A field study to predict Cd bioaccumulation in a soil-wheat system: Application of a geochemical model

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.

Source apportionment of soil PTE in a northern industrial county using PMF model: Partitioning strategies and uncertainty analysis

Positive matrix factorization (PMF) has commonly been applied for source apportionment of potentially toxic elements (PTE) in agricultural soil, however, spatial heterogeneity of PTE significantly undermines the accuracy and reliability of PMF results. In this study, a representative industrial-agricultural hub in North China (Xuanhua district, Zhangjiakou City) was selected as the research subject, multiple partition processing (PP) strategies and uncertainty analyses were integrated to advance the PMF modeling and associated algorithm mechanisms were comparatively discussed. Specifically, we adopted three methods to split the research area into several subzones according to industrial density (PP-1), population density (PP-2), and the ecological risk index (PP-3) respectively, to rectify the spatial bias phenomenon of PTE concentrations and to achieve a more interpretable result. Our results indicated that the obvious enrichment of Cd, Pb, and Zn was found in the agricultural soil, with Hg and Cd accounted for 83.49% of the overall potential ecological risk. Combining proper PP with PMF can significantly improve the modelling accuracy. Uncertainty analysis showed that interval ratios of tracer species (Cd, Pb, Hg, and Zn) calculated by PP-3 were consistently lower than that of PP-1 and PP-2, indicating that PP-3 coupled PMF can afford the optimal modeling results. It suggested that natural sources, fertilizers and pesticides, atmosphere deposition, mining, and smelting were recognized as the major contributor for the soil PTE contamination. The contribution of anthropogenic activities, specifically fertilizers and pesticides, and atmosphere deposition, increased by 1.64% and 5.91% compared to PMF results. These findings demonstrate that integration of proper partitioning processing into PMF can effectively improve the accuracy of the model even at the case of soil PTE contamination with high heterogeneity, offering support to subsequently implement directional control strategies.

Evaluating the protective capacity of soil heavy metals regulation limits on human health: A critical analysis concerning risk assessment - Importance of localization

Heavy metal pollution of agricultural soil is a major global concern, prompting the establishment of maximum allowable limits (MALs) to ensure food safety and protect human health. This study collected and compared MALs for six heavy metals (As, Cd, Hg, Pb, Zn, and Cu) in agricultural soils from representative countries and organizations (EU and WHO/FAO). The research evaluated the critical health risks and efficacy of these MALs under the hypothetical scenario of metals concentrations reaching the maximum allowable level. Safe thresholds for heavy metals were then derived based on maximum acceptable health risk levels. The comparative analysis revealed significant variations in the specific limit values and terms of MALs across countries and organizations, even for the same metal. This suggests that there is no consensus among countries and organizations regarding the level of metal-related health risks. Furthermore, the risk analysis of metal concentrations reaching the maximum level accentuated heightened risks associated with As, suggesting that the current risk of soil As exposure was underestimated, particularly for children. However, soil Cu, Cd, and Zn limits generally resulted in low health risks, implying that the current limits may overestimate their hazard. Overall, the results highlight that the current MALs for soil heavy metals may not fully safeguard human health. There is a critical need to optimize current soil MALs based on localized risks and the actual impact of these metals on human health. It is suggested to appropriately lower the limits of metals (such as As) whose impact on health risks is underestimated, and cautiously increase the limits of metals (such as Cu, Cd, and Zn) that currently pose minor health risks. This approach aims to reduce both over and insufficient protection problems of soil heavy metal MALs, emphasizing the importance of considering the locality in setting these limits.

Impact of meteorological factors on Cd availability and average concentration prediction in rice growth cycle

During the rice growth cycle, the average available cadmium concentration (CA-Cd) in the soil determines the Cd content in rice plant. Given defined soil properties and rice varieties, the meteorological factors play a crucial role in soil's available cadmium concentration (CCd) during the rice growth cycle. Thus, it is significant to investigate the influence of meteorological factors in CCd during the rice growth cycle and develop a predictive model for CA-Cd. The rice was cultivated under seven different sowing dates in Cd and As-contaminated soil in Hunan Province. Studied the impact of meteorological factors on paddy soil. The results showed that accumulated temperature (AT) and total precipitation (TP) were key factors affecting the soil CCd. The correlation coefficients between AT and TP with soil CA-Cd were 0.98 and -0.94 (p < 0.01), respectively. However, there was no significant correlation with CAs. AT mainly influenced the CCd during the grouting and maturity stages. A straightforward empirical prediction model was developed, capable of accurately forecasting CA-Cd during the rice growth cycle by considering meteorological factors and the initial soil CCd. This study supported a novel foundation for the precise prediction of Cd content in rice.

