Pristine/magnesium-loaded biochar and ZVI affect rice grain arsenic speciation and cadmium accumulation through different pathways in an alkaline paddy soil.

Cadmium (Cd) and arsenic (As) co-contamination has threatened rice production and food safety. It is challenging to mitigate Cd and As contamination in rice simultaneously due to their opposite geochemical behaviors. Mg-loaded biochar with outstanding adsorption capacity for As and Cd was used for the first time to remediate Cd/As contaminated paddy soils. In addition, the effect of zero-valent iron (ZVI) on grain As speciation accumulation in alkaline paddy soils was first investigated. The effect of rice straw biochar (SC), magnesium-loaded rice straw biochar (Mg/SC), and ZVI on concentrations of Cd and As speciation in soil porewater and their accumulation in rice tissues was investigated in a pot experiment. Addition of SC, Mg/SC and ZVI to soil reduced Cd concentrations in rice grain by 46.1%, 90.3% and 100%, and inorganic As (iAs) by 35.4%, 33.1% and 29.1%, respectively, and reduced Cd concentrations in porewater by 74.3%, 96.5% and 96.2%, respectively. Reductions of 51.6% and 87.7% in porewater iAs concentrations were observed with Mg/SC and ZVI amendments, but not with SC. Dimethylarsinic acid (DMA) concentrations in porewater and grain increased by a factor of 4.9 and 3.3, respectively, with ZVI amendment. The three amendments affected grain concentrations of iAs, DMA and Cd mainly by modulating their translocation within plant and the levels of As(III), silicon, dissolved organic carbon, iron or Cd in porewater. All three amendments (SC, Mg/SC and ZVI) have the potential to simultaneously mitigate Cd and iAs accumulation in rice grain, although the pathways are different.

Inhibition of microbially mediated total organic carbon decomposition in different types of cadmium contaminated soils with wheat straw addition.

Wheat straw returning is a common agronomic measure in the farmland. Understanding organic carbon transformation is of great significance for carbon budget under the premise of widespread distribution of cadmium (Cd) contaminated soils. An incubation experiment was conducted to assess the influence of Cd contamination on the decomposition and accumulation of total organic carbon (TOC) as well as the composition and abundance of bacterial communities in eight soil types with wheat straw addition. The results showed that inhibition of Cd contamination on microbially mediated organic carbon decomposition was affected by soil types. The lower cumulative C mineralization and higher TOC content could be observed in the acidic soils relative to that in the alkaline soils. The content of Cd in soil exhibits different effects on the inhibition in decomposition of TOC. The high dosage level of Cd had stronger inhibitory impact due to its high toxicity. The decomposition of TOC was restricted by a reduction in soil bacterial abundance and weakening of bacterial activities. Redundancy analysis (RDA) indicated that Proteobacteria and Gemmatimonadetes were abundant in alkaline Cd-contaminated soils with wheat straw addition, while Bacteroidetes dominated cumulative C mineralization in acidic Cd-contamination soils. Moreover, the abundance of predicted functional bacteria indicated that high-dose Cd-contamination and acid environment all inhibited the decomposition of TOC. The present study suggested that pH played an important role on carbon dynamics in the Cd-contaminated soils with wheat straw addition.

Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area.

Mining activities have resulted in a substantial accumulation of cadmium (Cd) in agricultural soils, particularly in southern China. Long-term Cd exposure can cause plant growth inhibition and various diseases. Rapid identification of the extent of soil Cd pollution and its driving factors are essential for soil management and risk assessment. However, traditional geostatistical methods are difficult to simulate the complex nonlinear relationships between soil Cd and potential features. In this study, sequential extraction and hotspot analyses indicated that Cd accumulation increased significantly near mining sites and exhibited high mobility. The concentration of Cd was estimated using three machine learning models based on 3169 topsoil samples, seven quantitative variables (soil pH, Fe, Ca, Mn, TOC, Al/Si and ba value) and three quantitative variables (soil parent rock, terrain and soil type). The random forest model achieved marginally better performance than the other models, with an R2 of 0.78. Importance analysis revealed that soil pH and Ca and Mn contents were the most significant factors affecting Cd accumulation and migration. Conversely, due to the essence of controlling Cd migration being soil property, soil type, terrain, and soil parent materials had little impact on the spatial distribution of soil Cd under the influence of mining activities. Our results provide a better understanding of the geochemical behavior of soil Cd in mining areas, which could be helpful for environmental management departments in controlling the diffusion of Cd pollution and capturing key targets for soil remediation.

