Characteristics of heavy metal transfer and their influencing factors in different soil-crop systems of the industrialization region, China

Bayesian risk prediction model: An accessible strategy to predict cadmium contamination risk in wheat grain grown in alkaline soils

Excessive cadmium (Cd) concentration in wheat grain is becoming a widespread concern in China. Considering the complexity of Cd transfer in the soil-wheat system, how the Cd risk in wheat grain be accurately predicted from the limited details available is of great significance for the risk management of Cd. Bayes' theory could leverage existing data by combining prior information and observational data, providing a promising strategy with which to calculate a more robust posterior probability of a grain sample exceeding the food safety standard (FSS) for Cd (0.1 mg kg-1). In the current study, a risk prediction model, based on Bayes' theory, was established to achieve a more accurate prediction of the wheat grain Cd risk from a limited number of soil parameters. The risk prediction model could predict the risk probability of wheat grain with a Cd concentration exceeding the FSS under a given soil concentration of either total Cd or diethylenetriaminepentaacetic acid (DTPA)-extractable Cd. Soil total Cd concentration proved to be a better variable for the model with greater predictive accuracy. The model predicted that fewer than 5% of the wheat grain would have a Cd concentration exceeding the FSS when grown in soil with a total Cd concentration of less than 0.299 mg kg-1. The risk probability rose significantly to 50% when the soil total Cd reached 0.778 mg kg-1. The accuracy of the model was greater than the widely applied multiple linear regression model, whereas previously published data from similar soil conditions also confirmed that the Bayesian model could predict wheat Cd risk with minimal error. The proposed model provides an accurate, accessible and cost-effective methodology for predicting Cd risk in wheat grown in alkaline soils before harvest. The wider application to other soil conditions, crops or contaminants using the Bayesian model is also promising for risk management authorities.

The accumulation of cadmium and lead in wheat grains is primarily determined by the soil-reducible cadmium level during wheat tillering

The significant increase in cadmium (Cd) and lead (Pb) pollution in agricultural soil has greatly heightened environmental contamination issues and the risk of human diseases. However, the mechanisms underlying the transformation of Cd and Pb in soil as well as the influencing factors during their accumulation in crop grains remain unclear. Based on the analysis of the distribution trend of Cd and Pb in soil during the growth and development stages of wheat (tillering, filling, and maturity) in alkaline heavy metal-polluted farmland in northern China, this study investigated the response mechanism of soil heavy metal form transformation to soil physicochemical properties, and elucidated the main determining periods and influencing factors for Cd and Pb enrichment in wheat grains. The results showed that an increase in CEC and SOM levels, along with a decrease in pH level, contributed to enhancing the bioavailability of Cd in the soil. This effect was particularly evident during the tillering stage and grain filling stage of wheat. Nevertheless, the effects of soil physicochemical properties on bioavailable Pb was opposite to that on bioavailable Cd. The enrichment of Cd and Pb in grain was significantly influenced by soil pH (r = -0.786, p < 0.01), SOM (r = 0.807, p < 0.01), K (r = -0.730, p < 0.01), AK (r = 0.474, p = 0.019), and AP (r = -0.487, p = 0.016). The reducible form of Cd in soil during the wheat tillering stage was identified as the primary factor contributing to the accumulation of Cd and Pb in wheat grains, with a significant contribution rate of 84.5%. This study provides a greater scientific evidence for the management and risk control of heavy metal pollution in alkaline farmland.

Ecological and health risk assessments of heavy metals and their accumulation in a peanut-soil system

Heavy metals pollution is a notable threat to environment and human health. This study evaluated the potential ecological and health risks of heavy metals (Cu, Cr, Cd, Pb, Zn, Ni, and As) and their accumulation in a peanut-soil system based on 34 soil and peanut kernel paired samples across China. Soil As and Cd posed the greatest pollution risk with 47.1% and 17.6% of soil samples exceeding the risk screen levels, respectively, with 26.5% and 20.6% of the soil sites at relatively strong potential ecological risk level, respectively, and with the geo-accumulation levels at several soil sites in the uncontaminated to moderately contaminated categories. About 35.29% and 2.94% of soil sites were moderately and severely polluted based on Nemerow comprehensive pollution index, respectively, and a total of 32.4% of samples were at moderate ecological hazard level based on comprehensive potential ecological risk index values. The Cd, Cr, Ni, and Cu contents exceeded the standard in 11.76, 8.82, 11.76 and 5.88% of the peanut kernel samples, respectively. Soil metals posed more health risks to children than adults in the order As > Ni > Cr > Cu > Pb > Zn > Cd for non-carcinogenic health risks and Ni > Cr ≫ Cd > As > Pb for carcinogenic health risks. The soil As non-cancer risk index for children was greater than the permitted limits at 14 sites, and soil Ni and Cr posed the greatest carcinogenic risk to adults and children at many soil sites. The metals in peanut did not pose a non-carcinogenic risk according to standard. Peanut kernels had strong enrichment ability for Cd with an average bio-concentration factor (BCF) of 1.62. Soil metals contents and significant soil properties accounted for 35-74% of the variation in the BCF values of metals based on empirical prediction models.

Contaminated soil remediation with nano-FeS loaded lignin hydrogel: A novel strategy to produce safe rice grains while reducing cadmium in paddy field

Cadmium (Cd) contamination in agricultural soil has been an elevated concern due to the high health risks associated with the transfer through the soil-food chain, particularly in the case of rice. Recently, there has numerous researches on the use of nanoparticle-loaded materials for heavy metal-polluted soil remediation, resulting in favorable outcomes. However, there has been limited research focus on the field-scale application and recovery. This study was aimed to validate the Cd reduction effect of the nano-FeS loaded lignin hydrogel composites (FHC) in mildly polluted paddies, and to propose a field-scale application method. Hence, a multi-site field experiment was conducted in southern China. After the application for 94-103 days, the FHC exhibited a high integrity and elasticity, with a recovery rate of 91.90%. The single-round remediation led to decreases of 0.42-31.72% in soil Cd content and 1.52-49.11% in grain Cd content. Additionally, this remediation technique did not adversely impact rice production. Consequently, applying FHC in the field was demonstrated to be an innovative, efficient, and promising remediation technology. Simultaneously, a strategy was proposed for reducing Cd levels while cultivating rice in mildly polluted fields using the FHC.

Effect of biological sewage sludge and its derived biochar on accumulation of potentially toxic elements by corn (Zea mays L.)

The land application of sewage sludge can cause different environmental problems due to the high content of potentially toxic elements (PTEs). The objective of this study was to compare the effect of urban biological sewage sludge (i.e. the waste of activated sludge process) and its derived biochar as the soil amendments on the bioavailability of PTEs and their bioaccumulation by corn (Zea mays L.) under two months of greenhouse conditions. The soil was treated by adding biochar samples at 0 (control), 1, 3, 5% w/w. The diethylenetriamine pentaacetic acid (DTPA)-extractable concentrations of PTEs including Zn, Pb, Cd, Cr, Ni, Fe, and Cu in soil and their accumulation by plant shoot and root were measured. Conversion of the biological sewage sludge into the biochar led to decrease the PTEs bioavailability and consequently decreased their contents in plant tissues. The DTPA extractable metal concentrations of produced biochar in comparison to the biological sewage sludge reduced 75% (Cd), 65% (Cr), 79% (Ni and Pb), 76% (Zn), 91% (Cu) and 88% (Fe). Therefore, the content of Ni, Fe, Zn and Cd in corn shoot was decreased 61, 32, 18 and 17% respectively in application of 5% biochar than of raw sewage sludge. Furthermore, the application of 5% biochar enhanced the physiological parameters of the plants including shoot dry weight (twice) and wet weight (2.25 times), stem diameter (1.70 times), chlorophyll content (1.03 times) in comparison to using 5% raw sewage sludge. The results of the study highlight that application of the biochar derived from urban biological sewage sludge in soil could decrease the risk of PTEs to the plant.

