pH-dependent structural changes of arsenic oxoacids in solution and solid phase: Raman spectrometry and computational studies

Risk assessment of antimony-arsenic contaminated soil remediated using zero-valent iron at different pH values combined with freeze-thaw cycles

Soil in mining wastelands is seriously polluted with heavy metals. Zero-valent iron (ZVI) is widely used for remediation of heavy metal-polluted soil because of its excellent adsorption properties; however, the remediation process is affected by complex environmental conditions, such as acid rain and freeze-thaw cycles. In this study, the effects of different pH values and freeze-thaw cycles on remediation of antimony (Sb)- and arsenic (As)-contaminated soil by ZVI were investigated in laboratory simulation experiments. The stability and potential human health risks associated with the remediated soil were evaluated. The results showed that ZVI has a significant stabilizing effect on Sb and As in both acidic and alkaline soils contaminated with dual levels of Sb and As, and the freeze-thaw process in different pH value solution systems further enhances the ability of ZVI to stabilize Sb and As, especially in acidic soils. However, it should be noted that apart from the pH=1.0 solution environment, ZVI's ability to stabilize As is attenuated under other circumstances, potentially leading to leaching of its unstable form and thereby increasing contamination risks. This indicates that the F1 (2% ZVI+pH=1 solution+freeze-thaw cycle) processing exhibits superior effectiveness. After F1 treatment, the bioavailability of Sb and As in both soils also significantly decreased during the gastric and intestinal stages (about 60.00%), the non-carcinogenic and carcinogenic risks of Sb and As in alkaline soils are eliminated for children and adults, with a decrease ranging from 60.00% to 70.00%, while in acidic soil, the non-carcinogenic and carcinogenic risks of As to adults and children is acceptable, but Sb still poses non-carcinogenic risks to children, despite reductions of about 65.00%. These findings demonstrate that soil pH is a crucial factor influencing the efficacy of ZVI in stabilizing Sb and As contaminants during freeze-thaw cycles. This provides a solid theoretical foundation for utilizing ZVI in the remediation of Sb- and As-contaminated soils, emphasizing the significance of considering both pH levels and freeze-thaw conditions to ensure effective and safe treatment.

Biochar performance for preventing cadmium and arsenic accumulation, and the health risks associated with mustard (Brassica juncea) grown in co-contaminated soils

Cadmium (Cd) and arsenic (As) in co-contaminated soil can enter the human body harming health via the food chain, such as vegetables. Biochar derived from waste has been used to reduce heavy metal uptake by plant, but long-term effects of biochar under Cd and As co-contaminated soil needs to be investigated. A following mustard (Brassica juncea) was grown on co-contaminated soil amended with different raw materials of biochar including biochars pyrolyzed by lignite coal (LCB), rice straw (RSB), silkworm excrement (SEB), and sugar refinery sludge (SSB). The results showed that compared to the control, Cd and As contents of mustard shoot in SSB treatment decreased by 45-49% and 19-37% in two growing seasons, respectively, which was the most effective among 4 biochars. This probably due to SSB owns more abundant Fe-O functional groups. Biochar also altered the microbial community composition, specifically SSB increased proteobacteria abundance by 50% and 80% in the first and second growing seasons, thereby promoted the simultaneous immobilization of Cd and As in soils which may reduce the potential risks to humans. In summary, considering the long-term effects and security of SSB application on mustard, not only is it an effective waste recycle option, but it should also be promoted as a promising approach for safe vegetable production in Cd and As co-contaminated soils.

Interfacial Self-Assembly of Surfactant-Free Au Nanoparticles as a Clean Surface-Enhanced Raman Scattering Substrate for Quantitative Detection of As5+ in Combination with Convolutional Neural Networks

Surface-enhanced Raman scattering (SERS) is a highly sensitive tool in the field of environmental testing. However, the detection and accurate quantification of weakly adsorbed molecules (such as heavy metal ions) remain a challenge. Herein, we combine clean SERS substrates capable of capturing heavy metal ions with convolutional neural network (CNN) algorithm models for quantitative detection of heavy metal ions in solution. The SERS substrate consists of surfactant-free Au nanoparticles (NPs) and l-cysteine molecules. As plasmonic nanobuilt blocks, surfactant-free Au NPs without physical or chemical barriers are more accessible to target molecules. The amino and carboxyl groups in the l-cysteine molecule can chelate As5+ ions. The CNN algorithm model is applied to quantify and predict the concentration of As5+ ions in samples. The results demonstrated that this strategy allows for fast and accurate prediction of As5+ ion concentrations, and the determination coefficient between the predicted and actual values is as high as 0.991.