Quantifying the mitigating effect of organic matter on heavy metal availability in soils with different manure applications: A geochemical modelling study

Manure is one of the main sources of heavy metal (HM) pollution on farmlands. It has become the focus of global ecological research because of its potential threat to human health and the sustainability of food systems. Soil pH and organic matter are improved by manure and play pivotal roles in determining soil HM behavior. Geochemical modeling has been widely used to assess and predict the behavior of soil HMs; however, there remains a research gap in manure applications. In this study, a geochemical model (LeachXS) coupled with a pH-dependent leaching test with continuously simulations over a broad pH range was used to determine the effects and pollution risks of pig or cattle manure separate application on soil HMs distribution. Both pig and cattle manure applications led to soil pH reduction in alkaline soils and increased organic matter content. Pig manure application resulted in a potential 90.5-156.0 % increase in soil HM content. Cattle manure did not cause significant HM contamination. The leaching trend of soil HMs across treatments exhibited a V-shaped change, with the lowest concentration at pH = 7, gradually increasing toward strong acids and bases. The dissolved organic matter-bound HM content directly increased the HM availability, especially for Cu (up to 8.4 %) after pig manure application. However, more HMs (Cr, Cu, Zn, Ni) were in the particulate organic matter-bound state than in other solid phases (e.g., Fe-Al(hydr) oxides, clay minerals), which inhibited the HMs leaching by more than 19.3 % after cattle manure application. Despite these variations, high HM concentrations introduced by pig manure raised the soil contamination risk, potentially exceeding 40 times at pH ±1. When manure is returned to the field, reducing its HM content and mitigating possible pollution is necessary to realize the healthy and sustainable development of circular agriculture.

The C2H2 family protein ZAT17 engages in the cadmium stress response by interacting with PRL1 in Arabidopsis

Cadmium (Cd) is a heavy metal and a toxic substance. Soil Cd pollution has emerged as a significant environmental issue that jeopardizes both the safety of agricultural products and human health. PLEIOTROPIC REGULATORY LOCUS 1 (PRL1) has been identified as a crucial factor in Cd stress and a series of defence mechanisms. However, the mechanism through which PRL1 mediates its downstream signalling has remained poorly understood. Here, we discovered a prl1-2 suppressor (sup8) for prl1-2 that complemented the defective development phenotype of prl1-2 under Cd stress. Gene cloning revealed a mutation in the C2H2 transcription factor ZAT17 as the basis for the sup8 phenotype. Genetic and biochemical studies indicated that ZAT17 acts as a negative regulator of Cd tolerance. Transcriptome analysis revealed that ZAT17 influences the alternative splicing (AS) process of multiple Cd-responsive genes by interacting with members of the MAC splicing complex, including PRL1 and CDC5. In conclusion, the identification of the novel gene ZAT17 enriches the understanding of the Cd stress response pathway and provides a valuable candidate locus for breeding Cd-resistant plant varieties.

Ecological risk assessment of heavy metals in tea plantation soil around Tai Lake region in Suzhou, China

Tea plant [Camellia sinensis (L.) O. Kuntze] is one of the important foliar cash crops in China, and its root system absorbs heavy metal (HM) elements enriched in the soil and transports them to the over ground part. In order to ensure the safety of the soil ecological environment and tea raw materials in the tea production area, the HM contents of soil and tea plant leaves in Suzhou tea plantations were detected, the relationship between HMs and soil physicochemical properties was analyzed, and the ecological risk of HMs in tea plantation soils was evaluated by using relevant detection techniques and evaluation models. The results showed that the average pH of tea plantation soils around Tai Lake in Suzhou was within the range suitable for the growth of tea plants. The pH, soil organic matter, total nitrogen, available phosphorus and available potassium of tea plantation soil satisfying the requirements of high quality, high efficiency and high yield ('3H') tea plantation accounted for 47.06%, 26.47%, 8.82%, 79.41% and 67.65%, respectively. Site 2 fully met the requirements of '3H' tea plantation. In addition, the contents of cadmium (Cd) and mercury (Hg) were extremely variable, and the average contents exceeded the background value of soil in Jiangsu Province, but the HM contents of tea leaves all met the pollution-free standard, and the HM contents of tea leaves around Tai Lake in Suzhou were generally at a safe level. The composite ecological risk index ranged from 0.05 to 0.60, and 32 of the 34 sample sites (except site 21 and site 23) are the most suitable agricultural land for tea plantations.

Prediction of cadmium and zinc phytoextraction by the hyperaccumulator Sedum plumbizincicola using a dynamic geochemical mechanical combination model

Phytoextraction with hyperaccumulators is an environmentally friendly and cost-effective technique for soil remediation but remediation time is largely dependent on experience due to variations in soil properties which restrict the application of this technique. Here, a novel dynamic multi-surface model (MSM) framework is proposed to predict the efficiency and duration of cadmium (Cd) and zinc (Zn) phytoextraction using the hyperaccumulator Sedum plumbizincicola. First, the application of MSM to S. plumbizincicola was investigated using 95 naturally contaminated soils. Using the 'default' settings and considering the pH and DOC content in the rhizosphere, the dissolved Cd/Zn predicted by MSMs showed strong correlations with metal uptake by shoots (R2 = 0.825/0.802 for Cd/Zn, n = 95) and outperformed chemical extraction methods. Then the MSMs were further integrated with time and Cd and Zn interactions to form dynamic-MSM combined (D-MSM-C) models to evaluate and predict phytoextraction efficiency and duration based on a six-season continuous pot experiment. The D-MSM-C models well predicted metal contents remaining in soils after each season with mean absolute percentage error (MAPE) = 20.4 % (Cd) and 2.46 % (Zn) (n = 66). This model is a powerful tool for assessing and predicting phytoremediation efficiency and duration and is applicable across diverse soil properties and multiple metal-contamination scenarios.

