Bioavailable arsenic and amorphous iron oxides provide reliable predictions for arsenic transfer in soil-wheat system

Determining soil conservation strategies: Ecological risk thresholds of arsenic and the influence of soil properties

The establishment of ecological risk thresholds for arsenic (As) plays a pivotal role in developing soil conservation strategies. However, despite many studies regarding the toxicological profile of As, such thresholds varying by diverse soil properties have rarely been established. This study aims to address this gap by compiling and critically examining an extensive dataset of As toxicity data sourced from existing literature. Furthermore, to augment the existing information, experimental studies on As toxicity focusing on barley-root elongation were carried out across various soil types. The As concentrations varied from 12.01 to 437.25 mg/kg for the effective concentrations that inhibited 10% of barley-root growth (EC10). The present study applied a machine-learning approach to investigate the complex associations between the toxicity thresholds of As and diverse soil properties. The results revealed that Mn-/Fe-ox and clay content emerged as the most influential factors in predicting the EC10 contribution. Additionally, by using a species sensitivity distribution model and toxicity data from 21 different species, the hazardous concentration for x% of species (HCx) was calculated for four representative soil scenarios. The HC5 values for acidic, neutral, alkaline, and alkaline calcareous soils were 80, 47, 40, and 28 mg/kg, respectively. This study establishes an evidence-based methodology for deriving soil-specific guidance concerning As toxicity thresholds.

Arsenic pollution concerning surface water and sediment of Jie River: A pilot area where gold smelting enterprises are concentrated

A comprehensive monitoring and risk assessment of arsenic (As) pollution concerning surface water and sediment is performed in the Jie River basin, where gold smelting enterprises are concentrated. The study area is divide into six regions, labeled as A, B, C, D, E, and F, from sewage outlets to downstream. Results shows that with far away from the sewage outlets, the total As concentrations in water and sediment gradually decrease from regions A to F. However, in region F, the concentration of bioavailable As significantly increases in the sediment due to the higher pH, leading to the transformation of As(V) into more mobile As(III). In sediment, Paracladius sp. exhibits strong resistance to As pollution in sediment, which can potentially elevate the risk of disease transmission. In water bodies, diatoms and euglena are the main phytoplankton in the Jie River while toxic cyanobacteria exhibits lower resistance to As pollution. Overall, measures should be taken to ecologically remediate the sediment in downstream while implementing appropriate isolation methods to prevent the spread of highly contaminated sediments from regions near sewage outlets.

How Fe-bearing materials affect soil arsenic bioavailability to rice: A meta-analysis

Arsenic (As) contamination is widespread in soil and poses a threat to agricultural products and human health due to its high susceptibility to absorption by rice. Fe-bearing materials (Fe-Mat) display significant potential for reducing As bioavailability in soil and bioaccumulation in rice. However, the remediation effect of various Fe-Mat is often inconsistent, and the response to diverse environmental factors is ambiguous. Here, we conducted a meta-analysis to quantitatively assess the effects of As in soils, rice roots, and grains based on 673, 321, and 305 individual observations from 67 peer-reviewed articles, respectively. On average, Fe-Mat reduced As bioavailability in soils, rice roots, and grains by 28.74 %, 33.48 %, and 44.61 %, respectively. According to the analysis of influencing factors, the remediation efficiency of Fe-Mat on As-contaminated soil was significantly enhanced with increasing Fe content in the material, in which the industry byproduct was the most effective in soils (-42.31 %) and rice roots (-44.57 %), while Fe-biochar was superior in rice grains (-54.62 %). The efficiency of Fe-Mat in minimizing soil As mobility was negatively correlated with soil Fe content, CEC, and pH. In addition, applying Fe-Mat in alkaline soils with higher silt, lower clay and available P was more effective in reducing As in rice grains. A higher efficiency of applying Fe-Mat under continuous flooding conditions (27.39 %) compared with alternate wetting and drying conditions (23.66 %) was also identified. Our results offer an important reference for the development of remediation strategies and methods for various As-contaminated paddy soils.

