Potential health risk assessment for inhabitants posed by heavy metals in rice in Zijiang River basin, Hunan Province, China

Toxic metals in rice among Asian countries: A review of occurrence and potential human health risks

Heavy metals such as cadmium (Cd), arsenic (As), and lead (Pb) pose significant health risks, particularly in Asia, where rice is a staple for nearly three billion people. Despite their known dangers and environmental prevalence, studies addressing their concentrations in rice across different regions and the associated health implications remain insufficient. This review systematically examines the occurrence and impact of these toxic elements, filling a critical gap in the literature. Data from seven countries indicate mean concentrations in the order of Pb > As>Cd, with values of 0.255 ± 0.013, 0.236 ± 0.317, and 0.136 ± 0.150 mg/kg, respectively. Uncertainty analysis shows extensive variability, especially for Cd, with a 95% confidence interval range from 0.220 to 0.992 mg/kg. The typical daily intake of heavy metals through rice consumption, in the order of As>Cd > Pb, frequently exceeds safe limits. Generally, data obtained from various studies showed that children were more prone to heavy metal contamination through rice consumption than adults. This review is fundamental for ongoing monitoring, future research, and management strategies to reduce heavy metal contamination in rice.

Environment-compatible heavy metal risk prediction method created with multilevel ensemble learning

Accurate health risk prediction (HRP) is an effective means of reducing the hazards of heavy metal (HM) exposure. It can address the drawbacks of lag and passivity faced by health risk assessment. This study innovatively proposed an HRP method, MEL-HR, based on multilevel ensemble learning (MEL) technology and environment compatibility. We conducted point and interval prediction experiments on health risks using 490 sets of data covering 17 environment factors. The point prediction results indicated that when the model predicts HI and TCR, the R2 values were 0.707 and 0.619, respectively. For P5, P50, and P95 in interval prediction, the R2 values of the model were 0.706, 0.703, and 0.672 for HI, and that for TCR were 0.620, 0.607, and 0.616, respectively. The analysis of feature importance indicated that, in addition to HM factors, longitude, mining area coefficient, and soil organic matter were key environmental factors affecting the MEL-HR model. Comparative experiments showed that compared to soil HMs-based MEL-HR, environment compatibility-based MEL-HR has improved the accuracy for HI and TCR by 19.83 % and 40.36 % for the point prediction and 22.06 % and 40.01 % for interval prediction. This study can provide technical support for targeted and resilient prevention and control of health risks.

The human health risks assessment posed by the presence of heavy metals in the rice varieties available in the Neyshabur market

The present study was designed to determine the levels of heavy metals (Cu, Pb, Ni, Cr, Zn, Mn, Cd, and Co), Mn, and As in Iranian-grown rice and imported rice consumed in Neyshabur City. For this research, 90 samples from 30 different brands widely consumed in this city were collected. The content of heavy metals and the health risks associated with their use were then studied. The study found that Zn (14.21 mg kg-1) had the highest content in Iranian and imported rice varieties, whereas Cd (0.02 mg kg-1) had the lowest value. The health risk assessment was also done in three scenarios and separately for two types of rice. The results showed that the total hazard quotient (i.e., THQ) was measured for all metals and all three scenarios, and for both types of rice, it is THQ > 1, which indicates the risk of non-carcinogenic in rice. The cancer risk for three scenarios and two types of imported and Iranian rice is in the unsafe range for As (8.80 × 10-4 to 7.00 × 10-3), Ni (4.60 × 10-4 to 3.60 × 10-3) and Cr (2.20 × 10-4 to 1.90 × 10-3) and negligible for Pb (1.09 × 10-6 to 1.49 × 10-5) and Cd (7.83 × 10-6 to 8.20 × 10-5).

A novel prediction approach driven by graph representation learning for heavy metal concentrations