Predicting Cd accumulation in rice and identifying nonlinear effects of soil nutrient elements based on machine learning methods

The spatial mismatch of Cd content in soil and rice causes difficulties in environmental management for paddy soil. To investigate the influence of soil environment on the accumulation of Cd in rice grain, we conducted a paired field sampling in the middle of the Xiangjiang River basin, examining the relationships between soil properties, soil nutrient elements, Cd content, plant uptake factor (PUFCd), and translocation factors in different rice organs (root, shoot, and grain). The total soil Cd (CdT) and available Cd (CdA) contents and PUFCd showed large spatial variability with ranges of 0.31-6.19 mg/kg, 0.03-3.07 mg/kg, and 0.02-3.51, respectively. Soil pH, CdT, CdA, and the contents of soil nutrient elements (Mg, Mn, Ca, P, Si, and B) were linearly correlated with grain Cd content (Cdg) and PUFCd. The decision tree analysis identified nonlinear effects of Si, Zn and Fe on rice Cd accumulation, which suggested that low Si and high Zn led to high Cdg, and low Si and Fe caused high PUFCd. Using the soil nutrient elements as predictor variables, random forest models successfully predicted the Cdg and PUFCd and performed better than multiple linear regressions. It suggested the impacts of soil nutrient elements on rice Cd accumulation should receive more attention.

Prediction of cadmium contents in rice grains from Quaternary sediment-distributed farmland using field investigations and machine learning

The Quaternary sediment-distributed regions of South China are suitable for rice cultivation, which is crucial for ensuring food security. Spatial correlations between soil cadmium (Cd) and rice Cd contents are generally poor, making the evaluation of rice quality and associated health risks challenging. In this study, we developed machine learning algorithms for predicting rice Cd contents using 654 data pairs of soil-rice samples collected in Guangxi province, China. After a comprehensive comparison, our results showed that the random forest (RF) had the better performance than artificial neural network (ANN) based on all the data (RMSEtesting 0.066 vs. 0.099 and R2testing 0.860 vs. 0.688). The feature importance analysis showed that soil CaO, Cd, elevation, and rainfall were the four most important features affecting the rice Cd contents in the study area. Using the established RF-predicated model, the rice Cd contents were predicted at the provincial level with an additional dataset of 1176 paddy soil samples. The prediction result revealed about 23 % of farmland cultivated rice with Cd content over 0.2 mg kg-1 in the study area. Therefore, it is recommended to implement strict measures by local agricultural departments to reduce rice Cd contents and ensure food safety in these areas. Our study provides valuable insights into the prediction of rice Cd contents, thus contributing to ensuring food safety and preventing Cd exposure-associated health risks.

Ensemble learning-based applied research on heavy metals prediction in a soil-rice system

Accurate prediction of heavy metal accumulation in soil ecosystems is crucial for maintaining healthy soil environments and ensuring high-quality agricultural products, as well as a challenging scientific task. In this study, we constructed a dataset containing 490 sets of multidimensional environmental covariate data and proposed prediction models for heavy metal concentrations (HMC) in a soil-rice system, EL-HMC (including RF-HMC and GBM-HMC), based on Random Forest (RF) and Gradient Boosting Machine (GBM) ensemble learning (EL) techniques. To reasonably evaluate the effectiveness of each model, Multiple linear and Bayesian regressions were selected as benchmark models (BM), and mean absolute error (MAE), root mean square error (RMSE), and determination coefficient R2 were selected as evaluation indicators. In addition, sensitivity and spatial autocorrelation (SAC) analyses were used to examine the robustness of the model. The results showed that the R2 values of RF-HMC and GBM-HMC for modeling available cadmium (Cd) concentrations in soil were 0.654 and 0.690, respectively, with an average increase of 48.0 % compared to the BMs. The R2 values of RF-HMC and GBM-HMC for predicting Cd, lead (Pb), chromium (Cr), and mercury (Hg) concentrations in rice ranged from 0.618 to 0.824 and 0.645 to 0.850, respectively, with an average increase of 58.2 % compared with the BMs. The corresponding MAEs and RMSEs of RF-HMC and GBM-HMC had low error levels. Sensitivity analysis of the input features and the SAC of the prediction bias showed that the EL-HMC models have excellent robustness. Therefore, the EL technology-based prediction models for HMCs proposed herein are practical and feasible, demonstrating better accuracy and stability than the traditional model. This study verifies the application potential of EL technology in pollution ecology and provides a new perspective and solution for sustainable management and precise prevention of heavy metal pollution in farmland soil at the regional scale.

Cadmium accumulation in paddy soils affected by geological weathering and mining: Spatial distribution patterns, bioaccumulation prediction, and safe land usage

The abnormal enrichment of cadmium (Cd) in soil caused by rock weathering and mining activities is an issue in southern China. Although the soil Cd content in these regions is extremely high, the bioavailability of Cd in the soils differs significantly. The carbonate area (CBA) and tin-mining area (TIA) in Hezhou City were investigated to determine the primary features of soil Cd mobility in these regions and improve environmental management. Lateral and vertical spatial distributions revealed different accumulation and migration mechanisms of soil Cd in the CBA and TIA. Further analyses revealed that mining activities and geological weathering resulted in different soil geochemical parameters, thus yielding significantly lower levels of Cd in rice grains in the CBA than in the TIA. The random forest (RF) model predicted the bioaccumulation factor (BAF) (R2 = 0.69) better than the support vector machine (SVM) model (R2 = 0.68). Subsequently, a novel land management scheme was proposed based on soil Cd and the prediction of Cd in rice to optimize the spatial resources of agricultural land and ensure the safety of rice for consumption. This study provides a novel approach for land management in Cd-contaminated areas.

Quantitative prediction of potential areas likely to yield Se-rich and Cd-low rice using fuzzy weights-of-evidence method

The research of high-quality agricultural products rich in selenium and low in cadmium (Se-rich and Cd-low, respectively) is related directly to the value of agricultural products and people's food safety. Now it is still challenging to carry out development planning for Se-rich rice. By fuzzy weights-of-evidence method, the geochemical soil survey data of Se and Cd from 27,833 surface soil samples and 804 rice samples was used to predict the probability of areas, in Hubei Province, China, that will likely yield (a) Se-rich and Cd-low rice, (b) Se-rich and Cd-normal rice and (c) Se-rich and Cd-high rice. The areas predicted to likely yield Se-rich and Cd-high rice, Se-rich and Cd-normal rice, and high quality (i.e., Se-rich and Cd-low) rice cover 6542.3 km2 (5.9 %), 35,845.9 km2 (32.6 %), 12,379.7 km2 (11.3 %), respectively, of the surveyed region. According to the predictive distribution probability mapping of Se and Cd, this paper gives preliminary suggestions on the use of endogenous and exogenous Se, and Cd-reduction measures in planting Se-rich rice in different regions of Hubei Province. This study provides a new perspective for rational rice planting of Se-rich agricultural products, and it lays a foundation for the effective implementation of a geochemical soil investigation engineering project, which is of great significance for improving the economic value of Se-rich agricultural products and sustainable utilization of Se land resources.

Translocation pattern of heavy metals in soil-rice systems at different growth stages: A case study in the Taihu region, Eastern China

Rice production is crucial for human nutrition and food safety globally. However, it has been a significant sink for potentially harmful metals because of intensive anthropogenic activities. The study was conducted to characterize heavy metal translocation from soil to rice at the filling, doughing and maturing stages, and influencing factors of their accumulation in rice. The distribution and accumulation patterns varied for metal species and growth stages. Cd and Pb accumulation mainly occurred in roots, Cu and Zn were readily transported to stems. Cd, Cu, and Zn accumulation in grains had a descending order of filling > doughing > maturing. Soil heavy metals, TN, EC, and pH exerted important impacts on heavy metals uptake by roots during the period from filling stage to maturing stage. Concentrations of heavy metals in grains were positively correlated with the translocation factors TF_stem-grain (from stem to grain) and TF_leaf-grain (from leaf to grain). Grain Cd exhibited significant correlations with total Cd and DTPA-Cd in the soil at each of the three growth stages. Moreover, Cd in maturing grain could be effectively predicted by soil pH and DTPA-Cd at the filling stage.

Safety of African grown rice: Comparative review of As, Cd, and Pb contamination in African rice and paddy fields

This review aimed to investigate the reported concentrations of arsenic (As), cadmium (Cd), and lead (Pb) in rice cultivated in Africa and African rice paddies compared to other regions. It also aimed to explore the factors influencing these concentrations and evaluate the associated health risks of elevated As, Cd, and Pb exposure. Relevant data were obtained from electronic databases such as PubMed, Scopus, and Google Scholar using specific keywords related to arsenic, cadmium, lead, rice, Africa, paddy, and grain. While the number of studies reporting the concentrations of As, Cd, and Pb in rice and rice paddies in Africa is relatively low compared to other regions, this review revealed that most of the African rice and paddy soils have low concentrations of these metals. However, some studies have reported elevated concentrations of As, Cd, and Pb in paddy fields, which is concerning due to the increased use of agrochemicals containing heavy metals in rice production. Nonetheless, agronomical interventions such as implementing alternate wetting and drying water management, cultivating cultivars with low accumulation of As, Cd, and Pb, amending rice fields with sorbents, and screening irrigation water can limit the bioaccumulation of these carcinogens in paddy fields using phytoremediation techniques. Therefore, we strongly urge African governments and organizations operating in Africa to enhance the capacity of rice farmers and extension officers in adopting approaches and practices that reduce the accumulation of these carcinogenic metals in rice. This is essential to achieve the sustainable development goal of providing safe food for all.