Reduced arsenic availability in paddy soil through Fe-organic ligand complexation mediated by bamboo biochar

The reuse of arsenic (As)-contaminated paddy fields is a global challenge because long-term flooding would result in As release due to the reductive dissolution of iron minerals. Biochar amendment is a common and effective remediation technique for As-contaminated paddy soil. However, the literature is still lacking in systematic research on the function of biochar in controlling the complexation of released dissolved organic matter (DOM) and iron oxides and its synergistic impact on the availability of As in flooded paddy soil. In the present study, bamboo biochar was prepared at different pyrolysis temperatures (300, 450 and 600 °C), as BB300, BB450 and BB600. Four paddy soil treatments including BB300, BB450, BB600 applications (1% ratio, m/m, respectively) and control (CK, no biochar application) were set and incubated for 60 d in flooding condition. The results showed that As availability represented by adsorbed As species (A-As) was mitigated by BB450 amendment compared with CK. The amendment of BB450 in paddy soil facilitated the complexation of HCl extractable Fe(III)/(II) and DOM and formation of amorphous iron oxides (e.g. complexed Fe species). Moreover, the abundance of Geobacteraceae and Xanthomonadaceae, as common electroactive bacteria, was promoted in the BB450 treated paddy soil in comparison to CK, which assisted to form amorphous iron oxides. The formed amorphous iron oxides then facilitated the formation of ternary complex (As-Fe-DOM) with highly stability, which could be considered as a mechanism for As immobilization after biochar was applied to the flooding paddy soil. Thus, the synergistic effect between amorphous iron oxides and electroactive stains could make main contribution to the passivation of released As in paddy soil under long-term flooding condition. This study provided a new insight for As immobilization via regulating iron-organic ligand complexation amendment with biochar in flooding paddy soil.

Effect of environmental factors on accumulation of trace metals in a typical shale gas exploitation area: A comprehensive investigation by machine learning and geodetector models

Whether a certain relationship is exist between shale gas exploitation and accumulation of trace metals in soil is a controversial issue in recent years. To date, few study clearly reveal the intrinsic contributions of natural and anthropogenic factors to accumulation of trace metals in soil. In this study, machine learning and geodetector models were integrated to investigate to contribution of environmental factors to variations of trace metals concentration. Before modeling, there are 10.33%-25.87% of soil considered as metal pollution, and the value of Pn further suggest that the Ba contribute the most to the comprehensive pollution index of trace metals in soil. The initial prediction of trace metals concentration by machine learning models is less effectively indicating the need for alternative approaches. To address this problem, post-constraints approach was used, and the post-constraint MSLR model demonstrates superior performance (R2 = 0.81) Additionally, through the utilization of geodetector model, the explanatory power (q) of CEC and SOM were identified as dominant natural factors with value of 0.055 and 0.089. respectively. Moreover, distance from working sites and working status were identified as the dominant anthropogenic factors associating to the spatial heterogeneity of trace metals in soil. The interaction between natural and anthropogenic factors showed a siginifacnt nonlinear enhancement effect on accumulation of Cr, Ba and Sr, and the highest value of q was 0.38 for SOM and distance. This study indicated that the potential metal contamination was related to shale gas exploitation and provide reference for controlling soil pollution in shale gas exploitation area and making management strategy.

Rhizosphere bacteria regulated arsenic bioavailability and accumulation in the soil-Chinese cabbage system

