Modelling cadmium contamination in paddy soils under long-term remediation measures: Model development and stochastic simulations

Therapeutic potential of silver nanoparticles from Helianthemum lippii extract for mitigating cadmium-induced hepatotoxicity: liver function parameters, oxidative stress, and histopathology in wistar rats

Introduction: This study explores the therapeutic potential of silver nanoparticles (Ag NPs) synthesized using a Helianthemum lippii extract in mitigating cadmium-induced hepatotoxicity in Wistar rats. Given the increasing environmental and health concerns associated with cadmium exposure, novel and eco-friendly therapeutic strategies are essential. Methods: Ag NPs were characterized using X-ray diffraction, UV-Vis spectrometry, and energy-dispersive X-ray spectroscopy with scanning electron microscopy, confirming their formation with a cubic crystal structure and particle sizes ranging from 4.81 to 12.84 nm. A sub-acute toxicity study of Ag NPs (2 mg/kg and 10 mg/kg) was conducted, showing no significant difference compared to untreated control rats (n = 3 animals/group). Subsequently, adult Wistar rats (n = 5/group) were divided into a control group and three experimental groups: Ag NPs alone, exposure to 50 mg/kg CdCl2 in drinking water for 35 days, and CdCl2 exposure followed by 0.1 mg/kg/day Ag NPs intraperitoneally for 15 days. Results: In the CdCl2-exposed group, there was a significant decrease in body weight and increases in alanine and aspartate transaminase levels (p < 0.05 vs. control), indicating hepatotoxicity. Additionally, antioxidant defenses were decreased, and malondialdehyde levels were elevated. Liver histology revealed portal fibrosis, inflammation, necrosis, sinusoid and hepatic vein dilation, and cytoplasmic vacuolations. Treatment with Ag NPs post-CdCl2 exposure mitigated several adverse effects on liver function and architecture and improved body weight. Discussion: This study demonstrates the efficacy of Ag NPs synthesized via a green method in reducing cadmium-induced liver damage. These findings support the potential of Ag NPs in therapeutic applications and highlight the importance of sustainable and eco-friendly nanoparticle synthesis methods. By addressing both toxicity concerns and therapeutic efficacy, this research aligns with the growing emphasis on environmentally conscious practices in scientific research and healthcare.

Cadmium accumulation in tropical island paddy soils: From environment and health risk assessment to model prediction

Cultivated soil quality is crucial because it directly affects food safety and human health, and rice is of primary concern because of its centrality to global food networks. However, a detailed understanding of cadmium (Cd) geochemical cycling in paddy soils is complicated by the multiple influencing factors present in many rice-growing areas that overlap with industrial centers. This study analyzed the pollution characteristics and health risks of Cd in paddy soils across Hainan Island and identified key influencing factors based on multi-source environmental data and prediction models. Approximately 27.07% of the soil samples exceeded the risk control standard screening value for Cd in China, posing an uncontaminated to moderate contamination risk. Cd concentration and exposure duration contributed the most to non-carcinogenic and carcinogenic risks to children, teens, and adults through ingestion. Among the nine prediction models tested, Extreme Gradient Boosting (XGBoost) exhibited the best performance for Cd prediction with soil properties having the highest importance, followed by climatic variables and topographic attributes. In summary, XGBoost reliably predicted the soil Cd concentrations on tropical islands. Further research should incorporate additional soil properties and environmental variables for more accurate predictions and to comprehensively identify their driving factors and corresponding contribution rates.

Modeling spatial trends and exchange fluxes of contaminants in agricultural soil under pollution prevention measures

Modeling the long-term trends of contaminants in topsoil under controlled measures is critical for sustainable agricultural environmental management. Traditional mass balance equations cannot predict spatial variation and exchange flux of regional soil contaminants for it lacks a method of assigning input-output parameters to each simulated cell. To overcome this limitation, we allocate the estimated source contribution flux to the spatial grid cell in the regional chemical mass balance by integrated positive matrix factorization (P-RCMB) with historical trends quantification. Focusing on Cd and As, which are elements with elevated risks of food intake and volatilization/infiltration, the model is applied to 30 ha of agricultural land near the enterprise. Predictions indicate an additional 13.5% of the soil is contaminated, and approximately 2.57 ha may accrue after 100 years at the site, with an uncertainty range of 0.98-5.3 ha. Clean water irrigation (CWI) reduces contamination expansion by approximately 42%, including approximately 4813 g ha-1 yr-1 net As infiltration, playing a dominant role in preventing the formation of severely contaminated soil. Stop straw return, green fertilizers use, and reduced atmospheric deposition control the exchange flux of Cd (114.9 g ha-1 yr-1) in moderate/slight contamination areas. For the different contaminants' cumulative trends in dryland and paddy fields, achieving a net cumulative flux close to zero in marginally contaminated areas presents a viable approach to optimize current emission standards. if trade-off straw removal and additional fertilizer inputs, a straw return rate of approximately 40% in Cd-contaminated soil will yield overall benefits. This model contributes valuable insights and tools for policymaking in contaminated land sustainable utilization and emission standard optimization.