Cadmium pollution leads to selectivity loss of glutamate receptor channels for permeation of Ca2+/Mn2+/Fe2+/Zn2+ over Cd2+ in rice plant

The selective permeation of glutamate receptor channels (GLRs) for essential and toxic elements in plant cells is poorly understood. The present study found that the ratios between cadmium (Cd) and 7 essential elements (i.e., K, Mg, Ca, Mn, Fe, Zn and Cu) in grains and vegetative organs increased significantly with the increase of soil Cd levels. Accumulation of Cd resulted in the significant increase of Ca, Mn, Fe and Zn content and the expression levels of Ca channel genes (OsCNGC1,2 and OsOSCA1.1,2.4), while remarkable reduction of glutamate content and expression levels of GLR3.1-3.4 in rice. When planted in the same Cd-polluted soil, mutant fc8 displayed significantly higher content of Ca, Fe, Zn and expression levels of GLR3.1-3.4 than its wild type NPB. On the contrary, the ratios between Cd and essential elements in fc8 were significantly lower than that in NPB. These results indicate that Cd pollution may damage the structural integrity of GLRs by inhibiting glutamate synthesis and expression levels of GLR3.1-3.4, which leads to the increase of ion influx but the decrease of preferential selectivity for Ca²⁺/ Mn²⁺/ Fe²⁺/ Zn²⁺ over Cd²⁺ through GLRs in rice cells.

Characteristics of cadmium accumulation and tolerance in apple plants grown in different soils

Cadmium (Cd) is a nonessential element and highly toxic to apple tree. However, Cd accumulation, translocation and tolerance in apple trees planted in different soils remain unknown. To investigate soil Cd bioavailability, plant Cd accumulation, physiological changes as well as gene expression patterns in apple trees grown in five different soils, 'Hanfu' apple seedlings were planted in orchard soils collected from Maliangou village (ML), Desheng village (DS), Xishan village (XS), Kaoshantun village (KS) and Qianertaizi village (QT), and subjected to 500 μM CdCl₂ for 70 d. Results showed that soils of ML and XS had higher content of organic matter (OM), clay and silt, and cation exchange capacity (CEC) but lower sand content than the other soils, thereby reduced Cd bioavailability, which could be reflected by lower concentrations and proportions of acid-soluble Cd but higher concentrations and proportions of reducible and oxidizable Cd. The plants grown in soils of ML and XS had relatively lower Cd accumulation levels and bio-concentration factors than those grown in the other soils. Excess Cd reduced plant biomass, root architecture, and chlorophyll content in all plants but to relatively lesser degree in those grown in soils of ML and XS. The plants grown in soils of ML, XS and QT had comparatively lower reactive oxygen species (ROS) content, less membrane lipid peroxidation, and higher antioxidant content and enzyme activity than those grown in soils of DS and KS. Transcript levels of genes regulating Cd uptake, transport and detoxification such as HA11, VHA4, ZIP6, IRT1, NAS1, MT2, MHX, MTP1, ABCC1, HMA4 and PCR2 displayed significant differences in roots of plants grown in different soils. These results indicate that soil types affect Cd accumulation and tolerance in apple plants, and plants grown in soils with higher OM content, CEC, clay and silt content and lower sand content suffer less Cd toxicity.

Human health risks associated with metals in paddy plant (Oryza sativa) based on target hazard quotient and target cancer risk

Paddy plants (Oryza sativa) contaminated with metals could be detrimental to human health if the concentrations of metals exceed the permissible limit. Thus, this study aims to assess the risk of the concentrations of As, Se, Cu, Cr, Co, and Ni and their distributions in various parts (roots, stems, leaves, and grains) of paddy plants collected from Sekinchan, Malaysia. Both soil and plant samples were digested according to the United States Environmental Protection Agency (USEPA) Method 3050B and the metal concentrations were determined by the Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). The highest mean translocation factor (TF) was from soil to roots (TF roots/soil ranged from 0.12 to 6.15) and the lowest was from leaves to grain (TF grain/leaves ranged from 0.06 to 0.87). Meanwhile, the bioaccumulation factor (BAF) for all metals was less than 1.0 indicating that paddy plants only absorb metals from the soil but do not accumulate in the grains. The average daily intake for As (1.15 ± 0.25 µg/kg/day) has exceeded the limit proposed by ATSDR and IRIS USEPA (0.30 µg/kg/day). Target cancer risk (TR) of 1.10 × 10^-3 for As through rice consumption indicates that the potential cancer risk exists in one out of 1000 exposed individuals. The results from this study could serve as a reference for researchers and policymakers to monitor and formulate strategies in managing As and other metals in paddy plants, especially in Southeast Asian countries.

Prediction heavy metals accumulation risk in rice using machine learning and mapping pollution risk

Rapid and accurate prediction of metal bioaccumulation in crops are important for assessing metal environmental risks. We aimed to incorporate machine learning modeling methods to predict heavy metal contents in rice crops and identify influencing factors. We conducted a field study in Jiangsu province, China, collecting 2123 pairs of soil-rice samples in a uniform measurement and using 10 machine learning algorithms to predict the uptake of Cd, Hg, As, and Pb in rice grain. The Extremely Randomized Tree model exhibited the best performance for rice-Cd and rice-Hg (Cd: R² = 0.824; Hg: R² = 0.626), while the Random Forest model performed best for As and Pb (As: R² = 0.389; Pb: R² = 0.325). The feature importance analysis showed that soil-Cd and pH had the highest impact on rice-Cd risk, which is in line with previous studies; while temperature and soil organic carbon were more important to rice-Hg than soil-Hg. Then, based on another set of 1867 uniformly distributed paddy soil samples in Jiangsu province, the Cd and Hg risks of soil and rice were visualized using the established models. Mapping result revealed an inconsistent pattern of hotspot distribution between soil-Hg and rice-Hg, i.e., a higher rice-Hg risk in the northern area, while higher soil-Hg in south. Our findings highlight the importance of temperature on Hg bioaccumulation risk to crops, which has often been overlooked in previous risk assessment processes.

Fate of selenium in a Se-enriched region of North China: Translocation, bioaccumulation, source, and health benefits

There are limited studies on the translocation and bioaccumulation of selenium (Se) in weak alkaline cultivated Se-enriched soil, and the sources and speciation of Se in wheat grains remain unclear. In this study, we measured the Se levels in soils, roots, stems, and wheat grains from Se-enriched cultivated land in Ci County, China, which has a high incidence of esophageal cancer. The Se levels in the roots were higher than those in the soils, indicating that wheat plants bioaccumulated high concentrations of Se from the soil (enrichment coefficient [EC] range from the soil to the root: 0.94-3.29). Redundancy analysis indicated that the bioaccumulated factor, translocation coefficient, and EC were mainly controlled by phosphorus, pH, and Fe₂O₃ (contribution rates: 37.5%, 19.5%, and 15.9%, respectively). Linear regression analysis revealed that the sources of Se in grains were mainly from the water-soluble fraction (R² = 0.55, at p < 0.05), the weakly acidic fraction (R² = 0.84, at p < 0.05), the reducible fraction (R² = 0.84, at p < 0.05), and the oxidizable fraction (R² = 0.70, at p < 0.05), as well as from atmospheric deposition (R² = 0.37, at p < 0.01). There is a significant correlation between the Se from atmospheric deposition and the oxidizable fraction (R² = 0.62, at p < 0.01) and the residual fraction (R² = 0.33, at p < 0.01). The contribution of Se input flux from atmospheric deposition was 5.50 g/hm² for one year. Furthermore, the average content of organic Se in wheat grains was 58.93%. The Se concentrations found in wheat grains were considered beneficial for human health based on a comparison with the Chinese Society of Nutrition standard and worldwide levels. The results of this study will increase the overall knowledge on the theme, which could help prevent and control the harmful effects of undesirable concentrations of Se on human health.