Tentative identification of phytochelatins, their derivatives, and Cd-phytochelatin complexes in Ocimum basilicum L. roots by Paper Spray Mass Spectrometry.

An unprecedented and direct PS-MS (paper spray ionization mass spectrometry) method was proposed for the detection of native peptides, that is, glutathiones (GSHs), homoglutathiones (hGSHs), and phytochelatins (PCs), in basil (Ocimum basilicum L.) roots before and after cadmium exposure. The roots were submitted to cold maceration followed by sonication with formic acid as the extractor solvent for sample preparation. PS-MS was used to analyze such extracts in the positive mode, and the results allowed for the detection of several GSHs, hGSHs, and PCs. Some of these PCs were not distinguished in the control samples, that is, basil roots not exposed to cadmium. Other PCs were noticed in both types of roots, uncontaminated and cadmium-contaminated, but the intensities were higher in the former samples. Moreover, long-time exposure to cadmium stimulated the formation of some of these PCs and their cadmium complexes. The results, therefore, provided some crucial insights into the defense mechanism of plants against an external stress condition due to exposure to a toxic heavy metal. The present study represents a promising alternative to investigate other crucial physiological processes in plants submitted to assorted stress conditions.

Effect of Genotype on Cadmium and Trace Element Accumulation in Wheat from Weakly Alkaline Cadmium-contaminated Soil.

Cadmium (Cd) contamination of farmland soils leads to Cd accumulation in crops and reduced micronutrient uptake, posing grave risks to food safety. Herein, we investigated the enrichment and transportation patterns of Cd and trace elements in different parts of six wheat genotypes grown in weakly alkaline Cd-contaminated soils via pot experiments. The results revealed that the wheat grain variety with high Cd accumulation (Ningmai13) demonstrated a 1.94-fold increase compared to the variety with low accumulation (Yanong0428). The transfer factor of Cd from wheat straw to grain ranged from 0.319 to 0.761, while the transfer factor of Cd from root to straw ranged from 0.167 to 0.461. Furthermore, the concentrations of other metals in wheat grains followed the order of Zn > Mn > Fe > Cu. There was a significant positive correlation between Cd and Mn in grains, indicating a potential synergistic effect. Overall, this study provides valuable insights into the regulation of micronutrient intake to modulate Cd uptake in wheat.

Reduction of the exchangeable cadmium content in soil by appropriately increasing the maturity degree of organic fertilizers.

To enhance the remediation effect of heavy metal pollution, organic fertilizers with different maturity levels were added to cadmium-contaminated soil. The remediation effect was determined by evaluating the form transformation and bioavailability of cadmium in heavy metal-contaminated soil. -Results showed that when the maturity was 50%, although the soil humus (HS) content increased, it didn't contribute to reducing the bioavailability of soil Cd. Appropriately increasing the maturity (GI ≥ 80%), the HS increased by 113.95%∼157.96%, and reduced significantly the bioavailability of soil Cd, among the exchangeable Cd decreased by 16.04%∼33.51% (P < 0.01). The structural equation modeling (SEM) revealed that HS content is a critical factor influencing the transformation of Cd forms and the reduction of exchangeable Cd accumulation; the HS and residual Cd content were positively correlated with the maturity (P < 0.01), while exchangeable Cd content was negatively correlated with maturity (P < 0.01), and the correlation increased with increasing maturity. In summary, appropriately increasing the maturity (GI ≥ 80%) can increase significantly HS, promote the transformation of exchangeable Cd into residual Cd, and ultimately enhance the effectiveness of organic fertilizers in the remediation of soil Cd pollution. These results provide a new insight into the remediation of Cd-contaminated soil through organic fertilizer as soil amendment in Cd-contaminated soil.