Model development and probabilistic risks of cadmium transport in slag-soil-groundwater systems with heterogeneous conditions

Prediction of the long-term risk of trace metals leaching from soils at smelting sites is essential for groundwater protection. Herein, a mass balance-based stochastic model was developed to simulate the transport and probabilistic risks of trace metals in heterogeneous slag-soil-groundwater systems. The model was applied to a smelting slag yard with three stacking scenarios, including (A) fixed stacking amount, (B) stacking amount increasing yearly, and (C) slag removal after 20 years. The simulations suggested that the leaching flux and net accumulation of Cd in soils of the slag yard and abandoned farmland were greatest for scenario (B), which was followed by scenarios (A) and (C). In the slag yard, a plateau occurred in the Cd leaching flux curves, followed by a sharp increase. After 100 years of leaching, only scenario (B) had a high probabilistic risk (>99.9 %) of threatening groundwater safety under heterogeneous conditions. <11.1 % of the exogenous Cd may leach into groundwater under the worst scenario. The key parameters affecting Cd leaching risk include runoff interception rate (IRCR), input flux from slag release (I), and stacking time (ST). The simulation results were consistent with the values measured in a field investigation and laboratory leaching experiments. The results should help guide remediation objectives and measures to minimize the leaching risk at smelting sites.

A novel four-dimensional prediction model of soil heavy metal pollution: Geographical explanations beyond artificial intelligence "black box"

The current artificial intelligence (AI)-based prediction approaches of soil pollutants are inadequate in estimating the geospatial source-sink processes and striking a balance between the interpretability and accuracy, resulting in poor spatial extrapolation and generalization. In this study, we developed and tested a geographically interpretable four-dimensional AI prediction model for soil heavy metal (Cd) contents (4DGISHM) in Shaoguan city of China from 2016 to 2030. The 4DGISHM approach characterized spatio-temporal changes in source-sink processes of soil Cd by estimating spatio-temporal patterns and the effects of drivers and their interactions of soil Cd at local to regional scales using TreeExplainer-based SHAP and parallel ensemble AI algorithms. The results demonstrate that the prediction model achieved MSE and R² values of 0.012 and 0.938, respectively, at a spatial resolution of 1 km. The predicted areas exceeding the risk control values for soil Cd across Shaoguan from 2022 to 2030 increased by 22.92% at the baseline scenario. By 2030, enterprise and transportation emissions (SHAP values 0.23 and 0.12 mg/kg, respectively) were the major drivers. The influence of driver interactions on soil Cd was marginal. Our approach surpasses the limitations of the AI "black box" by integrating spatio-temporal source-sink explanation and accuracy. This advancement enables geographically precise prediction and control of soil pollutants.

Forecasting contamination in an ecosystem based on a network model

This paper aims to predict heavy metal pollution based on ecological factors with a new approach, using artificial neural networks (ANNs), by significantly removing typical obstacles like time-consuming laboratory procedures and high implementation costs. Pollution prediction is crucial for the safety of all living things, for sustainable development, and for policymakers to make the right decisions. This study focuses on predicting heavy metal contamination in an ecosystem at a significantly lower cost because pollution assessment still primarily relies on conventional methods, which are recognized to have disadvantages. To accomplish this, the data collected for 800 plant and soil materials have been utilized in the production of an ANN. This research is the first to use an ANN to predict pollution very accurately and has found the network models to be very suitable systemic tools for modelling in pollution data analysis. The findings appear are promising to be very illuminating and pioneering for scientists, conservationists, and governments to swiftly and optimally develop their appropriate work programs to leave a functioning ecosystem for all living things. It has been observed that the relative errors calculated for each of the polluting heavy metals for training, testing, and holdout data are significantly low.

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.