Distribution and accumulation of cadmium in soil under wheat-cultivation system and human health risk assessment in coal mining area of China

The soil contamination caused by the discharge of cadmium (Cd) from coal mining activities has aroused continuous attention due to the detrimental effects on the human health. This study aimed to investigate the characteristics on distribution of Cd in soils and its accumulation in wheat grains under wheat-cultivation system, and further assess the human health risks to adults and children. 58 soils and wheat samples in pairs from Linhuan coal mining area, Anhui Province were collected and analyzed. Results showed that the concentrations of Cd in 17.24% of soil samples exceeded the limit value established by the Ministry of Ecology and Environment. The ordinary kriging interpolation displayed that the spatial variability of Cd concentrations in soils was mainly influenced by coal mining activities. The transfer capacity of Cd from soils to wheat roots was greater than that from the wheat roots to grains. Multiple linear regression model clarified that soil pH and exchangeable Cd fraction in soils were the critical factors affecting the Cd accumulation in wheat grains. The carcinogenic risk of Cd levels in our studied wheat grains was a concern but still within the acceptable range, while their non-carcinogenic hazard was negligible for adults and children. The calculation results were in accord with the uncertainty analysis conclusion based on Monte Carlo simulation. The study was expected to promote the source management and control strategy of reducing tailing discharge, and providing scientific references for current soil remediation and land degradation prevention.

Concentrations and bioconcentration factors of leaf microelements in response to environmental gradients in drylands of China

Determining response patterns of plant leaf elements to environmental variables would be beneficial in understanding plant adaptive strategies and in predicting ecosystem biogeochemistry processes. Despite the vital role of microelements in life chemistry and ecosystem functioning, little is known about how plant microelement concentrations, especially their bioconcentration factors (BCFs, the ratio of plant to soil concentration of elements), respond to large-scale environmental gradients, such as aridity, soil properties and anthropogenic activities, in drylands. The aim of the present study was to fill this important gap. We determined leaf microelement BCFs by measuring the concentrations of Mn, Fe, Ni, Cu and Zn in soils from 33 sites and leaves of 111 plants from 67 species across the drylands of China. Leaf microelement concentrations were maintained within normal ranges to satisfy the basic requirements of plants, even in nutrient-poor soil. Aridity, soil organic carbon (SOC) and electrical conductivity (EC) had positive effects, while soil pH had a negative effect on leaf microelement concentrations. Except for Fe, aridity affected leaf microelement BCFs negatively and indirectly by increasing soil pH and SOC. Anthropogenic activities and soil clay contents had relatively weak impacts on both leaf microelement concentrations and BCFs. Moreover, leaf microelement concentrations and BCFs shifted with thresholds at 0.89 for aridity and 7.9 and 8.9 for soil pH. Woody plants were positive indicator species and herbaceous plants were mainly negative indicator species of leaf microelement concentrations and BCFs for aridity and soil pH. Our results suggest that increased aridity limits the absorption of microelements by plant leaves and enhances leaf microelement concentrations. The identification of indicator species for the response of plant microelements to aridity and key soil characteristics revealed that woody species in drylands were more tolerant to environmental changes than herbaceous species.

Source-specific risk assessment for cadmium in wheat and maize: Towards an enrichment model for China

Cadmium (Cd) pollution of agricultural soil is of public concern due to its high potential toxicity and mobility. This study aimed to reveal the risk of Cd accumulation in soil and wheat/maize systems, with a specific focus on the source-specific ecological risk, human health risk and Cd enrichment model. For this we investigated more than 6100 paired soil and grain samples with 216 datasets including soil Cd contents, soil pH and grain Cd contents of 85 sites from China. The results showed that mining activities, sewage irrigation, industrial activities and agricultural practices were the critical factors causing Cd accumulation in wheat and maize cultivated sites. Thereinto, mining activities contributed to a higher Cd accumulation risk in the southwest China and Middle Yellow River regions; sewage irrigation influenced the Cd accumulation in the North China Plain. In addition, the investigated sites were classified into different categories by comparing their soil and grain Cd contents with the Chinese soil screening values and food safety values, respectively. Cd enrichment models were developed to predict the Cd levels in wheat and maize grains. The results showed that the models exhibited a good performance for predicting the grain Cd contents among safe and warning sites of wheat (R² = 0.61 and 0.72, respectively); while the well-fitted model for maize was prone to the overestimated sites (R² = 0.77). This study will provide national viewpoints for the risk assessments and prediction of Cd accumulation in soil and wheat/maize systems.

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.

Health risk assessment of heavy metal exposure through vegetable consumption around a phosphorus chemical plant in the Kaiyang karst area, southwestern China

The phosphorus chemical industry is an important source of heavy metals in farmland. Vegetables grown on contaminated soil potentially impose adverse effects on human health. In this study, the pollution status and health risks of heavy metals in vegetables around a phosphorus chemical plant in Kaiyang County, Guizhou Province, southwestern China, were assessed, and the low-accumulation vegetables were screened by bioaccumulation factor (BAF) and cluster analysis. Results showed the average concentrations of Hg, As, Cd, Pb, Cr, Mn, Co, and Zn in vegetables were 0.015, 0.728 0.382, 0.227, 0.850, 27.227, 0.525, and 6.438 mg/kg, respectively. The single-factor pollution index showed that Cd was moderately polluted, and Cr, Hg, As, and Pb were slightly polluted. The Nemerow pollution index showed that the overall heavy metal pollution was classified as moderately polluted. The accumulation of heavy metals in different vegetables varied greatly, and chard, crown daisy, chayote, pumpkin, eggplant, white radish, sweet potato, carrot, and potato were selected as the low-accumulator vegetables. The consumption of all vegetables except chayote poses both carcinogenic and noncarcinogenic risks; among them, the consumption of sweet potato leaves has the highest health risks. The local population needs to adjust plantation structure and change dietary habits, and government should strengthen the management of phosphorus chemical plant pollution.

Impact of Vanadium-Containing Stone Coal Smelting on Trace Metals in an Agricultural Soil-Vegetable System: Accumulation, Transfer, and Health Risks

Dietary exposure to trace metals (TMs) through vegetable consumption has been identified as a potential risk to human health. Fifty-one paired agricultural soil and leaf vegetable samples were collected around V-containing stone coal smelting sites in Hunan Province, China, to study the contamination and transfer characteristics of TMs (Cd, Cr, Cu, Pb, V, and Zn) in the soil-vegetable system. The health risk to local residents through vegetable ingestion was evaluated using Monte Carlo simulations. The results showed that 96.2%, 23.1%, 53.8%, 30.8%, 96.2%, and 69.2% of the soil samples had Cd, Cr, Cu, Pb, V, and Zn contents exceeding their related maximum allowable values, respectively. Cadmium and V were the primary pollutants based on the I_geo values. Moreover, 46.9% and 48.4% of vegetable samples exceeded the maximum permissible levels for Cd and Pb, respectively. There was a negative correlation between the bioaccumulation factors for Cd and V of the vegetable and soil physicochemical properties, including pH, organic matter, and free Fe₂O₃ content. Ingestion of garland chrysanthemum and pak choi posed high health risks, and Cd, V, and Pb were the primary contributors. These findings will help design strategies to minimize contamination and human exposure to soil-vegetable systems caused by V-containing stone coal smelting.

Convolutional graph neural networks-based research on estimating heavy metal concentrations in a soil-rice system

Estimating heavy metal concentrations in soil-rice systems is of great significance to identify the factors controlling heavy metal transfer in soil-crop ecosystems. Recent research utilizes the advantage of convolutional calculations to extract and learn complicated information from 17 environmental covariates in rice and achieve promising results. However, as the complexity and interconnectivity in soil-crop ecosystem, just relying on convolutional calculations and a deep network structure is far from enough. The data processed by traditional deep learning technologies even with convolutional calculations are limited to Euclidean space; these architectures do not have the ability to extract information from the relationships in graph structures, which may contain rich information. Thus, in this paper, we try to integrate graph information into convolutional calculations for heavy metal prediction and propose a model named ConvGNN-HM. ConvGNN-HM combines the advantages of graph learning and convolutional calculations to predict heavy metal concentrations in a soil-rice system with analysis of 17 environmental factors. For comparison, we conduct an experiment to compare ConvGNN-HM with techniques with convolutional neural networks, multilayer perceptron, back-propagation neural networks, support vector machine, random forest, Bayesian ridge regression, and multiple linear regression. The experimental results illustrate that ConvGNN-HM got the best prediction values; the R² values of ConvGNN-HM for cadmium (Cd), plumbum (Pb), chromium (Cr), arsenic (As), and hydrargyrum (Hg) in rice were 0.84, 0.75, 0.79, 0.49, and 0.83, respectively, and the MAE values were also acceptable. We further conduct sensitivity analysis to demonstrate the stability and robustness of ConvGNN-HM. This study demonstrates the usefulness of combining graph learning and convolutional calculations in the prediction of heavy metal concentrations and provides a new perspective to build multidimensional and multi-scale complex ecosystem models.