The potential risk of heavy metals (HMs) to public health is an issue of great concern. Early prediction is an effective means to reduce the accumulation of HMs. The current prediction methods rarely take internal correlations between environmental factors into consideration, which negatively affects the accuracy of the prediction model and the interpretability of intrinsic mechanisms. Graph representation learning (GraRL) can simultaneously learn the attribute relationships between environmental factors and graph structural information. Herein, we developed the GraRL-HM method to predict the HM concentrations in soil-rice systems. The method consists of two modules, which are PeTPG and GCN-HM. In PeTPG, a graphic structure was generated using graph representation and communitization technology to explore the correlations and transmission paths of different environmental factors. Subsequently, the GCN-HM model based on the graph convolutional neural network (GCN) was used to predict the HM concentrations. The GraRL-HM method was validated by 2295 sets of data covering 21 environmental factors. The results indicated that the PeTPG model simplified correlation paths between factor nodes from 396 to 184, reducing by 53.5 % graph scale by eliminating the invalid paths. The concise and efficient graph structure enhanced the learning efficiency and representation accuracy of downstream prediction models. The GCN-HM model was superior to the four benchmark models in predicting the HM concentration in the crop, improving R2 by 36.1 %. This study develops a novel approach to improve the prediction accuracy of pollutant accumulation and provides valuable insights into intelligent regulation and planting guidance for heavy metal pollution control.

Heavy metals pollution from smelting activities: A threat to soil and groundwater

Throughout the literature, the word "heavy metal" (HM) has been utilized to describe soil contamination; in this context, we characterize it as those elements with a density greater than 5 g per cubic centimeter. Contamination is one of the major global health concerns, especially in China. China's rapid urbanization over the past decades has caused widespread urban water, air, and soil degradation. This study provides a complete assessment of the soil contamination caused by heavy metals in China's mining and smelting regions. The study of heavy metals (HMs) includes an examination of their potential adverse impacts, their origins, and strategies for the remediation of soil contaminated by heavy metals. The presence of heavy metals in soil can be linked to both natural and anthropogenic processes. Studies have demonstrated that soils contaminated with heavy metals present potential health risks to individuals. Children are more vulnerable to the effects of heavy metal pollution than adults. The results highlight the significance of heavy metal pollution caused by mining and smelting operations in China. Soil contaminated with heavy metals poses significant health concerns, both carcinogenic and non-carcinogenic, particularly to children and individuals living in heavily polluted mining and smelting areas. Implementing physical, chemical, and biological remediation techniques is the most productive approach for addressing heavy metal-contaminated soil. Among these methods, phytoremediation has emerged as a particularly advantageous option due to its cost-effectiveness and environmentally favorable characteristics. Monitoring heavy metals in soils is of utmost importance to facilitate the implementation of improved management and remediation techniques for contaminated soils.

Uncertainty Evaluation of Soil Heavy Metal(loid) Pollution and Health Risk in Hunan Province: A Geographic Detector with Monte Carlo Simulation

Research on soil heavy metal(loid) pollution and health risk assessment is extensive, but a notable gap exists in systematically examining uncertainty in this process. We employ the Nemerow index, the health risk assessment model, and the geographic detector model (GDM) to analyze soil heavy metal(loid) pollution, assess health risks, and identify driving factors in Hunan Province, China. Furthermore, the Monte Carlo simulation (MCS) method is utilized to quantitatively evaluate the uncertainties associated with the sampling point positions, model parameters, and classification boundaries of the driving factors in these processes. The experimental findings reveal the following key insights: (1) Regions with high levels of heavy metal(loid) pollution, accompanied by low uncertainty, are identified in Chenzhou and Hengyang Cities in Hunan Province. (2) Arsenic (As) and chromium (Cr) are identified as the primary contributors to health risks. (3) The GDM results highlight strong nonlinear enhanced interactions among lithology and other factors. (4) The input GDM factors, such as temperature, river distance, and gross domestic product (GDP), show high uncertainty on the influencing degree of soil heavy metal(loid) pollution. This study thoroughly assesses high heavy metal(loid) pollution in Hunan Province, China, emphasizing uncertainty and offering a scientific foundation for land management and pollution remediation.

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.

A comparative study of different methods for the determination of cadmium in various tissues of ramie (Boehmeria nivea L.)

Remediation of cadmium (Cd) pollution is one of the priorities of global environmental governance and accurate detection of Cd content is a key link in remediation of Cd pollution. This study aimed to compare three methods (inductively coupled plasma optical emission spectrometry (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS), and graphite furnace-atomic absorption spectrometry (GF-AAS)) for the determination of Cd with different tissues of various ramie varieties, and distinguish the advantage and disadvantage of each method. In total, 162 samples of ramie (Boehmeria nivea L.), which is an ideal plant for heavy metal remediation, were detected and the results showed that the three methods were all suitable for the de-termination of Cd content in ramie. ICP-OES and ICP-MS were simpler, faster, and more sensitive than GF-AAS. ICP-MS could be recommended for the determination of samples with various concentrations of Cd. ICP-OES could be used for measurement of samples with > 100 mg/kg Cd content, while GF-AAS was suitable for the detection of samples with very high (> 550 mg/kg) or very low (< 10 mg/kg) Cd content. Overall, considering the accuracy, stability, and the cost of measurement, ICP-MS was the most suitable method for determination of Cd content. This study provides significant reference information for the research in the field of Cd pollution remediation.

