The removal of arsenic from water is essential for the protection of public health. To investigate the adsorption capabilities of laterite, sandstone, and shale for the removal of arsenic from aqueous solutions, column experiments were conducted. In this study, raw materials and heat-treated (calcined) materials were examined. The experiments assessed the influence of various parameters, including initial concentration, bed depth, and the effects of heat treatment. The findings revealed that the breakthrough curves were influenced by the initial concentration of arsenic, the depth of the bed, and the type of material used. For an initial arsenic concentration of 5 mg/L, columns containing 85 cm of calcined laterite, sandstone, and shale produced volumes of 7460 ml (1492 min), 3510 ml (702 min), and 4400 ml (880 min) of water with arsenic levels below 0.01 mg/L, respectively. These calcined materials demonstrate significant potential for the effective removal of arsenic from water.
N’Da Akoua Alice Koua-KoffiSandotin Lassina CoulibalyPetemanagnan Jean-Marie OuattaraLacina Coulibaly
Arsenic is a toxic element. Chronic exposure to arsenic can pose a variety of health problems including cancers, lung disease, skin lesions, diabetes, gangrene, reproductive disorders, hypertension, and heart disease. Globally the concern of arsenic is growing day by day. Addressing this concern, the study aimed to assess the arsenic level in raw rice grain and rice cooked with tubewell water and rainwater. The study was conducted at the Sholotaka Union of Gangni Upazila in Meherpur District of Khulna Division, Bangladesh in 2023. For this purpose, seven raw samples including rice grain, rainwater and tubewell water samples and six cooked rice samples were analyzed. Rice and water samples were digested using the USEPA method-3050B in Arsenic Center Jashore, under Asia Arsenic Network, Japan. The arsenic level in the samples was tested using the HG-AAS method using a Shimadzu model AA7000 (Japan) Atomic Absorption Spectrophotometer. The study’s findings revealed that arsenic concentration in rainwater samples consistently displays 0 mg/l indicating the absence of arsenic in this sample. Three (03) tube well water samples and three (03) raw rice grain samples showed a significant variation in arsenic concentration. The mean value of tubewell water samples T1, T2, and T3 was found 0.53 ± 0.003 mg/l, 0.31 ± 0.003 mg/l, and 0.65 ± 0.002 mg/l, respectively. Whereas raw rice grain samples RG1 showed a mean of 0.607 ± 0.007 mg/kg, RG2 at 0.458 ± 0.008 mg/kg, and RG3 at 0.7145 ± 0.001 mg/kg. The study found that rice cooked with tubewell water contained a higher arsenic concentration than rice cooked with rainwater. The most prominent finding of this study was that cooked rice using rainwater had a lower amount of arsenic than the raw rice grain. So, it is clearly said that using rainwater can minimize the amount of arsenic. Furthermore, the study indicates that the health risks associated with arsenic exposure have increased. Estimated daily intake (EDI) values for cooked rice samples ranged from 3.07 to 5.47 μg
Electrochemical conversion of hypertoxic trivalent arsenic to value-added metallic arsenic can not only contribute to pollution abatement,but also resources reutilization,therefore being widely explored.Electrochemical reduction of trivalent arsenic as a promising way is widely explored.However,the high efficiency conversion is retarded by the sluggish reduction kinetics of AsO33−and fierce evolution of side products of both H_(2)and toxic AsH_(3).Herein,by using the sodium citrate as the additive,the current efficiency for metal arsenic production is increased greatly from 60%to 91%,with the accompanied evolution of hypertoxic AsH_(3)being restrained from 0.15 Nm^(3)/t_(As)to 0.022 Nm^(3)/t_(As),promising a high-efficiency and green process.The electrochemical tests and electrode surface characterizations aswell as DFT calculations indicate that the added sodium citrate promotes both the diffusion of reactive AsO_(3)^(3−)towards the cathode and its subsequent adsorption on the Ti cathode,contributing to smoother reduction for generating metal arsenic,with the evolution of toxic AsH_(3)being hindered at the same time.The results can provide new insights for the highefficiency and greener conversion of hypertoxic trivalent arsenic to value-added metallic arsenic.
Shuiping ZhongTingyu XuHang ChenDing TangWen TanWei WengYanru Shi
The role of brassinosteroids(BRs)in enabling plants to respond effectively to adverse conditions is well known,though the precise mechanism of action that helps plants cope with arsenic(As)toxicity is still difficult to interpret.Therefore we tested the effect of brassinolide(BL)spray(0,0.5,and 1 mg·L^(-1))on As(0,and 10 mg·L^(-1))stressed tomato defense responses As stress led to the induction of oxidative stress,impaired chlorophyll and nitrogen metabolism,and Fe uptake,in conjunction with a reduction in plant growth and biomass.BL spray,on the contrary,protected the photo synthetic system and helped plants grow better under As stress.This was achieved by controlling the metabolism of chlorophyll and proline and lowering the amounts of methylglyoxal and H_(2)O_(2) through glyoxalaseⅠandⅡand antioxidant enzyme s.BL decreased arsenic accumulation by directing As sequestration towards vacuoles and increased Fe amount in the leaves and roots by regulating the expression of As(Lsil and Lsi2)and Fe(IRT1,IRT2,NRAMP1,and NRAMP3)transporters in As-stressed tomatoes.Furthermore,BL boosted adaptability against As phytotoxicity,while reducing the damaging impacts on photosynthesis,nitrogen metabolism,sulfur asimilation,and Fe absorption.These results offer a solid framework for the development of exogenous BRs-based breeding strategies for safer agricultural development.
Abolghassem EmamverdianAbazar GhorbaniNecla PehlivanJames BarkerMeisam ZargarMoxian ChenGuohua Liu
Arsenic(As)pollution in soils is a pervasive environmental issue.Biochar immobilization offers a promising solution for addressing soil As contamination.The efficiency of biochar in immobilizing As in soils primarily hinges on the characteristics of both the soil and the biochar.However,the influence of a specific property on As immobilization varies among different studies,and the development and application of arsenic passivation materials based on biochar often rely on empirical knowledge.To enhance immobilization efficiency and reduce labor and time costs,a machine learning(ML)model was employed to predict As immobilization efficiency before biochar application.In this study,we collected a dataset comprising 182 data points on As immobilization efficiency from 17 publications to construct three ML models.The results demonstrated that the random forest(RF)model outperformed gradient boost regression tree and support vector regression models in predictive performance.Relative importance analysis and partial dependence plots based on the RF model were conducted to identify the most crucial factors influencing As immobilization.These findings highlighted the significant roles of biochar application time and biochar pH in As immobilization efficiency in soils.Furthermore,the study revealed that Fe-modified biochar exhibited a substantial improvement in As immobilization.These insights can facilitate targeted biochar property design and optimization of biochar application conditions to enhance As immobilization efficiency.