Silicon-calcium fertilizer increased rice yield and quality by improving soil health.

It is important to ensure the nutritional quality and safe production of rice. Here, plot experiments were used to analyze the effects of three soil amendments-10 t ha-1 of biochar (BC), 1.5 t ha-1 of lime (LM), and 2.25 t ha-1 of silicon-calcium fertilizer (SC)-on the soil characteristics, rice yield and quality of double-cropping rice grown in mildly cadmium-polluted paddy fields. Compared with the control treatment (CK), the BC and SC treatments significantly improved rice processing, appearance and nutritional quality, but reduced cooking quality. All three soil amendments significantly reduced cadmium (Cd) content in brown rice. Soil amendments could significantly increase soil pH and reduce soil available Cd content. The application of the BC and SC treatments increased the content of each nutrient index in the soil (SOM, NN, AP, AK). Correlation analysis showed that the improvement in rice processing, appearance, and nutritional quality was mainly affected by the comprehensive effects of soil SOM, NN, AP and AK; the hygiene quality was mainly affected by soil pH and available Cd. In terms of benefit analysis combined with cost, the SC treatment had the highest benefit effect. Taken together, in mildly cadmium-polluted paddy fields, the application of silicon-calcium fertilizer improved the soil quality, thereby increased the yield and quality of rice, and had the best effect on increasing income.

Adsorption efficiency of chitosan/clinoptilolite (CS/CZ) composite for effective removal of Cd+2 and Cr+6 ions from wastewater effluents of dairy cattle farms.

The wastewater effluent is responsible for the major ecological impact of the dairy sectors. To avoid the negative consequences of heavy metal pollution on the ecosystem, creative, affordable, and efficient treatment methods are now required before the effluent flows into the surrounding area. This study was aimed at assessing the effectiveness of three different adsorbents for Cd+2 and Cr+6 ions from wastewater effluents of dairy farms, including chitosan (CS), clinoptilolite zeolite (CZ), and chitosan/clinoptilolite zeolite (CS/CZ) composite. The adsorption kinetics of the CS/CZ composite were established using the effects of the key variables (pH, agitation speed, adsorbent concentrations, and contact durations). The removal (%) and adsorption capacities, qe (mg/g), were calculated using the data from the adsorption kinetics. Wastewater samples (n = 60) were collected from the wastewater effluents of five farms. Cd+2 and Cr+6 ion concentrations in all collected samples were determined. Following the CS/CZ composite creation, it was characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (X-RD), and Fourier-transform infrared spectrum (FT-IR). The CS/CZ composite had an adsorption capacity of 92.4 and 96.5 mg/g for both Cd+2 and Cr+6 ions at a concentration of 2.0 g/100 ml, respectively, while the CZ adsorption capacities for the two ions were 87.5 mg/g and 61.0 mg/g, respectively, at 4.0 g/100 ml concentration. The CS was achieved at 55.56 mg/g and 33.3 mg/g, respectively, at the same concentration. The efficiency of heavy metal removal was enhanced by increasing adsorbent concentration, agitation speed, and contact duration. Using CS/CZ composite at 2.0 g/100 ml concentration, 180 min of contact time, and 300 rpm agitation speed, the greatest removal efficiencies for Cd+2 and Cr+6 ions (96.43 and 98.75%, respectively) were demonstrated.

Metabolic regulation mechanism of melatonin for reducing cadmium accumulation and improving quality in rice.