The accumulation of arsenic (As) in Chinese cabbage (Brassica rapa ssp. pekinensis) has recently been a source of concern for a potential risk to human health. It is unknown whether natural variations of As accumulation in different genotypes of Chinese cabbage are related to rhizobacterial characteristics. Experiments were conducted to investigate the mechanisms of rhizobacteria involving in As fates in a soil-Chinese cabbage system using various genotypes using high-throughput sequencing and quantitative PCR. There were significant differences in As accumulation in cabbage leaves between 32 genotypes, and genotypes of low-As-accumulation (LSA) and high-As-accumulation (HSA) were identified. The As concentrations in the shoots of LSA were 23.25 %, 24.19 %, 15.05 %, and 70.69 % lower than those of HSA in seedling stage (SS), rosette stage (RS), heading stage (HS), and mature stage (MS), respectively. Meanwhile, the relative abundances of phyla Patescibacteria (in RS), Acidobacteria and Rokubacteria (in HS) in the rhizosphere of LSA were 60.18 %, 28.19 %, and 45.38 % less than those of HSA, respectively. Additionally, both shoot-As and As translocation factor had significantly positive or negative correlations with the relative abundances of Rokubacteria or Actinobacteria. In LSA rhizosphere, the relative abundances of genera Flavobacterium (in SS), Ellin6055 and Sphingomonas (in HS) were 128.12 %, 83.69 % and 79.50 % higher than those of HSA, respectively. This demonstrated that rhizobacteria contribute to the accumulation and translocation of As in HSA and LSA. Furthermore, the gene copies of aioA and arsM in LSA rhizosphere were 25.54 % and 16.13 % higher than those of HSA, respectively, whereas the gene copies of arsC in LSA rhizosphere were 26.36 % less than those of HSA in MS, indicating that rhizobacteria are involved in As biotransformation in the soil. These results provide a comprehensive understanding of the relationship between characteristics of rhizobacterial communities and As variations in Chinese cabbage genotypes.

Ecological toxicity (ECx) of Pb and its prediction models in Chinese soils with different physiochemical properties

The lack of toxicological data becomes the main bottleneck of ecological risk assessment of lead (Pb) in Chinese soils. The present study assessed Pb toxicity on three underground test endpoints (barley root elongation, earthworm avoidance response, and substrate-induced respiration (SIR) of microorganism) in 10 different soils. Hormetic dose-response induced by Pb was >118 % for earthworm avoidance response. EC₁₀ and EC₅₀ (the effective concentrations of Pb that inhibit 10 % or 50 % of endpoint bioactivity and also represents the toxicity threshold of Pb) after leaching increased by 0.32-8.73 times, and 1.02-3.75 times, respectively. Leaching factor (LF) prediction models indicated pH and cation exchange capacity (CEC) were the vital predictors for LF₁₀ and LF₅₀, explaining 60.6 % and 73.1 % of variations, respectively. SIR was one sensitive test endpoint for Pb toxicity, with the lowest of EC₁₀ and EC₅₀ values (from 373.7 to 1008.5 mg·kg^-1, and from 837.1 to 2869.0 mg·kg^-1, respectively). The best prediction models between EC_x and soil properties is LogEC₅₀ = 1.324Log(pH) + 0.423Log(CEC) + 1.742 (R² = 0.761, p < 0.01). The results displayed significant implications for deriving EC_x of Pb, and provided a scientific basis for soil ecological risk assessment of Pb.

Enhanced oxidation and stabilization of arsenic in a soil-rice system by phytosynthesized iron oxide nanomaterials: Mechanistic differences under flooding and draining conditions

Despite arsenic (As) bioavailability being highly correlated with water status and the presence of iron (Fe) minerals, limited information is currently available on how externally applied Fe nanomaterials in soil-rice systems affect As oxidation and stabilization during flooding and draining events. Herein, the stabilization of As in a paddy soil by a phytosynthesized iron oxide nanomaterials (PION) and the related mechanism was investigated using a combination of chemical extraction and functional microbe analysis in soil at both flooding (60 d) and draining (120 d) stages. The application of PION decreased both specifically bound and non-specifically bound As. The As content in rice root, stem, husk and grain was reduced by 78.5, 17.3, 8.4 and 34.4%, respectively, whereas As(III) and As(V) in root declined by 96.9 and 33.3% for the 1% PION treatment after 120 d. Furthermore, the 1% PION treatment decreased the ratio of As(III)/As(V) in the rhizosphere soil, root and stem. Although PION had no significant effect on the overall Shannon index, the distribution of some specific functional microbes changed dramatically. While no As(III) oxidation bacteria were found at 60 d in any treatments, PION treatment increased As(III) oxidation bacteria by 3-9 fold after 120 d cultivation. Structural equation model analysis revealed that the ratio of Fe(III)/Fe(II) affected As stabilization directly at the flooding stage, whereas nitrate reduction and As(III) oxidation microbial groups played a significant role in the stabilization of As at the draining stage. These results highlight that PION exhibits a robust ability to reduce As availability to rice, with chemical oxidation, reduction inhibition and adsorption dominating at the flooding stage, while microbial oxidation, adsorption and coprecipitation dominant during draining.