The role of nickel in cadmium accumulation in rice

Rice is one of the world's staple foods. Cadmium (Cd) levels in paddy soil are still increasing, and "Cd-contaminated rice" is a frequent occurrence, posing a serious threat to human health. Therefore, Cd contamination in rice is a key issue in agricultural production that needs to be addressed urgently. The Cd accumulation in rice is closely related to other elements. In this study, the impact of nickel (Ni) on the uptake and accumulation of Cd in rice was revealed, and the mechanism was discussed. Statistical analysis of field data showed that Cd concentration in rice grains decreased exponentially with increasing Ni concentration in paddy soils, which was verified by the hydroponic experiments. Under 5 μmol/L Cd exposure conditions, the addition of Ni (100 μmol/L) reduced the Cd contents in roots, stems, and leaves by 81.6 %, 60.6 %, and 65.9 %, respectively. With the presence of Ni, the amount of iron plaque decreased, and the Cd content in the iron plaque was reduced due to the competition between Ni and Cd for adsorption sites. In addition, the migration of Cd from stems to leaves was reduced. At the same time, the distribution of Cd in the cell was altered, and the concentration of Cd in the root cell walls increased with increasing Ni addition under 5 μmol/L Cd exposure. These findings highlight the critical role of Ni in inhibiting Cd accumulation in rice, and provide important information for understanding the effects of coexisting elements in Cd-contaminated soils on Cd accumulation in crops.

Human-induced pollution and toxicity of river sediment by potentially toxic elements (PTEs) and accumulation in a paddy soil-rice system: A comprehensive watershed-scale assessment

This study aimed to assess pollution by potentially toxic elements (PTEs) in the Zarjoub and Goharroud river basins in northern Iran. Due to exposure to various types of pollution sources, these rivers are two of the most polluted rivers in Iran. They also play an important role in irrigation of paddy fields in the study area, increasing concerns about the contamination of rice grains by PTEs. Hence, we analyzed the concentrations of eight PTEs (i.e., As, Co, Cr, Cu, Mn, Ni, Pb, and Zn) at ten channel bed sediment sampling sites in each river, fifteen samples of paddy soils and fifteen co-located rice samples in the relevant watersheds. Results of the index-based assessment indicate moderate to heavy pollution and moderate toxicity for sediments in the Goharroud River, while both pollution and toxicity of the Zarjoub River sediment were characterized as moderate. Paddy soils in the watersheds were found to be moderate to heavily polluted by PTEs, but the values of the rice bioconcentration factor (RBCF) indicated intermediate absorption for Cu, Zn, and Mn, and weak and very weak absorption for Pb/Ni and As/Co/Cr, respectively. The concentration of Zn, Cu, Pb, and Cr was negatively correlated to the corresponding values of RBCF, highlighting the ability of rice grains to control bioaccumulation and regulate concentrations. Industrial/agricultural effluents, municipal wastewater, leachate of solid waste, traffic-related pollution, and weathering of parent materials were found to be responsible for pollution of the Zarjoub and Goharroud watersheds by PTEs. Mn, Cu, and Pb in rice grains might be responsible for non-carcinogenic diseases. Although weak absorption was observed for As and Cr in rice grains, the concentrations of these elements in rice grains indicate a high level of cancer risk if ingested. This study provides insights to control the pollution of sediment, paddy soils, and rice.

The lead and cadmium content in rice and risk to human health in China: A systematic review and meta-analysis

Numerous studies have investigated concentrations of lead (Pb) and cadmium (Cd) in rice in China, but have come to divergent conclusions. Therefore we systematically reviewed and meta-analyzed the available evidence on levels of Pb and Cd in rice in different regions of China in order to assess the potential risk to human health. The meta-analysis included 24 studies of Pb levels and 29 studies of Cd levels, published in 2011-2021. The pooled Pb concentration in rice was 0.10 mg per kg dry weight (95% CI 0.08-0.11), while the pooled Cd concentration was 0.16 mg per kg dry weight (95% CI 0.14-0.18). These levels are within the limits specified by national food safety standards. However, the total target hazard quotient for both metals exceeded 1.0 for adults and children, suggesting that rice consumption poses a health risk.