Melatonin acts as a potential regulator of cadmium (Cd) tolerance in rice. However, its practical value in rice production remains unclear. To validate the hypothesis that melatonin affects Cd accumulation and rice quality, a series of experiments were conducted. The results showed that exogenous melatonin application was associated with reduced Cd accumulation (23-43%) in brown rice. Fourier transform infrared spectroscopy (FTIR) analysis showed that exogenous melatonin affected the rice protein secondary structure and starch short-range structure. Metabolomics based on LC-MS/MS revealed that exogenous melatonin altered the brown rice metabolic profile, decreased fatty acid metabolite content, but increased amino acid metabolite, citric acid, melatonin biosynthetic metabolite, and plant hormone contents. These findings indicate that exogenous melatonin can effectively reduced Cd accumulation and improve rice quality through metabolic network regulation, serving as an effective treatment for rice cultivated in Cd-contaminated soil.

Quantification of sources and potential risks of cadmium, chromium, lead, mercury and arsenic in agricultural soils in a rapidly urbanizing region of southwest China: the case of Chengdu.

Rapid urbanization a major factor affecting heavy metal contamination on suburban agricultural soils. In order to assess the dynamic contamination of heavy metals in soil from agricultural land bordering a rapidly urbanizing area and the transfer of human health risks from contaminants in this process, 186 and 293 soil samples from agricultural land in suburban Chengdu were collected in September 2008 and September 2017, respectively. Several indicators, such as the integrated pollution index (PI) and the potential ecological risk index (RI), were employed for analyzing the heavy metal contamination levels, and the APCS-MLR receptor model were applied for analyzing the heavy metal sources. As a result, mean concentrations for five elements did not exceed the national soil pollution risk screening values in the two periods mentioned above. Nemerow's composite contamination index revealed an increase in soil contamination of arable land after 10 years of urbanization, with 3.75 and 1.02% of light and moderate sample plots, respectively, by 2017. The assessment for potential ecological risk indicated an increased level of eco-risk to high for most of the sample plots. Based on the APCS-MLR model, the origin and contribution to the five elements varied considerably between the two periods mentioned above. Among them, soil Pb changed from "industrial source" to "transportation source," soil Cr changed from "natural source" to "transportation source," and As and Hg changed from "industrial source" to "transportation source." As and Hg were associated with agricultural activities in both periods, and Cd was derived from industrial activities in both periods. The study suggests that inhalation has become a major contributor to non-cancer health risks in urbanization, unlike intake routes in previous periods, and that the increase in cancer risk is mainly due to children's consumption of agricultural products with As residues. The change in the main source of As to "transportation" also indicates a decrease in air quality during urbanization and the development of the transportation industry. This study provides a reference for the governments of rapidly urbanizing cities to formulate relevant highway and agricultural policies to safeguard the health of the people based on the current situation.

Prediction of the bioaccessibility and accumulation of cadmium in the soil-rice-human system based on optimized DGT and BCR coupled models.

Cadmium, as a typical heavy metal, has the potential to induce soil pollution and threaten human health through the soil-plant-human pathway. The conventional evaluation method based on the total content in soil cannot accurately represent the content migrated from the food chain to plants and the human body. Previous studies focused on the process of plant enrichment of heavy metals in soil, and very few studies directly predicted human exposure or risk through the labile state of Cd in soil. Hence, a relatively accurate and convenient prediction model of Cd release and translocation in the soil-rice-human system was developed. This model utilizes available Cd and soil parameters to predict the bioavailability of Cd in soil, as well as the in vitro bioaccessibility of Cd in cooked rice. The bioavailability of Cd was determined by the Diffusive Gradients in Thin-films technology and BCR sequential extraction procedure, offering in-situ quantification, which presents a significant advantage over traditional monitoring methods and aligns closely with the actual uptake of heavy metals by plants. The experimental results show that the prediction model based on the concentration of heavy metal forms measured by BCR sequential extraction procedure and diffusive gradients in thin-films technique can accurately predict the Cd uptake in rice grains, gastric and gastrointestinal phase (R2=0.712, 0.600 and 0.629). This model accurately predicts Cd bioavailability and bioaccessibility across the soil-rice-human pathway, informing actual human Cd intake, offering scientific support for developing more effective risk assessment methods.