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.

Predicting soil available cadmium by machine learning based on soil properties

Cadmium (Cd) accumulation in edible plant tissues poses a serious threat to human health through the food chain. Assessing the availability of soil Cd is crucial for evaluating associated environmental risks. However, existing experimental methods and traditional models are time-consuming and inefficient. In this study, we developed machine learning models to predict soil available Cd based on soil properties, using a dataset comprising 585 data points covering 585 soils. Traditional machine learning models exhibited prediction values beyond the theoretical range, urging the need for alternative approaches. To address this, different models were tested, and the post-constraint eXtreme Gradient Boosting (XGBoost) model was found to possess the best predictive performance (R2 =0.81) outperform traditional linear regression model in terms of accuracy. Furthermore, we explored the relationship between soil available Cd and wheat grain Cd and rice grain Cd. Linear regression models were developed using 302 data points for wheat and 563 data points for rice. Results demonstrated a significant correlation between soil available Cd and wheat grain Cd (R2 =0.487) as well as rice grain Cd (R2 =0.43).

Accumulation characteristics, driving factors, and model prediction of cadmium in soil-highland barley system on the Tibetan Plateau

Cadmium (Cd) poses major human health problems due to its high toxicity and organ bioaccumulation potential. This study collected and analysed 130 pairs of representative soil-highland barley samples on the Tibetan Plateau. The total soil Cd content (Cd-soil), available soil Cd (Cd-ava), and highland barley Cd contents (Cd-barley) ranged from 0.03 to 0.46 mg kg-1, 0.006-0.185 mg kg-1, and 0.57-13.62 μg kg-1, with mean values of 0.19 ± 0.01 mg kg-1, 0.045 ± 0.003 mg kg-1, and 4.57 ± 0.17 μg kg-1, respectively. Redundancy analysis (RDA) demonstrated that geographic factors and soil properties explained 28.46% of the variation in Cd-soil and Cd-ava, and precipitation (14.6%) and pH (9.1%) were the dominant factors. The structural equation model (SEM) indicated that Cd-soil and Cd-ava were predominantly controlled by pH. Furthermore, the Cd-soil, Cd-ava, and Cd-barley with significantly different environmental conditions were more accurately predicted by conditional inference trees-multiple linear regression (CITs-MLR). When Cd-soil is more than 0.376 mg kg-1, Cd-ava obtains the most accurate predictor (R2 =0.64, P < 0.01). This study provides new scientific insight into understanding the environmental biogeochemical nexus of Cd in the complex and fragile plateau environment and evaluating food security on the Tibetan Plateau under the self-sufficiency model of highland barley.

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.

Significant difference in the efficacies of silicon application regimes on cadmium species and environmental risks in rice rhizosphere

Silicon (Si) is commonly applied as base-fertilizer or foliar-topdressing to palliate the uptake-translocation-accumulation of cadmium (Cd) in rice through Si-Cd antagonism. However, little is known about the fate of Cd in rice rhizosphere soil and its eco-environmental effects under different Si treatments. Here, systematic works had been carried out to elucidate the Cd species, soil properties, and environmental risks in rice rhizosphere driven by different Si soil-fertilization regimes including CK (without Si-addition), TSi (added before transplanting stage), JSi (added at jointing stage), and TJSi (split into two equal parts, added half before transplanting and another half at jointing stage). Results showed that TJSi outperformed the rest of fertilization regimes. The solid-phase-Cd concentrations treated with TSi, TJSi and JSi were increased by 4.18%, 5.73% and 3.41%, respectively, when compared to CK. The labile Cd (F1+F2) proportion of TJSi was reduced by 16.30%, 9.30% and 6.78%, respectively, when compared to CK, TSi, and JSi. Simultaneously, the liquid-phase-Cd concentration was appreciably suppressed by TJSi throughout the rice lifecycle, while TSi mainly abated Cd dissociation during the vegetative period, and JSi attenuated it during the grain-filling stage. The mobility factor of Cd treated with TJSi was the lowest, which was significantly lower than that of TSi (9.30%) and JSi (6.78%), respectively. Similarly, the oral exposure risk of TJSi was reduced by 4.43% and 32.53%; and the food-chain exposure risk of TJSi was decreased by 13.03% and 42.78%. Additionally, TJSi was the most effective in promoting enzyme activities and nutrient content in rhizosphere soil. Overall, TJSi is more positive and sustainable than TSi and JSi in reconstructing Cd-contaminated rhizosphere environments and abating the environmental risks of Cd. Agronomic practices in Cd-contaminated paddy soils can be informed by applying Si-fertilizer separately before transplanting and at jointing stage to achieve soil welfare and food security.