An investigation on environmental pollution due to essential heavy metals: a prediction model through multilayer perceptrons

This research is to predict heavy metal levels in plants, particularly in Robinia pseudoacacia L., and soils using an effective artificial intelligence approach with some ecological parameters, thereby significantly eliminating common defects such as high cost and seriously tedious and time-consuming laboratory procedures. In this respect, the artificial neural network (ANN) is employed to estimate the concentrations of essential heavy metals such as Fe, Mn and Ni, depending on the Cu and Zn concentrations of plant and soil samples collected from five different locations. The derived relative errors for the constructed ANN model have been computed within the ranges 0.041-0.051, 0.017-0.025, and 0.026-0.029 for the training, testing and holdout data regarding Fe, Mn, and Ni, respectively. In addition, it has been realized that the relative errors could be diminished up to 0.007 for Fe, 0.014 for Mn and 0.022 for Ni by considering the Cu, Zn, location and plant parts as independent variables during the analysis. The results produced seem instructive and pioneering for environmentalists and scientists to design optimal study programs to leave a livable ecosystem.

Adsorption and pH Values Determine the Distribution of Cadmium in Terrestrial and Marine Soils in the Nansha Area, Pearl River Delta

Cadmium is a toxic element with a half-life of several decades, which can accumulate in the human body by entering the food chain and seriously harm health. The cadmium adsorption and desorption processes in the soil directly affect the migration, transformation, bioavailability, and ecotoxicity of this element in soil-plant systems. Coastal zones are located in the transitional zone between land and sea, and large amounts of terrigenous material input have important environmental effects on this ecosystem. The pH, hydrodynamic conditions, soil organic matter (SOM), and other factors defining the sea-land interaction within the sedimentary environment are significantly different from those defining land facies. In order to study the key factors affecting cadmium adsorption in soils at the sea-land interface in the Nansha area of the Pearl River Delta, a test was conducted on a column of undisturbed soil. The results showed that the adsorption constant K_F and the Cd²⁺ adsorption capacity of marine soils were higher than those of terrestrial soils. However, the saturation adsorption of cadmium in terrestrial sediments was higher than in marine sediments. Soil pH was an important factor affecting cadmium adsorption capacity in both terrestrial and ma-rine sediments. Neutral and alkaline topsoil conditions inhibited the vertical migration of cadmium, while the acidic environment favored it. The higher the clay and SOM were, the stronger the Cd²⁺ adsorption capacity of the soil was. These findings suggest that the distribution of cadmium in marine and continental sedimentary soils is not only related to adsorption, but also to the physical and chemical processes occurring in different sedimentary environments.

Effects of straw return with N fertilizer reduction on crop yield, plant diseases and pests and potential heavy metal risk in a Chinese rice paddy: A field study of 2 consecutive wheat-rice cycles

Understanding the comprehensive effect on crop production and quality, soil acidification, and Cd accumulation and distribution for wheat-rice rotation under N fertilization and continuous straw return is important for proper contaminated agricultural soil management. A 2-year paddy field experiment was conducted to study the effects of above factors change in the Zhejiang province, China. Fertilization treatments included: conventional N fertilizer application (N3), 20% reduction of N application (N2), 40% reduction of N application (N1), combined with three portions of straw incorporation: all straws retention (N3), half of the straws into the fields (S2), 20% straws retention(S1). The N1 treatments significantly decreased crop yields compared to N2 and N3 treatments. Except for C2-wheat, soil pH generally decreased with increasing N fertilizer input in the order of N1>N2>N3, regardless of how many straws was amended. Moreover, we found that straw addition plus N fertilization had a intersystem impacts on Cd accumulation, distribution and availability. Although total Cd had different trends among 4 experimental seasons, when the N reduced 20% applied, the DTPA-Cd contents were lowest among 3 out of four experimental seasons, except for that of C2-wheat, where N2 treatments ranked the second lower contents. For most seasons, Cd contents in straws were higher than soils and lowest in grains, and S2N2 treatment performed an intermediate value among all treatments. Furthermore, our study demonstrated that S2 or N2 treatments or S2N2 reduced the potential risk of plant diseases and pests with lower disease index, disease cluster rate. Notably, the relative outbreak of pests was remarkably suppressed under S2 treatments, especially S2N2. Thus, these findings demonstrated that in wheat-rice rotation reducing 20% N fertilization with 50% straw returning may be a win-win practice in this region for the equilibrium between agricultural productivity, quality and low Cd polluted risk.