Strengthen sunflowers resilience to cadmium in saline-alkali soil by PGPR-augmented biochar.

In the center of the Nile Delta in Egypt, the Kitchener drain as the primary drainage discharges about 1.9 billion m3 per year of water, which comprises agricultural drainage (75 %), domestic water (23 %), and industrial water (2 %), to the Mediterranean Sea. Cadmium (Cd) stands out as a significant contaminant in this drain; therefore, this study aimed to assess the integration of biochar (0, 5, and 10 ton ha-1) and three PGPRs (PGPR-1, PGPR-2, and PGPR-3) to alleviate the negative impacts of Cd on sunflowers (Helianthus annuus L.) in saline-alkali soil. The treatment of biochar (10 ton ha-1) and PGPR-3 enhanced the soil respiration, dehydrogenase, nitrogenase, and phosphatase activities by 137 %, 129 %, 326 %, and 127 %, while it declined soil electrical conductivity and available Cd content by 31.7 % and 61.3 %. Also, it decreased Cd content in root, shoot, and seed by 55.3 %, 50.7 %, and 92.5 %, and biological concentration and translocation factors by 55 % and 5 %. It also declined the proline, lipid peroxidation, H2O2, and electrolyte leakage contents by 48 %, 94 %, 80 %, and 76 %, whereas increased the catalase, peroxidase, superoxide dismutase, and polyphenol oxidase activities by 80 %, 79 %, 61 %, and 116 %. Same treatment increased seed and oil yields increased by 76.1 % and 76.2 %. The unique aspect of this research is its investigation into the utilization of biochar in saline-alkali soil conditions, coupled with the combined application of biochar and PGPR to mitigate the adverse effects of Cd contamination on sunflower cultivation in saline-alkali soil.

Combined effects of cadmium and simulated acid rain on soil microbial communities in the early cultivation of Populus beijingensis seedlings.

The combined cadmium (Cd) and acid rain pollution poses a significant threat to the global ecological environment. Previous studies on the combined adverse effects have predominantly focused on the aboveground plant physiological responses, with limited reports on the microbial response in the rhizosphere soil. This study employed Populus beijingensis seedlings and potting experiments to simulate the impacts of combined mild acid rain (pH=4.5, MA) or highly strong acid rain (pH=3.0, HA), and soil Cd pollution on the composition and diversity of microbial communities, as well as the physiochemical properties in the rhizosphere soil. The results showed that Cd decreased the content of inorganic nitrogen, resulting in an overall decrease of 49.10 % and 46.67 % in ammonium nitrogen and nitrate nitrogen, respectively. Conversely, acid rain was found to elevate the content of total potassium and soil organic carbon by 4.68 %-6.18 % and 8.64-19.16 %, respectively. Additionally, simulated acid rain was observed to decrease the pH level by 0.29-0.35, while Cd increased the pH level by 0.11. Moreover, Cd alone reduced the rhizosphere bacterial diversity, however, when combined with acid rain, regardless of its intensity, Cd was observed to increase the diversity. Fungal diversity was not influenced by the acid rain, but Cd increased fungal diversity to some extend under HA as observed in bacterial diversity. In addition, composition of the rhizosphere bacterial community was primarily influenced by the inorganic nitrogen components, while the fungal community was driven mainly by soil pH. Furthermore, "Metabolism" was emerged as the most significant bacterial function, which was markedly affected by the combined pollution, while Cd pollution led to a shift from symbiotroph to other trophic types for fungi. These findings suggest that simulated acid rain has a mitigating effect on the diversity of rhizosphere bacteria affected by Cd pollution, and also alters the trophic type of these microorganisms. This can be attributed to the acid rain-induced direct acidic environment, as well as the indirect changes in the availability or sources of carbon, nitrogen, or potassium.

