Ecological risk evaluation of combined pollution of herbicide siduron and heavy metals in soils

Synergy, antagonism, and feedback between soil properties and polychlorinated biphenyls

In this paper, the migration and transformation behavior of polychlorinated biphenyls (PCBs) in soil environmental system and their interaction with environmental factors were reviewed. The migration and transformation of PCBs are mainly regulated by soil organic matter, temperature and microorganisms. Soil organic matter immobilizes PCBs through adsorption sites and functional groups (including carbonyl and carboxyl groups), and microorganisms reduce and dechlorinate PCBs by reducing dehalogenase (anaerobic), biphenyl dioxygenase (aerobic) and other biological enzymes. However, these mechanisms are influenced by pH, temperature, water content, microbial population, and PCBs structure. In addition, there are significant differences in the response of PCBs conversion to oxygen content (aerobic and anaerobic) in soil systems. However, most current studies focus on the environmental behavior of PCBs from the perspective of single factors such as pH, soil organic matter, and microorganisms, and the comprehensive analysis under the interaction of multiple factors is limited. Therefore, the synergistic, antagonistic and feedback effects of PCBs in soil systems are analyzed comprehensively for the first time in this paper, which fills the gap of existing research. The aim is to provide a theoretical framework for the future environmental behavior effect of PCBs in soil and the contribution ability of environmental factors to PCBs pollution.

Exploring microgel adsorption: synthesis, classification, and pollutant removal dynamics

Microgels have gained significant importance for the removal of pollutants owing to their stimulus-responsive behavior, high stability, and reusable capacity. However, despite these advantages, several hurdles need to be overcome to fully maximize their potential as effective adsorbents for eradicating various contaminants from the environment, such as metallic cations, organic compounds, anions, harmful gases, and dyes. Therefore, a critical review on the adsorption of pollutants by microgels is needed. In this regard, this review presents the latest developments in the adsorptive properties of microgels. The synthetic methods, architectural structures, and stimulus-responsive behavior of microgels are explained in detail. In addition, this review explores various factors that directly influence the adsorption of pollutants by microgels, such as pH, feed composition, content of pollutants, content of comonomers, agitation time, temperature, microgel dose, nature of both adsorbates (pollutants) and adsorbents (microgels), nature of the medium, and ionic strength. Various adsorption isotherms are also explored together with the kinetic aspects of the adsorption process to provide a comprehensive understanding.

Impacts of biochar materials on copper speciation, bioavailability, and toxicity in chromated copper arsenate polluted soil

Trace element polluted soils pose risks to human and environmental health. Biochar can decrease trace element bioavailability in soils, but their resulting ability to reduce soil toxicity may vary significantly depending on feedstocks used, pyrolysis conditions, and the target pollutants. Chromated copper arsenate (CCA) polluted sites are common, but only very few types of biochar have been tested for these sites. Hence, we tested fourteen well-characterized biochar materials for their ability to bind Cu and reduce toxicity in a CCA polluted soil in a 56-day experiment. Biochar (1%, wt/wt) increased plant (wheat, Triticum aestivum L.) shoot and root growth by 6-58% and 0-73%, reduced soil toxicity to Arthrobacter globiformis by 7-55%, decreased bioavailable Cu (Pseudomonas fluorescens bioreporter) by 5-65%, and decreased free Cu2+ ion activities by 27-89%. The A. globiformis solid-contact test constituted a sensitive ecotoxicological endpoint and deserves further attention for assessment of soil quality. Oil seed rape straw biochar generally performed better than other tested biochar materials. Biochar performance was positively correlated with its high cation exchange capacity, multiple surface functional groups, and high nitrogen and phosphorus content. Our results pave the way for future selection of feedstocks for creation of modified biochar materials with optimal performance in CCA polluted soil.