The Status and Research Progress of Cadmium Pollution in Rice- (Oryza sativa L.) and Wheat- (Triticum aestivum L.) Cropping Systems in China: A Critical Review

The accumulation of cadmium in rice (Oryza sativa L.) and wheat (Triticum aestivum L.) is a serious threat to the safe use of farmland and to the health of the human diet that has attracted extensive attention from researchers. In this review, a bibliometric analysis was performed using a VOS viewer (1.6.18, Netherlands) to investigate the status of cadmium contamination in rice and wheat growing systems, human health risks, mechanisms of Cd uptake and transport, and the corresponding research hotspots. It has a certain reference value for the prevention and control of cadmium pollution in rice and wheat planting systems in China and abroad. The results showed that the Cd content in rice and wheat planting systems in the Yangtze River Basin was significantly higher than that in other areas of China, and the Cd content in rice and wheat grains and the hazard quotient (HQ) in Hunan Province was the highest. The average Cd concentration exceeded the recommended limit by about 62% for rice and 81% for wheat. The main reasons for the high Cd pollution in rice and wheat growing areas in Hunan are mining activities, phosphate fertilizer application, sewage irrigation, and electronic equipment manufacturing. In this review, we demonstrate that cadmium toxicity reduces the uptake and transport of essential elements in rice and wheat. Cadmium stress seriously affected the growth and morphology of plant roots. In the shoots, Cd toxicity was manifested by a series of physiological injuries, such as decreased photosynthesis, soluble protein, sugar, and antioxidant enzyme activity. Cadmium that accumulates in the shoots is transferred to grains and then passes up the food chain to people and animals. Therefore, methods for reducing cadmium content in grains of rice and wheat are urgently needed, especially in Cd-contaminated soil. Current research on Cd pollution in rice and wheat planting systems focuses on the bioavailability of Cd, soil rhizosphere changes in wheat and rice, and the role of antioxidant enzyme systems in alleviating heavy metal stress in rice and wheat.

Hazardous toxic metal(loid)s in top- and deep-soils during the transformation of aquaculture ponds restored to farmland

The pollution risks due to the soil migration of toxic metal(loid)s (TMs) are a greatly hazard to ecological environment as well as animal and human health. Previous studies have primarily focused on surface contamination while deep soil layers often contain dangerous levels of TMs. We used restored wheat and rice farmlands from aquaculture ponds as a case study to examine the ecological risk and distribution of TMs in soil profiles. The elements Cu, Zn, Cr, Cd, Hg and As were markedly enriched in the 60-180 cm soil layers of restored farmland, and their concentrations decreased in the several depths as follows: 120-180 cm > 60-120 cm > 0-60 cm. Concentrations of TMs were 9.5-128 % greater in the restored farmlands relative to farmlands not exposed to aquaculture practices. Cadmium and mercury were the most serious contaminants and increased the overall ecological risk. The subsoil of wheat farming system had the highest pollution risk versus the restored rice farmland at 60-120 cm due to elevated levels of Cu, Zn and Pb. Toxic metal(loid)s might be derived from natural sources in deep soil of conventional farmland whereas aquaculture practices were found to constitute the major contribution in the subsoil of restored farmland. Our results indicated that the TMs that were buried in deep soil layers migrated upward and were a significant pollution risk. Urgent actions should be taken to identify and alleviate the contamination sources of these deep soils in addition to the conventional leaching and migration processes of surface contaminants.

Potential Risk, Spatial Distribution, and Soil Identification of Potentially Toxic Elements in Lycium barbarum L. (Wolfberry) Fruits and Soil System in Ningxia, China

Eight potentially toxic elements (PTEs, including nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), lead (Pb), chromium (Cr), and mercury (Hg)) in Lycium barbarum L. (wolfberries) and the associated root soil from a genuine producing area were analyzed. The potential ecological risk of PTEs in the soil and the health risk of PTEs through wolfberry consumption were determined. Geostatistical methods were used to predict the PTE concentrations in the wolfberries and soil. Positive matrix factorization (PMF) was applied to identify the source of PTEs in the soil. The PTE concentrations in the soils were within the standard limits, and Cd in the wolfberries exceeded the standard limit at only one site. The bioconcentration factors (BCF) order for the different PTEs was Cd > Cu > 1 > Zn > Cr > As > Ni > Pb, indicating that Cd and Cu were highly accumulated in wolfberries. The multiple regression models for Ni, Cu, Zn, As, Pb, and Cr concentrations in the wolfberries exhibited good correlations (p < 0.1). The ecological risk for Hg in the soil was high, whereas the risks for the remaining PTEs were mostly medium or low. Health risks for inhabitants through wolfberry consumption were not obvious. The spatial distributions of the PTEs in the soil differed from the PTE concentrations in the wolfberries. Source identification results were in the order of natural source (48.2%) > industrial activity source (27.8%) > agricultural activity source (14.5%) > transportation source (9.5%). The present study can guide the site selection of wolfberry cultivation and ensure the safety of wolfberry products when considering PTE contamination.

Accumulation and risk assessment of heavy metals in rice: a case study for five areas of Guizhou Province, China

In the present study, the concentration and accumulation abilities of five heavy metals (Cd, Hg, As, Pb, Cr) in rice were assessed and their human health risk to local citizens had been evaluated. Soil and rice samples (125 samples) were collected from Guiyang (GY), Qiannan (QN), Bijie (BJ), Tongren (TR), and Zunyi (ZY) in Guizhou Province. Heavy metals were measured by inductively coupled plasma-mass spectrometry (ICP-MS) after microwave digestion. The mean concentrations of Cd, Hg, As, Pb, and Cr were 0.58, 0.65, 12.31, 38.70, and 87.30 mg/kg in soil and were 0.05, 0.005, 0.11, 0.07, and 0.34 mg/kg in rice, respectively. The bioconcentration factors (BCF) decreased with the order Cd > Hg > As > Cr > Pb. Non-carcinogenic risk in this study was evaluated using the method of the hazard quotient (HQ) and hazard index (HI). The mean HQ values for Cd, Hg, Pb, and Cr were all lower than the standard limit (1.0) for children and adults, except As with the mean HQ for children of 2.79. The mean HI values for children and adults were 4.22 and 1.42, which exceeded 1.0. The mean carcinogenic risk (CR) values of As and Pb for children and adults were higher than the upper limit of the acceptable range (1 × 10^-4) established by the United States Environmental Protection Agency (USEPA). In a conclusion, the non-carcinogenic and carcinogenic risks induced by heavy metals for children were higher than that for adults. This study revealed that consumption of rice in study areas may pose potential non-carcinogenic and carcinogenic risks to humans, and As was the largest contributor.

Pollution Characteristics and Health Risk Assessment of Heavy Metals in Agricultural Soils over the Past Five Years in Zhejiang, Southeast China

Heavy metal contamination in agricultural soils has attracted increasing attention in recent years. In this study, 1999 agricultural soil samples were collected from 11 cities in Zhejiang Province from 2016 to 2020, and the spatial and temporal variation characteristics of 3 of the most important heavy metals, i.e., lead (Pb), cadmium (Cd), and chromium (Cr) were analyzed. The results showed that Cd had a slightly higher sample over-standard rate of 12.06%. Spatial distribution and temporal trends showed that the Pb concentrations overall increased from 2016 to 2020 and mainly accumulated in southern Zhejiang. In addition, multiple exposure routes were evaluated for human health risks. Children are more susceptible to the adverse effects of heavy metals in agricultural soils, and oral ingestion was the major exposure route. Cr poses higher human health risks to humans than Pb and Cd in agricultural soils. Therefore, more rigid environmental monitoring and related soil remediation counter-measures for some sites with high concentrations of heavy metals are necessary to limit the potential threat to human health.