Historical and future trends of cadmium in rice soils deduced from long-term regional investigation and probabilistic modeling

When rice soils are contaminated by cadmium (Cd), the sources and timing of such contaminations need to be identified. In this study, we aimed to quantify the sources, history, and fate of Cd in the rice soils of southern China, by combining a near 10-year regional investigation, by developing a normalized positive matrix factorization algorithm, a Cd mass balance model, and probabilistic simulation. We simulated the historical contamination process of Cd in rice soils from 1991 to 2019 and the future changes from 2019 to 2069 under varying input parameters, as affected by different environmental management measures. Over the period of 1991-2019, the input flux of Cd through atmospheric deposition was estimated at 421 g ha^-1, which contributed 52.1% of the total increments in soil Cd concentration. Over the next decade, a 25.6% probability is predicted that the Cd concentration of local rice soils would increase from the baseline to the upper level of soil threshold, despite the efforts of environmental regulators. Removing the rice straw from production fields, cleaning up the irrigation channels, and strengthening environmental regulations would take approximately 50 years (2019-2069) to ensure that 90% of soils were safe for rice cultivation.

Spatio-Temporal Distribution of Environmental Health Risk of Heavy Metals in Industrial Wastewater of China during 1999-2018

In recent decades, environmental health risk caused by heavy metals in industrial wastewater (EHR-IHM) has become a serious issue globally, especially for China. Given the spatial difference of heavy metal emissions, hydrogeography, population distribution, etc., it is essential to estimate China's EHR-IHM from a high-resolution perspective. Based on the framework of USEtox, this study constructs an environmental health risk assessment method for heavy metals discharged from industrial wastewater by coupling the Pollutant Accumulation Model (PAM). This method also considers the process of heavy metal flows between upstream and downstream areas. Based on this constructed method, we investigate the spatio-temporal distribution of EHR-IHM of As, Cd, Cr(VI), Hg, and Pb in China from 1999 to 2018. Results showed that the EHR-IHM in China increased rapidly during 1999-2007 and decreased gradually during 2007-2018, with the highest Damage Level (DL) of 6.8 × 10⁴ disability-adjusted life years (DALY). As and Cr(VI) were the major heavy metal pollutants, which induced 58.9-70.6% and 23.9-36.2% of the total EHR-IHM, respectively. Intake of aquatic products was the dominant exposure route, accounting for over 84.1% of national EHR-IHM, followed by drinking water intake, accounting for 9.5-15.8%. Regarding spatial distribution, the regions with high EHR-IHM are mainly distributed in the middle-lower reaches of the Yangtze River, southeast coastal cities, Bohai Rim, etc.

Geographic information system-based health risk assessment of rural drinking water in Central China: a case study of You County, Hunan

This study assessed potential human health hazards posed by drinking water from centralized water supply systems in rural You County, along with its spatial distribution. While most previous studies have focused on source water or urban drinking water, this study evaluated the health risk posed by 20 common pollutants (arsenic, cadmium, chromium(VI), lead, mercury, selenium, cyanide, fluoride, nitrate nitrogen, trichloromethane, tetrachloromethane, chlorite, aluminum, iron, manganese, copper, zinc, ammonia nitrogen, chlorine dioxide, and volatile phenols) in rural terminal tap water. The assessment adopted the model recommended by the US Environmental Protection Agency (EPA) and was combined with the geographic information system (GIS) analysis to explore the spatial distribution of risk factors. Water samples were collected from 13 townships in You County across four quarters of 2019. The results indicated that the average carcinogenic risk of the rural drinking water was 2.45 × 10^-5, ranging from 1.80 × 10^-5 to 3.89 × 10^-5, which never exceeded the maximum acceptable range recommended by the US EPA (1.0 × 10^-4 ~ 1.0 × 10^-6). The average hazard index (HI), which reflects noncarcinogenic risk levels, was 0.75 and ranged from 0.34 to 1.74. Throughout the year, some townships presented HI > 1, indicating a non-carcinogenic risk. The GIS analysis indicated that noncarcinogenic risks were mainly distributed in the north, followed by the east and west. This is generally consistent with the spatial distribution of chlorite concentrations, which contribute most strongly to noncarcinogenic risk levels. The northern You County should therefore be prioritized for health risk control, followed by the eastern and western regions. Chlorite is the priority pollutant for control.