A New Method for Ecological Risk Assessment of Combined Contaminated Soil

Ecological risk assessment of combined polluted soil has been conducted mostly on the basis of the risk screening value (RSV) of a single pollutant. However, due to its defects, this method is not accurate enough. Not only were the effects of soil properties neglected, but the interactions among different pollutants were also overlooked. In this study, the ecological risks of 22 soils collected from four smelting sites were assessed by toxicity tests using soil invertebrates (Eisenia fetida, Folsomia candida, Caenorhabditis elegans) as subjects. Besides a risk assessment based on RSVs, a new method was developed and applied. A toxicity effect index (EI) was introduced to normalize the toxicity effects of different toxicity endpoints, rendering assessments comparable based on different toxicity endpoints. Additionally, an assessment method of ecological risk probability (RP), based on the cumulative probability distribution of EI, was established. Significant correlation was found between EI-based RP and the RSV-based Nemerow ecological risk index (NRI) (p < 0.05). In addition, the new method can visually present the probability distribution of different toxicity endpoints, which is conducive to aiding risk managers in establishing more reasonable risk management plans to protect key species. The new method is expected to be combined with a complex dose-effect relationship prediction model constructed by machine learning algorithm, providing a new method and idea for the ecological risk assessment of combined contaminated soil.

A machine learning based approach for estimating site-specific partition coefficient Kd of organic compounds: Application to nonionic pesticides

The partitioning coefficient K_d for a specific compound and location is not only a key input parameter of fate and transport models, but also critical in estimating the safety environmental concentration threshold. In order to reduce the uncertainty caused by non-linear interactions among environmental factors, machine learning based models for predicting K_d were developed in this work based on literature datasets of nonionic pesticides including molecular descriptors, soil properties, and experimental settings. The equilibrium concentration (C_e) values were specifically included for the reason that a varied range of K_d corresponding to a given C_e occurred in a real environment. By transforming 466 isotherms reported in the literature, 2618 paired equilibrium concentrations of liquid-solid (C_e-Q_e) data points were obtained. Results of SHapley Additive exPlanations revealed that soil organic carbon, C_e, and cavity formation were the most important. The distance-based applicability domain analysis was conducted for the 27 most frequently used pesticides with 15952 pieces of soil information from the HWSD-China dataset by setting three C_e scenarios (i.e., 10, 100, and 1000 μg L^-1). It was revealed the groups of compounds showing log K_d < 0.06 and log K_d > 1.19 were composed mostly of those with log K_ow of -0.800 and 5.50, respectively. When log K_d varied between 0.100 and 1.00, it was impacted by interactions among soil types, molecular descriptors, and C_e comprehensively, which accounted for 55% of the total 2618 calculations. It could be concluded that site-specific models developed in this work are necessary and practicable for the environmental risk assessment and management of nonionic organic compounds.

A newly-constructed bifunctional bacterial consortium for removing butyl xanthate and cadmium simultaneously from mineral processing wastewater: Experimental evaluation, degradation and biomineralization

Due to the technological limitations associated with beneficiation technology, large amounts of flotation reagents and heavy metals remain in mineral processing wastewater. Unfortunately, however, no treatment methods are available to mitigate the resulting pollution by them. In this study, a bacterial consortium SDMC (simultaneously degrade butyl xanthate and biomineralize cadmium) was constructed in an effort to simultaneously degrade butyl xanthate (BX) and biomineralize cadmium (Cd) by screening and domesticating two different bacterial species including Hypomicrobium and Sporosarcina. SDMC is efficient in removing the combined pollution due to BX and Cd with a 100% degradation rate for BX and 99% biomineralization rate for Cd within 4 h. Besides, SDMC can tolerate high concentrations of Fe(III) (0-40 mg/L). It has an excellent ability to utilize Fe(III) for enhanced removal of the combined pollutants. SDMC can effectively remove pollutants with a pH range of 6-9. Further, we discussed pathways for potential degradation and biomineralization: Cd(BX)₂-Cd²⁺, BX^-; BX^--CS₂, butyl perxanthate (BPX); Cd²⁺-(Ca0.67,Cd0.33)CO₃. The removal of the combined pollutants primarily entails decomposition, degradation, and biomineralization, C-O bond cleavage, and microbially induced carbonate precipitation (MICP). SDMC is a simple, efficient, and eco-friendly bifunctional bacterial consortium for effective treatment of BX-Cd combined pollution in mineral processing wastewater.