Exploring the Risk Thresholds of Soil Heavy Metals in Carbonate and Non-carbonate Rock Areas: The Case of Qianjiang District in Chongqing, China

To determine whether the national soil heavy metal standards (GB 15618-2018) are applicable to some carbonate and non-carbonate zones in Southwest China, rice and rhizosphere soil samples were collected in Chongqing and analyzed for heavy metal contents, pH, and other chemical parameters. In addition, regression analysis was also used to predict the risk threshold of soil heavy metals. The Cd risk screening value in GB 15618-2018 was strict for alkaline soils (pH > 7.5) as compared to those revealed in carbonate and non-carbonate areas, while the calculated pollution threshold for Cd in acidic soils (pH ≤ 5.5) in the non-carbonate area was lower than that in GB 15618-2018. Therefore, to improve the applicability of the evaluation results, a soil-crop system evaluation is recommended.

Driving effects and transfer prediction of heavy metal(loid)s in contaminated courtyard gardens using redundancy analysis and multilayer perceptron

The distribution and migration of heavy metal(loid)s in the soil-vegetable systems of courtyard gardens near mining areas have rarely been investigated, leading to potential food safety risks for residents. Moreover, the existing research is mainly focused on the total content of heavy metal(loid)s (tMetals) rather than the bioavailable contents (aMetals). In this study, 26 and 28 pairs of soil and vegetable samples were collected from the courtyard gardens near the Realgar mine in Baiyun Town and the lead-zinc (Pb-Zn) mine in Shuikoushan Town, respectively. The tMetal and aMetal of cadmium (Cd), mercury (Hg), arsenic (As), Pb, chromium (Cr), nickel (Ni), copper (Cu), Zn, manganese (Mn), iron (Fe), and calcium (Ca) in the samples were analyzed in this study. The results showed that courtyard gardens were polluted by various heavy metal(loid)s at varying degrees. The bioavailabilities of different metals varied significantly, among which Cd has the highest bioavailability (> 30%). In the transfer process of heavy metal(loid)s, the transfer rate (Tf) was ranked as soil-roots (1.50) > stems-leaves (1.07) > roots-stems (0.46) > stems-fruits (0.33). Redundancy analysis was used to evaluate the driving effects, and the results revealed that aCa, aZn, and aFe in soil could inhibit the absorption of aCd by plant roots. Soil organic matter was the inhibiting factor regarding the transfer of aAs and aCu, whereas it was also the promoting factor for transferring aPb, aNi, and aCr. Furthermore, the multilayer perceptron (MLP) could effectively predict the Tf of heavy metal(loid)s based on the aMetal. The R² values of the MLP were ranked as follows: 0.91 for As, 0.88 for Zn, 0.85 for Hg, 0.83 for Cu, 0.79 for Cr, 0.66 for Cd, 0.65 for Pb, and 0.52 for Ni. This study emphasizes the aMetal-based ecological characteristics and prediction ability. The study results are significant for guiding residents to strategize appropriate crop planting and ensure the safe production and consumption of vegetables.

Heavy metal ecological-health risk assessment under wheat-maize rotation system in a high geological background area in eastern China

A high geological background can increase the ecological and health risks associated with crop production; therefore, it is essential to assess the heavy metals and their impact. In this study, ecological and health risk impacts of heavy metal contamination, in combination with positive matrix factorization was assessed for an area with high geological background with wheat-maize cropping system, to provide a quantitative understanding of the effects of heavy metals, enabling its prevention and control. This study revealed that the comprehensive ecological risk (RI_wheat-maize) is 56.21 (low), with industries being the biggest contributors (34.22%). Comprehensive health risk (non-carcinogenic) assessment showed that industrial (40.98-49.30%) and natural (23.96-37.64%) factors were the primary (particularly of Cd and Zn) and secondary (particularly of Cr and Ni) contributors, respectively in eastern China. Comprehensive health risk (HI_wheat-maize) for children and adults were 0.74 and 0.42, respectively, indicating that non-carcinogenic risks were at an acceptable level. Soil ingestion was the primary pathway for health risks (62.23-73.00%), especially for children. Based on soil heavy metal sources and crop systems, source-ecological risk assessment and source-health risk assessment were used to provided valuable insights on making strategies to protect human health in high geological background areas.

Leaching experiments and risk assessment to explore the migration and risk of potentially toxic elements in soil from black shale

Black shale is rich in potentially toxic elements (PTEs) that migrate through rock weathering or rainfall, adversely affecting human health and the environment. In this study, simulated rainfall leaching experiments were used to investigate the migration patterns and leaching kinetics of PTEs in black shale from the Lower Cambrian Hetang Formation and to analyze the water quality index (WQI) of PTEs in the leachate. A comparison between the risk of PTEs in the leachate and those in the soil was also made to determine the risk sources, risk status, and distribution characteristics of PTEs in the study area. The WQI of the indoor column experimental leachate indicated the highest As contamination. The geo-accumulation index (I_geo) and potential ecological risk (Er) of soils in the entire region revealed that the risk of Cd was the highest. Furthermore, by mapping the distribution of I_geo and Er in soils, the risk level in the region where black shale is located was found to be significantly higher than that in other areas. Comparing the leaching rate of PTEs with the WQI from leaching experiments, the risk associated with As in soil can be inferred to originate mainly from the leaching of black shale. Previous studies on PTEs in black shale in the study area tended to focus on Cd; however, this study found that the risk of As was not negligible. The health risk assessment also showed that the risk at the location of black shale was beyond the accepted range. Overall, this study provided a new and important evaluation law for the level of pollution by PTEs and health risks in typical black shale regions.

Comparison of Pb and Cd in wheat grains under air-soil-wheat system near lead-zinc smelters and total suspended particulate introduced modeling attempt

The excessive accumulation of wheat grain metals and metalloids caused by ambient air contamination has drawn an increasing concern. However, at present, the differences in the pathways of cadmium and lead accumulation in wheat grains in an air-soil-wheat system are not clear. In this study, wheat was grown around a lead‑zinc smelting area and exposed to different soil Pb and Cd levels and different ambient air Pb and Cd levels. Lead and Cd accumulation in wheat grains was examined in this study. Two models of wheat grain Pb and Cd concentrations were established based on the 3 variables including soil Pb and Cd concentration, ambient air Pb and Cd concentration, and soil pH. The results showed that total suspended particulate (TSP), soil, and wheat grains exhibited different degrees of Pb and Cd contamination in the study area, and the contamination of Cd is more serious than Pb contamination. The Pb in wheat grains was more likely to derive from ambient air than from soil, whereas the impact of ambient air on the accumulation of Cd in wheat grains might be very limited. This speculation was confirmed by the results of the predictor variable relative weight method based on the multiple regression analysis. Introduction of ambient air factor (TSP Pb and Cd) greatly improved the modeling effect of wheat grains Pb, while the modeling of grain Cd was more dependent on soil pH and total soil Cd. This research suggests that the reduction in wheat grain Pb is likely to be achieved by the control over ambient air Pb, whereas the reduction in the wheat grain Cd by the remediation of soil pollutants.

Bioaccumulation characteristics, transfer model of heavy metals in soil-crop system and health assessment in plateau region, China

This study investigated the bioaccumulation and transfer of heavy metals including Cd, Cr, Cu, Mn, Ni, Pb and Zn in soil-crop system in Lhasa, and assessed the health risks of the edible part of the crops. The results showed that the average values of Cd, Cr, Cu, Mn, Ni, Pb and Zn were 0.15, 44.55, 24.68, 532.40, 22.47, 38.18 and 73.99 mg kg^-1 in natural soil, and 0.16, 46.93, 38.45, 559.13, 23.23, 40.03 and 83.29 mg kg^-1 in cultivated soil, respectively. Highland barley and wheat had the strongest ability to accumulate Zn in grain, the BCF values were 0.24 and 0.27, respectively, significant differences in the distribution of metal contents in crop root, stem, leaf and grain were observed. Root presented larger accumulation capacity in most metals, Zn and Cu was easily transferred in the plant organs, most metals in this study presented difficult to migrate from root to grain. The transfer peak of most metals in soil-crop system appeared from stem to leaf. The concentrations of Cr and Mn in crop grains could be predicted according to the multiple linear regression models. THQ and HI values of heavy metals in edible parts of both highland barley and wheat were below the safety threshold of 1, indicating no detrimental effects posed to adults health. This study helps to understand the accumulation and transfer of heavy metals in soil-crop system in plateau region.