Prediction of cadmium bioavailability in the rice-soil system on a county scale based on the multi-surface speciation model

Relative to total cadmium (Cd) content, bioavailable Cd in paddy soil is regarded as a more reasonable indicator for the risk of Cd bioaccumulation in rice. However, there is still a lack of approach to accurately predict the content of bioavailable Cd in paddy soil due to its heterogeneity and complexity. Here, multi-surface speciation model (MSM) was employed to predict the bioavailable Cd and Cd immobilization effect. Moreover, a precise remediation strategy was designed based on screening and scenario simulation of the sensitive factors with MSM. The results demonstrated that MSM can well predict Cd bioaccumulation risk in rice. The contribution of pH to Cd bioavailability was quantified under three analysis scenarios, accounting for 87.51% of the total variance of bioavailable Cd. In addition, the pH alert value (6.31 ± 0.52) for Cd risk was acquired for each rice field on a county scale. A precise map for the application amount of lime materials was constructed by taking CaCO₃ (3.38-15.75 t ha^-1) as a recommended economical and green immobilization agent. This study provides a potentially effective approach for risk assessment of Cd contamination in rice and important reference for precise Cd remediation in paddy soil.

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.

Interactions and quantification of multiple influencing factors on cadmium accumulation in soil-rice systems at a large region

The accumulation of Cd in soil-rice systems at a large region is often extremely complicated due to environmental heterogeneity and the interactions of multiple influencing factors. However, the interactive effects and quantification of the contributions of influencing factors on Cd accumulation in large regions remain unclear. In this study, conditional inference trees and random forest analysis were used to identify the interactions of various factors (soil properties, topography and demographic-economic), and quantify their contributions to Cd accumulation in soil-rice systems of Sichuan-Chongqing region, China. The results showed that Cd content in the soil was the most significant influencing factor on Cd accumulation in soil-rice systems, especially bioavailable Cd in soil contributed to 35.73 % and 54.78 % for soil total Cd (Cd_soil) and brown rice Cd (Cd_rice), respectively. Population density (PD) and elevation contributed 31.16 % and 27.40 % to Cd_soil content, respectively, and their interaction promoted the increase in Cd_soil content. Moreover, PD played a leading role in Cd_soil content when the elevation exceeded 324 m. The relative importances of slope and elevation for Cd_rice content were 16.81 % and 8.49 %, respectively, and their interaction facilitated the increment of Cd_rice content. As soil pH, gross domestic product (GDP) and slope decreased, the interaction of soil pH with GDP led to the increase of bioavailability factor (BAF), and that with slope enhanced the bioaccumulation factor (BCF). In addition, soil pH, PD and elevation were of considerable importance for the migration and transformation of Cd, with contributions of 22.11 %, 12.90 % and 12.52 % to BAF, and 5.05 %, 5.62 % and 5.50 % to BCF, respectively. This study is hopeful to provide a scientific insight into the prevention and control of Cd contamination in soil-rice systems at a large region.

Tracking cadmium pollution from source to receptor: A health-risk focused transfer continuum approach

Cadmium (Cd) exposure poses a substantial risk to human health. Despite this, the multi-stage process through which Cd is released to the environment before being taken up and impacting human receptors has rarely been investigated. Here we utilized an integrated model involving Cd emissions, atmospheric transport, deposition, uptake by rice, receptor ingestion and metabolic processing in quantifying the critical emission sources and human health risks of Cd. Atmospheric Cd emissions in the study area in southeastern China were estimated at 147 kg (2016), with >53 % of emissions from non-ferrous metals (NFM) smelting activities. Atmospheric Cd depositions caused elevated Cd content in soil and rice, accounting for 3-79 % and 50-85 % of, respectively, soil and rice Cd. Cumulative frequency analysis showed that an estimated 1.3 % of predicted urine Cd through the consumption of Cd-contaminated rice and exceeded existing safety standards (1 μg g^-1), thus highlighting the risks posed to health from high levels of Cd pollution. Applying stricter industrial emission standards to the NFM sector in particular and effective soil management practices could substantially reduce exposure to Cd pollution. The results contribute to understanding of the Cd transfer process and draw attention to the relative health benefits of interventions aimed at mitigating Cd levels and exposure risks at different stages along the Cd transfer continuum from source to receptor.

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.

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.