The Adsorption and Degradation of 2, 4-D Affected by Soil Organic Carbon and Clay

More has yet to be indicated on the adsorption and degradation processes, determining herbicides recycling in the environment. The sorption and degradation of 2, 4-D, affected by organic carbon (1.92-2.81%), soil clay (20-30%) and pH of the citrus orchards of Mazandaran province, Iran was investigated using HPLC equipped with UV detector for the identification and quantification of soil 2, 4-D. The adsorption (k_d) and degradation (K_deg) coefficients were determined using Freundlich and the first-degree kinetic equations. Gardens C (2.45 mL g^-1), and B (0.3 mL g^-1), with the highest (8.2 g day^-1) and least (2.7 g day^-1) degradation coefficients, had the highest and lowest K_d values. K_d variations with pH indicated higher adsorption of 2, 4-D in acidic pH. Due to the high presence of functional groups and soil biological activities, organic carbon affected the adsorption and degradation rates more effectively, which is of economic and environmental significance.

Response of soil enzyme activity and soil bacterial community to PCB dissipation across different soils

Soils are a repository for polychlorinated biphenyls (PCBs). A pot incubation experiment was performed with four soils (black soil, paddy soil, oasis soil, and fluvo-aquic soil) treated with Aroclor 1242 to achieve PCB concentrations of 5 mg kg^-1. The soil enzyme activities of protease, phosphatase, catalase, dehydrogenase, and laccase were determined by spectrophotometry. The soil bacterial communities were investigated using Illumina sequencing analysis. The results showed that the characteristics of the test soils varied among the soil types. The fluvo-aquic soil had the greatest PCB dissipation rate (86.41%), followed by the oasis (79.31%), paddy (56.09%), and black (50.65%) soils. The soil pH, cation exchange capacity, soil organic matter content, and particle diameter played significant roles in PCB dissipation from soils. The soil type had a greater influence than PCB contamination on the soil enzyme activities and bacterial communities (alpha diversity, community structure, and composition). Among the four soils, the bacterial communities of the fluvo-aquic soil were the most susceptible to PCB contamination. However, the bacterial communities of the black soil were not changed by PCB contamination.

Identifying Influencing Factors of Agricultural Soil Heavy Metals Using a Geographical Detector: A Case Study in Shunyi District, China

Identifying influencing factors of heavy metals is essential for soil evaluation and protection. This study investigates the use of a geographical detector to identify influencing factors of agricultural soil heavy metals from natural and anthropogenic aspects. We focused on six variables of soil heavy metals, i.e., As, Cd, Hg, Cu, Pb, Zn, and four influencing factors, i.e., soil properties (soil type and soil texture), digital elevation model (DEM), land use, and annual deposition fluxes. Experiments were conducted in Shunyi District, China. We studied the spatial correlations between variables of soil heavy metals and influencing factors at both single-object and multi-object levels. A geographical detector was directly used at the single-object level, while principal component analysis (PCA) and geographical detector were sequentially integrated at the multi-object level to identify influencing factors of heavy metals. Results showed that the concentrations of Cd, Cu, and Zn were mainly influenced by DEM (p = 0.008) and land use (p = 0.033) factors, while annual deposition fluxes were the main factors of the concentrations of Hg, Cd, and Pb (p = 0.000). Moreover, the concentration of As was primarily influenced by soil properties (p = 0.026), DEM (p = 0.000), and annual deposition flux (p = 0.000). The multi-object identification results between heavy metals and influencing factors included single object identification in this study. Compared with the results using the PCA and correlation analysis (CA) methods, the identification method developed at different levels can identify much more influencing factors of heavy metals. Due to its promising performance, identification at different levels can be widely employed for soil protection and pollution restoration.