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.

Spatial distribution of heavy metals in rice grains and human health risk assessment in Hunan Province, China

Rice is the main food in China, and its pollution by heavy metals has attracted widespread attention. In this study, rice grain samples were collected from 14 prefecture-level cities in Hunan Province, China. The contents of 9 heavy metals (i.e., As, Cr, Co, Ni, Cu, Zn, Cd, Pb, and Sb) were measured using graphite digestion-inductively coupled plasma mass spectrometry (ICP-MS). Pearson correlation analysis and principal component analysis were performed to evaluate the correlation among these heavy metals. In addition, ordinary kriging interpolation were applied to investigate the spatial distribution pattern of the heavy metals. Results showed that the average concentrations of these heavy metals were 0.48 (As), 1.28 (Cr), 0.03 (Co), 0.84 (Ni), 2.39 (Cu), 15.73 (Zn), 0.28 (Cd), 0.66 (Pb), and 0.0043 (Sb) mg/kg, respectively. The single-factor pollution index (SFPI) contamination assessment showed that As, Pb, Cr, Ni, and Cd accumulated significantly in the rice grain, with over-standard rates of 100%, 100%, 64.70%, 47.05%, and 44.12%, respectively. The Sb concentrations at the sampling sites were low, and there was no obvious pollution. Health risk assessment showed that the target hazard quotient followed the order of As> Cr> Cd> Pb> 1.0> Co> Cu> Zn> Ni> Sb, and the carcinogenic risk value was in the order of Cd> Ni> As> Cr> 1.0×10^-4> Pb. In particular, quick actions should be taken to regulate As, Cr, and Cd contents in rice because they posed greater non-carcinogenic and carcinogenic health risks than the others to the local residents.

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.

Convolutional neural networks-based health risk modelling of some heavy metals in a soil-rice system

The long-term consumption of heavy metal-rich rice can cause serious harm to human health. However, the existing health risk assessment (HRA) can only be performed after the rice has been harvested, and this approach belongs to a passive and lagging pattern. This study is the first to explore the feasibility of health risk (HR) prediction by proposing the indirect model CNNHR-IND and the direct model CNNHR-DIR based on the convolutional neural network (CNN) technology. The dataset included 390 pairs of soil-rice samples collected from You County, China, with 17 environmental covariates. The R² values for CNNHR-IND for non-carcinogenic and carcinogenic risks were 0.578 and 0.554, respectively, and those for CNNHR-DIR were 0.647 and 0.574, respectively. The results demonstrated that both models performed well, especially CNNHR-DIR had a higher estimation accuracy. The spatial autocorrelation analysis indicated that CNNHR-DIR exerted no systematic bias in the prediction results for health risks, confirming the rationality of the CNNHR-DIR model. The sensitivity analysis further confirmed the generalizability and robustness of CNNHR-DIR. This study proved the feasibility of HR prediction and the potential of CNN technology in HRA, and is significant regarding early risk warnings of rice planting and the sustainable development of public health.

Co-exposure of potentially toxic elements in wheat grains reveals a probabilistic health risk in Southwestern Guizhou, China

Bijie is located at a typical karst landform of Southwestern Guizhou, which presented high geological background values of potentially toxic elements (PTEs). Recently, whether PTE of wheat in Bijie is harmful to human health has aroused people's concern. To this end, the objectives of this study are to determine the concentrations of PTE [chromium (Cr), nickel (Ni), arsenic (As), lead (Pb), cadmium (Cd), and fluorine (F)] in wheat grains, identify contaminant sources, and evaluate the probabilistic risks to human beings. A total of 149 wheat grain samples collected from Bijie in Guizhou were determined using the inductively coupled plasma mass spectrometer (ICP-MS) and fluoride-ion electrode methods. The mean concentrations of Cr, Ni, As, Cd, Pb, and F were 3.250, 0.684, 0.055, 0.149, 0.039, and 4.539 mg/kg, respectively. All investigated PTEs met the standard limits established by the Food and Agriculture Organization except for Cr. For the source identification, Cr and Pb should be originated from industry activities, while Ni, As, and Cd might come from mixed sources, and F was possibly put down to the high geological background value. The non-carcinogenic and carcinogenic health risks were evaluated by the probabilistic approach (Monte Carlo simulation). The mean hazard quotient (HQ) values in the three populations were lower than the safety limit (1.0) with the exception of As (children: 1.03E+00). However, the mean hazard index (HI) values were all higher than 1.0 and followed the order: children (2.57E+00) > adult females (1.29E+00) > adult males (1.12E+00). In addition, the mean carcinogenic risk (CR) values for Cr, As, Pb, and Cd in three populations were all higher than 1E-06, which cannot be negligible. The mean threshold CR (TCR) values were decreased in the order of children (1.32E-02) > adult females (6.61E-03) > adult males (5.81E-03), respectively, all at unacceptable risk levels. Moreover, sensitivity analysis identified concentration factor (C _W ) as the most crucial parameter that affects human health. These findings highlight that co-exposure of PTE in wheat grains revealed a probabilistic human health risk. Corresponding measures should be undertaken for controlling pollution sources and reducing the risks for the local populace.