Congener-specificity, dioxygenation dependency and association with enzyme binding for biodegradation of polybrominated diphenyl ethers by typical aerobic bacteria: Experimental and theoretical studies

Polybrominated diphenyl ethers (PBDEs) are a group of organic pollutants that have attracted much concerns of scientific community over the ubiquitous distribution, chemical persistence and toxicological risks in the environment. Though a great number of aerobic bacteria have been isolated for the rapid removal of PBDEs, the knowledge about biodegradation characteristics and mechanism is less provided yet. Herein, the congener-specificity of aerobic biodegradation of PBDEs by typical bacteria, i.e. B. xenovorans LB400 was identified with the different biodegradation kinetics, of which the changes were largely hinged on the bromination pattern. The more bromination isomerically at ortho-sites other than meta-sites or the single bromination at one of aromatic rings might always exert the positive effect. The biodegradation of PBDEs should be thermodynamically constrained to some extent because the calculated Gibbs free energy changes of initial dioxygenation by quantum chemical method increased with the increase of bromination. Within the transition state theory, the high correlativity between the apparent biodegradation rates and Gibbs free energy changes implied the predominance and rate-limiting character of initial dioxygenation, while the regioselectivity of dioxygenation at the ortho/meta-sites was also manifested for the more negative charge population. The molecular binding with the active domain of dioxygenase BphA1 in aerobe was firstly investigated using docking approach. As significantly illustrated with the positive relationship, the higher binding affinity with BphA1 should probably signify the more rapid biodegradation. Besides the edge-on π-π stacking of PBDEs with F227 or Y277 and π-cation formulation with histidines (H233, H239) in BphA1, the reticular hydrophobic contacts appeared as the major force to underpin the high binding affinity and rapid biodegradation of PBDEs. Overall, the experimental and theoretical results would not only help understand the aerobic biodegradation mechanism, but facilitate enhancing applicability or strategy development of engineering bacteria for bioremediation of PBDEs in the environment.

Prediction of Cd Accumulation in Wheat (Triticum aestivum L.) and Simulation Calculation of Lime or Zn Fertilizer Remediated Soil

Soil Cd contamination to wheat raise wide concerns over food safety. It is essential to find the key factors affecting Cd accumulation in wheat and to establish a predictive model. The effects of pH, Zn, Ca, and DOM on the accumulation of Cd in wheat were investigated using hydroponic experiments. The results showed that Zn was the most important factor inhibiting Cd uptake in wheat. Models were developed to predict the Cd contents in wheat tissues based on the ion concentration. Meanwhile, the available Cd contents in soil were predicted using a geochemical multi-surface model (MSM) which is suitable for various soils and conditions. The combination of the hydroponic accumulation model and MSM exhibits good predictions of wheat-Cd (R² = 0.822-0.862, RMSE = 0.317-0.533). The results of this study can quantitatively predict the accumulation of Cd in wheat and provide a reference for soil remediation and safe wheat production.

The determination of regulating thresholds of soil pH under different cadmium stresses using a predictive model for rice safe production

Regulating soil pH becomes a crucial practice to alleviate cadmium (Cd) contamination. However, little is known about the threshold of soil pH for the safe production of rice at various soil Cd levels. In this paper, the relationships between soil pH values and the contents of available Cd extracted by calcium chloride (CaCl₂-Cd) in neutral and acidic soils were studied by mandatory acidification with H⁺ addition or neutralization with lime at various soil Cd levels. The results showed that the soil CaCl₂-Cd contents dramatically decreased with increasing soil pH, and a logarithmic function could well describe the relations of soil CaCl₂-Cd contents and soil pH at constant total Cd (CaCl₂-Cd model). The Cd contents in rice grain (grain-Cd) in relation to soil CaCl₂-Cd was further established through modified rice pot experiments. A model for the prediction of Cd content in rice grains (grain-Cd model) was set up, though which the grain-Cd content could be predicted based on soil pH and total Cd content. 122 data pairs of rice grain-Cd contents obtained at various soil total Cd contents and pH were employed from the literature to verify the reliability of the established model, approximately 95.08% of those data favorably located within the 1:1 line ± 0.5 unit area of the grain-Cd model. Notably, this model can be applied to determine the thresholds of soil pH at a specific Cd pollution level. For instance, to achieve a rice grain-Cd contents matching the Chinese national food safety limit of 0.2 mg kg^-1, the soil pH thresholds were estimated to be 5.05, 5.70, and 6.02 at soil Cd contents of 0.3, 0.6, and 0.8 mg kg^-1, respectively. In addition, the established model can also be used to estimate the health risk from rice in broad regions with various soil pH values and Cd contents.

Effect of land use pattern on the bioavailability of heavy metals: A case study with a multi-surface model

In modern agricultural practice, the land use pattern has been changing due to economic reasons and related policies, which significantly affects the basic physical and chemical properties of soils, thereby influencing the speciation and distribution of heavy metals (HMs) in soils. In this study, we selected three typical types of land use patterns (vegetable field, paddy field and forest field) in Shaoguan City, Guangdong Province, to analyze the content and distribution of HMs, screen the sensitive physicochemical properties, and predict the phytoavailability of HMs under different land use patterns with the multi-surface model (MSM). The forest field had relatively lower levels of labile and free HM ions than both paddy and vegetable fields, which may be attributed to the lower HM content in forest field. The modeling results revealed that organic matter (OM) is the primary carrier of HMs, accounting for 0.19%-97.92% of labile HMs. The sensitivity of soil physicochemical properties to free HM ions followed the order of pH > SOM > goethite > clay. Besides, the conversion of paddy field into vegetable or forest field increased the environmental risk of HMs. Our results may help better decision making in agricultural restructuring to reduce the risk of HM-contaminated soils, as well as give a demonstration for the application of the MSM in predicting the phytoavailability of HMs as a powerful technique.