Comparing desorption properties of pollutants on bentonite particles and in compacted bentonite

Desorption is one of the main factors causing groundwater and soil pollution. Therefore, the study of clay desorption characteristics is important for the prediction of groundwater and soil pollution. In previous studies, batch tests and column tests were used to study the desorption characteristics of pollutants on clay. However, the desorption parameters obtained via the two test methods were often quite different. To investigate differences in the desorption characteristics of different pollutants on clay particles and in compacted clay, batch and column desorption tests were conducted using cadmium chloride, fulvic acid, and sodium phosphate as the adsorbates and bentonite as the adsorbent. It was found that the unit particle surface area desorption distribution coefficients of pollutants on bentonite particles were approximately equal to the unit pore surface area distribution coefficients of pollutants in compacted bentonite. This indicates that the desorbed amount per unit of surface area is basically consistent, regardless of whether they are sorbed on particles or in compacted bentonite. A simple formula for determining the desorption retardation factor of pollutants in compacted bentonite is presented. The results of this study provide a reference for the prediction and evaluation of groundwater and soil pollution.

Evaluation of joint toxicity of heavy metals and herbicide mixtures in soils to earthworms (Eisenia fetida)

It is widely acknowledged that a simplified and robust approach to evaluating thecombined effects of chemical mixtures is critical for ecological risk assessment (ERA) of contaminated soil. The earthworm (Eisenia fetida) was used as a model to study the combined effects of polymetallic contamination and the herbicide siduron in field soil using a microcosm experiment. The responses of multiple biomarkers, including the activities of catalase (CAT), superoxide dismutase (SOD), glutathione reductase (GR) and acetylcholine esterase (AChE), the concentrations of glycogen, soluble protein (SP), malonaldehyde (MDA), and metallothionein (MT), and the neutral red uptake test (NRU), were investigated. Multivariate analysis, Principal Component Analysis (PCA) and Spearman's Rank Correlations analysis (BVSTEP) revealed that the activities of AChE and CAT and the NRU content were the prognostic biomarkers capturing the minimum data set of all the variables. Internal Cd (tissue Cd) in earthworms was closely related to the health status of worms under combined contamination of heavy metals and siduron. The integrated effect (E_mix) calculated based on the activities of AChE and CAT and NRU content using the stress index method had significantly linear regression with internal Cd (p<0.01). E_mix(10), E_mix(20), and E_mix(50) were then calculated, at 1.27, 1.63 and 2.71 mg/kg dry weight, respectively. It could be concluded that a bioassay-based approach incorporating multivariate analysis and internal dose was pragmatic and applicable to evaluating combined effects of chemical mixtures in soils under the guidance of the top-down evaluation concept of combined toxicity.

Quantification of heavy metal pollution for environmental assessment of soil condition

The aim of this study was to quantify heavy metal pollution for environmental assessment of soil quality using a flexible approach based on multivariate analysis. The study was conducted using 241 soil samples collected from agricultural, urban and rangeland areas in northwestern Iran. The heavy metals causing soil pollution (SP) in the study area were determined. The efficiency of principal component analysis (PCA) and discriminate analysis (DA) were compared to identify the critical heavy metals causing SP. Fourteen soil pollution indices were developed using non-linear and linear scoring equations and different integration methods. The indices were validated using the integrated pollution and potential ecological risk indices and by comparing their ability to detect soil pollution risk levels. Chromium (Cr), lead (Pb), Zinc (Zn) and copper (Cu) were identified as the significant pollutant elements using PCA, and the main pollutant elements identified using DA comprised cadmium (Cd), Zn and Pb. DA yielded a better data set for indexing SP and indicated high pollution risks for Cd > Pb > Zn. Sources of heavy metals were reliably identified using PCA, variation assessment and interrelationship evaluation of soil variables. Cr, nickel (Ni) and cobalt (Co) were found to have geogenic sources, and anthropogenic sources controlled the accumulation of Pb, Zn, Cd and Cu in soil. Linear function and additive integration were the best scoring and integrating methods for indexing HMP. The multivariate analysis provided a reliable and rapid method for indexing and mapping soil HMP.