Ecotoxicology of Heavy Metal(loid)-Enriched Particulate Matter: Foliar Accumulation by Plants and Health Impacts

Atmospheric contamination by heavy metal-enriched particulate matter (metal-PM) is highly topical nowadays because of its high persistence and toxic nature. Metal-PMs are emitted to the atmosphere by various natural and anthropogenic activities, the latter being the major source. After being released into the atmosphere, metal-PM can travel over a long distance and can deposit on the buildings, water, soil, and plant canopy. In this way, these metal-PMs can contaminate different parts of the ecosystem. In addition, metal-PMs can be directly inhaled by humans and induce several health effects. Therefore, it is of great importance to understand the fate and behavior of these metal-PMs in the environment. In this review, we highlighted the atmospheric contamination by metal-PMs, possible sources, speciation, transport over a long distance, and deposition on soil, plants, and buildings. This review also describes the foliar deposition and uptake of metal-PMs by plants. Moreover, the inhalation of these metal-PMs by humans and the associated health risks have been critically discussed. Finally, the article proposed some key management strategies and future perspectives along with the summary of the entire review. The abovementioned facts about the biogeochemical behavior of metal-PMs in the ecosystem have been supported with well-summarized tables (total 14) and figures (4), which make this review article highly informative and useful for researchers, scientists, students, policymakers, and the organizations involved in development and management. It is proposed that management strategies should be developed and adapted to cope with atmospheric release and contamination of metal-PM.

Input-output balance of cadmium in typical agriculture soils with historical sewage irrigation in China

The gradual increase of cadmium (Cd) in soils has caused environmental and health risk, and it's important to study the accumulation trend to evoke the awareness of farmland safety management. This research during the period of March in 2017-2018 evaluated the input (irrigation, atmospheric deposition, fertilizer and pesticide application) and the output (runoff and seepage, grain and straw uptake) of Cd in contaminated farmland irrigated with sewage water in Hebei Province. The experimental results indicated sewage irrigation (51.03%), and atmospheric deposition (46.35%) were the main input pathways; Grain uptake (42.72%) and straw removal (50.71%) played a major role in output fluxes. The input-output balance (net transport fluxes) of Cd in the farmland were estimated to be +3621.68 ~ +8899.78 mg·(ha·yr)^-1 under different conditions (sewage irrigation with straw returning/straw removal, clean water irrigation with straw returning/straw removal), representing there was a Cd inputting in the farmland during the study. Even in the case of the lowest net transport fluxes, the annual increase of Cd concentration in soils reached to 0.0014 mg/kg. Therefore, it's necessary to take action that cutting off those pathway inputs into farmland ecosystems, such as monitoring the water quality of irrigation water sources, applying fertilizer and pesticide properly. Furthermore, attentions need to be paid to the Cd input into the farmland and environmental risks that may arise while returning straw to the field for improving soil fertility and crop production.

Spatiotemporal modeling of soil heavy metals and early warnings from scenarios-based prediction

Prediction of soil heavy metal concentrations based on continuous site specific investigation can provide reference for soil metal contamination prevention and early warning of soil environmental quality. In this study, the spatiotemporal variations of soil heavy metals (Cd, Ni, Zn, Pb and Cu) in Wenling were analyzed with 132 and 169 soil samples gathered in 2011 and 2016. In addition, we adopted a scenario-simulation model to predict future dynamic concentrations of soil heavy metals under optimistic (the pollution inputs are zero under strict environmental policy) and default (the pollution status maintain constant) conditions. Results indicated that the paddy soil was contaminated mainly by Cd and Cu. Spatiotemporal maps revealed distinct patterns in the joint area, where soil Cd, Ni, Zn, Pb and Cu all increased in northwest. Soil heavy metal concentrations as well as the associated ecological risks would decline gradually under optimistic scenario, while sharply increase when no control acts are taken over long term in default condition. The percentages of soil Cd and Cu that exceeding their corresponding risk screening value (RSV) under the default condition would be 1.6 and 1.3 times higher than those under optimistic scenario 10 years later. The probability of high potential ecological risk in default condition would be twice higher than that under optimistic scenario in 2026. Overall, strengthening the control of pollution sources and strict environmental policy are very important for soil heavy metals contamination prevention and control.

