significant correlations existed between all of the HMs and mining pit area (p < 0.01), as well as between the Pb and Zn concentrations and direction (p < 0.05). Climate conditions had large influences on the HM concentrations. The concentrations of all studied HMs, except for Ni, were highest in Anthrosols and lowest in hydromorphic soils. The concentrations of all HMs, except for Hg, in land use types showed a descending trend of cultivated land > garden plot > grassland. Significantly negative correlations (p < 0.01) between all HM concentrations and elevation were observed. Cr, Zn, and Ni were significantly and positively correlated with the slope, and no HMs, except Cr, showed significant correlations with the parcel area. This paper provides insights for the policymakers regarding soil pollution control and management strategies near coal mine pits.

Characteristics of heavy metal concentrations and risk assessment for giant pandas and their habitat in the Qinling Mountains, China

High concentrations of heavy metals in the environment threaten the quality of ecosystems and the health of human beings and animals. Giant panda (Ailuropoda melanoleuca), which is endemic to China and a global conservation icon, has the largest density in the Qinling Mountains. This paper investigated the spatiotemporal variation of heavy metal concentrations in soil (N = 44) at the regional scale with three zones of urban areas, mountain edges, and central mountains, the temporal variation of heavy metal concentrations in three bamboo species (N = 19) and two types of feces (N = 10), and assessed the ecological risk and health risk for giant pandas and their habitat in the Qinling Mountains. The results showed that the median concentrations of studied eight heavy metals mercury (Hg), arsenic (As), copper (Cu), manganese (Mn), zinc (Zn), chromium (Cr), lead (Pb), and cadmium (Cd) in soil exceeded the background values of Shaanxi Province except Pb. The median concentrations of Hg, Zn, Cr, Pb, and Cd in bamboo surpassed the reference standard (RS) of national food safety limits in vegetables for human intake, but the concentration of Zn was within the nutrient range in the bamboo plants. Heavy metals were enriched more in feces of captive than the wild giant pandas, which illustrated either higher ingestion or lower digestibility for captive giant panda. Ecological risk assessment of soil by the geo-accumulation index (I_geo) and risk index (RI) showed strong pollution by Hg and moderate pollution by Cd. Health risk assessment by the hazard index (HI) showed a potential to strong risk for giant pandas exposed to Pb, As, and Hg. In addition, the concentrations of heavy metals in feces showed a higher exposure risk for captive giant pandas than wild giant pandas. We suggest that attention should be paid to and all effective measurements should be taken for reducing the emission of Hg, As, Pb, and Cd in the study area.

Quantitative identification of anthropogenic trace metal sources in surface river sediments from a hilly agricultural watershed, East China

Quantitative identification of anthropogenic trace metal sources in surface river sediments is vital for watershed pollution control and environmental safety. In this study, we developed a reliable approach by integrating enrichment factor (EF), multiple linear regression of absolute principal component scores (MLR-APCS), and Pb stable isotopes, and applied it to a typical hilly agricultural watershed in Eastern China. Results showed that trace metals have accumulated in the river sediments during long-term agricultural development, with special concern of Cu, Ni, Pb, and Cr that may pose adverse biological effects. Among them, Pb was the most anthropogenically impacted trace metal due to its high EF value, but its excessive concentration still did not exceed background concentration. Based on the excessive trace metal concentrations, atmospheric deposition, livestock manure, and chemical fertilizer were identified as the three major anthropogenic pollution sources, and their respective contributions were further estimated by using MLR-APCS model. Together with natural contributions, atmospheric deposition contributed on average 35.3%, 43.1%, and 30.4% of total Ni, Pb, and Cr concentrations in the sediments, respectively. Similarly, livestock manure contributed 41.0% of total Cu and 40.6% of total Zn concentrations, while chemical fertilizer was responsible for 44.3% of total Cd concentration. For Pb, the source contribution of atmospheric deposition to sediment pollution was also quantitatively assessed by isotopic analysis, which was generally close to the value of 43.1% and therefore verified the EF and MLR-APCS results.

Improved heavy metal mapping and pollution source apportionment in Shanghai City soils using auxiliary information

Soil heavy metal pollution can be a serious threat to human health and the environment. The accurate mapping of the spatial distribution of soil heavy metal pollutant concentrations enables the detection of high pollution areas and facilitates pollution source apportionment and control. To make full use of auxiliary soil properties information and show that they can improve mapping, a synthesis of the Bayesian Maximum Entropy (BME) theory and the Geographically Weighted Regression (GWR) model is proposed and implemented in the study of the Shanghai City soils (China). The results showed that, compared to traditional techniques, the proposed BME-GWR synthesis has certain important advantages: (a) it integrates heavy metal measurements and auxiliary information on a sound theoretical basis, and (b) it performs better in terms of both prediction accuracy and implementation flexibility (including the assimilation of multiple data sources). Based on the heavy metal concentration maps generated by BME-GWR, we found that the As, Cr and Pb concentration levels are high in the eastern part of Shanghai, whereas high Cd concentration levels were observed in the northwestern part of the city. Organic carbon and pH were significantly correlated with most of the heavy metals in Shanghai soils. We concluded that Cd pollution is mainly the result of agricultural activities, and that the Cr pollution is attributed to natural sources, whereas Pb and As have compound pollution sources. Future studies should investigate the implementation of BME-GWR in the case of space-time heavy metal mapping and its ability to integrate human activity information and soil category variables.