Precise and differentiated solutions for safe usage of Cd-polluted paddy fields at regional scale in southern China: Technical methods and field validation

Cadmium (Cd) contamination in rice grains has become a severe issue worldwide. This study aims to explore feasible technologies applicable to different risk lands and develop a practical solution for safe rice production at a regional scale. Despite inconsistent field conditions in the whole region, various foliar fertilizers could effectively decrease grain Cd content by 20.4-41.6 % and were capable of producing safe grains in low/medium-risk areas. At high-risk sites, foliage dressing coupled with alkaline fertilizers significantly reduced Cd accumulation and increased grain compliance rate to 95.0 %. The cost analysis and questionnaire survey showed the above technologies are low-cost, eco-friendly, and highly acceptable in real-world scenarios. The classification results by conditional inference tree (CIT) for CK and FS scenarios indicated grain Cd content is closely related to the interaction effects of soil Cd and pH. On these bases, the whole area was divided spatially into three different risk zones, and each zone matched a feasible method for safe production, subsequently developing a precise and differentiated solution. The estimation results demonstrate it can effectively improve the precision level of safe utilization of regional polluted lands and save more than half of the total cost, providing a new idea for regional Cd-polluted paddy fields management strategies.

Evaluating the contributions of leaf organ to wheat grain cadmium at the filling stage

Cadmium (Cd) is an element of global concern in agricultural fields owing to its high bioavailability and its risk to human health via the consumption of wheat products. However, whether wheat leaves can directly absorb atmospheric Cd and transport them to the grains along with the contribution of leaves to Cd accumulation in the grains is not clear. We evaluated this mechanism through three comparative treatments: 1) exposure to atmospheric deposition (CK), 2) no exposure to atmospheric deposition (T1), and 3) exposure to atmospheric deposition with leaf cutting (T2). The Cd accumulation rate of grains in the CK, T1, and T2 groups all showed an increasing trend, followed by a decreasing trend, which was consistent with the trend of filling rate. Moreover, the critical period for leaf Cd accumulation in the grains was the early filling period, and its contribution decreased gradually as filling progressed. The contribution of the leaves to grain Cd reached 31.73% at maturity, with the reactivation of stored Cd in leaves pre-flowering and the newly absorbed atmospheric Cd by leaves post-flowering contributing 19.76% and 11.97% to Cd accumulation in grains, respectively, at maturity. Sub-microstructure analysis of the leaves further confirmed that the direct Cd absorption by leaves from atmospheric deposition through stomata contributed to Cd accumulation in wheat grains. Therefore, controlling the sources of atmospheric Cd pollution and reducing Cd absorption by leaves during grain filling can effectively control Cd pollution of wheat grains. This study provides significant insights on how to more effectively control the Cd content of edible part of wheat and ensure food security.

Technical solutions for minimizing wheat grain cadmium: A field study in North China

The minimization of Cd pollution in wheat is urgently needed in many parts of the world. Thus, the aims of the present study were to evaluate the feasibility of popular technologies (i.e., soil amendment and low-Cd wheat cultivar) at sites with different Cd risk levels (high and low) and to propose a risk-based strategy for safe grain production. At a high-Cd site, wheat variety JM22 yielded significantly lower grain Cd than SX828, regardless of soil amendment (biochar, sepiolite, and microbial agent YZ1). Neither biochar nor sepiolite amendment reduced grain Cd, DTPA-Cd, or bioconcentration factors, possibly due to low dosage. Metagenomic sequencing and quantitative PCR showed that YZ1 colonization had little effect on rhizospheric fungal community structure and could not be sustained through winter. At a low-Cd site, significantly lower grain Cd was observed in JM22, LX99, and JM262, which could be used as low-Cd cultivars in the study area. Interestingly, the grain Cd of JM22 was linearly correlated with soil Cd (R² = 0.84), which allowed the inference of a soil Cd threshold of 1.55 mg·kg^-1, below which JM22 alone was capable of producing safe grain. Cost-benefit analysis also indicated that the use of low-Cd cultivars is promising for pollution control. This study provides viable technical solutions for minimizing the grain Cd of wheat grown in northern China.

Pseudomonas sp. TCd-1 significantly alters the rhizosphere bacterial community of rice in Cd contaminated paddy field