A dynamic model to evaluate the critical loads of heavy metals in agricultural soil

Estimation of critical load (CL) is important for soil environmental management and pollution prevention. We developed a mass balance-based dynamic critical load (DCL) model, which improved the model performance, applicability and functionality compared with the traditional one. Paddy soils in two typical fields in central south China and two scenarios were chosen as case studies. The result of case study showed that atmospheric deposition was the main source of Cd, Cu, Pb, and Zn in the soils, with percentage contributions ranging from 59.9 to 79.8%. Crop uptake, particularly the rice straw harvest, was the primary output pathway, accounting for 35.1-71.2% of the total output flux. The critical loads also known as annual input limits (I_max) of heavy metals in the paddy soils were calculated by the developed DCL model. For example, the Imax of Cd was recommended as 0.05 kg ha^-1 in the paddy soils under the default scenario for a protection period of 40 years, and that became 0.12 kg ha^-1 and 0.17 kg ha^-1 under the straw removal scenario in the two typical fields, respectively. The scenario simulation suggested that the straw removal strategy reduced the total concentrations of heavy metals (C_t) in the soils and notably increased the I_max. Meanwhile, the sensitivity analysis indicated that the changes of C_t and I_max can be controlled by adjusting the partition coefficient (K_d), plant uptake factor (PUF) and input flux. The mass balance-based DCL model provides a reference method to establish the standard for controlling heavy metal inputs to agricultural soil, this will be helpful to develop strategies for the prevention of soil contamination.

Input and output of cadmium (Cd) for paddy soil in central south China: fluxes, mass balance, and model predictions

It is important to provide a more comprehensive understanding of cadmium (Cd) input and output in different contamination zones. In this study, we choose 15 sampling areas in three types of contamination zones (industrial and mining, suburb, and rural) to systematically study the inventory of soil Cd input and output in Changzhutan (CZT) urban agglomerations, Hunan Province, China. The results showed that the value of total Cd input in industrial and mining (34.58 g/ha/year) was respectively about 2 and 3 times of that in suburb and in rural. Meanwhile, the total output flux in industrial and mining also presented highest value (38.67 g/ha/year) among the zones. As for the contributions, atmospheric deposition was responsible for 85-89% of the total input fluxes, which was significantly higher than those of irrigation water and fertilizer. Crop harvesting, especially straw removal, was the dominant output pathway, contributing 66-78%. Moreover, Cd annual balance illustrated that the net input fluxes under straw removal scenario were negative in all zones, and it was opposite under straw returning scenario. Further, the changes of soil Cd concentrations under straw returning and straw removal scenario were compared by a dynamic mathematical model. The modeling results presented that the soil Cd content continued to increase under straw returning in 100 years, while it was declining under straw removal scenario. This prediction indicated straw removal was an important remediation for Cd-polluted paddy soil, especially in Hunan. Nevertheless, more treatment measures need to conduct to reach the safety limits in paddy soil.

Hybrid silica aerogel nanocomposite adsorbents designed for Cd(II) removal from aqueous solution

Hybrid silica aerogel (HSA) nanoparticles were synthesized by sol-gel method and drying at ambient pressure. Also, two magnetic nanocomposites of HSA with Fe₃ O₄ nanoparticles and chitosan (CS) were prepared including HSA-Fe₃ O₄ and HSA-Fe₃ O₄ -CS. The morphology, structure, and magnetic properties of the HSA as well as its nanocomposites were analyzed by SEM, XRD, TGA, VSM, and ATR-FTIR techniques. The saturation magnetization (M_s ) values for the Fe₃ O₄ NPs, HSA-Fe₃ O_4, and HSA-Fe₃ O₄ -CS nanocomposite film were 69.93, 19.04, and 5.77 emu/g, respectively. Furthermore, the abilities of the HSA, HSA-Fe₃ O₄ , CS, and HSA-Fe₃ O₄ -CS adsorbents were assessed for removal of cadmium(II) heavy metal ions (100 ppm) from aqueous solution. All adsorbents removed/adsorbed the maximum Cd(II) ions in 120 min when adsorbent dosage = 20 mg and pH = 8. Moreover, the highest adsorption capacities were 58.5, 69.4, 65.8, and 71.9 mg/g for the HSA, CS, HSA-Fe₃ O_4, and HSA-Fe₃ O₄ -CS, respectively. Kinetic studies using all adsorbents verified that Cd(II) adsorption obeyed the second-order model illustrating the analyte chemisorption was happened on the adsorbent surfaces. All adsorption data were well consistent with the Langmuir isotherms. The reusability experiment confirmed that all of adsorbents could preserve >95% of their initial adsorption capacities even after five series of adsorption/desorption tests. PRACTITIONER POINTS: Hybrid silica aerogel (HSA), HSA-Fe₃ O_4, and HSA-Fe₃ O₄ -CS adsorbents were produced. Nanocomposites were characterized by XRD, TGA, SEM, VSM, and ATR-FTIR analysis. Adsorption of cadmium(II) ions by adsorbents was examined in aqueous solution. The highest adsorption capacity was obtained for the HSA-Fe₃ O₄ -CS (71.9 mg/g). Cd(II) adsorption followed second-order kinetics and Langmuir isotherm model.