Inoculation of Azospirillum brasilense and exogenous application of trans-zeatin riboside alleviates arsenic induced physiological damages in wheat (Triticum aestivum)

Due to increased industrialization, arsenic (As) in the soil has become a serious issue for wheat production since past few decades. We investigated the role of Azospirillum brasilense and trans-zeatin riboside (tZR) in the mitigation of arsenic toxicity in wheat for 2 years (2018-2019 and 2019-2020) in pot experiments. Wheat plants grown in soil artificially spiked with arsenic (50, 70, and 100 μM) was left alone or amended with A. brasilense, tZR, or their combination as mitigation strategies. A treatment without arsenic or amendments was maintained as control. Arsenic-induced physiological damages were noticed in the wheat plants. Detrimental effects on the plant physiological functions, such as disruption of cell membrane stability, reduced water uptake, and stomatal functions, were noticed with increase in As toxicity. Application of biological amendments reversed the effects of As toxicity by increasing wheat plant growth rate, leaf area, and photosynthesis and also yield. Therefore, application of tZR and wheat seed inoculation with A. brasilense could be a sustainable and environmentally friendly strategy to mitigate arsenic-induced crop physiological damages.

The toxicity of hexavalent chromium to soil microbial processes concerning soil properties and aging time

Chromium (Cr) pollution has attracted much attention due to its biological toxicity. However, little is known regarding Cr toxicity to soil microorganisms. The present study assesses the toxicity of Cr(VI) on two microbial processes, potential nitrification rate (PNR) and substrate-induced respiration (SIR), in a wide range of agricultural soils and detected the abundance of soil bacteria, fungi, ammonia-oxidizing bacteria and archaea. The toxicity thresholds of 10% and 50% effective concentrations (EC₁₀ and EC₅₀) for PNR varied by 32.18- and 38.66-fold among different soils, while for SIR they varied by 391.21- and 16.31-fold, respectively. Regression model analysis indicated that for PNR, CEC as a single factor explained 27% of the variation in EC₁₀, with soil clay being the key factor explaining 47.3% of the variation in EC₅₀. For SIR, organic matter and pH were found to be the most vital predictors for EC₁₀ and EC₅₀, explaining 34% and 61.1% of variation, respectively. In addition, extended aging time was found to significantly attenuate the toxicity of Cr on PNR. SIR was mainly driven by total bacteria rather than fungi, while PNR was driven by both AOA and AOB. These results were helpful in deriving soil Cr toxicity threshold based on microbial processes, and provided a theoretical foundation for ecological risk assessments and establishing a soil environmental quality criteria for Cr.

Optimal soil Eh, pH for simultaneous decrease of bioavailable Cd, As in co-contaminated paddy soil under water management strategies

The co-contamination with cadmium (Cd) and arsenic (As) in the paddy soil is the most seriously combined pollution of toxic elements in China, and it is rather difficult to decrease bioavailable Cd and As levels in soil because of the opposite ionic forms of bioavailable Cd (cation) and As (anion). This study explored the optimal conditions of Eh and pH in different soils for simultaneous decrease of Cd and As bioavailabilities in the soil-rice system through soil culture and rice pot experiments under water management strategies. The results showed that near neutral soil pH (7.0) were eventually observed under long-term flooding conditions. Under unflooded conditions, soil pH is the dominant factor influencing bioavailabilities of Cd and As, while under flooded conditions, Eh becomes the most important factor. Pot experiments showed that flooding significantly reduced the Cd concentration in rice grains from 54.5% to 95.5%, but concomitantly increased rice As concentration substantially (214%-302%). By evaluating the trade-off value between the bioavailabilities of Cd and As in the soil, the minimal trade-off value was obtained when the soil Eh was -130 mV and the pH was 6.8.