Bismuth Film along with dsDNA-Modified Electrode Surfaces as Promising (bio)Sensors in the Analysis of Heavy Metals in Soils.

Heavy metals constitute pollutants that are particularly common in air, water, and soil. They are present in both urban and rural environments, on land, and in marine ecosystems, where they cause serious environmental problems since they do not degrade easily, remain almost unchanged for long periods, and bioaccumulate. The detection and especially the quantification of metals require a systematic process. Regular monitoring is necessary because of seasonal variations in metal levels. Consequently, there is a significant need for rapid and low-cost metal determination methods. In this study, we compare and analytically validate absorption spectrometry with a sensitive voltammetric method, which uses a bismuth film-plated electrode surface and applies stripping voltammetry. Atomic absorption spectroscopy (AAS) represents a well-established analytical technique, while the applicability of anodic stripping voltammetry (ASV) in complicated sample matrices such as soil samples is currently unknown. This sample-handling challenge is investigated in the present study. The results show that the AAS and ASV methods were satisfactorily correlated and showed that the metal concentration in soils was lower than the limit values but with an increasing trend. Therefore, continuous monitoring of metal levels in the urban complex of a city is necessary and a matter of great importance. The limits of detection of cadmium (Cd) were lower when using the stripping voltammetry (SWASV) graphite furnace technique compared with those obtained with AAS when using the graphite furnace. However, when using flame atomic absorption spectroscopy (flame-AAS), the measurements tended to overestimate the concentration of Cd compared with the values found using SWASV. This highlights the differences in sensitivity and accuracy between these analytical methods for detecting Cd. The SWASV method has the advantage of being cheaper and faster, enabling the simultaneous determination of heavy elements across the range of concentrations that these elements can occur in Mediterranean soils. Additionally, a dsDNA biosensor is suggested for the discrimination of Cu(I) along with Cu(II) based on the oxidation peak of guanine, and adenine residues can be applied in the redox speciation analysis of copper in soil, which represents an issue of great importance.

Ions and nanoparticles of Ag and/or Cd metals in a model aquatic microcosm: Effects on the abundance, diversity and functionality of the sediment bacteriome.

Metals can be adsorbed on particulate matter, settle in sediments and cause alterations in aquatic environments. This study assesses the effect of Ag and/or Cd, both in ionic and nanoparticle (NP) forms, on the microbiome of sediments. For that purpose, aquatic controlled-microcosm experiments were exposed to an environmentally relevant and at tenfold higher doses of each form of the metals. Changes in the bacteriome were inferred by 16S rDNA sequencing. Ionic Ag caused a significant decrease of several bacterial families, whereas the effect was opposite when mixed with Cd, e.g., Desulfuromonadaceae family; in both cases, the bacteriome functionalities were greatly affected, particularly the nitrogen and sulfur metabolism. Compared to ionic forms, metallic NPs produced hardly any change in the abundance of microbial families, although the α-biodiversity of the bacteriome was reduced, and the functionality altered, when exposed to the NPs´ mixture. Our goal is to understand how metals, in different forms and combinations, released into the environment may endanger the health of aquatic ecosystems. This work may help to understand how aquatic metal pollution alters the structure and functionality of the microbiome and biogeochemical cycles, and how these changes can be addressed.

Perfluoroalkyl compounds in groundwater alter the spatial pattern of health risk in an arsenic­cadmium contaminated region.