A field study to estimate heavy metal concentrations in a soil-rice system: Application of graph neural networks

Accurate prediction of the concentration of heavy metals is of great significance for assessing the quality of agricultural products and reducing health risks. However, the complexity and interconnectivity of the farmland ecosystem restricts the improvement of the prediction accuracy of traditional methods. This research explored the application potential of graph neural network (GNN) technology, which can extract and learn information in large-scale networks in detail, in the field of heavy metal prediction for the first time. In this study, a heavy metal prediction model for rice, CoNet-GNN, was proposed with 17 environmental factors as input variables using the co-occurrence network and GNN. Experimental results using a dataset from a field study showed that the R² of CoNet-GNN for predicting Cd, Pb, Cr, As, and Hg had outstanding values of 0.872, 0.711, 0.683, 0.489, and 0.824, respectively. Sensitivity analysis further indicated that CoNet-GNN had good stability and robustness. Compared with random forest, gradient boosting, and multilayer perceptron, CoNet-GNN made a remarkable improvement to the prediction accuracy of all studied heavy metals. Therefore, CoNet-GNN can effectively simulate the rich relationships and laws between various factors in the soil-rice system and effectively characterize the influence diffusion path. Furthermore, it provides new ideas for heavy metal prediction based on network research methods and expands the technical scope of heavy metal evaluation.

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.

Convolutional neural network-based applied research on the enrichment of heavy metals in the soil-rice system in China

The enrichment of heavy metals in the soil-rice system is affected by various factors, which hampers the prediction of heavy metal concentrations. In this research, a prediction model (CNN-HM) of heavy metal concentrations in rice was constructed based on convolutional neural network (CNN) technology and 17 environmental factors. For comparison, other machine learning models, such as multiple linear regression, Bayesian ridge regression, support vector machine, and backpropagation neural networks, were applied. Furthermore, the LH-OAT method was used to evaluate the sensitivity of CNN-HM to each environmental factor. The results showed that the R² values of CNN-HM for Cd, Pb, Cr, As, and Hg were 0.818, 0.709, 0.688, 0.462, and 0.816, respectively, and both the MAE and RMAE values were acceptable. The sensitivity analysis showed that the concentrations of Cd and Pb, mechanical composition, soil pH, and altitude were the main sensitive features for CNN-HM. Compared with CNN-HM based on all input features, the performance of the quick prediction model that was based on the sensitive features did not degrade significantly, thereby indicating that CNN-HM has stronger stability and robustness. The quick prediction model has extensive application value for timely prediction of the enrichment of heavy metals in emergencies. This study demonstrated the effectiveness and practicability of CNNs in predicting heavy metal enrichment in the soil-rice system and provided a new perspective and solution for heavy metal prediction.

Use of artificial neural network to evaluate cadmium contamination in farmland soils in a karst area with naturally high background values

In recent years, the naturally high background value region of Cd derived from the weathering of carbonate has received wide attention. Due to the significant difference in soil Cd content and bioavailability among different parent materials, the previous land classification scheme based on total soil Cd content as the classification standard, has certain shortcomings. This study aims to explore the factors influencing soil Cd bioavailability in typical karst areas of Guilin and to suggest a scientific and effective farmland use management plan based on the prediction model. A total of 9393 and 8883 topsoil samples were collected from karst and non-karst areas, respectively. Meanwhile, 149 and 145 rice samples were collected together with rhizosphere soil in karst and non-karst areas, respectively. The results showed that the higher CaO level in the karst area was a key factor leading to elevated soil pH value. Although Cd was highly enriched in karst soils, the higher pH value and adsorption of Mn oxidation inhibited Cd mobility in soils. Conversely, the Cd content in non-karst soils was lower, whereas the Cd level in rice grains was higher. To select the optimal prediction model based on the correlation between Cd bioaccumulation factors and geochemical parameters of soil, artificial neural network (ANN) and linear regression prediction models were established in this study. The ANN prediction model was more accurate than the traditional linear regression model according to the evaluation parameters of the test set. Furthermore, a new land classification scheme based on an ANN prediction model and soil Cd concentration is proposed in this study, making full use of the spatial resources of farmland to ensure safe rice consumption.

Thermochemical conversion of heavy metal contaminated biomass: Fate of the metals and their impact on products

With the rapid depletion of fossil energy and increasingly severe environmental pollution, the development of biomass resources for biorefineries has become a new research focus. However, heavy metals may be released during the thermochemical treatment when the biomass materials used in biomass conversion are contaminated by heavy metals. This can cause secondary environmental pollution or transference to the target products, reducing product quality. Therefore, having a systematic understanding of the fate of heavy metals in biomass conversion is necessary for alleviating potential risks. This study presents the current status of contaminated biomass and conversion products involving thermochemical processes, the migration, transformation, and impact of heavy metals in biomass conversion was investigated, and the utilization of heavy metals in contaminated biomass was briefly outlined. This review aims to link biomass conversion to the fate of heavy metals, avoid existing risks as much as possible to produce cleaner products efficiently, and promote the sustainable development of heavy metal contaminated biomass resources.

Incorporating in vitro bioaccessibility into human health risk assessment of heavy metals and metalloid (As) in soil and pak choi (Brassica chinensis L.) from greenhouse vegetable production fields in a megacity in Northwest China

The rapid development of greenhouse vegetable production (GVP) in densely populated areas may cause the heavy metal/metalloid accumulation in soil and pose a threat to human health. In this study, 180 pairs of topsoil and pak choi (Brassica chinensis L.) samples were collected from GVP fields in Xi'an city in Northwest China to analyze health risks of Cd, Cr, Pb, and As in soil and pak choi combining in vitro bioaccessibility investigation. The results showed that Cd and Cr were common pollutants in both soil and pak choi. In the soil-pak choi system, the indexes of non-carcinogenic and carcinogenic risk for adults and children were 1.53, 2.68, and 1.37 × 10^-4, 8.14 × 10^-5, respectively, thereby indicating the presence of heavy metal/metalloid health risks for both groups. Based on the results, procedures to mitigate heavy metal/metalloid contamination risks should be discussed more during the development of GVP in the largest city in Northwest China.

Urbanization influences the distribution, enrichment, and ecological health risk of heavy metals in croplands

The contamination of urban soils with heavy elements due to the rapid development of urbanization and urban services has become a major environmental and human health challenge. This study provides insight into the urbanization controls on combined pollution severity and health risk potential of heavy metals in corn-cultivated urban versus non-urban soils. A multifaceted assessment was conducted using enrichment factor (EF), ecological risk (ER), bioconcentration factor (BCF), transmission factor (TF), hazard index (HI), and carcinogenic risk (CR). The results indicate a significant increase in the concentration of all metals in urban farmlands. When compared to the non-urban soils, EF implies a significant increase of all metals in the urban soil, downgrading this index from minimal enrichment (EF < 2) in the control soils to moderate enrichment (2 ≤ EF < 5) in the urban soils. Likewise, the average ER value showed an increase in the urban soils than in the control soils in the order of Fluvisols (66.6%) > Regosols (66.1%) > Cambisols (59.8%) > Calcisols (47%). The BCF and TF values for different elements decreased in the order of Cd (0.41-0.92) > Cu (0.1-0.23) > Zn (0.1-0.18) > Ni (0.01-0.03) > Pb (0.005-0.011) and Zn (0.75-0.94) > Cu (0.72-0.85) > Pb (0.09-0.63) > Cd (0.17-0.22) > Ni (0.01-0.21), respectively, which indicates that certain metals were not mobilized to the extent that they had been accumulated in the plant roots. The total carcinogenic risk was ranged from 5.88E-05 to 1.17E-04 for children and from 1.17E-04 to 2.30E-04 for adults, which implies a greater associated health risk for children.

Derivation of human health risk-based thresholds for lead in soils promote the production of safer wheat and rice

A reliable and accurate soil threshold helps prevent excessive dietary Pb intake risks to consumers of locally grown wheat and rice crops. Based on a three-year investigation of 206 wheat fields and 358 rice fields throughout China, this study aimed to improve the soil protection guidelines by investigating Pb accumulation in soil-wheat and soil-rice systems and by assessing Pb exposure risks through the soil-grain-human pathway. A site-specific bioconcentration factor (BCF, ratio of Pb concentration in plant to that in soil) was calculated and used to assess grain Pb intake risks instead of a generic BCF value to reduce data uncertainty. In addition to soil pH, cation-exchange capacity exerted a major influence on the Pb BCF variations in wheat, whereas the organic carbon dynamics affected the BCF variations in rice. Once normalized BCF against those soil variables, the distributions of BCF were log-normal in nature. Optimizing the pH and cation-exchange capacity of wheat soils would help protect 49.8% of local adults from excessive Pb dietary intake. The scenario soil thresholds linked to soil variables and grain Pb intake risks were then derived and validated by independent data from field surveys and published articles. Poor production practices in the wheat fields under study included using soils with low fertility.