Influencing factors and prediction of arsenic concentration in Pteris vittata: A combination of geodetector and empirical models

Phytoextraction using hyperaccumulator, Pteris vittata, to extract arsenic (As) from soil has been applied to large areas to achieve an As removal rate of 18% per year. However, remarkable difference among different studies and field practices has led to difficulties in the standardization of phytoextraction technology. In this study, data on As concentration in P. vittata and related environmental conditions were collected through literature search. A conceptual framework was proposed to guide the improvement of phytoextraction efficiency in the field. The following influencing factors of As concentration in this hyperaccumulator were identified: total As concentration in soil, soil available As, organic matter in soil, total potassium (K) concentration in soil, and annual rainfall. The geodetection results show that the main factors that affect As concentration in P. vittata include soil organic matter (q = 0.75), soil available As (q = 0.67), total K (q = 0.54), and rainfall (q = 0.42). The predictive models of As concentration in P. vittata were established separately for greenhouse and field conditions through multivariate linear stepwise regression method. Under greenhouse condition, soil available As was the most important influencing factor and could explain 41.4% of As concentration in P. vittata. Two dominant factors were detected in the field: soil available As concentration and average annual rainfall. The combination of these two factors gave better prediction results with R² = 0.762. The establishment of the model might help predict phytoextraction efficiency and contribute to technological standardization. The strategies that were used to promote As removal from soil by P. vittata were summarized and analyzed. Intercropping with suitable plants or a combination of different measures (e.g., phosphate fertilizer and water retention) was recommended in practice to increase As concentration in P. vittata.

A predictive model for arsenic accumulation in rice grains based on bioavailable arsenic and soil characteristics

Arsenic (As) is a well-known human carcinogen, and rice consumption is the main way Chinese people are exposed to As. In this study, 14 kinds of paddy soils were collected from the main rice-producing areas in China. The results showed that rice roots and leaves accumulated more As than stems and grains in the following sequence: As_root> As_leaf> As_stem> As_grain. The accumulation of As by rice grains mainly depends on the total As and bioavailable As (0.43 mol/L HNO₃ extractable As), which explained 32.2% and 22.2% of the variation in the grain As, respectively. In addition, soil pH, organic matter (OM) and clay contents were the major factors affecting grain As, explaining 13.1%, 7.9% and 5.3% of the variation, respectively. An effective prediction model was established via multiple linear regression as As_grain= 0.024 BAs - 0.225 pH+ 0.013 OM+ 0.648 EC - 0.320 TN - 0.088 TP - 0.002 AS+ 2.157 (R² =0.68, P < 0.01). Through the verification of the samples from both pot experiments and paddy fields, the model successfully provided accurate predictions for rice grain As.

Derivation of empirical model to predict the accumulation of Pb in rice grain

Lead contamination in soil has become a worldwide threat on food security and human health. To assess the Pb bioavailability and evaluate the safe use of low Pb polluted soil for food production, the speciation of Pb in 19 types of paddy soil were investigated by chemical extraction and X-ray absorption near-edge structure (XANES), and the uptake and accumulation characteristics of Pb in different soil-rice systems were investigated. Moreover, an empirical model was established to predict the content of Pb in rice grain, and field validation was conduct to evaluate model performance. Results showed that the proportion of available Pb in different soil satisfied normal distribution N (0.47, 0.23). Pb(CH₃COO)₂, GSH-Pb, PbO, PbHPO₄ and Pb₃(PO₄)₂ performed well in characterizing the speciation of Pb in different rhizosphere soils, and PbHPO₄ accounted for more than 70%. The exceedance of Pb in grain in CK, 0.5X and 1X treatment were 10.5%, 36.1% and 42.1%, respectively, and the accumulation of Pb in grain was significantly related with Pb content in root. Carbonate and organic bound Pb in rhizosphere soil were two major Pb species that influenced the accumulation of Pb in rice. Moreover, content of total Pb, clay and SOM performed well in predicting the Pb content in grain, both for pot and field samples. Above all, our predicting model worked well in evaluating Pb accumulation in rice grain among low polluted paddy farmland (Total Pb < 300 mg/kg).