Effects of combined soil amendments on Cd accumulation, translocation and food safety in rice: a field study in southern China

Excessive Cd content and high Cd/Zn ratio in rice grains threaten human health. To study the reduction effects of combined soil amendments on Cd content and Cd/Zn ratio in rice planting in soils with different Cd contamination levels, we conducted field trials in three regions of Hunan province, China. Six field treatments were designed in each study area, including control (CK), lime alone (L), lime combined with sepiolite (LS), phosphate fertilizer (LP), organic fertilizer (LO) and phosphate fertilizer + organic fertilizer (LPO). The application of the combined amendments reduced the Cd content in rice grains to less than the Food Health Standard of China (0.2 mg/kg) and the Cd/Zn ratio to less than the safety threshold of 0.015. The average reduction rates of grain Cd content under the combined treatments among the three regions increased with the increase in Cd content in the soil. Meanwhile, the amendments also decreased the soil available Cd and Zn concentration significantly. The LO had the highest efficiency on decreasing Cd content in rice grains among these amendments, which is ranged from 44.6% to 52.8% in the three regions compared with CK. Similarly, high reduction rates of Cd/Zn ratio were found in the LO treatment, with an average value of 57.3% among the three regions. The grain Cd contents and Cd/Zn ratios were significantly correlated with the soil available Cd concentrations, plant uptake factor and the straw to rice grain translocation factor (TF_gs) (P < 0.05). The results indicated that the combined soil amendments, especially lime combined with organic fertilizer, would be an effective way to control Cd content in rice.

Probabilistic health risk assessment for residents exposed to potentially toxic elements near typical mining areas in China

Public health problems caused by toxic elements in mining areas have always been an important topic worldwide. However, existing studies have focused on single exposure routes and common toxic elements, which might underestimate the risks faced by residents. In this study, three typical mining areas in central China were selected to assess the health risks of 14 potentially toxic elements through five exposure routes using Monte Carlo simulations. The results indicated that the 95th percentile non-carcinogenic risk values to humans via rice and vegetable ingestion ranged from 9.8 to 26.0 and 6.2 to 19.0. The corresponding carcinogenic risks ranged from 1.4E-2 to 6.3E-2 and from 2.9E-3 to 2.3E-2, respectively. Therefore, residents face serious health risks. Multi-element analysis showed that cadmium (Cd), boron (B), and arsenic (As) were the main contributors to rice non-carcinogenicity, whereas Cd and nickel (Ni) were the main elements of rice carcinogenicity. B and lead (Pb) played an essential role in the non-carcinogenesis of vegetables, and B, Ni, and Cd played an essential role in carcinogenesis. Accidental ingestion is the main route of soil exposure. In these three areas, the probability of non-carcinogenic risk faced by adults was 40%, 0%, and 1%, respectively, while the probabilities for children were 100%, 62%, and 83%, respectively. Regarding carcinogenicity, the risk for both adults and children was up to 100%. This study emphasizes the overall health risks in polluted areas via multi-route and multi-element analysis. This conclusion is helpful to comprehensively assess the potential health risks faced by residents in mining areas and provide baseline data support and a scientific basis for formulating reasonable risk control measures.