Heavy metals exposure is associated with early liver dysfunction among rural residents aged 40-75 years in southwest China

Heavy metals exposure has been associated with liver dysfunction in recent reports, while the hepatoxicity of lead (Pb) and cadmium (Cd) has been well established. However, the combined effects of multi-metal in real-world scenario on liver dysfunction are still unclear. This cross-sectional study examined associations between 10 biomarkers of early liver injury and multiple heavy metals levels. The levels of heavy metals/metalloid (magnesium [Mg], calcium [Ca], iron [Fe], zinc [Zn], arsenic [As], Cd, copper [Cu], and Pb) were measured in blood and urinary sample collected from 725 participants in a Cd-polluted area and an unpolluted area in southwest China. The early liver dysfunction biomarkers included the liver enzymes (ALT, ALP, AST, and GGT), proteins (TP, ALB, and GLO), and bilirubin (TBIL, DBIL, and IBIL). Confounder-adjusted beta coefficients were determined using multiple linear regression model analysis for the group-classified and gender-classified samples. Our results showed that blood Fe, Cd, and Cu levels were found to be positively related to elevated ALT levels and blood Cu was positively associated with AST levels in the Cd-polluted area, while the highest blood Zn quartile in the polluted area and blood Mg quartile in the unpolluted area were associated with lower ALT levels. Our finding implies that industrial pollution results in heavy metals of Cd and Pb exposure and effects of Fe, Cd, Cu, and Pb in the Cd-polluted area may be the main contributors to increase the risk of liver dysfunction while Zn in the Cd-polluted area and Mg in the unpolluted area may be the protective factors.

Kosteletzkya pentacarpos: A Potential Halophyte Candidate for Phytoremediation in the Meta(loid)s Polluted Saline Soils

Kosteletzkya pentacarpos (L.) Ledebour is a perennial facultative halophyte species from the Malvacea family that grows in coastal areas with high amounts of salt. The tolerance of K. pentacarpos to the high concentration of salt (0.5–1.5% salinity range of coastal saline land) has been widely studied for decades. Nowadays, with the dramatic development of the economy and urbanization, in addition to the salt, the accumulation of mate(loid)s in coastal soil is increasing, which is threatening the survival of halophyte species as well as the balance of wetland ecosystems. Recently, the capacity of K. pentacarpos to cope with either single heavy metal stress or a combination of multiple meta(loid) toxicities was studied. Hence, this review focused on summarizing the physiological and biochemical behaviors of K. pentacarpos that has been simultaneously exposed to the combination of several meta(loid) toxicities. How the salt accumulated by K. pentacarpos impacts the response to meta(loid) stress was discussed. We conclude that as a potential candidate for phytoremediation, K. pentacarpos was able to cope with various environmental constrains such as multiple meta(loid) stresses due to its relative tolerance to meta(loid) toxicity.

Higher zero valent iron soil amendments dosages markedly inhibit accumulation of As in Faya and Kilombero cultivars compared to Cd

Impact of zero valent iron (Fe°) amendment on grain-yield (GY) and grain-As and Cd accumulation in rice (Oryza sativa L.) cultivars Kilombero and Faya were investigated. Rice plants were amended with Fe° dosages of 0, 3.1, 6.2, and 12.4 g Fe°/kg soil in pots in greenhouse experiments under continuous flooding water regime. GY in each treatment was determined at maturity, grain-As and Cd and arsenic species concentrations were determined using ICP-MS and HPLC tandem ICP-MS respectively. Mean GY in Faya (5.5 ± 1.0 g/plant) and Kilombero (4.2 ± 0.4 g/plant) amended with at least 6.2 g Fe°/kg soil were at least 57% and 22% respectively significantly higher (F = 11; p = 0.003) than that in controls (3.7 ± 0.6 and 3.4 ± 0.4 g/plant). For As bioaccumulation, mean grain-As concentration in Faya T2 (≤227 ± 32 μg/kg) and Kilombero (≤218 ± 25 μg/kg) amended with at least 6.2 g Fe°/kg soil in were at least 83% and 77% respectively significantly lower (F = 7; p = 0.004) than that in controls (973 ± 43 μg/kg and 1278 ± 208 μg/kg). Mean grain-Cd concentrations in Faya (10 ± 2 μg/kg) and Kilombero (13 ± 3 μg/kg) amended with corresponding Fe° dosages were at least 26% and 39% significantly lower (F = 4; p < 0.05) than that in controls (18 ± 3 and 23 ± 1 μg/kg). Results indicated that amending Kilombero with at least 6.2 g/kg Fe° effectively optimally regulated both grain-As and Cd accumulation to values lower than the European Commission's legislated maximum contaminant limits (MCL) of 200 μg/kg without negating grain yield benefits. Our results suggest that bioaccumulation of both As and Cd in rice grains may be completely circumvented by adopting cultivar-specific Fe° amendment dosage.

A risk-based approach for the safety analysis of eight trace elements in Chinese flowering cabbage (Brassica parachinensis L.) in China

BACKGROUND

Most countries set regulatory values for the total trace element (TE) concentrations in soil, although there is growing interest in using a risk-based approach to evaluate the bioavailable TE using dilute salt extractants or other soil parameters, including pH and organic carbon_. The present study compares the current regulatory system (based on total TEs and pH) and a risk-based approach using 0.01 mol L^-1 CaCl₂ to estimate the bioavailable fraction.

RESULTS

In total, 150 paired samples of Chinese flowering cabbages (Brassica parachinensis) and their growth soils were collected, and the total and extractable concentrations of chromium (Cr), cadmium (Cd), lead (Pb), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As) and mercury (Hg), as well as soil pH and organic matter content, were measured. No more than 3.33% of the edible parts exceeded Chinese food safety standards, even when growing in soils exceeding the current regulatory thresholds by over 50%. The total soil Cd (1.5 mg kg^-1 ), as well as the extractable concentrations of Cd (0.1 mg kg^-1 ), Ni (0.03 mg kg^-1 ) and Zn (0.1 mg kg^-1 ), are the key factors affecting the TE concentrations in B. parachinensis.

CONCLUSION

Our findings suggest that the current soil regulatory guidelines for safe production of B. parachinensis are overly strict and conservative. A risk-based approach based on the extractable TE concentrations would provide a better indication for plant uptake of soil TEs and avoid the waste of farmlands that can still produce safe vegetables. Future research should focus on providing crop-specific available TE concentration guidelines to promote effective utilization of farmlands. © 2021 Society of Chemical Industry.

Application of cadmium prediction models for rice and maize in the safe utilization of farmland associated with tin mining in Hezhou, Guangxi, China

Cadmium (Cd) contamination in soil and crops caused by mining activities has become a prevalent concern in the world. Given that different crops have varying Cd bioaccumulation factors, crops with low Cd bioaccumulation abilities can be selected for the safe usage of Cd -contaminated lands. This study aimed to investigate Cd contamination in soil and crops and the influencing factors of soil Cd activity in a tin mining area (TMA) and control area (CA) and to put forward suggestions for the safe usage of farmlands by developing prediction models of Cd content in different crop grains. We collected 72 and 40 pairs of rice and maize grain samples, respectively, along with their rhizosphere soil samples and 6176 topsoil samples. The results showed that compared with the CA, the Cd pollution was more severe in the cultivated soil and crop grains around TMA. Furthermore, rice has a strong ability to transport Cd from soil to grains, whereas maize has a poor Cd uptake ability. The total organic carbon, CaO, pH, and Mn in soil play key roles in the transfer of Cd from soil to crop grains. Using these parameters and Cd concentration in soil, two sets of accurate Cd prediction models were developed for maize and rice. Based on the Cd concentration in the topsoil and predicted Cd concentration in crop grains, the safe utilization scheme of farmland was proposed. The proportions of priority protection, safe exploitation, planting adjustment, and strict control were 72.59%, 22.77%, 3.16%, and 1.48% in the TMA, respectively. The values reached 80.51% (priority protection), 19.12% (safe exploitation), 0.37% (planting adjustment), and 0% (strict control) in the CA. Thus, given the difference between Cd accumulation in rice and maize, adjustment of planting crops in contaminated farmlands can be applied to maximize the use of farmland resources.