The Exposome in the Era of One Health

Current studies on environmental chemistry mainly focus on a single stressor or single group of stressors, which does not reflect the multiple stressors in the dynamic exposome we are facing. Similarly, current studies on environmental toxicology mostly target humans, animals, or the environment separately, which are inadequate to solve the grand challenge of multiple receptors in One Health. Though chemical, biological, and physical stressors all pose health threats, the susceptibilities of different organisms are different. As such, significant relationships and interactions of the chemical, biological, and physical stressors in the environment and their holistic environmental and biological consequences remain unclear. Fortunately, the rapid developments in various techniques, as well as the concepts of multistressors in the exposome and multireceptor in One Health provide the possibilities to understand our environment better. Since the combined stressor is location-specific and mixture toxicity is species-specific, more comprehensive frameworks to guide risk assessment and environmental treatment are urgently needed. Here, three conceptual frameworks to categorize unknown stressors, spatially visualize the riskiest stressors, and investigate the combined effects of multiple stressors across multiple species within the concepts of the exposome and One Health are proposed for the first time.

Wheat (Triticum aestivum L.) grains uptake of lead (Pb), transfer factors and prediction models for various types of soils from China

Lead (Pb) contaminated in farmlands has become a deep threat to global food security and human health. In this study, the bioavailability of Pb in 18 types of soil to wheat (Triticum aestivum L.) grains were investigated, and reliable empirical models of Pb in wheat grains were established based on soil properties. The results showed that the average bioconcentration factor (BCF_{grain/total-Pb}) in acidic soils was approximately 3.30 times than that in alkaline soils (ANOVA P < 0.05). Significant positive relationships between wheat grain Pb concentration and soil total Pb or EDTA extractable Pb were presented through the results of simple linear regressions (P < 0.001). The stepwise multiple linear regression models indicated that soil pH and soil total Pb were determined to be the two most reliable and reasonable factors in predicting wheat grain Pb concentration, with 83.8% explanation of variation. Soil total Pb compared with EDTA extractable Pb was applied to better improve prediction models in describing Pb transfer from soils to wheat grains. Furthermore, grouped models divided into two parts with pH of 7.5 also generated well prediction in wheat grain Pb concentration. Our prediction models were successfully verified within 95% prediction intervals for published literature data (including other wheat varieties). Moreover, the results indicated that ungrouped models performed better in predicting accuracy within 400 mg kg^-1 of soil total Pb, and grouped models showed better extrapolation stability when Pb in soil were overly high. Our results in the study were conduce to evaluate food security of Pb in contaminated agricultural soils.

Predicting heavy metals uptake by spinach (Spinacia oleracea) grown in integrated industrial wastewater irrigated soils of Haridwar, India

This investigation aimed to assess the impacts of integrated industrial wastewater (IIW) irrigation on soil properties in the rural area of Haridwar, India, under cultivation of a leafy vegetable, i.e., spinach (Spinacia oleracea). Based on the field data of two cropping years (2016-2017 and 2017-2018), soil characteristics-based prediction models were developed to evaluate heavy metals (HM) uptake by spinach tissues (roots and leaves) using the multivariate regression method. The results showed a significant increase (P < 0.05) in the growth and productivity of spinach plants in IIW irrigated soils as compared to normal borewell water irrigation. For the prediction models, soil parameters including pH, organic matter (%), and HM (mg/Kg) availability showed a significant effect on the HM absorption process by spinach tissues. Besides this, the models were tested using ANOVA (P < 0.001), Student's t test, model efficiency (> 0.50), and coefficient of determination (R² > 0.81) tools. Furthermore, the prediction models were also verified for their applicability in the 2018-2019 cropping year which gave satisfactory outcomes. The findings of this investigation are important in terms of predicting hazardous HM accumulation in the vegetable crops being grown in wastewater irrigated soils.