Species- and organ-specific responses of agri-environmental plants to residual agricultural pollutants

Soil pollution by anthropogenic chemicals is a major concern for sustainability of crop production and of ecosystem functions mediated by natural plant biodiversity. The complex effects on plants are however difficult to apprehend. Plant communities of field margins, vegetative filter strips or rotational fallows are confronted with agricultural pollutants through residual soil contamination and/or through drift, run-off and leaching events that result from chemical applications. Exposure to xenobiotics and heavy metals causes biochemical, physiological and developmental effects. However, the range of doses, modalities of exposure, metabolization of contaminants into derived xenobiotics, and combinations of contaminants result in variable and multi-level effects. Understanding these complex plant-pollutant interactions cannot directly rely on toxicological or agronomical approaches that focus on the effects of field-rate pesticide applications. It must take into account exposure at root level, sublethal concentrations of bioactive compounds and functional biodiversity of the plant species that are affected. The present study deals with agri-environmental plant species of field margins, vegetative filter strips or rotational fallows in European agricultural landscapes. Root and shoot physiological and growth responses were compared under controlled conditions that were optimally adjusted for each plant species. Contrasted responses of growth inhibition, no adverse effect or growth enhancement depended on species, organ and nature of contaminant. However, all of the agricultural contaminants under study (pesticides, pesticide metabolites, heavy metals, polycyclic aromatic hydrocarbons) had significant effects under conditions of sublethal exposure on at least some of the plant species. The fungicide tebuconazole and polycyclic aromatic hydrocarbon fluoranthene, which gave highest levels of responses, induced both activation or inhibition effects, in different plant species or in different organs of the same plant species. These complex effects are discussed in terms of dynamics of agri-environmental plants and of ecological consequences of differential root-shoot growth under conditions of soil contamination.

Ecological risk of combined pollution on soil ecosystem functions: Insight from the functional sensitivity and stability

Assessing the ecological risk of combined pollution, especially from a holistic perspective with the consideration of the overarching functions of soil ecosystem, is crucial and beneficial to the improvement of ecological risk assessment (ERA) framework. In this study, four soils with similar physicochemical properties but contrasting heavy metals contamination levels were selected to explore changes in the integrated functional sensitivity (MSI), resistance (MRS) and resilience (MRL) of soil microbial communities subjected to herbicide siduron, based on which the ecological risk of the accumulation of siduron in the four studied soils were evaluated. The results suggested that the microbial biomass carbon, activity of denitrification enzyme and nitrogenase were indicative of MSI and MRS, and the same three parameters plus soil basal respiration were indicative of MRL. Significant dose-effect relationships between siduron residues in soils and MSI, MRS and MRL under combined pollution were observed. Heavy metal polluted soils showed higher sensitivity and lower resistance to the additional disturbance of herbicide siduron due to the lower microbial biomass, while the resilience of heavy metal polluted soils was much higher due to the pre-adaption to the chemical stresses. The quantifiable indicator microbial functional stability was incorporated in the framework of ERA and the results showed that the accumulation of siduron in the studied soils could exhibit potential harm to the integrated functional stability of soil microbial community. Thus, this work provides insights into the application of integrated function of soil microbial community into the framework of ERA.