Integrated health risk assessment strategies for emerging organic pollutants and heavy metals that coexist in water/soil media are lacking. Contents of perfluoroalkyl compounds and potentially toxic elements in multiple media were determined by investigating a county where a landfill and a tungsten mine coexist. The spatial characteristics and sources of contaminants were predicted by Geostatistics-based and multivariate statistical analysis, and their comprehensive health risks were assessed. The average contents of perfluorooctane acid, perfluorooctanesulfonic acid, arsenic, and cadmium in groundwater were 3.21, 0.77, 1.69, and 0.14 µg L-1, respectively; the maximum content of cadmium in soils and rice highly reached 2.12 and 1.52 mg kg-1, respectively. In soils, the contribution of mine lag to cadmium was 99 %, and fertilizer and pesticide to arsenic was 59.4 %. While in groundwater, arsenic, cadmium and perfluoroalkyl compounds near the landfill mainly came from leachate leakage. Significant correlations were found between arsenic in groundwater and arsenic and cadmium in soils, as well as perfluoroalkyl compounds in groundwater and pH and sulfate. Based on these correlations, the geographically optimal similarity model predicted high-level arsenic in groundwater near the tungsten mine and cadmium/perfluoroalkyl compounds around the landfill. The combination of analytic network process, entropy weighting method and game theory-based trade-off method with risk assessment model can assess the comprehensive risks of multiple pollutants. Using this approach, a high health-risk zone located around the landfill, which was mainly attributed to the presence of arsenic, cadmium and perfluorooctanesulfonic acid, was found. Overall, perfluoroalkyl compounds in groundwater altered the spatial pattern of health risks in an arsenic­cadmium contaminated area.

Predicting Cd(II) adsorption capacity of biochar materials using typical machine learning models for effective remediation of aquatic environments.

The screening and design of "green" biochar materials with high adsorption capacity play a pivotal role in promoting the sustainable treatment of Cd(II)-containing wastewater. In this study, six typical machine learning (ML) models, namely Linear Regression, Random Forest, Gradient Boosting Decision Tree, CatBoost, K-Nearest Neighbors, and Backpropagation Neural Network, were employed to accurately predict the adsorption capacity of Cd(II) onto biochars. A large dataset with 1051 data points was generated using 21 input variables obtained from batch adsorption experiments, including preparation conditions for biochar (2 features), physical properties of biochar (4 features), chemical composition of biochar (9 features), and adsorption experiment conditions (6 features). The rigorous evaluation and comparison of the ML models revealed that the CatBoost model exhibited the highest test R2 value (0.971) and the lowest RMSE (20.54 mg/g), significantly outperforming all other models. The feature importance analysis using Shapley Additive Explanations (SHAP) indicated that biochar chemical compositions had the greatest impact on model predictions of adsorption capacity (42.2 %), followed by adsorption conditions (37.57 %), biochar physical characteristics (12.38 %), and preparation conditions (7.85 %). The optimal experimental conditions optimized by partial dependence plots (PDP) are as follows: as high Cd(II) concentration as possible, C(%) of 33 %, N(%) of 0.3 %, adsorption time of 600 min, pyrolysis time of 50 min, biochar dosage of less than 2 g/L, O(%) of 42 %, biochar pH value of 11.2, and DBE of 1.15. This study unveils novel insights into the adsorption of Cd(II) and provides a comprehensive reference for the sustainable engineering of biochars in Cd(II) wastewater treatment.

The accumulation of cadmium and lead in wheat grains is primarily determined by the soil-reducible cadmium level during wheat tillering.