Research Progress on Heavy Metals Pollution in the Soil of Smelting Sites in China

Contamination by heavy metals is a significant issue worldwide. In recent decades, soil heavy metals pollutants in China had adverse impacts on soil quality and threatened food security and human health. Anthropogenic inputs mainly generate heavy metal contamination in China. In this review, the approaches were used in these investigations, focusing on geochemical strategies and metal isotope methods, particularly useful for determining the pathway of mining and smelting derived pollution in the soil. Our findings indicate that heavy metal distribution substantially impacts topsoils around mining and smelting sites, which release massive amounts of heavy metals into the environment. Furthermore, heavy metal contamination and related hazards posed by Pb, Cd, As, and Hg are more severe to plants, soil organisms, and humans. It's worth observing that kids are particularly vulnerable to Pb toxicity. And this review also provides novel approaches to control and reduce the impacts of heavy metal pollution. Hydrometallurgy offers a potential method for extracting metals and removing potentially harmful heavy metals from waste to reduce pollution. However, environmentally friendly remediation of contaminated sites is a significant challenge. This paper also evaluates current technological advancements in the remediation of polluted soil, such as stabilization/solidification, natural attenuation, electrokinetic remediation, soil washing, and phytoremediation. The ability of biological approaches, especially phytoremediation, is cost-effective and favorable to the environment.

Pollution monitoring, risk assessment and target remediation of heavy metals in rice from a five-year investigation in Western Fujian region, China

Recently, rice contamination by heavy metals (HMs) has become a severe problem. Taking the Western Fujian region as an example in this study, a total of 1311 rice samples containing eight HMs were collected from 2015 to 2019, then used to explore their pollution characteristics, health risks, and Spatio-temporal variations, finally derive the target remediation areas of the key pollutants. The results showed that average concentrations of all the HMs had not reached the limits of the National Standards of Food Safety, but pollution indexes of As (0.783) and Cu (0.665) were at accumulation level (>0.6), which posed high pollution risks. Furthermore, locations of higher HMs concentrations coincided with those of higher pollution estimation probabilities. The non-carcinogenic risk (4.150, 2.434) and carcinogenic risk (4.96 × 10^-3, 2.92 × 10^-3) for children and adults cannot be negligible, As and Cd were the largest contributors. Children were more susceptible than adults due to the metal concentrations and rice intake rate. The spatio-temporal changes indicated that a decreasing trend in average concentrations of HMs (except Cr), but As (0.37%-0.88%) contents increased in the west and northeast parts, and so did Cd (1.92%-5.11%) in the central region during monitoring. For the target remediation, particular regions in the western and eastern were used as risky areas of As and Cd, respectively. Our results will provide theoretical support for the pollution management of HMs in rice.

Probabilistic health risk assessment of inorganic arsenic and some heavy metals in rice produced from a typical multi-mining county, China

The potential impact of exposure to toxic elements in rice on human health has become a global public health issue. This study analyzed the pollution characteristics and probabilistic health risks of exposure to iAs, Pb, Cd, Cr, and Hg in rice produced in a typical multi-mining county using Monte Carlo simulation, a geographic information system, and bioavailability analysis. The results showed that the enrichment of As and Cd was prominent in rice, with mean tAs, iAs, and Cd contents of 0.34 ± 0.20, 0.15 ± 0.09, and 0.48 ± 0.50 mg·kg^-1, respectively. The probability of non-carcinogenic risk via rice consumption in adults and children exceeding the threshold was 72% and 78%, respectively, and that of carcinogenic risk was as high as 100%. Among toxic elements, Cd and iAs were the main risk factors for health risks. The high-level health-risk areas mainly occurred in the north-eastern and central parts of the study area. Sensitivity analysis highlighted that the top three influential parameters for non-carcinogenic risk in adults were Content(Cd), Content(iAs), and Bioaccessibility(Cd), whereas those in children were ingestion rate of rice, Content(Cd), and Content(iAs). The Content(Cd) was the decisive factor for carcinogenic risk, with a sensitivity coefficient of 78.0% in adults and 64.7% in children. Considering the high risk of ingestion of local rice in this area, it is imperative to place strict supervision and take control measures.