Cadmium (Cd) pollution of paddy soils is one of the main concerns causing food security and environmental problems. Microbial bioremediation is an effective and eco-friendly measure that uses microbes to reduce Cd accumulation in crops. Additionally, rhizosphere bacterial communities also act essential roles in crop tolerance of heavy metals. However, the effects of inoculations with Cd resistant bacteria on crop rhizosphere bacterial communities under Cd exposure are largely unknown. In this study, we used high-throughput 16S rRNA gene sequencing technologies to explore the community structure and co-occurrence network of the rhizosphere bacterial communities associated with the rice crop under different Cd treatments and the application of Cd-tolerant strain Pseudomonas sp. TCd-1. We found that the strain TCd-1 both significantly reduced the rhizobacterial alpha diversity and changed the beta diversity. PERMANOVA and NMDS analysis showed that Cd stress and TCd-1 strain could act as strong environmental filters resulting in observable differentiation of rhizobacterial community composition among different groups. In addition, RDA results indicated that the rhizosphere pH, root Cd content, catalase (CAT), urease (URE), gibberellic acid (GA3) exert significant association with rhizosphere bacterial assembly. PICRUSt analysis revealed that the TCd-1 strain improved the metabolic capacity of rhizosphere bacteria under Cd stress. Furthermore, co-occurrence network topological features and keystone taxa also varied among different groups. This study could provide necessary insights into developing an efficient bioremediation and safe production of rice crops in Cd contaminated paddy fields with the application of Pseudomonas sp. TCd-1 strain, as well as advance our understanding of the principles of rhizosphere bacterial community assembly under Cd stress.

Quantifying source-specific intake risks of wheat cadmium by associating source contributions of soil cadmium with human health risk

Sources of cadmium (Cd) contamination of farmlands and the potential risk to human health via dietary intake of wheat Cd are of great concern to consumers. A source-specific risk assessment (SSRA) model, which combined a positive matrix factorization receptor model and spatial analysis with a health risk assessment model, was developed based on a wheat field investigation in northern China. It was used to estimate the daily intake risk from different sources of ingesting Cd from wheat. The mixed source of wastewater and residues from industrial activities and atmospheric deposition were identified as the dominant sources of Cd contamination. Wheat Cd uptake could be predicted reliably from the pH and total Cd concentration of field soil. Based on the predictive model of Cd transfer from soil to wheat, the SSRA model then linked sources to the Cd intake risk from wheat grain. Results showed that the mixed source and the atmospheric deposition source accounted for 52.8% and 29.3%, respectively, of the wheat Cd intake risk. In combination with the spatial analysis, the potential risk of Cd contamination in western and central eastern areas was mainly attributed to the mixed source of wastewater and industrial residues, whereas the risk in the northwestern area was associated mainly with atmospheric deposition. Regionalized risk management strategies, focusing on different sources, were proposed to minimize the Cd input to field cropping system and to mitigate health risk for local residents.

Evaluation of Cadmium Transfer from Soil to the Human Body Through Maize Consumption in a Cadmium Anomaly Area of Southwestern China

Evaluating the bioavailability, bioaccessibility, and transferability of cadmium (Cd) in soil-grain-human systems is essential in areas with a Cd anomaly in the karst region of southwestern China. In the present study, the main controlling factors and prediction models for Cd transfer in a soil-grain-human system were investigated in a typical area where natural processes and anthropogenic activities interact in the karst region of southwestern China. The environmental availability of Cd (diethylenetriaminepentaacetic acid- and CaCl₂ -extractable Cd [ CdCaCl2 ]) in the soil varies significantly because of the diversity of soil properties. However, Cd concentrations in the maize grain were significantly related only to the CdCaCl2 concentrations in the soil (r = 0.595, p < 0.01), indicating that soil CdCaCl2 is a good indicator for evaluating Cd uptake by maize grain. Of all the measured soil properties, the soil cation exchange capacity (CEC) and the soil calcium (Ca_soil ) were the most important factors influencing Cd accumulation in the soil-maize grain system. A transfer model combining CdCaCl2 , soil CEC, and Ca_soil was sufficiently reliable for predicting Cd accumulation in the maize grain (R²  = 0.505). Although there is room for improvement regarding the prediction performance of the chain model combining soil CdCaCl2 with Ca_soil to predict the bioaccessible Cd concentration in maize grain (R²  = 0.344 for the gastric phase and R²  = 0.356 for the gastrointestinal phase), our findings provide a useful reference to further explore a model that can be used for a relatively rapid and reliable estimation of dietary Cd exposure for specific regions prior to crop harvest. Environ Toxicol Chem 2021;40:2923-2934. © 2021 SETAC.

Farmland heavy metals can migrate to deep soil at a regional scale: A case study on a wastewater-irrigated area in China

Heavy metal risks to human health in farmland of wastewater-irrigated areas have long been recognized. It remains to be shown whether farmland heavy metals from wastewater irrigation can migrate to deeper soil at a regional scale. In this study, nine soil cores deep to 30 m from three transects (A, B and C) of a linear wastewater reservoir and the adjacent farmland topsoils and wheat grains were sampled. Heavy metals including As, Cd, Cr, Cu, Pb and Zn in the soils and wheat grains were determined, and the grains' health risks were assessed using the Target Hazard Quotient (THQ). Considerably high contents of heavy metals in both total and soluble forms were detected in deep soils, especially for the transect B where total As of 73.0 mg kg^-1 at 29 m, Cd of 3.80 mg kg^-1 at 13 m and Pb of 214 mg kg^-1 at 30 m were detected. The silty clayey and silty layers of the transect B had higher contents of As, Cr, Cu, Pb and Zn compared with the sandy layers. Across the studied area, 19.5%-34.1% of the topsoil samples were contaminated by As, Cd, Cu, Pb and Zn, and 34.1% and 19.5% of the wheat grains were contaminated by Cd and Pb, respectively. Wheat grains from all the sampling sites had a combined target hazard quotient (TTHQ) value of >1, with As and Cd being the most important contributors. Our study revealed a wider and deeper risk of typical heavy metals originated from long-term wastewater irrigation in the sampling area, which may pose substantial health risks to the local residents via wheat grains and groundwater.