The significant increase in cadmium (Cd) and lead (Pb) pollution in agricultural soil has greatly heightened environmental contamination issues and the risk of human diseases. However, the mechanisms underlying the transformation of Cd and Pb in soil as well as the influencing factors during their accumulation in crop grains remain unclear. Based on the analysis of the distribution trend of Cd and Pb in soil during the growth and development stages of wheat (tillering, filling, and maturity) in alkaline heavy metal-polluted farmland in northern China, this study investigated the response mechanism of soil heavy metal form transformation to soil physicochemical properties, and elucidated the main determining periods and influencing factors for Cd and Pb enrichment in wheat grains. The results showed that an increase in CEC and SOM levels, along with a decrease in pH level, contributed to enhancing the bioavailability of Cd in the soil. This effect was particularly evident during the tillering stage and grain filling stage of wheat. Nevertheless, the effects of soil physicochemical properties on bioavailable Pb was opposite to that on bioavailable Cd. The enrichment of Cd and Pb in grain was significantly influenced by soil pH (r = -0.786, p < 0.01), SOM (r = 0.807, p < 0.01), K (r = -0.730, p < 0.01), AK (r = 0.474, p = 0.019), and AP (r = -0.487, p = 0.016). The reducible form of Cd in soil during the wheat tillering stage was identified as the primary factor contributing to the accumulation of Cd and Pb in wheat grains, with a significant contribution rate of 84.5%. This study provides a greater scientific evidence for the management and risk control of heavy metal pollution in alkaline farmland.

High sensitive detection of Cd, Hg, Pb and Cr in rice based on LA-MPT-OES with optimized excitation regions by two-dimensional characterization of plasma plume.

Direct, rapid and highly sensitive detection of heavy metals in rice is essential to ensure food safety. In this research, a combination of laser ablation and microwave plasma torch optical emission spectrometry (LA-MPT-OES) was proposed. Based on the optimal observation positions, a high sensitivity and direct determination of Cd, Hg, Pb and Cr in rice were realized. The limits of detection (LOD) were 0.97, 0.12, 0.61 and 0.15 µg/kg, respectively, which were reduced by one order of magnitude compared to the optimal observation height. In addition, the LOD was reduced by one to two orders of magnitude compared with the techniques that require sample pre-treatment. Moreover, the results of the Certified Reference Materials and real samples were in agreement with the reference values with a relative error in the range of 0.28% âˆ¼ 14.16%. The results demonstrated that LA-MPT-OES could be a promising tool to detect heavy metals in rice.

A competitive-type photoelectrochemical aptasensor for 17 beta-estradiol detection in microfluidic devices based on a novel Au@Cd:SnO2/SnS2 nanocomposite.

A competitive-type photoelectrochemical (PEC) aptasensor coupled with a novel Au@Cd:SnO2/SnS2 nanocomposite was designed for the detection of 17ß-estradiol (E2) in microfluidic devices. The designed Au@Cd:SnO2/SnS2 nanocomposites exhibit high photoelectrochemical activity owing to the good matching of cascade band-edge and the efficient separation of photo-generated e-/h+ pairs derived from the Cd-doped defects in the energy level. The Au@Cd:SnO2/SnS2 nanocomposites were loaded into carbon paste electrodes (CPEs) to immobilize complementary DNA (cDNA) and estradiol aptamer probe DNA (E2-Apt), forming a double-strand DNA structure on the CPE surface. As the target E2 interacts with the double-strand DNA, E2-Apt is sensitively released from the CPE, subsequently increasing the photocurrent intensity due to the reduced steric hindrance of the electrode surface. The competitive-type sensing mechanism, combined with high PEC activity of the Au@Cd:SnO2/SnS2 nanocomposites, contributed to the rapid and sensitive detection of E2 in a "signal on" manner. Under the optimized conditions, the PEC aptasensor exhibited a linear range from 1.0 × 10-13 mol L-1 to 3.2 × 10-6 mol L-1 and a detection limit of 1.2 × 10-14 mol L-1 (S/N = 3). Moreover, the integration of microfluidic device with smartphone controlled portable electrochemical workstation enables the on-site detection of E2. The small sample volume (10 µL) and short analysis time (40 min) demonstrated the great potential of this strategy for E2 detection in rat serum and river water. With these advantages, the PEC aptasensor can be utilized for point-of-care testing (POCT) in both clinical and environmental applications.