Distribution, Ecological Risk Assessment, and Bioavailability of Cadmium in Soil from Nansha, Pearl River Delta, China

Background: Cadmium (Cd) pollution poses a threat to human health. Examination of the spatial distribution of Cd in soils can be used to assess the risks posed to humans and the environment. Objective: This study determined the enrichment rules and factors influencing Cd pollution in Nansha, and evaluated the pollution characteristics and bioavailability of Cd in quaternary sediments through 7 deep soil profiles (0-200 cm), 4 boreholes, and 348 topsoil (0-20 cm) samples. Methods: The geo-accumulation index (Igeo) and the potential ecological risk index (Er) were used to assess ecological risk, and bioavailability was determined using multivariate, spatial distribution, and correlation matrix analyses. Results: From the Er, 52% of Nansha was classed as being at very high risk of Cd pollution; a further 36% was classed as dangerous. Cadmium was more abundant in clay soils than in sandy soils. Bioavailable Cd in quaternary sediments was significantly affected by the total Cd, and labile Cd accounted for more than half of the total Cd. Changes in pH mainly affected bioavailable Cd rather than total Cd, affecting the overall bioavailability of Cd. Conclusions: Nansha soils are commonly and seriously contaminated with Cd. An appropriate remediation treatment approach should be used to reduce Cd bioavailability. Furthermore, planting structures in farmland should be adjusted to avoid the impact of heavy metals on human health.

Simulation of Heavy Metals Migration in Soil-Wheat System of Mining Area

Heavy metals in the soil of mining areas have become a primary source of pollution, which could cause deleterious health effects in people exposed through soil-plant systems via multi-pathways. A long-term field experiment under natural conditions was carried out to explore the distribution characteristic and migration law of heavy metals in a soil-wheat system of a mining area in Xuzhou. According to the second level standard of environmental quality standards for soils of China (GB 15618-1995), 30.8 g of CrCl₃·6H₂O, 8.3 g of Pb(CH₃COO)₂·3H₂O, and 16.5 g of ZnSO₄·7H₂O were added into the soil of three experimental sites, respectively. The other experimental site with no additional compounds was used as the control site. The Cr, Pb, and Zn concentrations in the soil-wheat system were counted and their corresponding migration models were constructed. From 2014 to 2017, the mean concentrations of Cr (49.09 mg·kg⁻¹), Pb (20.08 mg·kg⁻¹), and Zn (39.11 mg·kg⁻¹) in the soil of the addition sites were higher than that of the control site. The mean concentrations of Cr, Pb, and Zn in wheat of the addition sites were greater than that of the control site with the values of 3.29, 0.06, and 29 mg·kg⁻¹. In comparison, the Cr, Pb, and Zn concentrations in the soil of all experimental sites were lower than the second level standard of environmental quality standards for soils of China (GB 15618-1995), whereas the Cr concentration exceeded its corresponding soil background value of Xuzhou in 2017. The Pb concentration in soil of the addition site was greater than its corresponding background value from 2014 to 2016. The Pb and Zn concentrations in wheat of all experimental sites were lower than the national hygienic standard for grains of China (GB2715-2005) and the national guidelines for cereals of China (NY 861-2004), but the Cr concentration significantly exceeded the national guidelines for cereals of China (NY 861-2004). By constructing the Identical-Discrepant-Contrary (IDC) gray connection models, the result showed that there was a non-linear relationship of Cr, Pb, and Zn concentrations in the soil-wheat system, and the absolute values of most correlation coefficients r were lower than 0.5 and the values of greyness fG(r) were more than 0.5. The curvilinear regression models could not reflect the relationship of Cr, Pb, and Zn concentrations in the soil-wheat system with the regression coefficient r2 values far less than 1. Due to the values of regression coefficient r2 being close to 1, this study suggested that the allocation estimation models could be used for simulating the Cr, Pb, and Zn migration in the soil-wheat system of a mining area in Xuzhou.