Cadmium accumulation in wheat and maize grains from China: Interaction of soil properties, novel enrichment models and soil thresholds

The cadmium (Cd) activity in soil has been widely studied. However, the interactive effects of soil properties (e.g. soil pH, CEC, and SOM) on Cd transfer from soil to grain are generally overlooked. In total 325 datasets including soil pH, CEC, SOM, and soil Cd content were used in this study. The descriptive statistics indicated that Cd content in wheat and maize soils ranged from 0.05 to 10.31 mg/kg and 0.02-13.68 mg/kg, with mean values of 0.87 and 1.14 mg/kg, respectively. Cd contents in wheat and maize grains were 0.01-1.36 mg/kg and 0.001-1.08 mg/kg with average values of 0.15 and 0.10 mg/kg, respectively. The results of SEM demonstrated that the interactive effects of soil properties contributed more to Cd transfer from soil to wheat grain than the soil Cd content. Subsequently, CITs-MLR indicated that the critical factors, including soil pH and total soil Cd content, could mask the contribution of other soil properties on Cd accumulation in grain; soil CEC may prevent Cd from leaching and therefore improve grain Cd level of wheat especially at acidic soil condition. The result of derived Cd thresholds revealed that current Cd thresholds are not completely suitable to wheat and maize grain at different soil conditions. This study provides a new model for further investigation on relationships between soil properties, soil Cd content and grain Cd level.

Highly selective simultaneous determination of Cu(ii), Co(ii), Ni(ii), Hg(ii), and Mn(ii) in water samples using microfluidic paper-based analytical devices

A new paper-based analytical device design was fabricated by a wax printing method for simultaneous determination of Cu(ii), Co(ii), Ni(ii), Hg(ii), and Mn(ii). Colorimetry was used to quantify these heavy metal ions using bathocuproine (Bc), dimethylglyoxime (DMG), dithizone (DTZ), and 4-(2-pyridylazo) resorcinol (PAR) as complexing agents. The affinity of complexing agents to heavy metal ions is dependent on the formation constant (Kf). To enhance the selectivity for heavy metal ion determination, the new device was designed with two pretreatment zones, where masking agents remove the interfering ions. It was found that two pretreatment zones worked better than a single pretreatment zone at removing interferences. The reaction time, sample and complexing agent volumes, and complexing agent concentrations were optimized. The analytical results were achieved with the lowest detectable concentrations of 0.32, 0.59, 5.87, 0.20, and 0.11 mg L-1 for Cu(ii), Co(ii), Ni(ii), Hg(ii), and Mn(ii), respectively. The linear ranges were found to be 0.32-63.55 mg L-1 (Cu(ii)), 0.59-4.71 mg L-1 (Co(ii)), 5.87-352.16 mg L-1 (Ni(ii)), 0.20-12.04 mg L-1 (Hg(ii)), and 0.11-0.55 mg L-1 (Mn(ii)). The lowest detectable concentration and linearity for the five metal ions allow the application of this device for the determination of heavy metal ions in various water samples. The sensor showed high selectivity and efficiency for simultaneous determination of Cu(ii), Co(ii), Ni(ii), Hg(ii), and Mn(ii) in drinking, tap, and pond water samples on a single device and detection with the naked eye. The results illustrated that the proposed sensor showed good accuracy and precision agreement with the standard ICP-OES method.

The role of interfacial reactions in controlling the distribution of Cd within goethite-humic acid-bacteria composites

Mineral-organic interfacial reactions strongly influence the adsorption, distribution and bioavailability of metal cations in soil systems. The molecular binding mechanisms and distribution of Cd onto goethite, humic acid, Pseudomonas putida cells, and their composites at different mass ratios were studied through the combination of bulk adsorption coupled with EXAFS, ITC and SCM. In binary and ternary composites, the energetics of the overall adsorption of Cd was dominated by the entropy of Cd adsorption onto the organic fraction. The formation of a type-B HA bridging complex >FeOH-HACOOCdOH enhanced Cd adsorption by 10-30% at low Cd concentrations, and more than 93.5% of the adsorbed Cd was bound onto HA fraction. In ternary systems, the component additivity over-estimated Cd adsorption onto bacteria by ~21.8%, likely due to site blocking effects. Models involving the masking of phosphoryl sites and HA bridging reactions can simulate the distribution of Cd in the composites. Our modelling suggests that HA is the main scavenger of Cd under a range of environmental conditions, and that bacteria become important in affecting the distribution of Cd under lower pH settings. This study demonstrates the impact of iron oxide-HA-bacteria interactions on the fate and distribution of Cd in soils and associated environments.