Heavy metals in soils and edible tissues of Lepidium meyenii (maca) and health risk assessment in areas influenced by mining activity in the Central region of Peru

Heavy metal contamination of soil and agricultural products is an environmental problem, has an adverse effect on the quality of food crops, and is a danger to food security and public health. The concentration of arsenic (As), cadmium (Cd), lead (Pb), iron (Fe) and zinc (Zn) in surface soils and edible hypocotyls tissues of two ecotypes of Lepidium meyenii Walpers (maca) was evaluated in three districts of the Junín province, Peru. In addition, the risk to human health due to exposure to heavy metals from maca consumption was evaluated. Soil samples and maca hypocotyls were collected in areas influenced by mining and metallurgical activity. The mean concentration of Cd (0.32 ± 0.23 mg/kg) and Pb (0.20 ± 0.12 mg/kg) in maca samples exceeded the values established by the Food and Agriculture Organization and the World Health Organization. The bioconcentration factor was less than 1. The estimated daily intake of each metal was below the oral reference dose. The hazard quotient and hazard index were less than 1, it is unlikely to cause non-cancer adverse health outcome. The cancer risk for As and Cd was higher than the tolerable limit (1 × 10-6) in children and adults. In the district of Ondores, the cancer risk for As in children was higher than the acceptable limit (1 × 10-4). Residents of the Ondores district would be more exposed to As and Cd from consumption of maca hypocotyls. It is very important to carry out continuous monitoring of other toxic metals in different ecotypes of maca (red, black, yellow, purple, creamy white, pink) in order to evaluate the variation in the accumulation of heavy metals and the level of toxicity of each metal between ecotypes.

Arsenic and Heavy Metals in Vietnamese Rice: Assessment of Human Exposure to These Elements through Rice Consumption

In this work, twelve heavy metals and arsenic, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Se, and Zn, in a rice sample collected from some areas of Vietnam have been quantified and implemented by using multiple analytical platforms such as ICP-MS, AAS, and mercury analyser. Seventy rice samples collected from the Red River Delta and mining zone activity were analysed. Concentration of heavy metals and arsenic in rice was analysed after appropriated sample digestion using internal or external calibration curves. The mean concentration (mg kg^-1 dried weight) of the analysed elements in rice samples decreased on the order of Mn (19.268) > Fe (13.624) > Zn (8.163) > Cu (3.138) > Ni (0.384) > Cr (0.296) > Co (0.279) > As (0.115) > Cd (0.111) > Pb (0.075) > Hg (0.007) > Se (<LOD). Mercury, a highly toxic element, has been only found in rice samples collected in the mining activity zone (frequency detection 14.5% of total samples). The experimental results indicated that the heavy metals and arsenic found in rice collected from mining activity zone were higher than those in rice harvested from normal cultivated areas like the Red River Delta. The heavy metals and arsenic content in Vietnamese rice samples were also compared with the concentration of heavy metals in other foreign rice samples in some recent publications. The estimated daily intake through rice consumption was calculated and compared with the level proposed by the Food and Agriculture Organization of the United Nations. The results indicated that the provisional daily intake of Cd was higher than the level proposed by FAO, while the intake of other heavy metals was in an acceptable range of CODEX standard.

Exposure to heavy metal contamination and probabilistic health risk assessment using Monte Carlo simulation: a study in the Southeast Iran

The rice contamination to heavy metals and its associated health risks have been less addressed in the southeast of Iran. In the present study, in the mentioned region, we assessed the concentration of nine elements in rice, and the health risk related to the measured elements was determined using the data which were gathered by a questionnaire. For this purpose, 36 samples of the 12 most widely consumed rice brands were collected. Using ICP-MS, the concentrations of Ni, Cr, Hg, Sr, Mn, Fe, Se, Ba, and Zn were measured in the studied samples as 0.599 ± 0.124, 0.483 ± 0.28, 0.0157 ± 0.005, 0.85 ± 1.307, 11.5 ± 1.97, 178.46 ± 67.27, 0.212 ± 0.083, 0.845 ± 0.62, and 8.416 ± 1.611 mg/kg, respectively. We found that, regarding the other studies, the levels of Ni, Cr, Hg, Fe, and Ba were higher. Besides, using 258 distributed questionnaires among citizens, the daily rice consumption was determined to be 295.66 ± 171.005 g/person/ day. Based on this consumption rate and Monto Carlo uncertainty simulation, Fe (0.741 ± 0.54 mg/kg/day) and Se (8.95E-04 ± 6.33E-04 mg/kg/day) showed the highest and lowest daily intake, respectively. Also, using Hazard Quotient (HQ), the non-carcinogenic risk effects of the surveyed elements were estimated. The obtained results of HQ revealed that Fe (2.48) and Mn (1.06) could pose non-carcinogenic health risks to consumers. Moreover, the calculated hazard Index showed that the overall health risk of the surveyed elements is in an unsafe range.