Bioaccumulation and toxicity of pentachloronitrobenzene to earthworm (Eisenia fetida)

Pentachloronitrobenzene (PCNB) has been widely utilized as a fungicide to control diseases. However, toxic effect data of PCNB on terrestrial invertebrate are not available till now. Herein, the earthworms (Eisenia fetida) were exposed to soil containing different levels of PCNB. Mortality, weight, accumulation, and physiological indexes of earthworms were determined on certain days. PCNB inhibited the growth of earthworms and induced a significant increase in the activity of antioxidative enzymes. ROS, SOD, and MDA of earthworms in the highest treatment group were 6.8, 4.4, and 3.8 times higher than those in the control group, respectively. In addition, earthworm coelomocytes were successfully extracted, cultured, and innovatively employed in in-vitro toxicity test to evaluate the toxic effect of PCNB. The biomarkers utilized in in-vitro toxicity test, including cell viability, intracellular ROS and extracellular LDH showed significant correlations with the PCNB in the culture media, indicating that the in-vitro toxicity test may serve as a useful tool for toxic assessment of pollutants to earthworms and other organisms.

Uncertainty analysis in source apportionment of heavy metals in road dust based on positive matrix factorization model and geographic information system

Based on 36 road dust samples from an urbanized area of Beijing in September 2016, the information about sources (types, proportions, and intensity in spatial) of heavy metals and uncertainties were analyzed using positive matrix factorization (PMF) model, bootstrap (BS), geographic information system (GIS) and Kriging. The mean concentration of most heavy metals was higher than the corresponding background, and mean concentration of Cd was six times of its background value. Types and proportions of four sources were identified: fuel combustion (33.64%), vehicle emission (25.46%), manufacture and use of metallic substances (22.63%), and use of pesticides, fertilizers, and medical devices (18.26%). The intensity of vehicle emission and the use of pesticides, fertilizers, and medical devices were more homogeneous in spatial (extents were 1.285 and 0.955), while intensity of fuel combustion and the manufacture and use of metallic substances varied largely (extents were 4.172 and 5.518). Uncertainty analysis contained three aspects: goodness of fit, bias and variability in the PMF solution, and impact of input data size. Goodness of fit was assessed by coefficient of determination (R²) of predicted and measured values, and R² of most species were higher than 0.56. Influenced by an outlier, R² of Ni decreased from 0.59 to 0.11. Result of bootstrap (BS) showed good robust of this four-factor configuration in PMF model, and contributions of base run of factors to most species were contained in the small interquartile range and close to median values of bootstrap. Size of input data also had influence on results of PMF model. Residuals changed largely with the increase of number of site, it varied at first and then kept stable after number of site reached 70.

Trace Element Uptake by Herbaceous Plants from the Soils at a Multiple Trace Element-Contaminated Site

The uptake of trace elements by wild herbaceous plants in a multiple trace element-contaminated site was investigated. The bioaccumulation factor (BF) of trace elements was markedly variable among the different plant species. On average, the BF for various trace elements was in the following decreasing order: Zn > Cu > Mn > Ni > As > Pb > Cr. The translocation factor among the investigated plant species was also considerably variable and showed the following decreasing order: Mn > Zn > Ni > Cu > Cr > As > Pb. Several hyperaccumulating plants were identified: Artemisia vulgaris for As, Mn and Zn, Phalaris arundinacea for Mn and Ni, Heracleum sphondylium for Cr and Zn, and Bistorta officinalis for Mn and Zn. The marked accumulation of trace elements in the plant tissue suggests that the site may not be suitable for urban agricultural production. The plant tissue-borne trace elements could affect microbial activities and consequently interfere with the ecosystem functioning in the affected areas.

Evaluation of combined toxicity of Siduron and cadmium on earthworm (Eisenia fetida) using Biomarker Response Index

Agrochemicals and heavy metals are widespread contaminants in urban soil and could co-exist as mixture, which could cause unexpected risk to terrestrial organism. To assess the joint effect of herbicide Siduron and Cd, a battery of sub-lethal biomarkers was studied using earthworm ecotoxicological assay. Most selected biomarkers appeared significant but complicated responses with the increasing concentration of contaminants after 28-day exposure. In order to quantify the overall effect of the mixture contaminants, Biomarker Response Index (BRI) was used to integrate the multiple responses. Concentration Addition Index (CAI) and Effect Addition Index (EAI) were introduced to assess types of joint effect. Results showed significantly dose-effect responses between BRI and contaminant exposure concentrations. Integrated toxicity increased obviously under joint treatments of Siduron and Cd compared to their individual treatments. According to CAI, a clear antagonism was observed at relatively lower effects and gradually transformed to slight synergism with an increase of effects, while EAI showed the joint effect of addition at the whole range of effect levels. Thus, compared to the simple analysis of those complicated responses, BRI is an effective method to determine the integrated toxicity of mixture and its combination with joint effect indices (CAI and EAI) provides more worthy risk assessment on toxicity interaction among compounds.