Inventories of heavy metal inputs and outputs to and from agricultural soils: A review

Heavy metal pollution of agricultural soils is an important issue around the world. To understand the overall pollution process, accurate determination of every input and output pathway of heavy metals to and from soils is essential. Hence, input and output inventory, a quantitative analysis method of heavy metals balance in agricultural soils, has been widely used. However, due to differences in geography, climate, socioeconomic factors, industrial and agricultural production, substantial variation exists among existing input and output inventories for different countries and regions. In this study, we systematically analyzed these differences and the findings will improve the compilation of inventories worldwide.

Modelling mass balance of cadmium in paddy soils under long term control scenarios

A simple mathematical model on the basis of the mass balance principle was developed to simulate the long-term changes of Cd in paddy soils. The model predicted the dynamics of cadmium concentration in soils under six alternative control scenarios, including rice straw incorporation into fields (A), removing straw from fields (B), irrigating paddies with groundwater (C), reducing atmospheric Cd deposition (D), liming (E), and integrating measures (F), which were used for Cd contaminated paddy fields in the central subtropical areas of China. The uncertainty of parameters was analyzed using Monte Carlo methods. Scenario simulation results showed that atmospheric deposition was the main external source of Cd, contributing 70% of the total inputs, and plant uptake was an important output pathway, responsible for 92% of the total outputs. Removing straw from fields was more effective than other single control scenarios, and integrating measures were more effective in lowering Cd concentration in contaminated paddy soils. The Cd concentration in soils can meet the critical value (0.3 mg kg-1) in a low-level Cd contaminated paddy field (0.68 mg kg-1) with integrating measures through 40 years of cultivation. In the same case, a high-level Cd contaminated field (1.48 mg kg-1) was converted to a low-level Cd contaminated field (0.54 mg kg-1). However, long term use of lime can increase the Cd concentration in paddy soils. Controllable factors that affected Cd accumulation in paddy soils were plant uptake factors, and the atmospheric deposition flux and irrigation water flux of Cd. Therefore, integrating measures including removing rice straw and preventing the emission of Cd into the atmosphere and irrigation water was the optimal approach to lower Cd concentration in contaminated paddy soils.

Environmental assessment of the effects of a municipal landfill on the content and distribution of heavy metals in Tanacetum vulgare L

Heavy metal pollution is an important concern because of its potential to affect human health. This study was conducted to analyze plants growing on a landfill body and in its surroundings to determine their potential for heavy metal accumulation. In addition, the enrichment coefficient (EC) for the plant/soil system was used for determining the environmental contamination from a landfill in terms of heavy metal accumulation. The samples were taken in 2013-2014. Of the analyzed metals, iron achieved the highest values in the samples, i.e. - stalk (103.4-6564.6 mg/kg DM), roots (6563.6-33,036.6 mg/kg DM), leaf (535.1-11,275 mg/kg DM) and soil (12,389-39,381.9 mg/kg DM). The highest concentrations were determined in 2013 for Fe, Mn and Zn. Iron achieved the highest concentrations in the years 2013-2014. Next, EC values were then calculated, with the highest noted for Cd. Cd, as well as Cr, Ni and Zn are accumulated mostly in the leaves, whereas Co, Cu, Fe, Hg, Mn and Pb are accumulated mainly in the roots of T. vulgare.

Prediction of soil cadmium distribution across a typical area of Chengdu Plain, China

A suitable method and appropriate environmental variables are important for accurately predicting heavy metal distribution in soils. However, the classical methods (e.g., ordinary kriging (OK)) have a smoothing effect that results in a tendency to neglect local variability, and the commonly used environmental variables (e.g., terrain factors) are ineffective for improving predictions across plains. Here, variables were derived from the obvious factors affecting soil cadmium (Cd), such as road traffic, and were used as auxiliary variables for a combined method (HASM_RBFNN) that was developed using high accuracy surface modelling (HASM) and radial basis function neural network (RBFNN) model. This combined method was then used to predict soil Cd distribution in a typical area of Chengdu Plain in China, considering the spatial non-stationarity of the relationships between soil Cd and the derived variables based on 339 surface soil samples. The results showed that HASM_RBFNN had lower prediction errors than OK, regression kriging (RK) and HASM_RBFNNs, which didn't consider the spatial non-stationarity of the soil Cd-derived variables relationships. Furthermore, HASM_RBFNN provided improved detail on local variations. The better performance suggested that the derived environmental variables were effective and HASM_RBFNN was appropriate for improving the prediction of soil Cd distribution across plains.