Characterization of microbial communities of soils from gold mine tailings and identification of mercury-resistant strain

To enrich the understanding of the complex environmental system of soil and microorganisms in gold tailings, we studied the effects of environmental factors on the microbial community diversity in gold mine tailing soil in Beijing, and the strains screened from the soil with serious mercury (Hg) pollution. The results showed that microbial diversity and community composition varied among sites, and at varying depths, soil microbes were significantly affected by soil environmental factors such as lead (Pb), Hg, pH, and total organic carbon (TOC). Pb and Hg negatively affected soil microbial diversity, and less-polluted soil showed increased microbial diversities and complex community structure. Community composition analysis showed that Firmicutes, Proteobacteria and Actinobacteria were the dominant microorganisms. Moreover, Hg-resistant bacterial species isolated from soil samples were identified as Pseudomonas plecoglossicida with a high Hg tolerance efficiency. This study is important in understanding the microbial diversity and function in gold mine tailing soils and can widen the application for bioremediation process.

Modeling of Trace Metal Migration and Accumulation Processes in a Soil-Wheat System in Lihe Watershed, China

Samples of wheat and soil were collected in the Lihe watershed in East China, the migration and accumulation processes of four common trace metals (Cu, Pb, Cd and Ni) in each part of the wheat plant (root, stem, leaf and grain) were analyzed, and a mechanistic model was proposed to simulate these processes based on wheat growth techniques. Model results show that Cu and Cd migrate more easily with wheat grains, while most Pb and Ni accumulate in roots. Modeling results were shown to be relatively good, with an error of 25.29% in value and 26.38% in fluctuation, and had smaller dispersion degree than actual measurement results. Monte Carlo simulation results also match quite well with actual measurement results, and modeling results are slightly smaller in the simulation of Leaf-Cu, Grain-Cu and Leaf-Ni. Trace metal pollution risk in wheat is evaluated based on this model; our results show that the northwest and northeast parts in the research area are not suitable for growing wheat. In general, this model is relatively accurate, and can evaluate the wheat pollution risk before seeding wheat, providing scientific references for the early selection of wheat safety sowing areas.

Greener Method for the Removal of Toxic Metal Ions from the Wastewater by Application of Agricultural Waste as an Adsorbent

The presence of inorganic pollutants such as metal ions (Ni2+, Pb2+, Cr6+) in water, probably by long-term geochemical changes and from the effluents of various industries, causes diseases and disorders (e.g., cancer, neurodegenerative diseases, muscular dystrophy, hepatitis, and multiple sclerosis). Conventional methods for their removal are limited by technical and economic barriers. In biosorption, low-cost and efficient biomaterials are used for this purpose. In this study, Brassica Campestris stems from the agriculture waste and has been used for the removal of Ni2+, Cr6+ and Pb2+ ions from an aqueous solution containing all the ions. Effect of different parameters, e.g., pH, contact time, metal ion initial concentration, adsorbent dose, agitation rate and temperature were analyzed and optimized. The adsorbent worked well for removal of the Pb2+ and Cr6+ as compared to Ni2+. The atomic absorption spectrophotometer (AAS) and FTIR investigation of adsorbent before and after shows a clear difference in the adsorbent capability. The highest adsorption percentage was found at 98%, 91%, and 49% respectively, under the optimized parameters. Furthermore, the Langmuir isotherm was found better in fitting to the experimental data than that of the Freundlich isotherm.